import asyncio
import json
import os
import ssl
from collections.abc import AsyncIterator, Coroutine, Iterator, Mapping, Sequence
from contextlib import asynccontextmanager
from functools import lru_cache
from types import MappingProxyType, ModuleType
from typing import TYPE_CHECKING, Any, Final, Literal, Optional, TypedDict, TypeVar, Union, cast, get_type_hints
from urllib.parse import parse_qs, urlencode, urlparse, urlunparse

import httpx
from httpx._types import FileContent
from openai.types.file_deleted import FileDeleted

import litellm
import litellm.litellm_core_utils
import litellm.types
import litellm.types.utils
from litellm._logging import _redact_string, verbose_logger
from litellm.anthropic_beta_headers_manager import update_headers_with_filtered_beta
from litellm.constants import REALTIME_WEBSOCKET_MAX_MESSAGE_SIZE_BYTES
from litellm.litellm_core_utils.agentic_loop_settings import (
    DEFAULT_MAX_AGENTIC_LOOPS,
    validated_max_agentic_loops,
)
from litellm.litellm_core_utils.asyncify import run_async_function
from litellm.litellm_core_utils.audio_utils.subtitle_utils import (
    SUBTITLE_RESPONSE_FORMATS,
    synthesize_subtitle_document,
)
from litellm.litellm_core_utils.llm_request_utils import serialize_multipart_form_fields
from litellm.litellm_core_utils.realtime_errors import realtime_error_event, websocket_close_reason
from litellm.litellm_core_utils.realtime_streaming import RealTimeStreaming
from litellm.litellm_core_utils.url_utils import encode_url_path_segment
from litellm.llms.base_llm.anthropic_messages.transformation import (
    BaseAnthropicMessagesConfig,
)
from litellm.llms.base_llm.audio_transcription.transformation import (
    BaseAudioTranscriptionConfig,
)
from litellm.llms.base_llm.base_model_iterator import (
    BaseModelResponseIterator,
    MockResponseIterator,
)
from litellm.llms.base_llm.batches.transformation import BaseBatchesConfig
from litellm.llms.base_llm.chat.transformation import BaseConfig
from litellm.llms.base_llm.containers.transformation import BaseContainerConfig
from litellm.llms.base_llm.embedding.transformation import BaseEmbeddingConfig
from litellm.llms.base_llm.evals.transformation import BaseEvalsAPIConfig
from litellm.llms.base_llm.files.transformation import (
    BaseFilesConfig,
    BaseFileUploadStream,
)
from litellm.llms.base_llm.google_genai.transformation import (
    BaseGoogleGenAIGenerateContentConfig,
)
from litellm.llms.base_llm.image_edit.transformation import BaseImageEditConfig
from litellm.llms.base_llm.image_generation.transformation import (
    BaseImageGenerationConfig,
)
from litellm.llms.base_llm.ocr.transformation import BaseOCRConfig, OCRResponse
from litellm.llms.base_llm.realtime.http_transformation import BaseRealtimeHTTPConfig
from litellm.llms.base_llm.realtime.transformation import BaseRealtimeConfig
from litellm.llms.base_llm.rerank.transformation import BaseRerankConfig
from litellm.llms.base_llm.responses.transformation import BaseResponsesAPIConfig
from litellm.llms.base_llm.search.transformation import BaseSearchConfig, SearchResponse
from litellm.llms.base_llm.skills.transformation import BaseSkillsAPIConfig
from litellm.llms.base_llm.text_to_speech.transformation import BaseTextToSpeechConfig
from litellm.llms.base_llm.vector_store.transformation import (
    BaseDirectVectorStoreConfig,
    BaseVectorStoreConfig,
)
from litellm.llms.base_llm.vector_store_files.transformation import (
    BaseVectorStoreFilesConfig,
)
from litellm.llms.base_llm.videos.transformation import BaseVideoConfig
from litellm.llms.custom_httpx.http_handler import (
    AsyncHTTPHandler,
    HTTPHandler,
    _get_httpx_client,
    get_async_httpx_client,
)
from litellm.responses.streaming_iterator import (
    BaseResponsesAPIStreamingIterator,
    MockResponsesAPIStreamingIterator,
    ProjectQuotaCallback,
    ResponsesAPIStreamingIterator,
    ResponsesWebSocketStreaming,
    SyncResponsesAPIStreamingIterator,
)
from litellm.types.containers.main import (
    ContainerFileListResponse,
    ContainerListResponse,
    ContainerObject,
    DeleteContainerResult,
)
from litellm.types.files import StreamingMediaUploadConfig, TwoStepFileUploadConfig
from litellm.types.integrations.custom_logger import (
    AgenticLoopPlan,
    AgenticLoopRequestPatch,
    AgenticLoopSafetyError,
)
from litellm.types.llms.anthropic_messages.anthropic_response import (
    AnthropicMessagesResponse,
)
from litellm.types.llms.anthropic_skills import (
    DeleteSkillResponse,
    ListSkillsResponse,
    Skill,
)
from litellm.types.llms.openai import (
    CreateBatchRequest,
    CreateFileRequest,
    FileContentRequest,
    HttpxBinaryResponseContent,
    OpenAIFileObject,
    ResponseInputParam,
    ResponsesAPIOptionalRequestParams,
    ResponsesAPIResponse,
)
from litellm.types.realtime import RealtimeQueryParams
from litellm.types.rerank import RerankResponse
from litellm.types.responses.main import DeleteResponseResult
from litellm.types.router import GenericLiteLLMParams
from litellm.types.utils import (
    CallTypes,
    EmbeddingResponse,
    FileTypes,
    LiteLLMBatch,
    TranscriptionResponse,
)
from litellm.types.vector_store_files import (
    VectorStoreFileContentResponse,
    VectorStoreFileCreateRequest,
    VectorStoreFileDeleteResponse,
    VectorStoreFileListQueryParams,
    VectorStoreFileListResponse,
    VectorStoreFileObject,
    VectorStoreFileUpdateRequest,
)
from litellm.types.vector_stores import (
    VectorStoreCreateOptionalRequestParams,
    VectorStoreCreateResponse,
    VectorStoreSearchOptionalRequestParams,
    VectorStoreSearchResponse,
)
from litellm.types.videos.main import VideoObject
from litellm.utils import (
    CustomStreamWrapper,
    ImageResponse,
    ModelResponse,
    ProviderConfigManager,
    async_pre_call_deployment_hook,
)


def _rust_responses_websocket_enabled(
    custom_llm_provider: str | None,
    litellm_params: GenericLiteLLMParams,
) -> bool:
    return custom_llm_provider == "openai" and litellm_params.get("rust") is True


from .http_handler import get_shared_realtime_ssl_context

if TYPE_CHECKING:
    import tiktoken
    from aiohttp import ClientSession
    from websockets.asyncio.client import ClientConnection

    from litellm.integrations.custom_logger import CustomLogger
    from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj
    from litellm.llms.anthropic.experimental_pass_through.messages.fake_stream_iterator import (
        FakeAnthropicMessagesStreamIterator,
    )
    from litellm.llms.anthropic.experimental_pass_through.messages.streaming_iterator import (
        AnthropicMessagesStreamingResponse,
    )
    from litellm.llms.base_llm.passthrough.transformation import BasePassthroughConfig
    from litellm.types.llms.openai_evals import (
        CancelEvalResponse,
        CancelRunResponse,
        DeleteEvalResponse,
        Eval,
        ListEvalsResponse,
        ListRunsResponse,
        Run,
        RunDeleteResponse,
    )

    LiteLLMLoggingObj = _LiteLLMLoggingObj
else:
    LiteLLMLoggingObj = Any

_ResponseT = TypeVar("_ResponseT")


class _DeleteRequestKwargs(TypedDict, total=False):
    url: str
    headers: dict[str, str]
    timeout: float | httpx.Timeout | None
    json: dict[str, object]


class _MediaUploadKwargs(TypedDict, total=False):
    headers: dict[str, str]
    content: Iterator[bytes] | AsyncIterator[bytes]
    timeout: float | httpx.Timeout


def _google_genai_streaming_hidden_params(
    *,
    api_base: str,
    litellm_params: GenericLiteLLMParams,
    logging_obj: LiteLLMLoggingObj,
    response_headers: httpx.Headers,
) -> dict[str, object]:
    """Pre-stream metadata for proxy response headers (mirrors CustomStreamWrapper._hidden_params)."""
    from litellm.litellm_core_utils.core_helpers import process_response_headers

    _model_info: Final[Mapping[str, object]] = dict(getattr(litellm_params, "model_info", None) or {})
    _raw_id: Final = _model_info.get("id") or logging_obj.get_router_model_id() or ""
    _model_id: Final = _raw_id if isinstance(_raw_id, str) else str(_raw_id)
    return {
        "model_id": _model_id,
        "api_base": api_base,
        "cache_key": "",
        "response_cost": "",
        "additional_headers": process_response_headers(response_headers),
    }


@lru_cache(maxsize=None)
def _responses_api_optional_request_param_names() -> frozenset[str]:
    return frozenset(get_type_hints(ResponsesAPIOptionalRequestParams).keys())


def _custom_logger_callbacks(logging_obj: LiteLLMLoggingObj) -> list["CustomLogger"]:
    from litellm.integrations.custom_logger import CustomLogger
    from litellm.litellm_core_utils.litellm_logging import (
        get_custom_logger_compatible_class,
    )

    dynamic_success_callbacks: Final = getattr(logging_obj, "dynamic_success_callbacks", None)
    callbacks: Final = list(litellm.callbacks)
    if isinstance(dynamic_success_callbacks, (list, tuple)):
        callbacks.extend(dynamic_success_callbacks)

    custom_loggers: Final[list[CustomLogger]] = []
    for cb in callbacks:
        if isinstance(cb, str):
            resolved = get_custom_logger_compatible_class(cb)
            if resolved is None:
                continue
            cb = resolved
        if isinstance(cb, CustomLogger):
            custom_loggers.append(cb)
    return custom_loggers


def _has_pre_call_deployment_hook(logging_obj: LiteLLMLoggingObj) -> bool:
    from litellm.integrations.custom_logger import CustomLogger

    base_func: Final = CustomLogger.async_pre_call_deployment_hook
    for cb in _custom_logger_callbacks(logging_obj):
        cb_func = getattr(type(cb), "async_pre_call_deployment_hook", base_func)
        if getattr(cb_func, "__func__", cb_func) is not getattr(base_func, "__func__", base_func):
            return True
    return False


def _collect_ws_project_quota_callbacks() -> tuple[ProjectQuotaCallback, ...]:
    """Duck-type discover proxy hooks exposing per-frame project ITPM/OTPM
    enforcement, so the Responses WebSocket loop can charge every
    ``response.create`` frame, not just the connection's first one.

    Uses duck-typing on ``litellm.callbacks`` (rather than importing the
    proxy hook directly) to avoid a layering violation (SDK importing from
    the proxy layer).
    """
    import litellm as _litellm

    callbacks: Final = cast(  # cast-ok: callback registry is inspected before protocol use
        Sequence[object], _litellm.callbacks
    )
    return tuple(
        cast(ProjectQuotaCallback, callback)  # cast-ok: required callback method is callable
        for callback in callbacks
        if callable(getattr(callback, "enforce_project_io_token_quota_for_frame", None))
    )


class BaseLLMHTTPHandler:
    async def _make_common_async_call(
        self,
        async_httpx_client: AsyncHTTPHandler,
        provider_config: BaseConfig,
        api_base: str,
        headers: dict,
        data: dict,
        timeout: float | httpx.Timeout,
        litellm_params: dict,
        logging_obj: LiteLLMLoggingObj,
        stream: bool = False,
        signed_json_body: bytes | None = None,
    ) -> httpx.Response:
        """Common implementation across stream + non-stream calls. Meant to ensure consistent error-handling."""
        max_retry_on_unprocessable_entity_error: Final = provider_config.max_retry_on_unprocessable_entity_error

        response: httpx.Response | None = None
        for i in range(max(max_retry_on_unprocessable_entity_error, 1)):
            try:
                response = await async_httpx_client.post(
                    url=api_base,
                    headers=headers,
                    data=(signed_json_body if signed_json_body is not None else json.dumps(data)),
                    timeout=timeout,
                    stream=stream,
                    logging_obj=logging_obj,
                )
            except httpx.HTTPStatusError as e:
                hit_max_retry = i + 1 == max_retry_on_unprocessable_entity_error
                should_retry = provider_config.should_retry_llm_api_inside_llm_translation_on_http_error(
                    e=e, litellm_params=litellm_params
                )
                if should_retry and not hit_max_retry:
                    data = provider_config.transform_request_on_unprocessable_entity_error(e=e, request_data=data)
                    continue
                else:
                    raise self._handle_error(e=e, provider_config=provider_config)
            except Exception as e:
                raise self._handle_error(e=e, provider_config=provider_config)
            break

        if response is None:
            raise provider_config.get_error_class(
                error_message="No response from the API",
                status_code=422,  # don't retry on this error
                headers={},
            )

        return response

    def _make_common_sync_call(
        self,
        sync_httpx_client: HTTPHandler,
        provider_config: BaseConfig,
        api_base: str,
        headers: dict,
        data: dict,
        timeout: float | httpx.Timeout,
        litellm_params: dict,
        logging_obj: LiteLLMLoggingObj,
        stream: bool = False,
        signed_json_body: bytes | None = None,
    ) -> httpx.Response:
        max_retry_on_unprocessable_entity_error: Final = provider_config.max_retry_on_unprocessable_entity_error

        response: httpx.Response | None = None

        for i in range(max(max_retry_on_unprocessable_entity_error, 1)):
            try:
                response = sync_httpx_client.post(
                    url=api_base,
                    headers=headers,
                    data=(signed_json_body if signed_json_body is not None else json.dumps(data)),
                    timeout=timeout,
                    stream=stream,
                    logging_obj=logging_obj,
                )
            except httpx.HTTPStatusError as e:
                hit_max_retry = i + 1 == max_retry_on_unprocessable_entity_error
                should_retry = provider_config.should_retry_llm_api_inside_llm_translation_on_http_error(
                    e=e, litellm_params=litellm_params
                )
                if should_retry and not hit_max_retry:
                    data = provider_config.transform_request_on_unprocessable_entity_error(e=e, request_data=data)
                    continue
                else:
                    raise self._handle_error(e=e, provider_config=provider_config)
            except Exception as e:
                raise self._handle_error(e=e, provider_config=provider_config)
            break

        if response is None:
            raise provider_config.get_error_class(
                error_message="No response from the API",
                status_code=422,  # don't retry on this error
                headers={},
            )

        return response

    async def async_completion(
        self,
        custom_llm_provider: str,
        provider_config: BaseConfig,
        api_base: str,
        headers: dict,
        data: dict,
        timeout: float | httpx.Timeout,
        model: str,
        model_response: ModelResponse,
        logging_obj: LiteLLMLoggingObj,
        messages: list,
        optional_params: dict,
        litellm_params: dict,
        encoding: "tiktoken.Encoding | None",
        api_key: str | None = None,
        client: AsyncHTTPHandler | None = None,
        json_mode: bool = False,
        signed_json_body: bytes | None = None,
        shared_session: Optional["ClientSession"] = None,
    ):
        if client is None:
            verbose_logger.debug(
                "Creating HTTP client with shared_session: %s", id(shared_session) if shared_session else None
            )
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
                shared_session=shared_session,
            )
        else:
            async_httpx_client = client

        response: Final = await self._make_common_async_call(
            async_httpx_client=async_httpx_client,
            provider_config=provider_config,
            api_base=api_base,
            headers=headers,
            data=data,
            timeout=timeout,
            litellm_params=litellm_params,
            stream=False,
            logging_obj=logging_obj,
            signed_json_body=signed_json_body,
        )
        initial_response: Final = provider_config.transform_response(
            model=model,
            raw_response=response,
            model_response=model_response,
            logging_obj=logging_obj,
            api_key=api_key,
            request_data=data,
            messages=messages,
            optional_params=optional_params,
            litellm_params=litellm_params,
            encoding=encoding,
            json_mode=json_mode,
        )

        # Call agentic chat completion hooks
        final_response: Final = await self._call_agentic_chat_completion_hooks(
            response=initial_response,
            model=model,
            messages=messages,
            optional_params=optional_params,
            logging_obj=logging_obj,
            stream=False,
            custom_llm_provider=custom_llm_provider,
            kwargs=litellm_params,
        )

        return final_response if final_response is not None else initial_response

    def completion(
        self,
        model: str,
        messages: list,
        api_base: str | None,
        custom_llm_provider: str,
        model_response: ModelResponse,
        encoding: "tiktoken.Encoding | None",
        logging_obj: LiteLLMLoggingObj,
        optional_params: dict,
        timeout: float | httpx.Timeout,
        litellm_params: dict,
        acompletion: bool,
        stream: bool | None = False,
        fake_stream: bool = False,
        api_key: str | None = None,
        headers: dict[str, Any] | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        provider_config: BaseConfig | None = None,
        shared_session: Optional["ClientSession"] = None,
    ):
        json_mode: Final[bool] = optional_params.pop("json_mode", False)
        extra_body: Final[dict | None] = optional_params.pop("extra_body", None)

        provider_config = provider_config or ProviderConfigManager.get_provider_chat_config(
            model=model, provider=litellm.LlmProviders(custom_llm_provider)
        )
        if provider_config is None:
            raise ValueError(f"Provider config not found for model: {model} and provider: {custom_llm_provider}")

        fake_stream = (
            fake_stream
            or optional_params.pop("fake_stream", False)
            or provider_config.should_fake_stream(model=model, custom_llm_provider=custom_llm_provider, stream=stream)
        )

        # get config from model, custom llm provider
        headers = provider_config.validate_environment(
            api_key=api_key,
            headers=headers or {},
            model=model,
            messages=messages,
            optional_params=optional_params,
            api_base=api_base,
            litellm_params=litellm_params,
        )

        api_base = provider_config.get_complete_url(
            api_base=api_base,
            api_key=api_key,
            model=model,
            optional_params=optional_params,
            stream=stream,
            litellm_params=litellm_params,
        )

        data: dict[str, object] = provider_config.transform_request(
            model=model,
            messages=messages,
            optional_params=optional_params,
            litellm_params=litellm_params,
            headers=headers,
        )

        if extra_body is not None:
            data = {**data, **extra_body}

        headers, signed_json_body = provider_config.sign_request(
            headers=headers,
            optional_params=optional_params,
            request_data=data,
            api_base=api_base,
            api_key=api_key,
            stream=stream,
            fake_stream=fake_stream,
            model=model,
        )

        ## LOGGING
        logging_obj.pre_call(
            input=messages,
            api_key=api_key,
            additional_args={
                "complete_input_dict": data,
                "api_base": api_base,
                "headers": headers,
            },
        )

        # Check if stream was converted for WebSearch interception
        # This is set by the async_pre_request_hook in WebSearchInterceptionLogger
        if litellm_params.get("_websearch_interception_converted_stream", False):
            logging_obj.model_call_details["websearch_interception_converted_stream"] = True

        if acompletion is True:
            if stream is True:
                data = self._add_stream_param_to_request_body(
                    data=data,
                    provider_config=provider_config,
                    fake_stream=fake_stream,
                )
                return self.acompletion_stream_function(
                    model=model,
                    messages=messages,
                    api_base=api_base,
                    headers=headers,
                    custom_llm_provider=custom_llm_provider,
                    provider_config=provider_config,
                    timeout=timeout,
                    logging_obj=logging_obj,
                    data=data,
                    fake_stream=fake_stream,
                    client=(client if client is not None and isinstance(client, AsyncHTTPHandler) else None),
                    litellm_params=litellm_params,
                    json_mode=json_mode,
                    optional_params=optional_params,
                    signed_json_body=signed_json_body,
                )

            else:
                return self.async_completion(
                    custom_llm_provider=custom_llm_provider,
                    provider_config=provider_config,
                    api_base=api_base,
                    headers=headers,
                    data=data,
                    timeout=timeout,
                    model=model,
                    model_response=model_response,
                    logging_obj=logging_obj,
                    api_key=api_key,
                    messages=messages,
                    optional_params=optional_params,
                    litellm_params=litellm_params,
                    encoding=encoding,
                    client=(client if client is not None and isinstance(client, AsyncHTTPHandler) else None),
                    json_mode=json_mode,
                    signed_json_body=signed_json_body,
                    shared_session=shared_session,
                )

        if stream is True:
            data = self._add_stream_param_to_request_body(
                data=data,
                provider_config=provider_config,
                fake_stream=fake_stream,
            )
            if provider_config.has_custom_stream_wrapper is True:
                return provider_config.get_sync_custom_stream_wrapper(
                    model=model,
                    custom_llm_provider=custom_llm_provider,
                    logging_obj=logging_obj,
                    api_base=api_base,
                    headers=headers,
                    data=data,
                    signed_json_body=signed_json_body,
                    messages=messages,
                    client=client,
                    json_mode=json_mode,
                )
            completion_stream, headers = self.make_sync_call(
                provider_config=provider_config,
                api_base=api_base,
                headers=headers,
                data=data,
                signed_json_body=signed_json_body,
                original_data=data,
                model=model,
                messages=messages,
                logging_obj=logging_obj,
                timeout=timeout,
                fake_stream=fake_stream,
                client=(client if client is not None and isinstance(client, HTTPHandler) else None),
                litellm_params=litellm_params,
                json_mode=json_mode,
                optional_params=optional_params,
            )
            return CustomStreamWrapper(
                completion_stream=completion_stream,
                model=model,
                custom_llm_provider=custom_llm_provider,
                logging_obj=logging_obj,
                _response_headers=headers,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            sync_httpx_client = client

        response: Final = self._make_common_sync_call(
            sync_httpx_client=sync_httpx_client,
            provider_config=provider_config,
            api_base=api_base,
            headers=headers,
            data=data,
            signed_json_body=signed_json_body,
            timeout=timeout,
            litellm_params=litellm_params,
            logging_obj=logging_obj,
        )
        return provider_config.transform_response(
            model=model,
            raw_response=response,
            model_response=model_response,
            logging_obj=logging_obj,
            api_key=api_key,
            request_data=data,
            messages=messages,
            optional_params=optional_params,
            litellm_params=litellm_params,
            encoding=encoding,
            json_mode=json_mode,
        )

    def make_sync_call(
        self,
        provider_config: BaseConfig,
        api_base: str,
        headers: dict,
        data: dict,
        signed_json_body: bytes | None,
        original_data: dict,
        model: str,
        messages: list,
        logging_obj,
        optional_params: dict,
        litellm_params: dict,
        timeout: float | httpx.Timeout,
        fake_stream: bool = False,
        client: HTTPHandler | None = None,
        json_mode: bool = False,
    ) -> tuple[object, dict]:
        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(
                {
                    "ssl_verify": litellm_params.get("ssl_verify", None),
                }
            )
        else:
            sync_httpx_client = client
        stream = True
        if fake_stream is True:
            stream = False

        response: Final = self._make_common_sync_call(
            sync_httpx_client=sync_httpx_client,
            provider_config=provider_config,
            api_base=api_base,
            headers=headers,
            data=data,
            signed_json_body=signed_json_body,
            timeout=timeout,
            litellm_params=litellm_params,
            stream=stream,
            logging_obj=logging_obj,
        )

        if fake_stream is True:
            model_response: Final[ModelResponse] = provider_config.transform_response(
                model=model,
                raw_response=response,
                model_response=litellm.ModelResponse(),
                logging_obj=logging_obj,
                request_data=original_data,
                messages=messages,
                optional_params=optional_params,
                litellm_params=litellm_params,
                encoding=None,
                json_mode=json_mode,
            )

            completion_stream: object = MockResponseIterator(model_response=model_response, json_mode=json_mode)
        else:
            completion_stream = provider_config.get_model_response_iterator(
                streaming_response=response.iter_lines(),
                sync_stream=True,
                json_mode=json_mode,
            )

        # LOGGING
        logging_obj.post_call(
            input=messages,
            api_key="",
            original_response="first stream response received",
            additional_args={"complete_input_dict": data},
        )

        return completion_stream, dict(response.headers)

    async def acompletion_stream_function(
        self,
        model: str,
        messages: list,
        api_base: str,
        custom_llm_provider: str,
        headers: dict,
        provider_config: BaseConfig,
        timeout: float | httpx.Timeout,
        logging_obj: LiteLLMLoggingObj,
        data: dict,
        litellm_params: dict,
        optional_params: dict,
        fake_stream: bool = False,
        client: AsyncHTTPHandler | None = None,
        json_mode: bool | None = None,
        signed_json_body: bytes | None = None,
    ):
        if provider_config.has_custom_stream_wrapper is True:
            return await provider_config.get_async_custom_stream_wrapper(
                model=model,
                custom_llm_provider=custom_llm_provider,
                logging_obj=logging_obj,
                api_base=api_base,
                headers=headers,
                data=data,
                messages=messages,
                client=client,
                json_mode=json_mode,
                signed_json_body=signed_json_body,
            )

        completion_stream, _response_headers = await self.make_async_call_stream_helper(
            model=model,
            custom_llm_provider=custom_llm_provider,
            provider_config=provider_config,
            api_base=api_base,
            headers=headers,
            data=data,
            messages=messages,
            logging_obj=logging_obj,
            timeout=timeout,
            fake_stream=fake_stream,
            client=client,
            litellm_params=litellm_params,
            optional_params=optional_params,
            json_mode=json_mode,
            signed_json_body=signed_json_body,
        )
        streamwrapper: Final = CustomStreamWrapper(
            completion_stream=completion_stream,
            model=model,
            custom_llm_provider=custom_llm_provider,
            logging_obj=logging_obj,
            _response_headers=_response_headers,
        )
        return streamwrapper

    async def make_async_call_stream_helper(
        self,
        model: str,
        custom_llm_provider: str,
        provider_config: BaseConfig,
        api_base: str,
        headers: dict,
        data: dict,
        messages: list,
        logging_obj: LiteLLMLoggingObj,
        timeout: float | httpx.Timeout,
        litellm_params: dict,
        optional_params: dict,
        fake_stream: bool = False,
        client: AsyncHTTPHandler | None = None,
        json_mode: bool | None = None,
        signed_json_body: bytes | None = None,
    ) -> tuple[object, httpx.Headers]:
        """
        Helper function for making an async call with stream.

        Handles fake stream as well.
        """
        if client is None:
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client
        stream = True
        if fake_stream is True:
            stream = False

        response: Final = await self._make_common_async_call(
            async_httpx_client=async_httpx_client,
            provider_config=provider_config,
            api_base=api_base,
            headers=headers,
            data=data,
            signed_json_body=signed_json_body,
            timeout=timeout,
            litellm_params=litellm_params,
            stream=stream,
            logging_obj=logging_obj,
        )

        if fake_stream is True:
            model_response: Final[ModelResponse] = provider_config.transform_response(
                model=model,
                raw_response=response,
                model_response=litellm.ModelResponse(),
                logging_obj=logging_obj,
                request_data=data,
                messages=messages,
                optional_params=optional_params,
                litellm_params=litellm_params,
                encoding=None,
                json_mode=json_mode,
            )

            completion_stream: object = MockResponseIterator(model_response=model_response, json_mode=json_mode)
        else:
            completion_stream = provider_config.get_model_response_iterator(
                streaming_response=response.aiter_lines(), sync_stream=False
            )
            if isinstance(completion_stream, BaseModelResponseIterator):
                completion_stream.http_response = response
        # LOGGING
        logging_obj.post_call(
            input=messages,
            api_key="",
            original_response="first stream response received",
            additional_args={"complete_input_dict": data},
        )

        return completion_stream, response.headers

    def _add_stream_param_to_request_body(
        self,
        data: dict[str, object],
        provider_config: BaseConfig,
        fake_stream: bool,
    ) -> dict[str, object]:
        """
        Some providers like Bedrock invoke do not support the stream parameter in the request body, we only pass `stream` in the request body the provider supports it.
        """

        if fake_stream is True:
            # remove 'stream' from data
            new_data: Final = data.copy()
            new_data.pop("stream", None)
            return new_data
        if provider_config.supports_stream_param_in_request_body is True:
            data["stream"] = True
        return data

    def embedding(
        self,
        model: str,
        input: list,
        timeout: float,
        custom_llm_provider: str,
        logging_obj: LiteLLMLoggingObj,
        api_base: str | None,
        optional_params: dict,
        litellm_params: dict,
        model_response: EmbeddingResponse,
        api_key: str | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        aembedding: bool | None = False,
        headers: dict[str, Any] | None = None,
    ) -> EmbeddingResponse:
        provider_config: Final = ProviderConfigManager.get_provider_embedding_config(
            model=model, provider=litellm.LlmProviders(custom_llm_provider)
        )
        if provider_config is None:
            raise ValueError(f"Provider {custom_llm_provider} does not support embedding")
        embedding_extra_body: Final[Mapping[str, object] | None] = optional_params.pop("extra_body", None)
        # get config from model, custom llm provider
        headers = provider_config.validate_environment(
            api_key=api_key,
            headers=headers or {},
            model=model,
            messages=[],
            optional_params=optional_params,
            litellm_params=litellm_params,
        )

        api_base = provider_config.get_complete_url(
            api_base=api_base,
            api_key=api_key,
            model=model,
            optional_params=optional_params,
            litellm_params=litellm_params,
        )

        data: Final = provider_config.transform_embedding_request(
            model=model,
            input=input,
            optional_params=optional_params,
            headers=headers,
        )
        if embedding_extra_body:
            data.update(embedding_extra_body)

        # Some providers (e.g. OCI) require request signing after the body is built.
        # The default BaseConfig.sign_request returns (headers, None) — a no-op for
        # providers that don't need signing.
        headers, signed_body = provider_config.sign_request(
            headers=headers,
            optional_params=optional_params,
            request_data=data,
            api_base=api_base,
            api_key=api_key,
            model=model,
        )

        ## LOGGING
        logging_obj.pre_call(
            input=input,
            api_key=api_key,
            additional_args={
                "complete_input_dict": data,
                "api_base": api_base,
                "headers": headers,
            },
        )

        if aembedding is True:
            return self.aembedding(
                request_data=data,
                api_base=api_base,
                headers=headers,
                model=model,
                custom_llm_provider=custom_llm_provider,
                provider_config=provider_config,
                model_response=model_response,
                logging_obj=logging_obj,
                api_key=api_key,
                timeout=timeout,
                client=client,
                optional_params=optional_params,
                litellm_params=litellm_params,
                signed_body=signed_body,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        try:
            if signed_body is not None:
                response = sync_httpx_client.post(
                    url=api_base,
                    headers=headers,
                    data=signed_body,
                    timeout=timeout,
                )
            else:
                response = sync_httpx_client.post(
                    url=api_base,
                    headers=headers,
                    data=json.dumps(data),
                    timeout=timeout,
                )
        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=provider_config,
            )

        return provider_config.transform_embedding_response(
            model=model,
            raw_response=response,
            model_response=model_response,
            logging_obj=logging_obj,
            api_key=api_key,
            request_data=data,
            optional_params=optional_params,
            litellm_params=litellm_params,
        )

    async def aembedding(
        self,
        request_data: dict,
        api_base: str,
        headers: dict,
        model: str,
        custom_llm_provider: str,
        provider_config: BaseEmbeddingConfig,
        model_response: EmbeddingResponse,
        logging_obj: LiteLLMLoggingObj,
        optional_params: dict,
        litellm_params: dict,
        api_key: str | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        signed_body: bytes | None = None,
    ) -> EmbeddingResponse:
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        try:
            if signed_body is not None:
                response = await async_httpx_client.post(
                    url=api_base,
                    headers=headers,
                    data=signed_body,
                    timeout=timeout,
                )
            else:
                response = await async_httpx_client.post(
                    url=api_base,
                    headers=headers,
                    json=request_data,
                    timeout=timeout,
                )
        except Exception as e:
            raise self._handle_error(e=e, provider_config=provider_config)

        return provider_config.transform_embedding_response(
            model=model,
            raw_response=response,
            model_response=model_response,
            logging_obj=logging_obj,
            api_key=api_key,
            request_data=request_data,
            optional_params=optional_params,
            litellm_params=litellm_params,
        )

    def rerank(
        self,
        model: str,
        custom_llm_provider: str,
        logging_obj: LiteLLMLoggingObj,
        provider_config: BaseRerankConfig,
        optional_rerank_params: dict,
        timeout: float | httpx.Timeout | None,
        model_response: RerankResponse,
        _is_async: bool = False,
        headers: dict[str, object] | None = None,
        api_key: str | None = None,
        api_base: str | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        litellm_params: dict[str, Any] | None = None,
    ) -> RerankResponse:
        # get config from model, custom llm provider
        headers = provider_config.validate_environment(
            api_key=api_key,
            headers=headers or {},
            model=model,
            optional_params=optional_rerank_params,
            litellm_params=litellm_params,
        )

        api_base = provider_config.get_complete_url(
            api_base=api_base,
            model=model,
            optional_params=optional_rerank_params,
        )

        data: Final = provider_config.transform_rerank_request(
            model=model,
            optional_rerank_params=optional_rerank_params,
            headers=headers,
            litellm_params=litellm_params,
        )

        ## LOGGING
        logging_obj.pre_call(
            input=optional_rerank_params.get("query", ""),
            api_key=api_key,
            additional_args={
                "complete_input_dict": data,
                "api_base": api_base,
                "headers": headers,
            },
        )

        if _is_async is True:
            return self.arerank(
                model=model,
                request_data=data,
                custom_llm_provider=custom_llm_provider,
                provider_config=provider_config,
                logging_obj=logging_obj,
                model_response=model_response,
                api_base=api_base,
                headers=headers,
                api_key=api_key,
                timeout=timeout,
                client=client,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client()
        else:
            sync_httpx_client = client

        try:
            response: Final = sync_httpx_client.post(
                url=api_base,
                headers=headers,
                data=json.dumps(data),
                timeout=timeout,
            )
        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=provider_config,
            )

        return provider_config.transform_rerank_response(
            model=model,
            raw_response=response,
            model_response=model_response,
            logging_obj=logging_obj,
            api_key=api_key,
            request_data=data,
        )

    async def arerank(
        self,
        model: str,
        request_data: dict,
        custom_llm_provider: str,
        provider_config: BaseRerankConfig,
        logging_obj: LiteLLMLoggingObj,
        model_response: RerankResponse,
        api_base: str,
        headers: dict,
        api_key: str | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
    ) -> RerankResponse:
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(llm_provider=litellm.LlmProviders(custom_llm_provider))
        else:
            async_httpx_client = client
        try:
            response: Final = await async_httpx_client.post(
                url=api_base,
                headers=headers,
                data=json.dumps(request_data),
                timeout=timeout,
                logging_obj=logging_obj,
            )
        except Exception as e:
            raise self._handle_error(e=e, provider_config=provider_config)

        return provider_config.transform_rerank_response(
            model=model,
            raw_response=response,
            model_response=model_response,
            logging_obj=logging_obj,
            api_key=api_key,
            request_data=request_data,
        )

    def _prepare_audio_transcription_request(
        self,
        model: str,
        audio_file: FileTypes,
        optional_params: dict,
        litellm_params: dict,
        logging_obj: LiteLLMLoggingObj,
        api_key: str | None,
        api_base: str | None,
        headers: dict[str, object] | None,
        provider_config: BaseAudioTranscriptionConfig,
    ) -> tuple[dict, str, dict | bytes | None, dict | None]:
        """
        Shared logic for preparing audio transcription requests.
        Returns: (headers, complete_url, data, files)
        """
        # Handle the response based on type
        from litellm.llms.base_llm.audio_transcription.transformation import (
            AudioTranscriptionRequestData,
        )

        headers = provider_config.validate_environment(
            api_key=api_key,
            headers=headers or {},
            model=model,
            messages=[],
            optional_params=optional_params,
            litellm_params=litellm_params,
        )

        complete_url: Final = provider_config.get_complete_url(
            api_base=api_base,
            api_key=api_key,
            model=model,
            optional_params=optional_params,
            litellm_params=litellm_params,
        )

        # Transform the request to get data
        transformed_result: Final = provider_config.transform_audio_transcription_request(
            model=model,
            audio_file=audio_file,
            optional_params=optional_params,
            litellm_params=litellm_params,
        )

        # All providers now return AudioTranscriptionRequestData
        if not isinstance(transformed_result, AudioTranscriptionRequestData):
            raise ValueError(f"Provider {provider_config.__class__.__name__} must return AudioTranscriptionRequestData")

        data: Final = transformed_result.data
        files: Final = transformed_result.files
        if transformed_result.content_type is not None:
            headers["Content-Type"] = transformed_result.content_type

        ## LOGGING
        logging_obj.pre_call(
            input=optional_params.get("query", ""),
            api_key=api_key,
            additional_args={
                "complete_input_dict": data or {},
                "api_base": complete_url,
                "headers": headers,
            },
        )

        return headers, complete_url, data, files

    def _transform_audio_transcription_response(
        self,
        provider_config: BaseAudioTranscriptionConfig,
        model: str,
        response: httpx.Response,
        model_response: TranscriptionResponse,
        logging_obj: LiteLLMLoggingObj,
        optional_params: dict,
        api_key: str | None,
    ) -> TranscriptionResponse:
        """Shared logic for transforming audio transcription responses."""
        transformed: Final = provider_config.transform_audio_transcription_response(
            raw_response=response,
        )
        if not provider_config.supports_subtitle_synthesis:
            return transformed
        requested_format: Final = optional_params.get("response_format")
        if not isinstance(requested_format, str) or requested_format not in SUBTITLE_RESPONSE_FORMATS:
            return transformed
        document: Final = synthesize_subtitle_document(
            words=transformed.get("words"),
            response_format=requested_format,
        )
        if document is not None:
            transformed.text = document
        if "words" in transformed:
            delattr(transformed, "words")
        return transformed

    def audio_transcriptions(
        self,
        model: str,
        audio_file: FileTypes,
        optional_params: dict,
        litellm_params: dict,
        model_response: TranscriptionResponse,
        timeout: float,
        max_retries: int,
        logging_obj: LiteLLMLoggingObj,
        api_key: str | None,
        api_base: str | None,
        custom_llm_provider: str,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        atranscription: bool = False,
        headers: dict[str, object] | None = None,
        provider_config: BaseAudioTranscriptionConfig | None = None,
        shared_session: Optional["ClientSession"] = None,
    ) -> TranscriptionResponse | Coroutine[object, object, TranscriptionResponse]:
        if provider_config is None:
            raise ValueError(f"No provider config found for model: {model} and provider: {custom_llm_provider}")

        if atranscription is True:
            return self.async_audio_transcriptions(
                model=model,
                audio_file=audio_file,
                optional_params=optional_params,
                litellm_params=litellm_params,
                model_response=model_response,
                timeout=timeout,
                max_retries=max_retries,
                logging_obj=logging_obj,
                api_key=api_key,
                api_base=api_base,
                custom_llm_provider=custom_llm_provider,
                client=client,
                headers=headers,
                provider_config=provider_config,
                shared_session=shared_session,
            )

        # Prepare the request
        (
            headers,
            complete_url,
            data,
            files,
        ) = self._prepare_audio_transcription_request(
            model=model,
            audio_file=audio_file,
            optional_params=optional_params,
            litellm_params=litellm_params,
            logging_obj=logging_obj,
            api_key=api_key,
            api_base=api_base,
            headers=headers,
            provider_config=provider_config,
        )

        if client is None or not isinstance(client, HTTPHandler):
            client = _get_httpx_client()

        json_data: Final = data if files is None and isinstance(data, dict) else None

        try:
            response: Final = client.post(
                url=complete_url,
                headers=headers,
                data=data if json_data is None else None,
                files=files,
                json=json_data,
                timeout=timeout,
            )
        except Exception as e:
            raise self._handle_error(e=e, provider_config=provider_config)

        return self._transform_audio_transcription_response(
            provider_config=provider_config,
            model=model,
            response=response,
            model_response=model_response,
            logging_obj=logging_obj,
            optional_params=optional_params,
            api_key=api_key,
        )

    async def async_audio_transcriptions(
        self,
        model: str,
        audio_file: FileTypes,
        optional_params: dict,
        litellm_params: dict,
        model_response: TranscriptionResponse,
        timeout: float,
        max_retries: int,
        logging_obj: LiteLLMLoggingObj,
        api_key: str | None,
        api_base: str | None,
        custom_llm_provider: str,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        headers: dict[str, object] | None = None,
        provider_config: BaseAudioTranscriptionConfig | None = None,
        shared_session: Optional["ClientSession"] = None,
    ) -> TranscriptionResponse:
        if provider_config is None:
            raise ValueError(f"No provider config found for model: {model} and provider: {custom_llm_provider}")

        # Prepare the request
        (
            headers,
            complete_url,
            data,
            files,
        ) = self._prepare_audio_transcription_request(
            model=model,
            audio_file=audio_file,
            optional_params=optional_params,
            litellm_params=litellm_params,
            logging_obj=logging_obj,
            api_key=api_key,
            api_base=api_base,
            headers=headers,
            provider_config=provider_config,
        )

        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
                shared_session=shared_session,
            )
        else:
            async_httpx_client = client

        json_data: Final = data if files is None and isinstance(data, dict) else None

        try:
            response: Final = await async_httpx_client.post(
                url=complete_url,
                headers=headers,
                data=data if json_data is None else None,
                files=files,
                json=json_data,
                timeout=timeout,
            )
        except Exception as e:
            raise self._handle_error(e=e, provider_config=provider_config)

        return self._transform_audio_transcription_response(
            provider_config=provider_config,
            model=model,
            response=response,
            model_response=model_response,
            logging_obj=logging_obj,
            optional_params=optional_params,
            api_key=api_key,
        )

    def _prepare_ocr_request(
        self,
        model: str,
        document: dict[str, str],
        optional_params: dict,
        logging_obj: LiteLLMLoggingObj,
        api_key: str | None,
        api_base: str | None,
        headers: dict[str, object] | None,
        provider_config: BaseOCRConfig,
        litellm_params: dict,
    ) -> tuple[dict[str, object], str, dict[str, object], None]:
        """
        Shared logic for preparing OCR requests.
        Returns: (headers, complete_url, data, files)
        """
        from litellm.llms.base_llm.ocr.transformation import OCRRequestData

        headers = provider_config.validate_environment(
            api_key=api_key,
            api_base=api_base,
            headers=headers or {},
            model=model,
            litellm_params=litellm_params,
        )

        complete_url: Final = provider_config.get_complete_url(
            api_base=api_base,
            model=model,
            optional_params=optional_params,
            litellm_params=litellm_params,
        )

        # Transform the request to get data and files
        transformed_result: Final = provider_config.transform_ocr_request(
            model=model,
            document=document,
            optional_params=optional_params,
            headers=headers,
            api_key=api_key,
            api_base=api_base,
        )

        # All providers return OCRRequestData
        if not isinstance(transformed_result, OCRRequestData):
            raise ValueError(f"Provider {provider_config.__class__.__name__} must return OCRRequestData")

        # Data is always a dict for Mistral OCR format
        if not isinstance(transformed_result.data, dict):
            raise ValueError(f"Expected dict data for OCR request, got {type(transformed_result.data)}")

        data: Final = transformed_result.data

        ## LOGGING
        logging_obj.pre_call(
            input="OCR document processing",
            api_key=api_key,
            additional_args={
                "complete_input_dict": data,
                "api_base": complete_url,
                "headers": headers,
            },
        )

        return headers, complete_url, data, None

    async def _async_prepare_ocr_request(
        self,
        model: str,
        document: dict[str, str],
        optional_params: dict,
        logging_obj: LiteLLMLoggingObj,
        api_key: str | None,
        api_base: str | None,
        headers: dict[str, object] | None,
        provider_config: BaseOCRConfig,
        litellm_params: dict,
    ) -> tuple[dict[str, object], str, dict[str, object], None]:
        """
        Async version of _prepare_ocr_request for providers that need async transforms.
        Returns: (headers, complete_url, data, files)
        """
        from litellm.llms.base_llm.ocr.transformation import OCRRequestData

        headers = provider_config.validate_environment(
            api_key=api_key,
            api_base=api_base,
            headers=headers or {},
            model=model,
            litellm_params=litellm_params,
        )

        complete_url: Final = provider_config.get_complete_url(
            api_base=api_base,
            model=model,
            optional_params=optional_params,
            litellm_params=litellm_params,
        )

        # Use async transform (providers can override this method if they need async operations)
        transformed_result: Final = await provider_config.async_transform_ocr_request(
            model=model,
            document=document,
            optional_params=optional_params,
            headers=headers,
            api_key=api_key,
            api_base=api_base,
        )

        # All providers return OCRRequestData
        if not isinstance(transformed_result, OCRRequestData):
            raise ValueError(f"Provider {provider_config.__class__.__name__} must return OCRRequestData")

        # Data is always a dict for Mistral OCR format
        if not isinstance(transformed_result.data, dict):
            raise ValueError(f"Expected dict data for OCR request, got {type(transformed_result.data)}")

        data: Final = transformed_result.data

        ## LOGGING
        logging_obj.pre_call(
            input="OCR document processing",
            api_key=api_key,
            additional_args={
                "complete_input_dict": data,
                "api_base": complete_url,
                "headers": headers,
            },
        )

        return headers, complete_url, data, None

    def _transform_ocr_response(
        self,
        provider_config: BaseOCRConfig,
        model: str,
        response: httpx.Response,
        logging_obj: LiteLLMLoggingObj,
        optional_params: Mapping[str, object],
    ) -> OCRResponse:
        """Shared logic for transforming OCR responses."""
        return provider_config.transform_ocr_response(
            model=model,
            raw_response=response,
            logging_obj=logging_obj,
            optional_params=optional_params,
        )

    def ocr(
        self,
        model: str,
        document: dict[str, str],
        optional_params: dict,
        timeout: float | httpx.Timeout,
        logging_obj: LiteLLMLoggingObj,
        api_key: str | None,
        api_base: str | None,
        custom_llm_provider: str,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        aocr: bool = False,
        headers: dict[str, object] | None = None,
        provider_config: BaseOCRConfig | None = None,
        litellm_params: dict | None = None,
    ) -> OCRResponse | Coroutine[object, object, OCRResponse]:
        """
        Sync OCR handler.
        """
        if provider_config is None:
            raise ValueError(f"No provider config found for model: {model} and provider: {custom_llm_provider}")

        if litellm_params is None:
            litellm_params = {}

        if aocr is True:
            return self.async_ocr(
                model=model,
                document=document,
                optional_params=optional_params,
                timeout=timeout,
                logging_obj=logging_obj,
                api_key=api_key,
                api_base=api_base,
                custom_llm_provider=custom_llm_provider,
                client=client,
                headers=headers,
                provider_config=provider_config,
                litellm_params=litellm_params,
            )

        # Prepare the request
        headers, complete_url, data, files = self._prepare_ocr_request(
            model=model,
            document=document,
            optional_params=optional_params,
            logging_obj=logging_obj,
            api_key=api_key,
            api_base=api_base,
            headers=headers,
            provider_config=provider_config,
            litellm_params=litellm_params,
        )

        if client is None or not isinstance(client, HTTPHandler):
            client = _get_httpx_client()

        try:
            # Make the POST request with JSON data (Mistral format)
            response: Final = client.post(
                url=complete_url,
                headers=headers,
                json=data,
                timeout=timeout,
            )
        except Exception as e:
            raise self._handle_error(e=e, provider_config=provider_config)

        return self._transform_ocr_response(
            provider_config=provider_config,
            model=model,
            response=response,
            logging_obj=logging_obj,
            optional_params=optional_params,
        )

    async def async_ocr(
        self,
        model: str,
        document: dict[str, str],
        optional_params: dict,
        timeout: float | httpx.Timeout,
        logging_obj: LiteLLMLoggingObj,
        api_key: str | None,
        api_base: str | None,
        custom_llm_provider: str,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        headers: dict[str, object] | None = None,
        provider_config: BaseOCRConfig | None = None,
        litellm_params: dict | None = None,
    ) -> OCRResponse:
        """
        Async OCR handler.
        """
        if provider_config is None:
            raise ValueError(f"No provider config found for model: {model} and provider: {custom_llm_provider}")

        if litellm_params is None:
            litellm_params = {}

        # Prepare the request using async prepare method
        headers, complete_url, data, files = await self._async_prepare_ocr_request(
            model=model,
            document=document,
            optional_params=optional_params,
            logging_obj=logging_obj,
            api_key=api_key,
            api_base=api_base,
            headers=headers,
            provider_config=provider_config,
            litellm_params=litellm_params,
        )

        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
            )
        else:
            async_httpx_client = client

        try:
            # Make the async POST request with JSON data (Mistral format)
            response: Final = await async_httpx_client.post(
                url=complete_url,
                headers=headers,
                json=data,
                timeout=timeout,
            )
        except Exception as e:
            raise self._handle_error(e=e, provider_config=provider_config)

        # Use async response transform for async operations
        return await provider_config.async_transform_ocr_response(
            model=model,
            raw_response=response,
            logging_obj=logging_obj,
            optional_params=optional_params,
        )

    def search(
        self,
        query: str | list[str],
        optional_params: dict,
        timeout: float | httpx.Timeout,
        logging_obj: LiteLLMLoggingObj,
        api_key: str | None,
        api_base: str | None,
        custom_llm_provider: str,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        asearch: bool = False,
        headers: dict[str, object] | None = None,
        provider_config: BaseSearchConfig | None = None,
    ) -> SearchResponse | Coroutine[object, object, SearchResponse]:
        """
        Sync Search handler.
        """
        if provider_config is None:
            raise ValueError(f"No provider config found for provider: {custom_llm_provider}")

        if asearch is True:
            return self.async_search(
                query=query,
                optional_params=optional_params,
                timeout=timeout,
                logging_obj=logging_obj,
                api_key=api_key,
                api_base=api_base,
                custom_llm_provider=custom_llm_provider,
                client=client,
                headers=headers,
                provider_config=provider_config,
            )

        # Validate environment and get headers
        headers = provider_config.validate_environment(
            api_key=api_key,
            api_base=api_base,
            headers=headers or {},
        )

        # Transform the request
        data: Final = provider_config.transform_search_request(
            query=query,
            optional_params=optional_params,
        )

        # Get complete URL (pass data for providers that need request body for URL construction)
        complete_url: Final = provider_config.get_complete_url(
            api_base=api_base,
            optional_params=optional_params,
            data=data,
            api_key=api_key,
        )

        signed_headers, signed_json_body = provider_config.sign_request(
            headers=headers,
            optional_params=optional_params,
            request_data=data,
            api_base=complete_url,
            api_key=api_key,
        )

        ## LOGGING
        logging_obj.pre_call(
            input=query if isinstance(query, str) else str(query),
            api_key=api_key,
            additional_args={
                "complete_input_dict": data,
                "api_base": complete_url,
                "headers": headers,
            },
        )

        if client is None or not isinstance(client, HTTPHandler):
            client = _get_httpx_client()

        # Check HTTP method from provider config
        http_method: Final = provider_config.get_http_method()

        try:
            if http_method == "GET":
                # Make GET request (URL already contains query params from get_complete_url)
                # Note: timeout is set on the client itself, not per-request for GET
                response = client.get(
                    url=complete_url,
                    headers=signed_headers,
                )
            else:
                # A signed body must be sent verbatim, re-serializing it would break the signature
                response = client.post(
                    url=complete_url,
                    headers=signed_headers,
                    data=signed_json_body,
                    json=data if signed_json_body is None else None,
                    timeout=timeout,
                )
        except Exception as e:
            raise self._handle_error(e=e, provider_config=provider_config)

        return provider_config.transform_search_response(
            raw_response=response,
            logging_obj=logging_obj,
            optional_params=optional_params,
        )

    async def async_search(
        self,
        query: str | list[str],
        optional_params: dict,
        timeout: float | httpx.Timeout,
        logging_obj: LiteLLMLoggingObj,
        api_key: str | None,
        api_base: str | None,
        custom_llm_provider: str,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        headers: dict[str, object] | None = None,
        provider_config: BaseSearchConfig | None = None,
    ) -> SearchResponse:
        """
        Async Search handler.
        """
        if provider_config is None:
            raise ValueError(f"No provider config found for provider: {custom_llm_provider}")

        # Validate environment and get headers
        headers = provider_config.validate_environment(
            api_key=api_key,
            api_base=api_base,
            headers=headers or {},
        )

        # Transform the request first
        data: Final = provider_config.transform_search_request(
            query=query,
            optional_params=optional_params,
            api_key=api_key,
            api_base=api_base,
            headers=headers or {},
        )

        # Get complete URL (pass data for providers that need request body for URL construction)
        complete_url: Final = provider_config.get_complete_url(
            api_base=api_base,
            optional_params=optional_params,
            data=data,
            api_key=api_key,
        )

        signed_headers, signed_json_body = provider_config.sign_request(
            headers=headers,
            optional_params=optional_params,
            request_data=data,
            api_base=complete_url,
            api_key=api_key,
        )

        ## LOGGING
        logging_obj.pre_call(
            input=query if isinstance(query, str) else str(query),
            api_key=api_key,
            additional_args={
                "complete_input_dict": data,
                "api_base": complete_url,
                "headers": headers,
            },
        )

        if client is None or not isinstance(client, AsyncHTTPHandler):
            # For search providers, use special Search provider type
            from litellm.types.llms.custom_http import httpxSpecialProvider

            async_httpx_client = get_async_httpx_client(llm_provider=httpxSpecialProvider.Search)
        else:
            async_httpx_client = client

        # Check HTTP method from provider config
        http_method: Final = provider_config.get_http_method().upper()

        try:
            if http_method == "GET":
                # Make async GET request (URL already contains query params from get_complete_url)
                # Note: timeout is set on the client itself, not per-request for GET
                response = await async_httpx_client.get(
                    url=complete_url,
                    headers=signed_headers,
                )
            else:
                # A signed body must be sent verbatim, re-serializing it would break the signature
                response = await async_httpx_client.post(
                    url=complete_url,
                    headers=signed_headers,
                    data=signed_json_body,
                    json=data if signed_json_body is None else None,
                    timeout=timeout,
                )
        except Exception as e:
            raise self._handle_error(e=e, provider_config=provider_config)

        return provider_config.transform_search_response(
            raw_response=response,
            logging_obj=logging_obj,
            optional_params=optional_params,
        )

    async def _async_post_anthropic_messages_with_http_error_retry(
        self,
        async_httpx_client: AsyncHTTPHandler,
        request_url: str,
        headers: dict,
        # str when the caller passes a pre-serialized (unsigned) body to avoid
        # re-dumping; bytes when a provider signed the request (e.g. Bedrock).
        signed_json_body: str | bytes | None,
        request_body: dict,
        stream: bool,
        logging_obj: LiteLLMLoggingObj,
        provider_config: BaseAnthropicMessagesConfig,
        litellm_params: GenericLiteLLMParams,
        api_key: str | None,
        model: str,
        timeout: float | httpx.Timeout | None = None,
    ) -> httpx.Response:
        max_attempts: Final = max(provider_config.max_retry_on_anthropic_messages_http_error, 1)
        litellm_params_dict: Final = dict(litellm_params)
        optional_params_dict: Final = dict(litellm_params)
        for attempt_idx in range(max_attempts):
            try:
                response = await async_httpx_client.post(
                    url=request_url,
                    headers=headers,
                    data=signed_json_body or json.dumps(request_body),
                    stream=stream or False,
                    logging_obj=logging_obj,
                    timeout=timeout,
                )
                response.raise_for_status()
                return response
            except httpx.HTTPStatusError as e:
                hit_max_attempt = attempt_idx + 1 == max_attempts
                should_retry = provider_config.should_retry_anthropic_messages_on_http_error(
                    e=e, litellm_params=litellm_params_dict
                )
                if should_retry and not hit_max_attempt:
                    verbose_logger.debug(
                        "Anthropic /v1/messages: invalid thinking signature; "
                        "stripping thinking blocks and retrying (attempt %s/%s).",
                        attempt_idx + 2,
                        max_attempts,
                    )
                    provider_config.transform_anthropic_messages_request_on_http_error(e=e, request_data=request_body)
                    headers, signed_json_body = provider_config.sign_request(
                        headers=headers,
                        optional_params=optional_params_dict,
                        request_data=request_body,
                        api_base=request_url,
                        api_key=api_key,
                        stream=stream,
                        fake_stream=False,
                        model=model,
                    )
                    logging_obj.model_call_details.update(request_body)
                    continue
                raise self._handle_error(e=e, provider_config=provider_config)
            except Exception as e:
                raise self._handle_error(e=e, provider_config=provider_config)

        raise RuntimeError("unreachable: anthropic messages HTTP retry loop exited without return")

    @staticmethod
    def _resolve_anthropic_messages_timeout(
        litellm_params: GenericLiteLLMParams,
        stream: bool,
        custom_llm_provider: str,
    ) -> float | httpx.Timeout | None:
        from litellm.litellm_core_utils.completion_timeout import CompletionTimeout
        from litellm.litellm_core_utils.request_timeout_resolver import (
            get_configured_request_timeout,
        )
        from litellm.utils import supports_httpx_timeout

        stream_timeout: Final = litellm_params.get("stream_timeout") if stream else None
        model_timeout: Final = stream_timeout if stream_timeout is not None else litellm_params.get("timeout")
        request_timeout: Final = litellm_params.get("request_timeout")
        global_timeout: Final = get_configured_request_timeout()
        if model_timeout is None and request_timeout is None and global_timeout is None:
            return None
        return CompletionTimeout.resolve(
            model_timeout,
            {"request_timeout": request_timeout},
            custom_llm_provider,
            global_timeout=global_timeout,
            supports_httpx_timeout=supports_httpx_timeout,
        )

    async def async_anthropic_messages_handler(
        self,
        model: str,
        messages: list[dict],
        anthropic_messages_provider_config: BaseAnthropicMessagesConfig,
        anthropic_messages_optional_request_params: dict,
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        client: AsyncHTTPHandler | None = None,
        extra_headers: dict[str, object] | None = None,
        api_key: str | None = None,
        api_base: str | None = None,
        stream: bool | None = False,
        kwargs: dict[str, Any] | None = None,
    ) -> AnthropicMessagesResponse | AsyncIterator:
        from litellm.litellm_core_utils.get_provider_specific_headers import (
            ProviderSpecificHeaderUtils,
        )

        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(llm_provider=litellm.LlmProviders.ANTHROPIC)
        else:
            async_httpx_client = client

        # Prepare headers
        kwargs = kwargs or {}
        provider_specific_header: Final = cast(
            litellm.types.utils.ProviderSpecificHeader | Sequence[litellm.types.utils.ProviderSpecificHeader] | None,
            kwargs.get("provider_specific_header", None),
        )
        provider_specific_headers: Final = ProviderSpecificHeaderUtils.get_provider_specific_headers(
            provider_specific_header=provider_specific_header,
            custom_llm_provider=custom_llm_provider,
        )
        forwarded_headers: Final = kwargs.get("headers", None)
        # Also check for extra_headers in kwargs (from config or direct calls)
        extra_headers_from_kwargs: Final = kwargs.get("extra_headers", None)
        # Merge all header sources: forwarded < extra_headers < provider_specific
        merged_headers: Final = {}
        if forwarded_headers:
            merged_headers.update(forwarded_headers)
        if extra_headers_from_kwargs:
            merged_headers.update(extra_headers_from_kwargs)
        if provider_specific_headers:
            merged_headers.update(provider_specific_headers)
        (
            headers,
            api_base,
        ) = anthropic_messages_provider_config.validate_anthropic_messages_environment(
            headers=merged_headers or {},
            model=model,
            messages=messages,
            optional_params=anthropic_messages_optional_request_params,
            litellm_params=dict(litellm_params),
            api_key=api_key,
            api_base=api_base,
        )

        if anthropic_messages_provider_config.should_filter_anthropic_beta_headers():
            headers = update_headers_with_filtered_beta(headers=headers, provider=custom_llm_provider)

        from litellm.llms.vertex_ai.vertex_llm_base import VertexBase

        explicit_vertex_location: Final = VertexBase.explicit_vertex_ai_location(MappingProxyType(dict(litellm_params)))
        vertex_location_params: Final = (
            MappingProxyType({"vertex_location": explicit_vertex_location})
            if explicit_vertex_location
            else MappingProxyType({})
        )
        logging_obj.update_from_kwargs(
            kwargs=kwargs,
            model=model,
            optional_params=dict(anthropic_messages_optional_request_params),
            litellm_params={
                "preset_cache_key": None,
                "stream_response": {},
                "model_info": kwargs.get("model_info"),
                **vertex_location_params,
                **anthropic_messages_optional_request_params,
            },
            custom_llm_provider=custom_llm_provider,
        )

        additional_drop_params: Final[list[str]] = litellm_params.get("additional_drop_params") or []
        if additional_drop_params:
            from litellm.litellm_core_utils.dot_notation_indexing import delete_nested_value

            for path in additional_drop_params:
                anthropic_messages_optional_request_params = delete_nested_value(
                    anthropic_messages_optional_request_params, path
                )

        # Prepare request body
        request_body: Final = anthropic_messages_provider_config.transform_anthropic_messages_request(
            model=model,
            messages=messages,
            anthropic_messages_optional_request_params=anthropic_messages_optional_request_params,
            litellm_params=litellm_params,
            headers=headers,
        )
        logging_obj.stream = stream
        logging_obj.model_call_details.update(request_body)

        # Make the request
        request_url: Final = anthropic_messages_provider_config.get_complete_url(
            api_base=api_base,
            api_key=api_key,
            model=model,
            optional_params=dict(
                litellm_params
            ),  # this uses the invoke config, which expects aws_* params in optional_params
            litellm_params=dict(litellm_params),
            stream=stream,
        )

        headers, signed_json_body = anthropic_messages_provider_config.sign_request(
            headers=headers,
            optional_params=dict(litellm_params),  # dynamic aws_* params are passed under litellm_params
            request_data=request_body,
            api_base=request_url,
            api_key=api_key,
            stream=stream,
            fake_stream=False,
            model=model,
        )

        # The request body was serialized once for the pre-call log input and
        # again for the wire (json.dumps is O(payload), large for long-context
        # Claude Code history). Serialize once and reuse for both. Only when
        # the provider didn't sign the request (sign_request no-op for the
        # native anthropic path -> signed_json_body is None); signed providers
        # (e.g. Bedrock) keep their signed body untouched. The HTTP-error
        # retry path mutates + re-signs the body, so it still re-serializes
        # internally -- this only deduplicates the success path.
        request_body_json: Final = json.dumps(request_body)

        logging_obj.pre_call(
            input=[{"role": "user", "content": request_body_json}],
            api_key="",
            additional_args={
                "complete_input_dict": request_body,
                "api_base": str(request_url),
                "headers": headers,
            },
        )

        rust_messages_response: Final = await self._maybe_rust_anthropic_messages(
            custom_llm_provider=custom_llm_provider,
            litellm_params=litellm_params,
            has_agentic_hook=self._has_agentic_completion_hook(logging_obj),
            model=model,
            api_key=api_key,
            api_base=api_base,
            headers=headers,
            request_body=request_body,
            timeout=self._resolve_anthropic_messages_timeout(
                litellm_params=litellm_params,
                stream=stream or False,
                custom_llm_provider=custom_llm_provider,
            ),
        )
        if rust_messages_response is not None:
            if stream:
                return self._rust_anthropic_messages_fake_stream(rust_messages_response)
            return await self._finalize_anthropic_messages_response(
                initial_response=rust_messages_response,
                model=model,
                messages=messages,
                anthropic_messages_provider_config=anthropic_messages_provider_config,
                anthropic_messages_optional_request_params=anthropic_messages_optional_request_params,
                logging_obj=logging_obj,
                custom_llm_provider=custom_llm_provider,
                api_key=api_key,
                kwargs=kwargs,
            )

        response: Final = await self._async_post_anthropic_messages_with_http_error_retry(
            async_httpx_client=async_httpx_client,
            request_url=request_url,
            headers=headers,
            signed_json_body=(signed_json_body if signed_json_body is not None else request_body_json),
            request_body=request_body,
            stream=stream or False,
            logging_obj=logging_obj,
            provider_config=anthropic_messages_provider_config,
            litellm_params=litellm_params,
            api_key=api_key,
            model=model,
            timeout=self._resolve_anthropic_messages_timeout(
                litellm_params=litellm_params,
                stream=stream or False,
                custom_llm_provider=custom_llm_provider,
            ),
        )

        # used for logging + cost tracking
        logging_obj.model_call_details["httpx_response"] = response

        initial_response: AsyncIterator | AnthropicMessagesResponse
        if stream:
            from litellm.llms.anthropic.experimental_pass_through.messages.streaming_iterator import (
                AnthropicMessagesStreamingResponse,
                anthropic_messages_stream_hidden_params,
            )

            completion_stream: Final = anthropic_messages_provider_config.get_async_streaming_response_iterator(
                model=model,
                httpx_response=response,
                request_body=request_body,
                litellm_logging_obj=logging_obj,
            )
            stream_hidden_params: Final = anthropic_messages_stream_hidden_params(response.headers)

            if not self._has_agentic_completion_hook(logging_obj):
                # No callback overrides async_should_run_agentic_loop, so the
                # agentic wrapper's only effect would be buffering every chunk
                # and rebuilding the response from SSE at end-of-stream to call
                # hooks that all return (False, {}). Stream through directly and
                # skip that per-chunk + end-of-stream overhead.
                return AnthropicMessagesStreamingResponse(
                    completion_stream=completion_stream,
                    hidden_params=stream_hidden_params,
                )

            from litellm.llms.anthropic.experimental_pass_through.messages.agentic_streaming_iterator import (
                AgenticAnthropicStreamingIterator,
            )

            held_back_tool_names: Final = self._server_fulfilled_tools_in_request(
                logging_obj=logging_obj,
                tools=anthropic_messages_optional_request_params.get("tools"),
            )
            initial_response = AgenticAnthropicStreamingIterator(
                completion_stream=completion_stream,
                http_handler=self,
                model=model,
                messages=messages,
                anthropic_messages_provider_config=anthropic_messages_provider_config,
                anthropic_messages_optional_request_params=anthropic_messages_optional_request_params,
                logging_obj=logging_obj,
                custom_llm_provider=custom_llm_provider,
                kwargs={**kwargs, "api_key": api_key} if api_key else kwargs,
                hold_back=bool(held_back_tool_names),
                server_fulfilled_tool_names=held_back_tool_names,
            )
            return AnthropicMessagesStreamingResponse(
                completion_stream=initial_response,
                hidden_params=stream_hidden_params,
            )
        else:
            initial_response = anthropic_messages_provider_config.transform_anthropic_messages_response(
                model=model,
                raw_response=response,
                logging_obj=logging_obj,
            )

        return await self._finalize_anthropic_messages_response(
            initial_response=initial_response,
            model=model,
            messages=messages,
            anthropic_messages_provider_config=anthropic_messages_provider_config,
            anthropic_messages_optional_request_params=anthropic_messages_optional_request_params,
            logging_obj=logging_obj,
            custom_llm_provider=custom_llm_provider,
            api_key=api_key,
            kwargs=kwargs,
        )

    async def _finalize_anthropic_messages_response(
        self,
        *,
        initial_response: AnthropicMessagesResponse,
        model: str,
        messages: list[dict],
        anthropic_messages_provider_config: BaseAnthropicMessagesConfig,
        anthropic_messages_optional_request_params: dict,
        logging_obj: LiteLLMLoggingObj,
        custom_llm_provider: str,
        api_key: str | None,
        kwargs: dict,
    ) -> AnthropicMessagesResponse | AsyncIterator:
        # Inject api_key into kwargs so follow-up calls in agentic hooks can
        # authenticate. api_key is a named param here (not in kwargs), so
        # _prepare_followup_kwargs would miss it otherwise.
        kwargs_for_agentic: Final = {**kwargs, "api_key": api_key} if api_key else kwargs
        # Call agentic completion hooks (non-streaming path only)
        final_response: Final = await self._call_agentic_completion_hooks(
            response=initial_response,
            model=model,
            messages=messages,
            anthropic_messages_provider_config=anthropic_messages_provider_config,
            anthropic_messages_optional_request_params=anthropic_messages_optional_request_params,
            logging_obj=logging_obj,
            stream=False,
            custom_llm_provider=custom_llm_provider,
            kwargs=kwargs_for_agentic,
        )

        return self._maybe_wrap_in_fake_stream(
            final_response if final_response is not None else initial_response,
            logging_obj,
            "anthropic_messages",
        )

    @staticmethod
    def _rust_env_enabled() -> bool:
        return os.getenv("LITELLM_RUST", "").strip().lower() in {"1", "true", "yes", "on"}

    @staticmethod
    async def _maybe_rust_anthropic_messages(
        *,
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        has_agentic_hook: bool,
        model: str,
        api_key: str | None,
        api_base: str | None,
        headers: dict,
        request_body: dict,
        timeout: float | httpx.Timeout | None,
    ) -> AnthropicMessagesResponse | None:
        if custom_llm_provider not in ("azure_ai", "anthropic"):
            return None
        if litellm_params.get("rust") is not True and not BaseLLMHTTPHandler._rust_env_enabled():
            return None
        if has_agentic_hook:
            return None

        from litellm.rust_bridge import messages as rust_messages_bridge

        upstream_body: Final = {key: value for key, value in request_body.items() if key != "stream"}
        try:
            rust_response: Final = await rust_messages_bridge.amessages(
                model=model,
                body=upstream_body,
                api_key=api_key,
                api_base=api_base,
                custom_llm_provider=custom_llm_provider,
                extra_headers=headers,
                timeout=timeout,
            )
        except Exception as rust_error:  # noqa: BLE001  # rollout-safety fallback: any Rust bridge failure must fall back to the Python path
            verbose_logger.debug(
                "Rust Anthropic messages bridge raised %s; falling back to Python path",
                type(rust_error).__name__,
            )
            return None
        if rust_response is None:
            return None

        response_obj: Final = cast(AnthropicMessagesResponse, dict(rust_response))
        response_obj["_hidden_params"] = {"additional_headers": {"x-litellm-rust": "true"}}
        return response_obj

    @staticmethod
    def _rust_anthropic_messages_fake_stream(
        rust_response: AnthropicMessagesResponse,
    ) -> "AnthropicMessagesStreamingResponse":
        from litellm.llms.anthropic.experimental_pass_through.messages.fake_stream_iterator import (
            FakeAnthropicMessagesStreamIterator,
        )
        from litellm.llms.anthropic.experimental_pass_through.messages.streaming_iterator import (
            AnthropicMessagesStreamHiddenParams,
            AnthropicMessagesStreamingResponse,
        )

        completion_stream = cast(AsyncIterator[bytes], FakeAnthropicMessagesStreamIterator(response=rust_response))
        hidden_params: Final = AnthropicMessagesStreamHiddenParams(additional_headers={"x-litellm-rust": "true"})
        return AnthropicMessagesStreamingResponse(
            completion_stream=completion_stream,
            hidden_params=hidden_params,
        )

    def anthropic_messages_handler(
        self,
        model: str,
        messages: list[dict],
        anthropic_messages_provider_config: BaseAnthropicMessagesConfig,
        anthropic_messages_optional_request_params: dict,
        custom_llm_provider: str,
        _is_async: bool,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        api_key: str | None = None,
        api_base: str | None = None,
        stream: bool | None = False,
        kwargs: dict[str, object] | None = None,
    ) -> AnthropicMessagesResponse | Coroutine[object, object, AnthropicMessagesResponse | AsyncIterator]:
        """
        LLM HTTP Handler for Anthropic Messages
        """
        if _is_async:
            # Return the async coroutine if called with _is_async=True
            return self.async_anthropic_messages_handler(
                model=model,
                messages=messages,
                anthropic_messages_provider_config=anthropic_messages_provider_config,
                anthropic_messages_optional_request_params=anthropic_messages_optional_request_params,
                client=client if isinstance(client, AsyncHTTPHandler) else None,
                custom_llm_provider=custom_llm_provider,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                api_key=api_key,
                api_base=api_base,
                stream=stream,
                kwargs=kwargs,
            )
        raise ValueError("anthropic_messages_handler is not implemented for sync calls")

    def _run_sync_responses_pre_call_deployment_hook(
        self,
        *,
        model: str,
        input: str | ResponseInputParam,
        custom_llm_provider: str,
        response_api_optional_request_params: dict[str, object],
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
    ) -> tuple[
        str,
        str | ResponseInputParam,
        str,
        dict[str, object],
        GenericLiteLLMParams,
    ]:
        if not _has_pre_call_deployment_hook(logging_obj):
            return (
                model,
                input,
                custom_llm_provider,
                response_api_optional_request_params,
                litellm_params,
            )

        modified_kwargs: Final = run_async_function(
            async_pre_call_deployment_hook,
            {
                **dict(litellm_params),
                **response_api_optional_request_params,
                "model": model,
                "input": input,
                "custom_llm_provider": custom_llm_provider,
            },
            CallTypes.responses.value,
        )
        if modified_kwargs is None:
            return (
                model,
                input,
                custom_llm_provider,
                response_api_optional_request_params,
                litellm_params,
            )

        optional_param_names: Final = _responses_api_optional_request_param_names()
        updated_response_params: Final = {
            **response_api_optional_request_params,
            **{key: value for key, value in modified_kwargs.items() if key in optional_param_names},
        }
        updated_litellm_params: Final = GenericLiteLLMParams(
            **{
                **dict(litellm_params),
                **{
                    key: value
                    for key, value in modified_kwargs.items()
                    if key not in optional_param_names and key not in {"model", "input", "custom_llm_provider"}
                },
            }
        )
        return (
            str(modified_kwargs["model"]) if "model" in modified_kwargs else model,
            cast(
                str | ResponseInputParam,
                modified_kwargs["input"] if "input" in modified_kwargs else input,
            ),
            (
                str(modified_kwargs["custom_llm_provider"])
                if "custom_llm_provider" in modified_kwargs
                else custom_llm_provider
            ),
            updated_response_params,
            updated_litellm_params,
        )

    def response_api_handler(
        self,
        model: str,
        input: str | ResponseInputParam,
        responses_api_provider_config: BaseResponsesAPIConfig,
        response_api_optional_request_params: dict[str, Any],
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        extra_body: Mapping[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
        fake_stream: bool = False,
        litellm_metadata: dict[str, object] | None = None,
        shared_session: Optional["ClientSession"] = None,
    ) -> (
        ResponsesAPIResponse
        | BaseResponsesAPIStreamingIterator
        | Coroutine[object, object, ResponsesAPIResponse | BaseResponsesAPIStreamingIterator]
    ):
        """
        Handles responses API requests.
        When _is_async=True, returns a coroutine instead of making the call directly.

        Keeps the pre-transform request context for streaming so post-call hooks/metadata
        (added for Responses API parity with chat) receive the original params instead of
        the provider-shaped body that caused them to be skipped before.
        """

        if _is_async:
            # Return the async coroutine if called with _is_async=True
            return self.async_response_api_handler(
                model=model,
                input=input,
                responses_api_provider_config=responses_api_provider_config,
                response_api_optional_request_params=response_api_optional_request_params,
                custom_llm_provider=custom_llm_provider,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                extra_body=extra_body,
                timeout=timeout,
                client=client if isinstance(client, AsyncHTTPHandler) else None,
                fake_stream=fake_stream,
                litellm_metadata=litellm_metadata,
                shared_session=shared_session,
            )

        (
            model,
            input,
            custom_llm_provider,
            response_api_optional_request_params,
            litellm_params,
        ) = self._run_sync_responses_pre_call_deployment_hook(
            model=model,
            input=input,
            custom_llm_provider=custom_llm_provider,
            response_api_optional_request_params=response_api_optional_request_params,
            litellm_params=litellm_params,
            logging_obj=logging_obj,
        )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers = responses_api_provider_config.validate_environment(
            headers=response_api_optional_request_params.get("extra_headers", {}) or {},
            model=model,
            litellm_params=litellm_params,
        )

        if extra_headers:
            headers.update(extra_headers)

        # Check if streaming is requested
        stream = response_api_optional_request_params.get("stream", False)

        api_base: Final = responses_api_provider_config.get_complete_url(
            api_base=litellm_params.api_base,
            litellm_params=dict(litellm_params),
        )

        data = responses_api_provider_config.transform_responses_api_request(
            model=model,
            input=input,
            response_api_optional_request_params=response_api_optional_request_params,
            litellm_params=litellm_params,
            headers=headers,
        )
        data = BaseResponsesAPIConfig.normalize_responses_api_request_dict(data)

        if extra_body:
            data.update(extra_body)
        stream = bool(stream or data.get("stream"))

        # Preserve the OpenAI-style request context (not sent to the provider) for streaming
        # hooks/metadata; the streaming iterator now consumes this to run deployment hooks
        # with the same info as chat, including litellm_params.
        request_context: Final[dict[str, object]] = {"input": input}
        try:
            request_context.update(response_api_optional_request_params)
        except Exception:
            pass
        # Needed by streaming callbacks/metadata helpers to reconstruct api_base/model_id
        # but never included in the outbound provider payload.
        request_context["litellm_params"] = dict(litellm_params)

        is_stream_request: Final = bool(stream)
        if is_stream_request and fake_stream is True:
            stream, data = self._prepare_fake_stream_request(
                stream=stream,
                data=data,
                fake_stream=fake_stream,
            )

        # Sign after the body is final (post-transform/normalize/extra_body and post
        # fake-stream prep) so signed bytes match what we send. No-op for providers
        # that inherit the default sign_request.
        headers, signed_body = responses_api_provider_config.sign_request(
            headers=headers,
            optional_params=dict(litellm_params),
            request_data=data,
            api_base=api_base,
            api_key=litellm_params.api_key,
            model=model,
            stream=stream,
            fake_stream=fake_stream,
        )
        body_kwargs: Final[dict[str, Any]] = {"data": signed_body} if signed_body is not None else {"json": data}

        ## LOGGING
        logging_obj.pre_call(
            input=input,
            api_key="",
            additional_args={
                "complete_input_dict": data,
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            if is_stream_request:
                response = sync_httpx_client.post(
                    url=api_base,
                    headers=headers,
                    timeout=timeout or float(response_api_optional_request_params.get("timeout", 0)),
                    stream=stream,
                    **body_kwargs,
                )
                if fake_stream is True:
                    return MockResponsesAPIStreamingIterator(
                        response=response,
                        model=model,
                        logging_obj=logging_obj,
                        responses_api_provider_config=responses_api_provider_config,
                        litellm_metadata=litellm_metadata,
                        custom_llm_provider=custom_llm_provider,
                        request_data=request_context,
                        call_type=CallTypes.responses.value,
                    )

                return SyncResponsesAPIStreamingIterator(
                    response=response,
                    model=model,
                    logging_obj=logging_obj,
                    responses_api_provider_config=responses_api_provider_config,
                    litellm_metadata=litellm_metadata,
                    custom_llm_provider=custom_llm_provider,
                    request_data=request_context,
                    call_type=CallTypes.responses.value,
                )
            else:
                response = sync_httpx_client.post(
                    url=api_base,
                    headers=headers,
                    timeout=timeout or float(response_api_optional_request_params.get("timeout", 0)),
                    **body_kwargs,
                )
        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=responses_api_provider_config,
            )

        initial_response: Final = responses_api_provider_config.transform_response_api_response(
            model=model,
            raw_response=response,
            logging_obj=logging_obj,
        )

        if self._has_agentic_completion_hook(logging_obj):
            final_response: Final = run_async_function(
                self._call_agentic_completion_hooks,
                response=initial_response,
                model=model,
                messages=(input if isinstance(input, list) else [{"role": "user", "content": input}]),
                anthropic_messages_provider_config=responses_api_provider_config,
                anthropic_messages_optional_request_params=response_api_optional_request_params,
                logging_obj=logging_obj,
                stream=False,
                custom_llm_provider=custom_llm_provider,
                kwargs=dict(litellm_params),
                api_surface="responses",
            )
            return final_response if final_response is not None else initial_response

        return initial_response

    async def async_response_api_handler(
        self,
        model: str,
        input: str | ResponseInputParam,
        responses_api_provider_config: BaseResponsesAPIConfig,
        response_api_optional_request_params: dict,
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        extra_body: Mapping[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        fake_stream: bool = False,
        litellm_metadata: dict[str, object] | None = None,
        shared_session: Optional["ClientSession"] = None,
    ) -> ResponsesAPIResponse | BaseResponsesAPIStreamingIterator:
        """
        Async version of the responses API handler.
        Uses async HTTP client to make requests.
        """
        if client is None or not isinstance(client, AsyncHTTPHandler):
            verbose_logger.debug(
                "Creating HTTP client for responses API with shared_session: %s",
                id(shared_session) if shared_session else None,
            )
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
                shared_session=shared_session,
            )
        else:
            async_httpx_client = client

        headers = responses_api_provider_config.validate_environment(
            headers=response_api_optional_request_params.get("extra_headers", {}) or {},
            model=model,
            litellm_params=litellm_params,
        )

        if extra_headers:
            headers.update(extra_headers)

        # Check if streaming is requested
        stream = response_api_optional_request_params.get("stream", False)

        api_base: Final = responses_api_provider_config.get_complete_url(
            api_base=litellm_params.api_base,
            litellm_params=dict(litellm_params),
        )

        data = responses_api_provider_config.transform_responses_api_request(
            model=model,
            input=input,
            response_api_optional_request_params=response_api_optional_request_params,
            litellm_params=litellm_params,
            headers=headers,
        )
        data = BaseResponsesAPIConfig.normalize_responses_api_request_dict(data)

        if extra_body:
            data.update(extra_body)
        stream = bool(stream or data.get("stream"))

        # Preserve the OpenAI-style request context (not sent to the provider) for streaming
        # hooks/metadata; the streaming iterator now consumes this to run deployment hooks
        # with the same info as chat, including litellm_params.
        request_context: Final[dict[str, object]] = {"input": input}
        try:
            request_context.update(response_api_optional_request_params)
        except Exception:
            pass
        # Needed by streaming callbacks/metadata helpers to reconstruct api_base/model_id
        # but never included in the outbound provider payload.
        request_context["litellm_params"] = dict(litellm_params)

        is_stream_request: Final = bool(stream)
        if is_stream_request and fake_stream is True:
            stream, data = self._prepare_fake_stream_request(
                stream=stream,
                data=data,
                fake_stream=fake_stream,
            )

        headers, signed_body = responses_api_provider_config.sign_request(
            headers=headers,
            optional_params=dict(litellm_params),
            request_data=data,
            api_base=api_base,
            api_key=litellm_params.api_key,
            model=model,
            stream=stream,
            fake_stream=fake_stream,
        )
        body_kwargs: Final[dict[str, Any]] = {"data": signed_body} if signed_body is not None else {"json": data}

        ## LOGGING
        logging_obj.pre_call(
            input=input,
            api_key="",
            additional_args={
                "complete_input_dict": data,
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            if is_stream_request:
                response = await async_httpx_client.post(
                    url=api_base,
                    headers=headers,
                    timeout=timeout or float(response_api_optional_request_params.get("timeout", 0)),
                    stream=stream,
                    **body_kwargs,
                )

                if fake_stream is True:
                    return MockResponsesAPIStreamingIterator(
                        response=response,
                        model=model,
                        logging_obj=logging_obj,
                        responses_api_provider_config=responses_api_provider_config,
                        litellm_metadata=litellm_metadata,
                        custom_llm_provider=custom_llm_provider,
                        request_data=request_context,
                        call_type=CallTypes.responses.value,
                    )

                # Return the streaming iterator
                return ResponsesAPIStreamingIterator(
                    response=response,
                    model=model,
                    logging_obj=logging_obj,
                    responses_api_provider_config=responses_api_provider_config,
                    litellm_metadata=litellm_metadata,
                    custom_llm_provider=custom_llm_provider,
                    request_data=request_context,
                    call_type=CallTypes.responses.value,
                )
            else:
                response = await async_httpx_client.post(
                    url=api_base,
                    headers=headers,
                    timeout=timeout or float(response_api_optional_request_params.get("timeout", 0)),
                    **body_kwargs,
                )

        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=responses_api_provider_config,
            )

        initial_response: Final = responses_api_provider_config.transform_response_api_response(
            model=model,
            raw_response=response,
            logging_obj=logging_obj,
        )

        final_response: Final = await self._call_agentic_completion_hooks(
            response=initial_response,
            model=model,
            messages=(input if isinstance(input, list) else [{"role": "user", "content": input}]),
            anthropic_messages_provider_config=responses_api_provider_config,
            anthropic_messages_optional_request_params=response_api_optional_request_params,
            logging_obj=logging_obj,
            stream=False,
            custom_llm_provider=custom_llm_provider,
            kwargs=dict(litellm_params),
            api_surface="responses",
        )

        result: Final = final_response if final_response is not None else initial_response
        interception_converted_stream: Final = litellm_params.get(
            "_code_interpreter_interception_converted_stream"
        ) or litellm_params.get("_websearch_interception_converted_stream")
        if interception_converted_stream and not litellm_params.get("_agentic_loop_depth"):
            return self._wrap_responses_response_as_fake_stream(
                result=result,
                model=model,
                responses_api_provider_config=responses_api_provider_config,
                logging_obj=logging_obj,
                custom_llm_provider=custom_llm_provider,
            )
        return result

    async def async_delete_response_api_handler(
        self,
        response_id: str,
        responses_api_provider_config: BaseResponsesAPIConfig,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        custom_llm_provider: str | None,
        extra_headers: dict[str, object] | None = None,
        extra_body: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
        shared_session: Optional["ClientSession"] = None,
    ) -> DeleteResponseResult:
        """
        Async version of the delete response API handler.
        Uses async HTTP client to make requests.
        """
        if client is None or not isinstance(client, AsyncHTTPHandler):
            verbose_logger.debug(
                "Creating HTTP client for delete_response with shared_session: %s",
                id(shared_session) if shared_session else None,
            )
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
                shared_session=shared_session,
            )
        else:
            async_httpx_client = client

        headers: Final = responses_api_provider_config.validate_environment(
            headers=extra_headers or {}, model="None", litellm_params=litellm_params
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = responses_api_provider_config.get_complete_url(
            api_base=litellm_params.api_base,
            litellm_params=dict(litellm_params),
        )

        url, data = responses_api_provider_config.transform_delete_response_api_request(
            response_id=response_id,
            api_base=api_base,
            litellm_params=litellm_params,
            headers=headers,
        )

        headers.setdefault("Content-Type", "application/json")

        ## LOGGING
        logging_obj.pre_call(
            input=input,
            api_key="",
            additional_args={
                "complete_input_dict": data,
                "api_base": api_base,
                "headers": headers,
            },
        )

        delete_kwargs: Final[_DeleteRequestKwargs] = {
            "url": url,
            "headers": headers,
            "timeout": timeout,
        }
        if data:
            delete_kwargs["json"] = data

        try:
            response: Final = await async_httpx_client.delete(**delete_kwargs)

        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=responses_api_provider_config,
            )

        return responses_api_provider_config.transform_delete_response_api_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    def delete_response_api_handler(
        self,
        response_id: str,
        responses_api_provider_config: BaseResponsesAPIConfig,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        custom_llm_provider: str | None,
        extra_headers: dict[str, object] | None = None,
        extra_body: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
        shared_session: Optional["ClientSession"] = None,
    ) -> DeleteResponseResult | Coroutine[object, object, DeleteResponseResult]:
        """
        Async version of the responses API handler.
        Uses async HTTP client to make requests.
        """
        if _is_async:
            return self.async_delete_response_api_handler(
                response_id=response_id,
                responses_api_provider_config=responses_api_provider_config,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                custom_llm_provider=custom_llm_provider,
                extra_headers=extra_headers,
                extra_body=extra_body,
                timeout=timeout,
                client=client,
                shared_session=shared_session,
            )
        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = responses_api_provider_config.validate_environment(
            headers=extra_headers or {}, model="None", litellm_params=litellm_params
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = responses_api_provider_config.get_complete_url(
            api_base=litellm_params.api_base,
            litellm_params=dict(litellm_params),
        )

        url, data = responses_api_provider_config.transform_delete_response_api_request(
            response_id=response_id,
            api_base=api_base,
            litellm_params=litellm_params,
            headers=headers,
        )

        headers.setdefault("Content-Type", "application/json")

        ## LOGGING
        logging_obj.pre_call(
            input=input,
            api_key="",
            additional_args={
                "complete_input_dict": data,
                "api_base": api_base,
                "headers": headers,
            },
        )

        delete_kwargs: Final[_DeleteRequestKwargs] = {
            "url": url,
            "headers": headers,
            "timeout": timeout,
        }
        if data:
            delete_kwargs["json"] = data

        try:
            response: Final = sync_httpx_client.delete(**delete_kwargs)

        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=responses_api_provider_config,
            )

        return responses_api_provider_config.transform_delete_response_api_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    def get_responses(
        self,
        response_id: str,
        responses_api_provider_config: BaseResponsesAPIConfig,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        custom_llm_provider: str | None = None,
        extra_headers: dict[str, object] | None = None,
        extra_body: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
        shared_session: Optional["ClientSession"] = None,
    ) -> ResponsesAPIResponse | Coroutine[object, object, ResponsesAPIResponse]:
        """
        Get a response by ID
        Uses GET /v1/responses/{response_id} endpoint in the responses API
        """
        if _is_async:
            return self.async_get_responses(
                response_id=response_id,
                responses_api_provider_config=responses_api_provider_config,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                custom_llm_provider=custom_llm_provider,
                extra_headers=extra_headers,
                extra_body=extra_body,
                timeout=timeout,
                client=client,
                shared_session=shared_session,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = responses_api_provider_config.validate_environment(
            headers=extra_headers or {}, model="None", litellm_params=litellm_params
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = responses_api_provider_config.get_complete_url(
            api_base=litellm_params.api_base,
            litellm_params=dict(litellm_params),
        )

        url, data = responses_api_provider_config.transform_get_response_api_request(
            response_id=response_id,
            api_base=api_base,
            litellm_params=litellm_params,
            headers=headers,
        )

        ## LOGGING
        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "complete_input_dict": data,
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            response: Final = sync_httpx_client.get(url=url, headers=headers, params=data)
            response.raise_for_status()
        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=responses_api_provider_config,
            )

        return responses_api_provider_config.transform_get_response_api_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    async def async_get_responses(
        self,
        response_id: str,
        responses_api_provider_config: BaseResponsesAPIConfig,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        custom_llm_provider: str | None = None,
        extra_headers: dict[str, object] | None = None,
        extra_body: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        shared_session: Optional["ClientSession"] = None,
    ) -> ResponsesAPIResponse:
        """
        Async version of get_responses
        """
        if client is None or not isinstance(client, AsyncHTTPHandler):
            verbose_logger.debug(
                "Creating HTTP client for get_responses with shared_session: %s",
                id(shared_session) if shared_session else None,
            )
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
                shared_session=shared_session,
            )
        else:
            async_httpx_client = client

        headers: Final = responses_api_provider_config.validate_environment(
            headers=extra_headers or {}, model="None", litellm_params=litellm_params
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = responses_api_provider_config.get_complete_url(
            api_base=litellm_params.api_base,
            litellm_params=dict(litellm_params),
        )

        url, data = responses_api_provider_config.transform_get_response_api_request(
            response_id=response_id,
            api_base=api_base,
            litellm_params=litellm_params,
            headers=headers,
        )

        ## LOGGING
        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "complete_input_dict": data,
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            response: Final = await async_httpx_client.get(url=url, headers=headers, params=data)
            response.raise_for_status()
        except Exception as e:
            verbose_logger.debug("Error retrieving response: %s", e)
            raise self._handle_error(
                e=e,
                provider_config=responses_api_provider_config,
            )

        return responses_api_provider_config.transform_get_response_api_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    #####################################################################
    ################ LIST RESPONSES INPUT ITEMS HANDLER ###########################
    #####################################################################
    def list_responses_input_items(
        self,
        response_id: str,
        responses_api_provider_config: BaseResponsesAPIConfig,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        custom_llm_provider: str | None = None,
        after: str | None = None,
        before: str | None = None,
        include: list[str] | None = None,
        limit: int = 20,
        order: Literal["asc", "desc"] = "desc",
        extra_headers: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
        shared_session: Optional["ClientSession"] = None,
    ) -> dict | Coroutine[object, object, dict]:
        if _is_async:
            return self.async_list_responses_input_items(
                response_id=response_id,
                responses_api_provider_config=responses_api_provider_config,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                custom_llm_provider=custom_llm_provider,
                after=after,
                before=before,
                include=include,
                limit=limit,
                order=order,
                extra_headers=extra_headers,
                timeout=timeout,
                client=client,
                shared_session=shared_session,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = responses_api_provider_config.validate_environment(
            headers=extra_headers or {}, model="None", litellm_params=litellm_params
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = responses_api_provider_config.get_complete_url(
            api_base=litellm_params.api_base,
            litellm_params=dict(litellm_params),
        )

        url, params = responses_api_provider_config.transform_list_input_items_request(
            response_id=response_id,
            api_base=api_base,
            litellm_params=litellm_params,
            headers=headers,
            after=after,
            before=before,
            include=include,
            limit=limit,
            order=order,
        )

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "complete_input_dict": params,
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            response: Final = sync_httpx_client.get(url=url, headers=headers, params=params)
            response.raise_for_status()
        except Exception as e:
            raise self._handle_error(e=e, provider_config=responses_api_provider_config)

        return responses_api_provider_config.transform_list_input_items_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    async def async_list_responses_input_items(
        self,
        response_id: str,
        responses_api_provider_config: BaseResponsesAPIConfig,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        custom_llm_provider: str | None = None,
        after: str | None = None,
        before: str | None = None,
        include: list[str] | None = None,
        limit: int = 20,
        order: Literal["asc", "desc"] = "desc",
        extra_headers: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        shared_session: Optional["ClientSession"] = None,
    ) -> dict:
        if client is None or not isinstance(client, AsyncHTTPHandler):
            verbose_logger.debug(
                "Creating HTTP client for list_input_items with shared_session: %s",
                id(shared_session) if shared_session else None,
            )
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
                shared_session=shared_session,
            )
        else:
            async_httpx_client = client

        headers: Final = responses_api_provider_config.validate_environment(
            headers=extra_headers or {}, model="None", litellm_params=litellm_params
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = responses_api_provider_config.get_complete_url(
            api_base=litellm_params.api_base,
            litellm_params=dict(litellm_params),
        )

        url, params = responses_api_provider_config.transform_list_input_items_request(
            response_id=response_id,
            api_base=api_base,
            litellm_params=litellm_params,
            headers=headers,
            after=after,
            before=before,
            include=include,
            limit=limit,
            order=order,
        )

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "complete_input_dict": params,
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            response: Final = await async_httpx_client.get(url=url, headers=headers, params=params)
            response.raise_for_status()
        except Exception as e:
            raise self._handle_error(e=e, provider_config=responses_api_provider_config)

        return responses_api_provider_config.transform_list_input_items_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    def _extract_upload_url_from_response(
        self,
        response: httpx.Response,
        upload_url_location: str,
        upload_url_key: str = "upload_url",
    ) -> tuple[str | None, dict | None]:
        """
        Extract upload URL from initial file creation response.

        Args:
            response: HTTP response from initial file creation request
            upload_url_location: Where to find URL ('headers' or 'body')
            upload_url_key: Key name for URL in response body (default: 'upload_url')

        Returns:
            Tuple of (upload_url, response_data)
            - upload_url: The extracted upload URL, or None if not found
            - response_data: Parsed response body (for 'body' location), or None
        """
        if upload_url_location == "headers":
            # Google Cloud Storage style - URL in X-Goog-Upload-URL header
            upload_url = response.headers.get("X-Goog-Upload-URL")
            return upload_url, None
        else:
            # Response body style (e.g., Manus, S3 presigned URLs)
            try:
                response_data: Final = response.json()
                upload_url = response_data.get(upload_url_key)
                return upload_url, response_data if upload_url else None
            except Exception:
                return None, None

    def create_file(
        self,
        create_file_data: CreateFileRequest,
        litellm_params: dict,
        provider_config: BaseFilesConfig,
        headers: dict,
        api_base: str | None,
        api_key: str | None,
        logging_obj: LiteLLMLoggingObj,
        _is_async: bool = False,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        timeout: float | httpx.Timeout | None = None,
    ) -> OpenAIFileObject | Coroutine[object, object, OpenAIFileObject]:
        """
        Creates a file using Gemini's two-step upload process
        """
        # get config from model, custom llm provider
        headers = provider_config.validate_environment(
            api_key=api_key,
            headers=headers,
            model="",
            messages=[],
            optional_params={},
            litellm_params=litellm_params,
        )

        api_base = provider_config.get_complete_file_url(
            api_base=api_base,
            api_key=api_key,
            model="",
            optional_params={},
            litellm_params=litellm_params,
            data=create_file_data,
        )
        if api_base is None:
            raise ValueError("api_base is required for create_file")

        # Get the transformed request data for both steps
        transformed_request = provider_config.transform_create_file_request(
            model="",
            create_file_data=create_file_data,
            litellm_params=litellm_params,
            optional_params={},
        )

        if _is_async:
            return self.async_create_file(
                transformed_request=transformed_request,
                litellm_params=litellm_params,
                provider_config=provider_config,
                headers=headers,
                api_base=api_base,
                logging_obj=logging_obj,
                client=client,
                timeout=timeout,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client()
        else:
            sync_httpx_client = client

        if isinstance(transformed_request, dict) and "initial_request" in transformed_request:
            # Handle two-step uploads (TwoStepFileUploadConfig)
            # Used by providers like Manus, Google Cloud Storage
            try:
                # Step 1: Initial request to get upload URL
                initial_response: Final = sync_httpx_client.post(
                    url=api_base,
                    headers={
                        **headers,
                        **transformed_request["initial_request"]["headers"],
                    },
                    data=json.dumps(transformed_request["initial_request"]["data"]),
                    timeout=timeout,
                )

                # Extract upload URL from response
                (
                    upload_url,
                    initial_response_data,
                ) = self._extract_upload_url_from_response(
                    response=initial_response,
                    upload_url_location=transformed_request.get("upload_url_location", "headers"),
                    upload_url_key=transformed_request.get("upload_url_key", "upload_url"),
                )

                if not upload_url:
                    raise ValueError("Failed to get upload URL from initial request")

                # Step 2: Upload the actual file
                upload_method: Final = transformed_request["upload_request"].get("method", "POST").lower()
                upload_response = getattr(sync_httpx_client, upload_method)(
                    url=upload_url,
                    headers=transformed_request["upload_request"]["headers"],
                    data=transformed_request["upload_request"]["data"],
                    timeout=timeout,
                )

                # Store initial response for transformation
                if initial_response_data:
                    litellm_params["initial_file_response"] = initial_response_data
            except Exception as e:
                raise self._handle_error(
                    e=e,
                    provider_config=provider_config,
                )
        elif (
            isinstance(transformed_request, dict)
            and "method" in transformed_request
            and "initial_request" not in transformed_request
        ):
            # Handle pre-signed requests (e.g., from Bedrock S3 uploads)
            # Type narrowing: this is a plain dict, not TwoStepFileUploadConfig
            presigned_request: Final = cast(dict[str, Any], transformed_request)
            upload_response = getattr(sync_httpx_client, presigned_request["method"].lower())(
                url=presigned_request["url"],
                headers=presigned_request["headers"],
                data=presigned_request["data"],
                timeout=timeout,
            )
        elif isinstance(transformed_request, dict) and "streaming_media_upload" in transformed_request:
            media_cfg: Final = cast(StreamingMediaUploadConfig, transformed_request["streaming_media_upload"])
            try:
                upload_response = self._upload_media(
                    client=sync_httpx_client,
                    url=api_base,
                    base_headers=headers,
                    body_stream=cast(BaseFileUploadStream, media_cfg["body_stream"]),
                    content_type=media_cfg.get("content_type") or "application/octet-stream",
                    timeout=timeout,
                )
            except Exception as e:
                verbose_logger.exception("Error creating file: %s", e)
                raise self._handle_error(e=e, provider_config=provider_config)
        elif isinstance(transformed_request, str) or isinstance(transformed_request, bytes):
            # Handle traditional file uploads
            # Ensure transformed_request is a string for httpx compatibility
            if isinstance(transformed_request, bytes):
                transformed_request = transformed_request.decode("utf-8")

            # Use the HTTP method specified by the provider config
            http_method: Final = provider_config.file_upload_http_method.upper()
            if http_method == "PUT":
                upload_response = sync_httpx_client.put(
                    url=api_base,
                    headers=headers,
                    data=transformed_request,
                    timeout=timeout,
                )
            else:  # Default to POST
                upload_response = sync_httpx_client.post(
                    url=api_base,
                    headers=headers,
                    data=transformed_request,
                    timeout=timeout,
                )
        elif isinstance(transformed_request, dict) and "file" in transformed_request:
            # Handle multipart form-data uploads (e.g., Anthropic Files API)
            # The dict contains tuples suitable for httpx's `files` parameter
            file_request: Final = cast(dict[str, Any], transformed_request)
            upload_response = sync_httpx_client.post(
                url=api_base,
                headers=headers,
                files=file_request,
                timeout=timeout,
            )
        else:
            raise ValueError(f"Unsupported transformed_request type: {type(transformed_request)}")

        # Store the upload URL in litellm_params for the transformation method
        # Honour the URL already set by transform_create_file_request (e.g. Bedrock pre-signed S3 uploads),
        # fall back to api_base for providers that do not set it.
        litellm_params_with_url: Final = dict(litellm_params)
        if "upload_url" not in litellm_params:
            litellm_params_with_url["upload_url"] = api_base

        return provider_config.transform_create_file_response(
            model=None,
            raw_response=upload_response,
            logging_obj=logging_obj,
            litellm_params=litellm_params_with_url,
        )

    async def async_create_file(
        self,
        transformed_request: Union[bytes, str, dict, "TwoStepFileUploadConfig"],
        litellm_params: dict,
        provider_config: BaseFilesConfig,
        headers: dict,
        api_base: str,
        logging_obj: LiteLLMLoggingObj,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        timeout: float | httpx.Timeout | None = None,
    ):
        """
        Creates a file using Gemini's two-step upload process
        """
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(llm_provider=provider_config.custom_llm_provider)
        else:
            async_httpx_client = client

        #########################################################
        # Debug Logging
        #########################################################
        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                # A streaming upload config holds a reference to the (potentially
                # huge) upload payload; logging deep-copies additional_args, so log
                # a placeholder instead of re-materializing the payload.
                "complete_input_dict": (
                    "<streaming media upload>"
                    if isinstance(transformed_request, dict) and "streaming_media_upload" in transformed_request
                    else transformed_request
                ),
                "api_base": api_base,
                "headers": headers,
            },
        )

        if isinstance(transformed_request, dict) and "initial_request" in transformed_request:
            # Handle two-step uploads (TwoStepFileUploadConfig)
            # Used by providers like Manus, Google Cloud Storage
            try:
                # Step 1: Initial request to get upload URL
                initial_response: Final = await async_httpx_client.post(
                    url=api_base,
                    headers={
                        **headers,
                        **transformed_request["initial_request"]["headers"],
                    },
                    data=json.dumps(transformed_request["initial_request"]["data"]),
                    timeout=timeout,
                )

                # Extract upload URL from response
                (
                    upload_url,
                    initial_response_data,
                ) = self._extract_upload_url_from_response(
                    response=initial_response,
                    upload_url_location=transformed_request.get("upload_url_location", "headers"),
                    upload_url_key=transformed_request.get("upload_url_key", "upload_url"),
                )

                if not upload_url:
                    raise ValueError("Failed to get upload URL from initial request")

                # Step 2: Upload the actual file
                upload_method: Final = transformed_request["upload_request"].get("method", "POST").lower()
                upload_response = await getattr(async_httpx_client, upload_method)(
                    url=upload_url,
                    headers=transformed_request["upload_request"]["headers"],
                    data=transformed_request["upload_request"]["data"],
                    timeout=timeout,
                )

                # Store initial response for transformation
                if initial_response_data:
                    litellm_params["initial_file_response"] = initial_response_data
            except Exception as e:
                verbose_logger.exception("Error creating file: %s", e)
                raise self._handle_error(
                    e=e,
                    provider_config=provider_config,
                )
        elif (
            isinstance(transformed_request, dict)
            and "method" in transformed_request
            and "initial_request" not in transformed_request
        ):
            # Handle pre-signed requests (e.g., from Bedrock S3 uploads)
            # Type narrowing: this is a plain dict, not TwoStepFileUploadConfig
            presigned_request: Final = cast(dict[str, Any], transformed_request)
            upload_response = await getattr(async_httpx_client, presigned_request["method"].lower())(
                url=presigned_request["url"],
                headers=presigned_request["headers"],
                data=presigned_request["data"],
                timeout=timeout,
            )
        elif isinstance(transformed_request, dict) and "streaming_media_upload" in transformed_request:
            media_cfg: Final = cast(StreamingMediaUploadConfig, transformed_request["streaming_media_upload"])
            try:
                upload_response = await self._aupload_media(
                    client=async_httpx_client,
                    url=api_base,
                    base_headers=headers,
                    body_stream=cast(BaseFileUploadStream, media_cfg["body_stream"]),
                    content_type=media_cfg.get("content_type") or "application/octet-stream",
                    timeout=timeout,
                )
            except Exception as e:
                verbose_logger.exception("Error creating file: %s", e)
                raise self._handle_error(e=e, provider_config=provider_config)
        elif isinstance(transformed_request, str) or isinstance(transformed_request, bytes):
            # Handle traditional file uploads
            # Note: transformed_request can be bytes (for binary files like PDFs)
            # or str (for text files like JSONL). httpx handles both correctly.
            # Use the HTTP method specified by the provider config
            http_method: Final = provider_config.file_upload_http_method.upper()
            if http_method == "PUT":
                upload_response = await async_httpx_client.put(
                    url=api_base,
                    headers=headers,
                    data=transformed_request,
                    timeout=timeout,
                )
            else:  # Default to POST
                upload_response = await async_httpx_client.post(
                    url=api_base,
                    headers=headers,
                    data=transformed_request,
                    timeout=timeout,
                )
        elif isinstance(transformed_request, dict) and "file" in transformed_request:
            # Handle multipart form-data uploads (e.g., Anthropic Files API)
            # The dict contains tuples suitable for httpx's `files` parameter
            upload_response = await async_httpx_client.post(
                url=api_base,
                headers=headers,
                files=transformed_request,
                timeout=timeout,
            )
        else:
            raise ValueError(f"Unsupported transformed_request type: {type(transformed_request)}")

        return provider_config.transform_create_file_response(
            model=None,
            raw_response=upload_response,
            logging_obj=logging_obj,
            litellm_params=litellm_params,
        )

    # The fine-grained transform stream (one piece per JSONL row) is regrouped
    # into blocks of this size before upload, so the request yields a manageable
    # number of chunks; never more than one block is buffered.
    _MEDIA_UPLOAD_BLOCK_SIZE = 4 * 1024 * 1024

    @staticmethod
    def _iter_in_blocks(byte_iter: Iterator[bytes], block_size: int) -> Iterator[bytes]:
        buf: Final = bytearray()
        for piece in byte_iter:
            buf.extend(piece)
            while len(buf) >= block_size:
                yield bytes(buf[:block_size])
                del buf[:block_size]
        if buf:
            yield bytes(buf)

    def _check_media_upload_response(self, resp: httpx.Response) -> None:
        if resp.status_code not in (200, 201):
            resp.raise_for_status()
            raise ValueError(f"media upload: unexpected status {resp.status_code}")

    def _upload_media(
        self,
        *,
        client: HTTPHandler,
        url: str,
        base_headers: dict[str, str],
        body_stream: BaseFileUploadStream,
        content_type: str,
        timeout: float | httpx.Timeout | None,
    ) -> httpx.Response:
        headers: Final = {**base_headers, "Content-Type": content_type}
        kwargs: Final[_MediaUploadKwargs] = {
            "headers": headers,
            "content": self._iter_in_blocks(body_stream.iter_bytes(), self._MEDIA_UPLOAD_BLOCK_SIZE),
        }
        if timeout is not None:
            kwargs["timeout"] = timeout
        resp: Final = client.client.post(url, **kwargs)
        self._check_media_upload_response(resp)
        return resp

    async def _aupload_media(
        self,
        *,
        client: AsyncHTTPHandler,
        url: str,
        base_headers: dict[str, str],
        body_stream: BaseFileUploadStream,
        content_type: str,
        timeout: float | httpx.Timeout | None,
    ) -> httpx.Response:
        """Stream the transformed body straight to a single media upload. Each
        block is produced on a worker thread (the transform never runs on the
        event loop) and sent with chunked transfer-encoding, so the body is
        neither buffered in memory nor staged to disk, and the upload is one
        continuous request rather than the many sequential round-trips of the
        resumable path that overran client/LB timeouts."""
        headers: Final = {**base_headers, "Content-Type": content_type}
        block_iter: Final = iter(self._iter_in_blocks(body_stream.iter_bytes(), self._MEDIA_UPLOAD_BLOCK_SIZE))
        done: Final = object()

        async def _abody() -> AsyncIterator[bytes]:
            while True:
                block = await asyncio.to_thread(next, block_iter, done)
                if block is done:
                    break
                yield cast(bytes, block)

        kwargs: Final[_MediaUploadKwargs] = {"headers": headers, "content": _abody()}
        if timeout is not None:
            kwargs["timeout"] = timeout
        resp: Final = await client.client.post(url, **kwargs)
        await resp.aread()
        self._check_media_upload_response(resp)
        return resp

    def create_batch(
        self,
        create_batch_data: "CreateBatchRequest",
        litellm_params: dict,
        provider_config: "BaseBatchesConfig",
        headers: dict,
        api_base: str | None,
        api_key: str | None,
        logging_obj: "LiteLLMLoggingObj",
        _is_async: bool = False,
        client: Union["HTTPHandler", "AsyncHTTPHandler"] | None = None,
        timeout: float | httpx.Timeout | None = None,
        model: str | None = None,
    ) -> Union["LiteLLMBatch", Coroutine[object, object, "LiteLLMBatch"]]:
        """
        Creates a batch using provider-specific batch creation process
        """
        # get config from model, custom llm provider
        if model is None:
            raise ValueError("model is required for create_batch")

        headers = provider_config.validate_environment(
            api_key=api_key,
            headers=headers,
            model=model,
            messages=[],
            optional_params={},
            litellm_params=litellm_params,
        )

        api_base = provider_config.get_complete_batch_url(
            api_base=api_base,
            api_key=api_key,
            model=model,
            optional_params={},
            litellm_params=litellm_params,
            data=create_batch_data,
        )
        if api_base is None:
            raise ValueError("api_base is required for create_batch")

        # Get the transformed request data
        transformed_request: Final = provider_config.transform_create_batch_request(
            model=model,
            create_batch_data=create_batch_data,
            litellm_params=litellm_params,
            optional_params={},
        )

        if _is_async:
            return self.async_create_batch(
                transformed_request=transformed_request,
                litellm_params=litellm_params,
                provider_config=provider_config,
                headers=headers,
                api_base=api_base,
                logging_obj=logging_obj,
                client=client,
                timeout=timeout,
                create_batch_data=create_batch_data,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client()
        else:
            sync_httpx_client = client

        try:
            if isinstance(transformed_request, dict) and "method" in transformed_request:
                # Handle pre-signed requests (e.g., from Bedrock with AWS auth)
                batch_response = getattr(sync_httpx_client, transformed_request["method"].lower())(
                    url=transformed_request["url"],
                    headers=transformed_request["headers"],
                    data=transformed_request["data"],
                    timeout=timeout,
                )
            elif isinstance(transformed_request, dict):
                # For other providers that use JSON requests
                batch_response = sync_httpx_client.post(
                    url=api_base,
                    headers={**headers, "Content-Type": "application/json"},
                    json=transformed_request,
                    timeout=timeout,
                )
            else:
                # Handle other request types if needed
                batch_response = sync_httpx_client.post(
                    url=api_base,
                    headers=headers,
                    data=transformed_request,
                    timeout=timeout,
                )
        except Exception as e:
            verbose_logger.exception("Error creating batch: %s", e)
            raise self._handle_error(
                e=e,
                provider_config=provider_config,
            )

        # Store original request for response transformation
        litellm_params_with_request: Final = {
            **litellm_params,
            "original_batch_request": create_batch_data,
        }

        return provider_config.transform_create_batch_response(
            model=model,
            raw_response=batch_response,
            logging_obj=logging_obj,
            litellm_params=litellm_params_with_request,
        )

    def retrieve_batch(
        self,
        batch_id: str,
        litellm_params: dict,
        provider_config: "BaseBatchesConfig",
        headers: dict,
        api_base: str | None,
        api_key: str | None,
        logging_obj: "LiteLLMLoggingObj",
        _is_async: bool = False,
        client: Union["HTTPHandler", "AsyncHTTPHandler"] | None = None,
        timeout: float | httpx.Timeout | None = None,
        model: str | None = None,
    ) -> Union["LiteLLMBatch", Coroutine[object, object, "LiteLLMBatch"]]:
        """
        Retrieve a batch using provider-specific configuration.
        """
        # Transform the request using provider config
        transformed_request: Final = provider_config.transform_retrieve_batch_request(
            batch_id=batch_id,
            optional_params=litellm_params,
            litellm_params=litellm_params,
        )

        if _is_async:
            return self.async_retrieve_batch(
                transformed_request=transformed_request,
                litellm_params=litellm_params,
                provider_config=provider_config,
                headers=headers,
                api_base=api_base,
                logging_obj=logging_obj,
                client=client,
                timeout=timeout,
                batch_id=batch_id,
                model=model,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client()
        else:
            sync_httpx_client = client

        try:
            if isinstance(transformed_request, dict) and "method" in transformed_request:
                # Handle pre-signed requests (e.g., from Bedrock with AWS auth)
                method: Final = transformed_request["method"].lower()
                request_kwargs: Final = {
                    "url": transformed_request["url"],
                    "headers": transformed_request["headers"],
                }

                # Only add data for non-GET requests
                if method != "get" and transformed_request.get("data") is not None:
                    request_kwargs["data"] = transformed_request["data"]

                batch_response = getattr(sync_httpx_client, method)(**request_kwargs)
            elif isinstance(transformed_request, dict) and api_base:
                # For other providers that use JSON requests
                batch_response = sync_httpx_client.get(
                    url=api_base,
                    headers={**headers, "Content-Type": "application/json"},
                    params=transformed_request,
                )
            else:
                # Handle other request types if needed
                if not api_base:
                    raise ValueError("api_base is required for non-pre-signed requests")
                batch_response = sync_httpx_client.get(
                    url=api_base,
                    headers=headers,
                )
        except Exception as e:
            verbose_logger.exception("Error retrieving batch: %s", e)
            raise self._handle_error(
                e=e,
                provider_config=provider_config,
            )

        return provider_config.transform_retrieve_batch_response(
            model=model,
            raw_response=batch_response,
            logging_obj=logging_obj,
            litellm_params=litellm_params,
        )

    async def async_create_batch(
        self,
        transformed_request: bytes | str | dict,
        litellm_params: dict,
        provider_config: "BaseBatchesConfig",
        headers: dict,
        api_base: str,
        logging_obj: "LiteLLMLoggingObj",
        client: Union["HTTPHandler", "AsyncHTTPHandler"] | None = None,
        timeout: float | httpx.Timeout | None = None,
        create_batch_data: Optional["CreateBatchRequest"] = None,
        model: str | None = None,
    ):
        """
        Async version of create_batch
        """
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(llm_provider=provider_config.custom_llm_provider)
        else:
            async_httpx_client = client

        #########################################################
        # Debug Logging
        #########################################################
        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "complete_input_dict": transformed_request,
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            if isinstance(transformed_request, dict) and "method" in transformed_request:
                # Handle pre-signed requests (e.g., from Bedrock with AWS auth)
                batch_response = await getattr(async_httpx_client, transformed_request["method"].lower())(
                    url=transformed_request["url"],
                    headers=transformed_request["headers"],
                    data=transformed_request["data"],
                    timeout=timeout,
                )
            elif isinstance(transformed_request, dict):
                # For other providers that use JSON requests
                batch_response = await async_httpx_client.post(
                    url=api_base,
                    headers={**headers, "Content-Type": "application/json"},
                    json=transformed_request,
                    timeout=timeout,
                )
            else:
                # Handle other request types if needed
                batch_response = await async_httpx_client.post(
                    url=api_base,
                    headers=headers,
                    data=transformed_request,
                    timeout=timeout,
                )
        except Exception as e:
            verbose_logger.exception("Error creating batch: %s", e)
            raise self._handle_error(
                e=e,
                provider_config=provider_config,
            )

        # Store original request for response transformation (for async version)
        litellm_params_with_request: Final = {
            **litellm_params,
            "original_batch_request": create_batch_data or {},
        }

        return provider_config.transform_create_batch_response(
            model=model,
            raw_response=batch_response,
            logging_obj=logging_obj,
            litellm_params=litellm_params_with_request,
        )

    async def async_retrieve_batch(
        self,
        transformed_request: bytes | str | dict,
        litellm_params: dict,
        provider_config: "BaseBatchesConfig",
        headers: dict,
        api_base: str | None,
        logging_obj: "LiteLLMLoggingObj",
        client: Union["HTTPHandler", "AsyncHTTPHandler"] | None = None,
        timeout: float | httpx.Timeout | None = None,
        batch_id: str | None = None,
        model: str | None = None,
    ):
        """
        Async version of retrieve_batch
        """
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(llm_provider=provider_config.custom_llm_provider)
        else:
            async_httpx_client = client

        #########################################################
        # Debug Logging
        #########################################################
        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "complete_input_dict": transformed_request,
                "api_base": api_base,
                "headers": headers,
                "batch_id": batch_id,
            },
        )

        try:
            if isinstance(transformed_request, dict) and "method" in transformed_request:
                # Handle pre-signed requests (e.g., from Bedrock with AWS auth)
                method: Final = transformed_request["method"].lower()
                request_kwargs: Final = {
                    "url": transformed_request["url"],
                    "headers": transformed_request["headers"],
                }

                # Only add data for non-GET requests
                if method != "get" and transformed_request.get("data") is not None:
                    request_kwargs["data"] = transformed_request["data"]

                batch_response = await getattr(async_httpx_client, method)(**request_kwargs)
            elif isinstance(transformed_request, dict) and api_base:
                # For other providers that use JSON requests
                batch_response = await async_httpx_client.get(
                    url=api_base,
                    headers={**headers, "Content-Type": "application/json"},
                    params=transformed_request,
                )
            else:
                # Handle other request types if needed
                if not api_base:
                    raise ValueError("api_base is required for non-pre-signed requests")
                batch_response = await async_httpx_client.get(
                    url=api_base,
                    headers=headers,
                )
        except Exception as e:
            verbose_logger.exception("Error retrieving batch: %s", e)
            raise self._handle_error(
                e=e,
                provider_config=provider_config,
            )

        return provider_config.transform_retrieve_batch_response(
            model=model,
            raw_response=batch_response,
            logging_obj=logging_obj,
            litellm_params=litellm_params,
        )

    def cancel_response_api_handler(
        self,
        response_id: str,
        responses_api_provider_config: BaseResponsesAPIConfig,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        custom_llm_provider: str | None,
        extra_headers: dict[str, object] | None = None,
        extra_body: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
        shared_session: Optional["ClientSession"] = None,
    ) -> ResponsesAPIResponse | Coroutine[object, object, ResponsesAPIResponse]:
        """
        Async version of the responses API handler.
        Uses async HTTP client to make requests.
        """
        if _is_async:
            return self.async_cancel_response_api_handler(
                response_id=response_id,
                responses_api_provider_config=responses_api_provider_config,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                custom_llm_provider=custom_llm_provider,
                extra_headers=extra_headers,
                extra_body=extra_body,
                timeout=timeout,
                client=client,
                shared_session=shared_session,
            )
        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = responses_api_provider_config.validate_environment(
            headers=extra_headers or {}, model="None", litellm_params=litellm_params
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = responses_api_provider_config.get_complete_url(
            api_base=litellm_params.api_base,
            litellm_params=dict(litellm_params),
        )

        url, data = responses_api_provider_config.transform_cancel_response_api_request(
            response_id=response_id,
            api_base=api_base,
            litellm_params=litellm_params,
            headers=headers,
        )

        ## LOGGING
        logging_obj.pre_call(
            input=response_id,
            api_key="",
            additional_args={
                "complete_input_dict": data,
                "api_base": url,
                "headers": headers,
            },
        )

        try:
            response: Final = sync_httpx_client.post(url=url, headers=headers, json=data, timeout=timeout)

        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=responses_api_provider_config,
            )

        return responses_api_provider_config.transform_cancel_response_api_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    async def async_cancel_response_api_handler(
        self,
        response_id: str,
        responses_api_provider_config: BaseResponsesAPIConfig,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        custom_llm_provider: str | None,
        extra_headers: dict[str, object] | None = None,
        extra_body: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
        shared_session: Optional["ClientSession"] = None,
    ) -> ResponsesAPIResponse:
        """
        Async version of the cancel response API handler.
        Uses async HTTP client to make requests.
        """
        if client is None or not isinstance(client, AsyncHTTPHandler):
            verbose_logger.debug(
                "Creating HTTP client for cancel_response with shared_session: %s",
                id(shared_session) if shared_session else None,
            )
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
                shared_session=shared_session,
            )
        else:
            async_httpx_client = client

        headers: Final = responses_api_provider_config.validate_environment(
            headers=extra_headers or {}, model="None", litellm_params=litellm_params
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = responses_api_provider_config.get_complete_url(
            api_base=litellm_params.api_base,
            litellm_params=dict(litellm_params),
        )

        url, data = responses_api_provider_config.transform_cancel_response_api_request(
            response_id=response_id,
            api_base=api_base,
            litellm_params=litellm_params,
            headers=headers,
        )

        ## LOGGING
        logging_obj.pre_call(
            input=response_id,
            api_key="",
            additional_args={
                "complete_input_dict": data,
                "api_base": url,
                "headers": headers,
            },
        )

        try:
            response: Final = await async_httpx_client.post(url=url, headers=headers, json=data, timeout=timeout)

        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=responses_api_provider_config,
            )

        return responses_api_provider_config.transform_cancel_response_api_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    def compact_response_api_handler(
        self,
        model: str,
        input: Union[str, "ResponseInputParam"],
        responses_api_provider_config: BaseResponsesAPIConfig,
        response_api_optional_request_params: dict,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        custom_llm_provider: str | None,
        extra_headers: dict[str, object] | None = None,
        extra_body: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
        shared_session: Optional["ClientSession"] = None,
    ) -> ResponsesAPIResponse | Coroutine[object, object, ResponsesAPIResponse]:
        """
        Handler for the compact responses API.
        """
        if _is_async:
            return self.async_compact_response_api_handler(
                model=model,
                input=input,
                responses_api_provider_config=responses_api_provider_config,
                response_api_optional_request_params=response_api_optional_request_params,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                custom_llm_provider=custom_llm_provider,
                extra_headers=extra_headers,
                extra_body=extra_body,
                timeout=timeout,
                client=client,
                shared_session=shared_session,
            )
        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers = responses_api_provider_config.validate_environment(
            headers=extra_headers or {}, model=model, litellm_params=litellm_params
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = responses_api_provider_config.get_complete_url(
            api_base=litellm_params.api_base,
            litellm_params=dict(litellm_params),
        )

        (
            url,
            data,
        ) = responses_api_provider_config.transform_compact_response_api_request(
            model=model,
            input=input,
            response_api_optional_request_params=response_api_optional_request_params,
            api_base=api_base,
            litellm_params=litellm_params,
            headers=headers,
        )
        data = BaseResponsesAPIConfig.normalize_responses_api_request_dict(data)

        headers, signed_body = responses_api_provider_config.sign_request(
            headers=headers,
            optional_params=dict(litellm_params),
            request_data=data,
            api_base=url,
            api_key=litellm_params.api_key,
            model=model,
        )
        body_kwargs: Final[dict[str, Any]] = {"data": signed_body} if signed_body is not None else {"json": data}

        ## LOGGING
        logging_obj.pre_call(
            input=input,
            api_key="",
            additional_args={
                "complete_input_dict": data,
                "api_base": url,
                "headers": headers,
            },
        )

        try:
            response: Final = sync_httpx_client.post(url=url, headers=headers, timeout=timeout, **body_kwargs)

        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=responses_api_provider_config,
            )

        return responses_api_provider_config.transform_compact_response_api_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    async def async_compact_response_api_handler(
        self,
        model: str,
        input: Union[str, "ResponseInputParam"],
        responses_api_provider_config: BaseResponsesAPIConfig,
        response_api_optional_request_params: dict,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        custom_llm_provider: str | None,
        extra_headers: dict[str, object] | None = None,
        extra_body: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
        shared_session: Optional["ClientSession"] = None,
    ) -> ResponsesAPIResponse:
        """
        Async version of the compact response API handler.
        """
        if client is None or not isinstance(client, AsyncHTTPHandler):
            verbose_logger.debug(
                "Creating HTTP client for compact_response with shared_session: %s",
                id(shared_session) if shared_session else None,
            )
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
                shared_session=shared_session,
            )
        else:
            async_httpx_client = client

        headers = responses_api_provider_config.validate_environment(
            headers=extra_headers or {}, model=model, litellm_params=litellm_params
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = responses_api_provider_config.get_complete_url(
            api_base=litellm_params.api_base,
            litellm_params=dict(litellm_params),
        )

        (
            url,
            data,
        ) = responses_api_provider_config.transform_compact_response_api_request(
            model=model,
            input=input,
            response_api_optional_request_params=response_api_optional_request_params,
            api_base=api_base,
            litellm_params=litellm_params,
            headers=headers,
        )
        data = BaseResponsesAPIConfig.normalize_responses_api_request_dict(data)

        headers, signed_body = responses_api_provider_config.sign_request(
            headers=headers,
            optional_params=dict(litellm_params),
            request_data=data,
            api_base=url,
            api_key=litellm_params.api_key,
            model=model,
        )
        body_kwargs: Final[dict[str, Any]] = {"data": signed_body} if signed_body is not None else {"json": data}

        ## LOGGING
        logging_obj.pre_call(
            input=input,
            api_key="",
            additional_args={
                "complete_input_dict": data,
                "api_base": url,
                "headers": headers,
            },
        )

        try:
            response: Final = await async_httpx_client.post(url=url, headers=headers, timeout=timeout, **body_kwargs)

        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=responses_api_provider_config,
            )

        return responses_api_provider_config.transform_compact_response_api_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    def retrieve_file(
        self,
        file_id: str,
        provider_config: BaseFilesConfig,
        litellm_params: dict,
        headers: dict,
        logging_obj: LiteLLMLoggingObj,
        _is_async: bool = False,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        timeout: float | httpx.Timeout | None = None,
    ) -> OpenAIFileObject | Coroutine[object, object, OpenAIFileObject]:
        """
        Retrieve file metadata by ID
        """
        if _is_async:
            return self.async_retrieve_file(
                file_id=file_id,
                provider_config=provider_config,
                litellm_params=litellm_params,
                headers=headers,
                logging_obj=logging_obj,
                client=client,
                timeout=timeout,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client()
        else:
            sync_httpx_client = client

        # Get URL and params from provider config
        url, params = provider_config.transform_retrieve_file_request(
            file_id=file_id,
            optional_params={},
            litellm_params=litellm_params,
        )

        # Validate environment and get headers
        headers = provider_config.validate_environment(
            api_key=litellm_params.get("api_key"),
            headers=headers,
            model="",
            messages=[],
            optional_params={},
            litellm_params=litellm_params,
        )

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
                "file_id": file_id,
            },
        )

        try:
            response: Final = sync_httpx_client.get(url=url, headers=headers, params=params)
        except Exception as e:
            raise self._handle_error(e=e, provider_config=provider_config)

        return provider_config.transform_retrieve_file_response(
            raw_response=response,
            logging_obj=logging_obj,
            litellm_params=litellm_params,
        )

    async def async_retrieve_file(
        self,
        file_id: str,
        provider_config: BaseFilesConfig,
        litellm_params: dict,
        headers: dict,
        logging_obj: LiteLLMLoggingObj,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        timeout: float | httpx.Timeout | None = None,
    ) -> OpenAIFileObject:
        """
        Async retrieve file metadata by ID
        """
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(llm_provider=provider_config.custom_llm_provider)
        else:
            async_httpx_client = client

        # Get URL and params from provider config
        url, params = provider_config.transform_retrieve_file_request(
            file_id=file_id,
            optional_params={},
            litellm_params=litellm_params,
        )

        # Validate environment and get headers
        headers = provider_config.validate_environment(
            api_key=litellm_params.get("api_key"),
            headers=headers,
            model="",
            messages=[],
            optional_params={},
            litellm_params=litellm_params,
        )

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
                "file_id": file_id,
            },
        )

        try:
            response: Final = await async_httpx_client.get(url=url, headers=headers, params=params)
        except Exception as e:
            raise self._handle_error(e=e, provider_config=provider_config)

        return provider_config.transform_retrieve_file_response(
            raw_response=response,
            logging_obj=logging_obj,
            litellm_params=litellm_params,
        )

    def delete_file(
        self,
        file_id: str,
        provider_config: BaseFilesConfig,
        litellm_params: dict,
        headers: dict,
        logging_obj: LiteLLMLoggingObj,
        _is_async: bool = False,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        timeout: float | httpx.Timeout | None = None,
    ) -> Union["FileDeleted", Coroutine[object, object, "FileDeleted"]]:
        """
        Delete a file by ID
        """
        if _is_async:
            return self.async_delete_file(
                file_id=file_id,
                provider_config=provider_config,
                litellm_params=litellm_params,
                headers=headers,
                logging_obj=logging_obj,
                client=client,
                timeout=timeout,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client()
        else:
            sync_httpx_client = client

        # Get URL and params from provider config
        url, params = provider_config.transform_delete_file_request(
            file_id=file_id,
            optional_params={},
            litellm_params=litellm_params,
        )

        # Validate environment and get headers
        headers = provider_config.validate_environment(
            api_key=litellm_params.get("api_key"),
            headers=headers,
            model="",
            messages=[],
            optional_params={},
            litellm_params=litellm_params,
        )

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
                "file_id": file_id,
            },
        )

        try:
            response: Final = sync_httpx_client.delete(url=url, headers=headers, params=params)
        except Exception as e:
            raise self._handle_error(e=e, provider_config=provider_config)

        return provider_config.transform_delete_file_response(
            raw_response=response,
            logging_obj=logging_obj,
            litellm_params=litellm_params,
        )

    async def async_delete_file(
        self,
        file_id: str,
        provider_config: BaseFilesConfig,
        litellm_params: dict,
        headers: dict,
        logging_obj: LiteLLMLoggingObj,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        timeout: float | httpx.Timeout | None = None,
    ) -> "FileDeleted":
        """
        Async delete a file by ID
        """
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(llm_provider=provider_config.custom_llm_provider)
        else:
            async_httpx_client = client

        # Get URL and params from provider config
        url, params = provider_config.transform_delete_file_request(
            file_id=file_id,
            optional_params={},
            litellm_params=litellm_params,
        )

        # Validate environment and get headers
        headers = provider_config.validate_environment(
            api_key=litellm_params.get("api_key"),
            headers=headers,
            model="",
            messages=[],
            optional_params={},
            litellm_params=litellm_params,
        )

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
                "file_id": file_id,
            },
        )

        try:
            response: Final = await async_httpx_client.delete(url=url, headers=headers, params=params, timeout=timeout)
        except Exception as e:
            raise self._handle_error(e=e, provider_config=provider_config)

        return provider_config.transform_delete_file_response(
            raw_response=response,
            logging_obj=logging_obj,
            litellm_params=litellm_params,
        )

    def list_files(
        self,
        purpose: str | None,
        provider_config: BaseFilesConfig,
        litellm_params: dict,
        headers: dict,
        logging_obj: LiteLLMLoggingObj,
        _is_async: bool = False,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        timeout: float | httpx.Timeout | None = None,
    ) -> list[OpenAIFileObject] | Coroutine[object, object, list[OpenAIFileObject]]:
        """
        List all files
        """
        if _is_async:
            return self.async_list_files(
                purpose=purpose,
                provider_config=provider_config,
                litellm_params=litellm_params,
                headers=headers,
                logging_obj=logging_obj,
                client=client,
                timeout=timeout,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client()
        else:
            sync_httpx_client = client

        # Get URL and params from provider config
        url, params = provider_config.transform_list_files_request(
            purpose=purpose,
            optional_params={},
            litellm_params=litellm_params,
        )

        # Validate environment and get headers
        headers = provider_config.validate_environment(
            api_key=litellm_params.get("api_key"),
            headers=headers,
            model="",
            messages=[],
            optional_params={},
            litellm_params=litellm_params,
        )

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
                "purpose": purpose,
            },
        )

        try:
            response: Final = sync_httpx_client.get(url=url, headers=headers, params=params)
        except Exception as e:
            raise self._handle_error(e=e, provider_config=provider_config)

        return provider_config.transform_list_files_response(
            raw_response=response,
            logging_obj=logging_obj,
            litellm_params=litellm_params,
        )

    async def async_list_files(
        self,
        purpose: str | None,
        provider_config: BaseFilesConfig,
        litellm_params: dict,
        headers: dict,
        logging_obj: LiteLLMLoggingObj,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        timeout: float | httpx.Timeout | None = None,
    ) -> list[OpenAIFileObject]:
        """
        Async list all files
        """
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(llm_provider=provider_config.custom_llm_provider)
        else:
            async_httpx_client = client

        # Get URL and params from provider config
        url, params = provider_config.transform_list_files_request(
            purpose=purpose,
            optional_params={},
            litellm_params=litellm_params,
        )

        # Validate environment and get headers
        headers = provider_config.validate_environment(
            api_key=litellm_params.get("api_key"),
            headers=headers,
            model="",
            messages=[],
            optional_params={},
            litellm_params=litellm_params,
        )

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
                "purpose": purpose,
            },
        )

        try:
            response: Final = await async_httpx_client.get(url=url, headers=headers, params=params)
        except Exception as e:
            raise self._handle_error(e=e, provider_config=provider_config)

        return provider_config.transform_list_files_response(
            raw_response=response,
            logging_obj=logging_obj,
            litellm_params=litellm_params,
        )

    def retrieve_file_content(
        self,
        file_content_request: "FileContentRequest",
        provider_config: BaseFilesConfig,
        litellm_params: dict,
        headers: dict,
        logging_obj: LiteLLMLoggingObj,
        _is_async: bool = False,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        timeout: float | httpx.Timeout | None = None,
    ) -> Union["HttpxBinaryResponseContent", Coroutine[object, object, "HttpxBinaryResponseContent"]]:
        """
        Retrieve file content by ID
        """
        if _is_async:
            return self.async_retrieve_file_content(
                file_content_request=file_content_request,
                provider_config=provider_config,
                litellm_params=litellm_params,
                headers=headers,
                logging_obj=logging_obj,
                client=client,
                timeout=timeout,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client()
        else:
            sync_httpx_client = client

        # Get URL and params from provider config
        url, params = provider_config.transform_file_content_request(
            file_content_request=file_content_request,
            optional_params={},
            litellm_params=litellm_params,
        )

        # Validate environment and get headers
        headers = provider_config.validate_environment(
            api_key=litellm_params.get("api_key"),
            headers=headers,
            model="",
            messages=[],
            optional_params={},
            litellm_params=litellm_params,
        )

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
                "file_id": file_content_request.get("file_id"),
            },
        )

        try:
            response: Final = sync_httpx_client.get(url=url, headers=headers, params=params)
        except Exception as e:
            raise self._handle_error(e=e, provider_config=provider_config)

        if response.status_code >= 400:
            raise provider_config.get_error_class(
                error_message=response.text,
                status_code=response.status_code,
                headers=response.headers,
            )

        return provider_config.transform_file_content_response(
            raw_response=response,
            logging_obj=logging_obj,
            litellm_params=litellm_params,
        )

    async def async_retrieve_file_content(
        self,
        file_content_request: "FileContentRequest",
        provider_config: BaseFilesConfig,
        litellm_params: dict,
        headers: dict,
        logging_obj: LiteLLMLoggingObj,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        timeout: float | httpx.Timeout | None = None,
    ) -> "HttpxBinaryResponseContent":
        """
        Async retrieve file content by ID
        """
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(llm_provider=provider_config.custom_llm_provider)
        else:
            async_httpx_client = client

        # Get URL and params from provider config
        url, params = provider_config.transform_file_content_request(
            file_content_request=file_content_request,
            optional_params={},
            litellm_params=litellm_params,
        )

        # Validate environment and get headers
        headers = provider_config.validate_environment(
            api_key=litellm_params.get("api_key"),
            headers=headers,
            model="",
            messages=[],
            optional_params={},
            litellm_params=litellm_params,
        )

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
                "file_id": file_content_request.get("file_id"),
            },
        )

        try:
            response: Final = await async_httpx_client.get(url=url, headers=headers, params=params)
        except Exception as e:
            raise self._handle_error(e=e, provider_config=provider_config)

        if response.status_code >= 400:
            raise provider_config.get_error_class(
                error_message=response.text,
                status_code=response.status_code,
                headers=response.headers,
            )

        return provider_config.transform_file_content_response(
            raw_response=response,
            logging_obj=logging_obj,
            litellm_params=litellm_params,
        )

    def _prepare_fake_stream_request(
        self,
        stream: bool,
        data: dict,
        fake_stream: bool,
    ) -> tuple[bool, dict]:
        """
        Handles preparing a request when `fake_stream` is True.
        """
        if fake_stream is True:
            stream = False
            data.pop("stream", None)
            return stream, data
        return stream, data

    @staticmethod
    def _get_agentic_loop_settings(kwargs: dict) -> tuple[int, int, list[str]]:
        depth: Final = int(kwargs.get("_agentic_loop_depth", 0) or 0)
        configured: Final = validated_max_agentic_loops(
            kwargs.get("max_agentic_loops"), field="litellm_params.max_agentic_loops"
        )
        max_loops: Final = DEFAULT_MAX_AGENTIC_LOOPS if configured is None else configured
        fingerprints: Final = list(kwargs.get("_agentic_loop_fingerprints", []) or [])
        return depth, max_loops, fingerprints

    @staticmethod
    def _has_agentic_completion_hook(logging_obj: LiteLLMLoggingObj) -> bool:
        """
        True if any registered callback actually overrides
        ``async_should_run_agentic_loop`` (the gate every agentic hook goes
        through). The base ``CustomLogger`` implementation returns
        ``(False, {})``, so when nothing overrides it the agentic
        post-processing is a guaranteed no-op and the streaming wrapper that
        buffers + rebuilds the whole response from SSE just to call it can be
        skipped entirely.

        Function-identity comparison (not a leaf ``__dict__`` check) so an
        override inherited through any intermediate class is still detected --
        a false negative here would silently disable agentic features.

        String entries in ``litellm.callbacks`` (e.g. ``"datadog"``) are
        resolved to their ``CustomLogger`` instance via
        ``get_custom_logger_compatible_class`` -- same pattern as
        ``ProxyLogging._callback_capabilities`` -- so a string-registered
        agentic callback is detected too.
        """
        from litellm.integrations.custom_logger import CustomLogger

        base_func: Final = CustomLogger.async_should_run_agentic_loop
        for cb in _custom_logger_callbacks(logging_obj):
            cb_func = getattr(type(cb), "async_should_run_agentic_loop", base_func)
            if getattr(cb_func, "__func__", cb_func) is not getattr(base_func, "__func__", base_func):
                return True
        return False

    @staticmethod
    def _server_fulfilled_tools_in_request(logging_obj: LiteLLMLoggingObj, tools: object) -> frozenset[str]:
        """The request's tools that a registered callback fulfills server-side (e.g. ``headroom_retrieve``)."""
        if not isinstance(tools, list) or not tools:
            return frozenset()
        from litellm.litellm_core_utils.prompt_templates.factory import has_tool_with_name

        return frozenset(
            name
            for cb in _custom_logger_callbacks(logging_obj)
            for name in getattr(cb, "server_fulfilled_tool_names", frozenset())
            if has_tool_with_name(tools, name)
        )

    @staticmethod
    def _check_agentic_loop_safety(
        tool_calls: object,
        fingerprints: list[str],
        depth: int,
        max_loops: int,
        model: str,
    ) -> str:
        """
        Evaluate agentic-loop safety guards (fingerprint cycle / max depth).

        Raises AgenticLoopSafetyError on abort.  Returns the current fingerprint
        on success.

        These checks must not be swallowed by the per-callback ``except Exception``
        block that wraps callback dispatch — they are bounded-loop / cycle-break
        safety rails and must abort the agentic dispatch when they trip.
        """
        fingerprint: Final = BaseLLMHTTPHandler._fingerprint_agentic_tools(tool_calls)
        if fingerprint in fingerprints:
            raise AgenticLoopSafetyError("Agentic loop detected repeated tool-call fingerprint; aborting rerun")
        if depth >= max_loops:
            raise AgenticLoopSafetyError(f"Exceeded max_agentic_loops={max_loops} for model={model}")
        return fingerprint

    @staticmethod
    def _fingerprint_agentic_tools(tools: object) -> str:
        try:
            return json.dumps(tools, sort_keys=True, default=str)
        except Exception:
            return str(tools)

    @staticmethod
    def _refused_agentic_tool_identifiers(tool_calls: object) -> tuple[frozenset[str], frozenset[str]]:
        """
        Collect the ids and names of the tool calls a safety rail just refused.

        Callbacks hand back either a bare list of tool calls or a dict wrapping
        that list under ``tool_calls``, and both the anthropic and responses
        shapes carry an ``id`` (or ``call_id``) plus a ``name``.
        """
        calls: Final = tool_calls.get("tool_calls") if isinstance(tool_calls, dict) else tool_calls
        if not isinstance(calls, list):
            return frozenset(), frozenset()
        dict_calls: Final = (call for call in calls if isinstance(call, dict))
        fields: Final = tuple((call.get("id"), call.get("call_id"), call.get("name")) for call in dict_calls)
        ids: Final = frozenset(
            value for call_id, caller_id, _ in fields for value in (call_id, caller_id) if isinstance(value, str)
        )
        names: Final = frozenset(name for _, _, name in fields if isinstance(name, str))
        return ids, names

    @staticmethod
    def _is_refused_tool_use_block(block: object, refused_ids: frozenset[str], refused_names: frozenset[str]) -> bool:
        """
        Whether this response block belongs to a tool call the rail refused.

        An id settles it on its own, so a block carrying one is matched on the id
        alone and a client's own tool call survives even where it happens to
        share a name with a refused one. The name is only consulted for tool call
        shapes that arrive without an id.
        """
        if not isinstance(block, dict) or block.get("type") != "tool_use":
            return False
        block_id: Final = block.get("id")
        if isinstance(block_id, str) and refused_ids:
            return block_id in refused_ids
        return block.get("name") in refused_names

    @staticmethod
    def _can_replace_turn_with_terminal_response(stream: bool, api_surface: str) -> bool:
        """
        Whether a refused rerun can still be answered with a finalized turn.

        Only the anthropic messages surface can. The responses surface carries a
        pydantic model the finalizer does not rewrite, so it keeps raising, which
        is what every surface did before this path learned to end the turn.

        The messages and responses call sites pass ``stream=False``, because
        interception converts an intercepted stream to non-streaming before the
        loop runs and rebuilds the SSE stream from the finalized turn
        afterwards. ``AgenticStreamingIterator`` passes ``stream=True``, and
        that path keeps raising: its events are already on the wire, so a
        finalized turn would reach the client as a second message rather than
        as a replacement.
        """
        return not stream and api_surface == "anthropic_messages"

    @staticmethod
    def _finalize_refused_agentic_response(response: object, tool_calls: object) -> object:
        """
        Turn the response into a terminal turn after a safety rail refused the rerun.

        The refused tool calls target tools LiteLLM injected on the client's
        behalf, so a client that never declared them cannot send back a matching
        ``tool_result``. Their blocks are dropped and a ``tool_use`` stop reason
        is closed out as ``end_turn``, which is what a provider-native web search
        turn returns once it stops calling tools.

        A ``tool_use`` block the client itself declared is left alone, and while
        one is still in the response the stop reason stays ``tool_use`` so the
        client knows to answer it.
        """
        if not isinstance(response, dict):
            return response

        refused_ids, refused_names = BaseLLMHTTPHandler._refused_agentic_tool_identifiers(tool_calls)
        finalized: Final = dict(response)
        content: Final = finalized.get("content")
        if isinstance(content, list):
            kept_blocks: Final = [
                block
                for block in content
                if not BaseLLMHTTPHandler._is_refused_tool_use_block(block, refused_ids, refused_names)
            ]
            finalized["content"] = kept_blocks
            client_tool_use_remains: Final = any(
                isinstance(block, dict) and block.get("type") == "tool_use" for block in kept_blocks
            )
            if not client_tool_use_remains and finalized.get("stop_reason") == "tool_use":
                finalized["stop_reason"] = "end_turn"
        return finalized

    async def _execute_anthropic_agentic_plan(
        self,
        plan: AgenticLoopPlan,
        model: str,
        messages: list[dict],
        anthropic_messages_optional_request_params: dict,
        logging_obj: "LiteLLMLoggingObj",
        kwargs: dict,
        depth: int,
        max_loops: int,
        fingerprints: list[str],
        fingerprint: str,
        stream: bool = False,
        callback: Optional["CustomLogger"] = None,
    ) -> AnthropicMessagesResponse | AsyncIterator[object]:
        from litellm.anthropic_interface import messages as anthropic_messages

        patch: Final = plan.request_patch or AgenticLoopRequestPatch()
        if patch.messages is None:
            raise ValueError("Agentic loop plan missing patched messages")

        full_model_name = model
        if logging_obj is not None:
            agentic_params: Final[Mapping[str, object]] = logging_obj.model_call_details.get("agentic_loop_params", {})
            full_model_name = cast(str, agentic_params.get("model", model))

        optional_params: Final = dict(anthropic_messages_optional_request_params)
        optional_params.update(patch.optional_params)
        if patch.tools is not None:
            optional_params["tools"] = patch.tools

        max_tokens = patch.max_tokens
        if max_tokens is None:
            max_tokens = cast(int | None, optional_params.pop("max_tokens", None))
        else:
            optional_params.pop("max_tokens", None)
        if max_tokens is None:
            max_tokens = cast(int, kwargs.get("max_tokens", 1024))

        internal_keys: Final = {"litellm_logging_obj"}
        kwargs_for_followup: Final = {
            k: v
            for k, v in kwargs.items()
            if not k.startswith("_websearch_interception")
            and not k.startswith("_compression_interception")
            and k not in internal_keys
            and k not in optional_params
        }
        kwargs_for_followup.update(patch.kwargs)
        kwargs_for_followup["_agentic_loop_depth"] = depth + 1
        kwargs_for_followup["max_agentic_loops"] = max_loops
        kwargs_for_followup["_agentic_loop_fingerprints"] = fingerprints + [fingerprint]

        response: AnthropicMessagesResponse | AsyncIterator[object] = await anthropic_messages.acreate(
            **{
                "max_tokens": max_tokens,
                "messages": patch.messages,
                "model": patch.model or full_model_name,
                "stream": stream,
                **optional_params,
                **kwargs_for_followup,
            }
        )

        if callback is not None:
            try:
                response = await callback.async_post_agentic_loop_response_hook(
                    response=response, plan=plan, kwargs=kwargs
                )
            except Exception as e:
                _call_id: Final = getattr(logging_obj, "litellm_call_id", "unknown")
                verbose_logger.exception(
                    "LiteLLM.AgenticHookError: Exception in "
                    "async_post_agentic_loop_response_hook [call_id=%s model=%s]: %s",
                    _call_id,
                    model,
                    str(e),
                )

        return response

    async def _execute_responses_agentic_plan(
        self,
        plan: AgenticLoopPlan,
        model: str,
        response_api_optional_request_params: dict,
        logging_obj: "LiteLLMLoggingObj",
        kwargs: dict,
        depth: int,
        max_loops: int,
        fingerprints: list[str],
        fingerprint: str,
        callback: Optional["CustomLogger"] = None,
    ) -> ResponsesAPIResponse | BaseResponsesAPIStreamingIterator:
        patch: Final = plan.request_patch or AgenticLoopRequestPatch()
        if patch.messages is None:
            raise ValueError("Agentic loop plan missing patched responses input")

        optional_params = dict(response_api_optional_request_params)
        optional_params.update(patch.optional_params)
        if patch.tools is not None:
            optional_params["tools"] = patch.tools
        optional_params = {
            k: v
            for k, v in optional_params.items()
            if k != "stream" and k != "_code_interpreter_interception_converted_stream"
        }

        internal_keys: Final = {"litellm_logging_obj"}
        kwargs_for_followup: Final = {
            k: v
            for k, v in kwargs.items()
            if not k.startswith("_websearch_interception")
            and not k.startswith("_compression_interception")
            and k != "_code_interpreter_interception_converted_stream"
            and k not in internal_keys
            and k not in optional_params
        }
        kwargs_for_followup.update(patch.kwargs)
        kwargs_for_followup["_agentic_loop_depth"] = depth + 1
        kwargs_for_followup["max_agentic_loops"] = max_loops
        kwargs_for_followup["_agentic_loop_fingerprints"] = fingerprints + [fingerprint]

        try:
            response: ResponsesAPIResponse | BaseResponsesAPIStreamingIterator = await litellm.aresponses(
                model=patch.model or model,
                input=patch.messages,
                **optional_params,
                **kwargs_for_followup,
            )

            if callback is not None:
                try:
                    response = await callback.async_post_agentic_loop_response_hook(
                        response=response, plan=plan, kwargs=kwargs
                    )
                except Exception as e:
                    _call_id: Final = getattr(logging_obj, "litellm_call_id", "unknown")
                    verbose_logger.exception(
                        "LiteLLM.AgenticHookError: Exception in "
                        "async_post_agentic_loop_response_hook [call_id=%s model=%s]: %s",
                        _call_id,
                        model,
                        str(e),
                    )

            return response
        finally:
            if callback is not None:
                await self._run_agentic_loop_cleanup(
                    callback=callback,
                    plan=plan,
                    kwargs=kwargs,
                    logging_obj=logging_obj,
                    model=model,
                )

    @staticmethod
    async def _run_agentic_loop_cleanup(
        callback: "CustomLogger",
        plan: AgenticLoopPlan,
        kwargs: dict,
        logging_obj: "LiteLLMLoggingObj",
        model: str,
    ) -> None:
        try:
            await callback.async_agentic_loop_cleanup_hook(plan=plan, kwargs=kwargs)
        except Exception as e:
            _call_id: Final = getattr(logging_obj, "litellm_call_id", "unknown")
            verbose_logger.exception(
                "LiteLLM.AgenticHookError: Exception in async_agentic_loop_cleanup_hook [call_id=%s model=%s]: %s",
                _call_id,
                model,
                str(e),
            )

    def _wrap_responses_response_as_fake_stream(
        self,
        result: ResponsesAPIResponse,
        model: str,
        responses_api_provider_config: BaseResponsesAPIConfig,
        logging_obj: "LiteLLMLoggingObj",
        custom_llm_provider: str,
    ) -> MockResponsesAPIStreamingIterator:
        """
        Wrap a completed responses result as a synthetic stream.

        Used when an interceptor forced stream=False to run the agentic loop on
        the non-streaming path, but the caller originally asked for streaming.
        """
        import httpx

        from litellm.responses.streaming_iterator import (
            MockResponsesAPIStreamingIterator,
        )

        payload: Final = result.model_dump() if hasattr(result, "model_dump") else result
        raw_response: Final = httpx.Response(status_code=200, json=payload)
        return MockResponsesAPIStreamingIterator(
            response=raw_response,
            model=model,
            responses_api_provider_config=responses_api_provider_config,
            logging_obj=logging_obj,
            custom_llm_provider=custom_llm_provider,
        )

    async def _execute_chat_completion_agentic_plan(
        self,
        plan: AgenticLoopPlan,
        model: str,
        messages: list[dict],
        optional_params: dict,
        kwargs: dict,
        custom_llm_provider: str,
        depth: int,
        max_loops: int,
        fingerprints: list[str],
        fingerprint: str,
    ) -> Any:
        patch: Final = plan.request_patch or AgenticLoopRequestPatch()
        if patch.messages is None:
            raise ValueError("Agentic loop plan missing patched messages")

        full_model_name = patch.model or model
        if "/" not in full_model_name:
            full_model_name = f"{custom_llm_provider}/{full_model_name}"

        optional_params_for_followup: Final = dict(optional_params)
        optional_params_for_followup.update(patch.optional_params)
        if patch.tools is not None:
            optional_params_for_followup["tools"] = patch.tools

        internal_params: Final = {
            "_websearch_interception",
            "acompletion",
            "litellm_logging_obj",
            "custom_llm_provider",
            "model_alias_map",
            "stream_response",
            "custom_prompt_dict",
        }
        kwargs_for_followup: Final = {
            k: v
            for k, v in kwargs.items()
            if not k.startswith("_websearch_interception")
            and not k.startswith("_compression_interception")
            and k not in internal_params
        }
        kwargs_for_followup.update(patch.kwargs)
        kwargs_for_followup["_agentic_loop_depth"] = depth + 1
        kwargs_for_followup["max_agentic_loops"] = max_loops
        kwargs_for_followup["_agentic_loop_fingerprints"] = fingerprints + [fingerprint]

        return await litellm.acompletion(
            model=full_model_name,
            messages=patch.messages,
            **optional_params_for_followup,
            **kwargs_for_followup,
        )

    def _maybe_wrap_in_fake_stream(
        self,
        response: _ResponseT,
        logging_obj: Optional["LiteLLMLoggingObj"],
        api_surface: str,
    ) -> Union[_ResponseT, "FakeAnthropicMessagesStreamIterator"]:
        """
        If the original request was streaming but converted to non-streaming for
        WebSearch interception, wrap the dict response in a FakeAnthropicMessagesStreamIterator.

        The converted-stream flag is only ever set by anthropic-messages websearch
        interception, and the wrapper rebuilds an Anthropic SSE stream, so wrapping
        is gated on ``api_surface == "anthropic_messages"`` to leave other surfaces
        (e.g. the responses API) untouched.
        """
        if api_surface != "anthropic_messages":
            return response
        websearch_converted_stream: Final = (
            logging_obj.model_call_details.get("websearch_interception_converted_stream", False)
            if logging_obj is not None
            else False
        )
        if websearch_converted_stream and isinstance(response, dict):
            from typing import cast

            from litellm._logging import verbose_logger
            from litellm.llms.anthropic.experimental_pass_through.messages.fake_stream_iterator import (
                FakeAnthropicMessagesStreamIterator,
            )
            from litellm.types.llms.anthropic_messages.anthropic_response import (
                AnthropicMessagesResponse,
            )

            verbose_logger.debug(
                "WebSearchInterception: Agentic loop completed, converting non-streaming response to fake stream"
            )
            return FakeAnthropicMessagesStreamIterator(response=cast(AnthropicMessagesResponse, response))
        return response

    async def _call_agentic_completion_hooks(
        self,
        response: object,
        model: str,
        messages: list[dict],
        anthropic_messages_provider_config: "BaseAnthropicMessagesConfig",
        anthropic_messages_optional_request_params: dict,
        logging_obj: "LiteLLMLoggingObj",
        stream: bool,
        custom_llm_provider: str,
        kwargs: dict,
        api_surface: str = "anthropic_messages",
    ) -> Any | None:
        """
        Call agentic completion hooks for all custom loggers (Anthropic Messages API).

        1. Call async_should_run_agentic_loop to check if agentic loop is needed
        2. If yes, call async_run_agentic_loop to execute the loop

        Returns the response from agentic loop, or None if no hook runs.
        """
        from litellm._logging import verbose_logger
        from litellm.integrations.custom_logger import CustomLogger

        callbacks: Final = litellm.callbacks + (logging_obj.dynamic_success_callbacks or [])
        tools: Final = anthropic_messages_optional_request_params.get("tools", [])
        depth, max_loops, fingerprints = self._get_agentic_loop_settings(kwargs=kwargs)

        hook_kwargs: Final = {**kwargs, "_agentic_loop_api_surface": api_surface}

        for callback in callbacks:
            if not isinstance(callback, CustomLogger):
                continue

            should_run: bool = False
            tool_calls: object = None
            try:
                # First: Check if agentic loop should run.  Wrap in try/except
                # to shield from buggy user callbacks — a callback crash should
                # not abort the whole request.
                (
                    should_run,
                    tool_calls,
                ) = await callback.async_should_run_agentic_loop(
                    response=response,
                    model=model,
                    messages=messages,
                    tools=tools,
                    stream=stream,
                    custom_llm_provider=custom_llm_provider,
                    kwargs=hook_kwargs,
                )
            except Exception as e:
                verbose_logger.exception(
                    "LiteLLM.AgenticHookError: Exception in async_should_run_agentic_loop [call_id=%s model=%s]: %s",
                    logging_obj.litellm_call_id,
                    model,
                    str(e),
                )
                continue

            if not should_run:
                continue

            # Safety guards must run OUTSIDE the callback try/except — they are
            # bounded-loop / cycle-break rails, not callback bugs.
            try:
                fingerprint = self._check_agentic_loop_safety(
                    tool_calls=tool_calls,
                    fingerprints=fingerprints,
                    depth=depth,
                    max_loops=max_loops,
                    model=model,
                )
            except AgenticLoopSafetyError as e:
                if not self._can_replace_turn_with_terminal_response(stream, api_surface):
                    raise
                verbose_logger.warning(
                    "LiteLLM.AgenticLoopRefused: ending turn [call_id=%s model=%s]: %s",
                    logging_obj.litellm_call_id,
                    model,
                    str(e),
                )
                return self._maybe_wrap_in_fake_stream(
                    self._finalize_refused_agentic_response(response=response, tool_calls=tool_calls),
                    logging_obj,
                    api_surface,
                )

            try:
                kwargs_with_provider = hook_kwargs.copy()
                kwargs_with_provider["custom_llm_provider"] = custom_llm_provider
                build_plan_overridden = (
                    callback.__class__.async_build_agentic_loop_plan is not CustomLogger.async_build_agentic_loop_plan
                )
                if not build_plan_overridden:
                    agentic_result: object = await callback.async_run_agentic_loop(
                        tools=tool_calls,
                        model=model,
                        messages=messages,
                        response=response,
                        anthropic_messages_provider_config=anthropic_messages_provider_config,
                        anthropic_messages_optional_request_params=anthropic_messages_optional_request_params,
                        logging_obj=logging_obj,
                        stream=stream,
                        kwargs=kwargs_with_provider,
                    )
                    return self._maybe_wrap_in_fake_stream(agentic_result, logging_obj, api_surface)

                plan = await callback.async_build_agentic_loop_plan(
                    tools=tool_calls,
                    model=model,
                    messages=messages,
                    response=response,
                    anthropic_messages_provider_config=anthropic_messages_provider_config,
                    anthropic_messages_optional_request_params=anthropic_messages_optional_request_params,
                    logging_obj=logging_obj,
                    stream=stream,
                    kwargs=kwargs_with_provider,
                )

                if plan.response_override is not None:
                    return self._maybe_wrap_in_fake_stream(plan.response_override, logging_obj, api_surface)
                if plan.terminate:
                    verbose_logger.debug(
                        "Agentic loop terminated by callback=%s reason=%s",
                        callback.__class__.__name__,
                        plan.stop_reason,
                    )
                    return self._maybe_wrap_in_fake_stream(response, logging_obj, api_surface)
                if not plan.run_agentic_loop:
                    continue

                if api_surface == "responses":
                    return await self._execute_responses_agentic_plan(
                        plan=plan,
                        model=model,
                        response_api_optional_request_params=anthropic_messages_optional_request_params,
                        logging_obj=logging_obj,
                        kwargs=kwargs_with_provider,
                        depth=depth,
                        max_loops=max_loops,
                        fingerprints=fingerprints,
                        fingerprint=fingerprint,
                        callback=callback,
                    )

                return self._maybe_wrap_in_fake_stream(
                    await self._execute_anthropic_agentic_plan(
                        plan=plan,
                        model=model,
                        messages=messages,
                        anthropic_messages_optional_request_params=anthropic_messages_optional_request_params,
                        logging_obj=logging_obj,
                        kwargs=kwargs_with_provider,
                        depth=depth,
                        max_loops=max_loops,
                        fingerprints=fingerprints,
                        fingerprint=fingerprint,
                        stream=stream,
                        callback=callback,
                    ),
                    logging_obj,
                    api_surface,
                )
            except Exception as e:
                _call_id = getattr(logging_obj, "litellm_call_id", "unknown")
                verbose_logger.exception(
                    "LiteLLM.AgenticHookError: Exception in agentic completion hooks [call_id=%s model=%s]: %s",
                    _call_id,
                    model,
                    str(e),
                )

        # Check if we need to convert response to fake stream
        # This happens when:
        # 1. Stream was originally True but converted to False for WebSearch interception
        # 2. No agentic loop ran (LLM didn't use the tool)
        # 3. We have a non-streaming response that needs to be converted to streaming
        result: Final = self._maybe_wrap_in_fake_stream(response, logging_obj, api_surface)
        if result is not response:
            return result

        return None

    async def _call_agentic_chat_completion_hooks(
        self,
        response: ModelResponse,
        model: str,
        messages: list[dict],
        optional_params: dict,
        logging_obj: "LiteLLMLoggingObj",
        stream: bool,
        custom_llm_provider: str,
        kwargs: dict,
    ) -> Any | None:
        """
        Call agentic chat completion hooks for all custom loggers (Chat Completions API).

        1. Call async_should_run_chat_completion_agentic_loop to check if agentic loop is needed
        2. If yes, call async_run_chat_completion_agentic_loop to execute the loop

        Returns the response from agentic loop, or None if no hook runs.
        """
        from litellm._logging import verbose_logger
        from litellm.integrations.custom_logger import CustomLogger

        callbacks: Final = litellm.callbacks + (logging_obj.dynamic_success_callbacks or [])
        tools: Final = optional_params.get("tools", [])
        depth, max_loops, fingerprints = self._get_agentic_loop_settings(kwargs=kwargs)

        for callback in callbacks:
            if not isinstance(callback, CustomLogger):
                continue
            if not hasattr(callback, "async_should_run_chat_completion_agentic_loop"):
                continue

            should_run: bool = False
            tool_calls: object = None
            try:
                (
                    should_run,
                    tool_calls,
                ) = await callback.async_should_run_chat_completion_agentic_loop(
                    response=response,
                    model=model,
                    messages=messages,
                    tools=tools,
                    stream=stream,
                    custom_llm_provider=custom_llm_provider,
                    kwargs=kwargs,
                )
            except Exception as e:
                verbose_logger.exception(
                    "LiteLLM.AgenticHookError: Exception in async_should_run_chat_completion_agentic_loop: %s",
                    str(e),
                )
                continue

            if not should_run:
                continue

            # Safety guards must run OUTSIDE the callback try/except — they are
            # bounded-loop / cycle-break rails that must propagate to the caller.
            fingerprint = self._check_agentic_loop_safety(
                tool_calls=tool_calls,
                fingerprints=fingerprints,
                depth=depth,
                max_loops=max_loops,
                model=model,
            )

            try:
                kwargs_with_provider = kwargs.copy() if kwargs else {}
                kwargs_with_provider["custom_llm_provider"] = custom_llm_provider
                build_plan_overridden = (
                    callback.__class__.async_build_chat_completion_agentic_loop_plan
                    is not CustomLogger.async_build_chat_completion_agentic_loop_plan
                )
                if not build_plan_overridden:
                    return await callback.async_run_chat_completion_agentic_loop(
                        tools=tool_calls,
                        model=model,
                        messages=messages,
                        response=response,
                        optional_params=optional_params,
                        logging_obj=logging_obj,
                        stream=stream,
                        kwargs=kwargs_with_provider,
                    )

                plan = await callback.async_build_chat_completion_agentic_loop_plan(
                    tools=tool_calls,
                    model=model,
                    messages=messages,
                    response=response,
                    optional_params=optional_params,
                    logging_obj=logging_obj,
                    stream=stream,
                    kwargs=kwargs_with_provider,
                )

                if plan.response_override is not None:
                    return plan.response_override
                if plan.terminate:
                    verbose_logger.debug(
                        "Agentic chat loop terminated by callback=%s reason=%s",
                        callback.__class__.__name__,
                        plan.stop_reason,
                    )
                    return response
                if not plan.run_agentic_loop:
                    continue

                return await self._execute_chat_completion_agentic_plan(
                    plan=plan,
                    model=model,
                    messages=messages,
                    optional_params=optional_params,
                    kwargs=kwargs_with_provider,
                    custom_llm_provider=custom_llm_provider,
                    depth=depth,
                    max_loops=max_loops,
                    fingerprints=fingerprints,
                    fingerprint=fingerprint,
                )
            except Exception as e:
                verbose_logger.exception("LiteLLM.AgenticHookError: Exception in chat completion agentic hooks: %s", e)

        # Check if we need to convert response to fake stream for chat completions
        # This happens when:
        # 1. Stream was originally True but converted to False for WebSearch interception
        # 2. No agentic loop ran (LLM didn't use the tool)
        # 3. We have a non-streaming response that needs to be converted to streaming
        websearch_converted_stream: Final = (
            logging_obj.model_call_details.get("websearch_interception_converted_stream", False)
            if logging_obj is not None
            else False
        )

        if websearch_converted_stream:
            from litellm._logging import verbose_logger
            from litellm.llms.base_llm.base_model_iterator import (
                convert_model_response_to_streaming,
            )

            verbose_logger.debug(
                "WebSearchInterception: No tool call made, converting non-streaming chat completion to fake stream"
            )

            # Convert the non-streaming ModelResponse to a fake stream
            if hasattr(response, "choices"):
                # Use the existing converter for ModelResponse
                fake_stream: Final = convert_model_response_to_streaming(response)
                return fake_stream

        return None

    def _handle_error(
        self,
        e: Exception,
        provider_config: Union[
            BaseConfig,
            BaseRerankConfig,
            BaseResponsesAPIConfig,
            BaseImageEditConfig,
            BaseImageGenerationConfig,
            BaseVectorStoreConfig,
            BaseVectorStoreFilesConfig,
            BaseGoogleGenAIGenerateContentConfig,
            BaseAnthropicMessagesConfig,
            BaseBatchesConfig,
            BaseOCRConfig,
            BaseVideoConfig,
            BaseSearchConfig,
            BaseTextToSpeechConfig,
            BaseSkillsAPIConfig,
            "BasePassthroughConfig",
            "BaseContainerConfig",
            BaseEvalsAPIConfig,
        ],
    ):
        received_status_code: Final = (
            e.response.status_code if isinstance(e, httpx.HTTPStatusError) else getattr(e, "status_code", None)
        )
        status_code = received_status_code if isinstance(received_status_code, int) else 500
        error_headers = getattr(e, "headers", None)
        if isinstance(e, httpx.HTTPStatusError):
            error_text = e.response.text
        else:
            error_text = getattr(e, "text", str(e))
        error_response: Final = getattr(e, "response", None)
        if error_headers is None and error_response:
            error_headers = getattr(error_response, "headers", None)
        if error_response and hasattr(error_response, "text"):
            error_text = getattr(error_response, "text", error_text)
        if error_headers:
            error_headers = dict(error_headers)
        else:
            error_headers = {}

        if provider_config is None:
            from litellm.llms.base_llm.chat.transformation import BaseLLMException

            raise BaseLLMException(
                status_code=status_code,
                message=error_text,
                headers=error_headers,
                status_code_is_synthesized=not isinstance(received_status_code, int),
            )

        provider_error: Final = provider_config.get_error_class(
            error_message=error_text,
            status_code=status_code,
            headers=error_headers,
        )
        if not isinstance(received_status_code, int):
            provider_error.status_code_is_synthesized = True
        raise provider_error

    @staticmethod
    def _append_query_params(url: str, query_params: RealtimeQueryParams | None) -> str:
        """Append query_params to url, skipping keys already present in the URL."""
        if not query_params:
            return url
        from urllib.parse import parse_qsl, urlencode, urlparse, urlunparse

        parsed: Final = urlparse(url)
        existing: Final = dict(parse_qsl(parsed.query))
        extras: Final = {k: v for k, v in query_params.items() if k not in existing}
        if not extras:
            return url
        new_query: Final = parsed.query + ("&" if parsed.query else "") + urlencode(extras)
        return urlunparse(parsed._replace(query=new_query))

    @staticmethod
    async def _open_realtime_backend_ws(
        websockets_module: ModuleType,
        url: str,
        headers: dict,
        ssl_context: bool | str | ssl.SSLContext,
        *,
        open_timeout: float = 8.0,
        max_attempts: int = 3,
    ) -> "ClientConnection":
        """Open the backend realtime websocket, retrying a hung open handshake.

        The upstream Live handshake (e.g. Gemini Live) intermittently hangs on
        open; waiting longer never recovers a hung attempt, but a fresh attempt
        almost always connects in ~1s. So bound each attempt with ``open_timeout``
        and retry, instead of surfacing one slow handshake to the caller as a
        fatal 1011. A bounded attempt that timed out already spaced out the
        retry, so no extra backoff is needed. Deterministic rejections (auth /
        handshake status) are not retried.
        """
        # Handshake-status rejections are deterministic (auth / 4xx): retrying
        # cannot help and the caller must see the upstream status, not a generic
        # 1011. websockets <15 raises InvalidStatusCode, >=15 raises InvalidStatus.
        deterministic_errors: Final = tuple(
            exc
            for exc in (
                getattr(websockets_module.exceptions, "InvalidStatus", None),
                getattr(websockets_module.exceptions, "InvalidStatusCode", None),
            )
            if exc is not None
        )
        last_exc: BaseException | None = None
        for _ in range(max_attempts):
            try:
                return await websockets_module.connect(
                    url,
                    additional_headers=headers,
                    max_size=REALTIME_WEBSOCKET_MAX_MESSAGE_SIZE_BYTES,
                    ssl=ssl_context,
                    open_timeout=open_timeout,
                )
            except deterministic_errors:
                raise
            except (
                TimeoutError,
                OSError,
                websockets_module.exceptions.WebSocketException,
            ) as e:
                last_exc = e
        assert last_exc is not None  # loop only exits via return or a captured exc
        raise last_exc

    async def async_realtime(
        self,
        model: str,
        websocket: Any,
        logging_obj: LiteLLMLoggingObj,
        provider_config: BaseRealtimeConfig,
        headers: dict,
        api_base: str | None = None,
        api_key: str | None = None,
        client: Any | None = None,
        timeout: float | None = None,
        user_api_key_dict: Any | None = None,
        litellm_metadata: dict[str, object] | None = None,
        query_params: RealtimeQueryParams | None = None,
    ):
        import websockets

        url: Final = provider_config.get_complete_url(api_base, model, api_key)
        headers = provider_config.validate_environment(
            headers=headers,
            model=model,
            api_key=api_key,
        )

        try:
            ssl_context = get_shared_realtime_ssl_context()
            if url.startswith("wss://") and ssl_context is False:
                # Keep TLS for wss:// while honoring SSL_VERIFY=False semantics.
                ssl_context = ssl.SSLContext(ssl.PROTOCOL_TLS_CLIENT)
                ssl_context.check_hostname = False
                ssl_context.verify_mode = ssl.CERT_NONE
            backend_ws: Final = await self._open_realtime_backend_ws(websockets, url, headers, ssl_context)
            async with backend_ws:
                _request_data: Final[dict[str, object]] = {}
                if litellm_metadata:
                    _request_data["litellm_metadata"] = litellm_metadata
                realtime_streaming: Final = RealTimeStreaming(
                    websocket,
                    backend_ws,
                    logging_obj,
                    provider_config,
                    model,
                    user_api_key_dict=user_api_key_dict,
                    request_data=_request_data,
                    force_transcription_model=(
                        model if (query_params or {}).get("intent") == "transcription" else None
                    ),
                )

                # Auto-send session setup if the provider requires it (e.g.
                # Gemini/Vertex AI Live needs a `setup` before any realtime_input).
                # Build the streaming handler first so a transcription guardrail's
                # auto-response disable can be folded into this one setup: Gemini
                # rejects a second setup, so a follow-up disable would be dropped
                # and the guardrail bypassed.
                _session_config: str | None = None
                if provider_config.requires_session_configuration():
                    _session_config = provider_config.session_configuration_request(model)
                    if _session_config:
                        _session_config = realtime_streaming._maybe_inject_guardrail_auto_response_disable(
                            _session_config
                        )
                        await backend_ws.send(_session_config)
                        realtime_streaming.session_configuration_request = _session_config

                # For providers that defer setup until client session.update, optionally
                # send synthetic session.created to unblock clients waiting on connect.
                if not provider_config.requires_session_configuration():
                    synthetic_session: Final = provider_config.transform_session_created_event(
                        model=model,
                        logging_session_id=logging_obj.litellm_trace_id,
                        session_configuration_request=None,
                    )
                    if synthetic_session is not None:
                        synthetic_session_str: Final = json.dumps(synthetic_session)
                        # Record before sending so the synthetic session.created is
                        # captured in the session log alongside provider-driven
                        # events; without this it would be silently absent from
                        # success_handler / async_success_handler payloads.
                        realtime_streaming.store_message(synthetic_session_str)
                        await websocket.send_text(synthetic_session_str)
                        realtime_streaming._session_created_sent_to_client = True
                        verbose_logger.debug("Sent synthetic session.created to client to unblock connection")

                await realtime_streaming.bidirectional_forward()

        except websockets.exceptions.InvalidStatusCode as e:
            verbose_logger.exception("Error connecting to backend: %s", e)
            await websocket.close(code=e.status_code, reason=_redact_string(str(e)))
        except Exception as e:
            verbose_logger.exception("Error connecting to backend: %s", e)
            redacted_error: Final = _redact_string(str(e))
            try:
                await websocket.send_text(realtime_error_event(redacted_error, error_type="server_error"))
            except Exception:  # noqa: BLE001  # best-effort notice: a dead client socket must not skip the close below
                verbose_logger.debug("Could not send realtime error event to client; closing anyway")
            try:
                await websocket.close(
                    code=1011,
                    reason=websocket_close_reason(
                        _redact_string(f"Internal server error: {e}"),
                        fallback="Internal server error",
                    ),
                )
            except RuntimeError as close_error:
                if "already completed" in str(close_error) or "websocket.close" in str(close_error):
                    # The WebSocket is already closed or the response is completed, so we can ignore this error
                    pass
                else:
                    # If it's a different RuntimeError, we might want to log it or handle it differently
                    raise Exception(f"Unexpected error while closing WebSocket: {close_error}")

    async def async_realtime_client_secret_handler(
        self,
        api_base: str,
        api_key: str,
        request_data: dict[str, object],
        logging_obj: LiteLLMLoggingObj,
        timeout: float | httpx.Timeout,
        provider_config: BaseRealtimeHTTPConfig | None = None,
        model: str | None = None,
        extra_headers: dict[str, object] | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        api_version: str | None = None,
    ) -> httpx.Response:
        """
        Forward POST /v1/realtime/client_secrets to upstream provider.

        Uses provider_config (BaseRealtimeHTTPConfig) for URL construction and
        header auth when available; falls back to the legacy OpenAI-style defaults.
        """
        return await self._async_realtime_session_post(
            endpoint="client_secrets",
            api_base=api_base,
            api_key=api_key,
            request_data=request_data,
            logging_obj=logging_obj,
            timeout=timeout,
            provider_config=provider_config,
            model=model,
            extra_headers=extra_headers,
            client=client,
            api_version=api_version,
        )

    async def async_realtime_transcription_session_handler(
        self,
        api_base: str,
        api_key: str,
        request_data: dict[str, object],
        logging_obj: LiteLLMLoggingObj,
        timeout: float | httpx.Timeout,
        provider_config: BaseRealtimeHTTPConfig | None = None,
        model: str | None = None,
        extra_headers: dict[str, object] | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        api_version: str | None = None,
    ) -> httpx.Response:
        """Forward POST /v1/realtime/transcription_sessions to upstream provider."""
        return await self._async_realtime_session_post(
            endpoint="transcription_sessions",
            api_base=api_base,
            api_key=api_key,
            request_data=request_data,
            logging_obj=logging_obj,
            timeout=timeout,
            provider_config=provider_config,
            model=model,
            extra_headers=extra_headers,
            client=client,
            api_version=api_version,
        )

    async def _async_realtime_session_post(
        self,
        endpoint: Literal["client_secrets", "transcription_sessions"],
        api_base: str,
        api_key: str,
        request_data: dict[str, object],
        logging_obj: LiteLLMLoggingObj,
        timeout: float | httpx.Timeout,
        provider_config: Any | None = None,
        model: str | None = None,
        extra_headers: dict[str, object] | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        api_version: str | None = None,
    ) -> httpx.Response:
        """
        Shared POST flow for the realtime HTTP session endpoints
        (client_secrets and transcription_sessions).

        Uses provider_config (BaseRealtimeHTTPConfig) for URL construction and
        header auth when available; falls back to the legacy OpenAI-style defaults.
        """
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders.OPENAI,
            )
        else:
            async_httpx_client = client

        if provider_config is not None:
            if endpoint == "transcription_sessions":
                url = provider_config.get_transcription_session_url(
                    api_base=api_base, model=model or "", api_version=api_version
                )
            else:
                url = provider_config.get_complete_url(api_base=api_base, model=model or "", api_version=api_version)
            headers: dict[str, object] = provider_config.validate_environment(
                headers={}, model=model or "", api_key=api_key
            )
        else:
            url = f"{api_base.rstrip('/')}/v1/realtime/{endpoint}"
            headers = {
                "Authorization": f"Bearer {api_key}",
                "Content-Type": "application/json",
            }

        if extra_headers:
            headers.update(extra_headers)

        logging_obj.pre_call(
            input=request_data,
            api_key="",
            additional_args={
                "complete_input_dict": request_data,
                "api_base": url,
                "headers": headers,
            },
        )

        try:
            return await async_httpx_client.post(
                url=url,
                headers=headers,
                json=request_data,
                timeout=timeout,
            )
        except Exception as e:
            if provider_config is not None:
                raise self._handle_error(
                    e=e,
                    provider_config=provider_config,
                )
            raise

    async def async_realtime_calls_handler(
        self,
        api_base: str,
        openai_ephemeral_key: str,
        sdp_body: bytes,
        logging_obj: LiteLLMLoggingObj,
        timeout: float | httpx.Timeout,
        provider_config: Any | None = None,
        model: str | None = None,
        session_config: dict[str, object] | None = None,
        extra_headers: dict[str, object] | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        api_version: str | None = None,
    ) -> httpx.Response:
        """
        Forward POST /v1/realtime/calls (SDP exchange) to upstream provider.

        Uses provider_config (BaseRealtimeHTTPConfig) for URL construction and
        header auth when available; falls back to the legacy OpenAI-style defaults.

        OpenAI's GA realtime API expects multipart/form-data with:
          - sdp: the SDP offer (text)
          - session: JSON string with {"type": "realtime", "model": "...", ...}
        """
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders.OPENAI,
            )
        else:
            async_httpx_client = client

        if provider_config is not None:
            url = provider_config.get_realtime_calls_url(api_base=api_base, model=model or "", api_version=api_version)
            headers: dict[str, object] = provider_config.get_realtime_calls_headers(ephemeral_key=openai_ephemeral_key)
        else:
            url = f"{api_base.rstrip('/')}/v1/realtime/calls"
            headers = {
                "Authorization": f"Bearer {openai_ephemeral_key}",
            }

        if extra_headers:
            headers.update(extra_headers)

        # Build multipart form data: sdp + session JSON
        session_data: Final = session_config or {}
        if "type" not in session_data:
            session_data["type"] = "realtime"
        if "model" not in session_data and model:
            session_data["model"] = model

        sdp_text: Final = sdp_body.decode("utf-8") if isinstance(sdp_body, bytes) else sdp_body

        files: Final = {
            "sdp": (None, sdp_text, "text/plain"),
            "session": (None, json.dumps(session_data), "application/json"),
        }

        logging_obj.pre_call(
            input="realtime_sdp_offer",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
                "session": session_data,
            },
        )

        try:
            return await async_httpx_client.post(
                url=url,
                headers=headers,
                files=files,
                timeout=timeout,
            )
        except Exception as e:
            if provider_config is not None:
                raise self._handle_error(
                    e=e,
                    provider_config=provider_config,
                )
            raise

    async def async_responses_websocket(
        self,
        model: str,
        websocket: Any,
        logging_obj: LiteLLMLoggingObj,
        responses_api_provider_config: BaseResponsesAPIConfig | None,
        api_base: str | None = None,
        api_key: str | None = None,
        timeout: float | None = None,
        user_api_key_dict: Any | None = None,
        litellm_metadata: dict[str, object] | None = None,
        custom_llm_provider: str | None = None,
        first_message: str | None = None,
        **kwargs: Any,
    ):
        """
        Handles Responses API WebSocket mode.

        For providers with native websocket support (OpenAI, Azure):
        - Opens a persistent WebSocket to the provider's /v1/responses endpoint
        - Proxies response.create events bidirectionally for lower-latency agentic workflows

        For providers without native websocket support (all others):
        - Uses ManagedResponsesWebSocketHandler which makes HTTP streaming calls
        - Forwards events over the websocket connection
        """
        _ws_quota_callbacks: Final = _collect_ws_project_quota_callbacks()

        if responses_api_provider_config is None or not responses_api_provider_config.supports_native_websocket():
            from litellm.responses.streaming_iterator import (
                ManagedResponsesWebSocketHandler,
            )

            handler: Final = ManagedResponsesWebSocketHandler(
                websocket=websocket,
                model=model,
                logging_obj=logging_obj,
                user_api_key_dict=user_api_key_dict,
                litellm_metadata=litellm_metadata,
                api_key=api_key,
                api_base=api_base,
                timeout=timeout,
                custom_llm_provider=custom_llm_provider,
                first_message=first_message,
                quota_callbacks=_ws_quota_callbacks,
                **kwargs,
            )
            await handler.run()
            return

        import websockets
        from websockets.asyncio.client import ClientConnection

        litellm_params: Final = GenericLiteLLMParams.model_validate(
            {
                "api_base": api_base,
                "api_key": api_key,
                **kwargs,
            }
        )
        headers: Final = responses_api_provider_config.validate_environment(
            headers={},
            model=model,
            litellm_params=litellm_params,
        )
        if api_key:
            headers["Authorization"] = f"Bearer {api_key}"

        ws_url = responses_api_provider_config.get_websocket_url(
            api_base=api_base,
            litellm_params=dict(litellm_params),
        )
        # Some providers (e.g. OpenAI) require ?model= in the WebSocket URL.
        # Providers that send the model in the request body (e.g. Azure) set
        # model_in_websocket_url() to False to suppress this append.
        if responses_api_provider_config.model_in_websocket_url():
            _parsed: Final = urlparse(ws_url)
            _qs: Final = parse_qs(_parsed.query)
            if "model" not in _qs:
                _qs["model"] = [model]
                ws_url = urlunparse(_parsed._replace(query=urlencode({k: v[0] for k, v in _qs.items()})))

        try:
            ssl_context = get_shared_realtime_ssl_context()
            if ws_url.startswith("wss://") and ssl_context is False:
                ssl_context = ssl.SSLContext(ssl.PROTOCOL_TLS_CLIENT)
                ssl_context.check_hostname = False
                ssl_context.verify_mode = ssl.CERT_NONE

            logging_obj.pre_call(
                input=None,
                api_key=api_key or "",
                additional_args={
                    "api_base": ws_url,
                    "headers": headers,
                    "complete_input_dict": {"mode": "responses_websocket"},
                },
            )

            @asynccontextmanager
            async def _backend_connection():
                if _rust_responses_websocket_enabled(custom_llm_provider, litellm_params):
                    from litellm.rust_bridge import responses_websocket as rust_responses_websocket

                    rust_backend: Final = await rust_responses_websocket.connect(
                        url=ws_url,
                        headers={str(key): str(value) for key, value in headers.items()},
                        timeout=timeout,
                    )
                    if rust_backend is not None:
                        yield rust_backend
                        return

                async with websockets.connect(
                    ws_url,
                    additional_headers=headers,
                    max_size=REALTIME_WEBSOCKET_MAX_MESSAGE_SIZE_BYTES,
                    ssl=ssl_context,
                ) as backend:
                    yield backend

            async with _backend_connection() as backend_ws:
                _request_data: Final[dict[str, object]] = {}
                if litellm_metadata:
                    _request_data["litellm_metadata"] = litellm_metadata

                _ws_guardrail_callbacks: list = []
                _ws_output_guardrail_callbacks: list = []
                try:
                    import litellm as _litellm

                    # Use duck-typing so any guardrail that exposes the PII
                    # masking interface works, not just _OPTIONAL_PresidioPIIMasking.
                    # This avoids a layering violation (SDK importing from proxy).
                    _ws_guardrail_callbacks = [
                        cb
                        for cb in _litellm.callbacks
                        if callable(getattr(cb, "check_pii", None))
                        and callable(getattr(cb, "get_presidio_settings_from_request_data", None))
                        and callable(getattr(cb, "_unmask_pii_text", None))
                        and getattr(cb, "output_parse_pii", False)
                    ]
                    _ws_output_guardrail_callbacks = [
                        cb
                        for cb in _litellm.callbacks
                        if callable(getattr(cb, "check_pii", None))
                        and callable(getattr(cb, "get_presidio_settings_from_request_data", None))
                        and getattr(cb, "apply_to_output", False)
                    ]
                except Exception as _guardrail_exc:
                    verbose_logger.warning(
                        "Responses WebSocket: failed to collect guardrail "
                        "callbacks — PII masking will be skipped. Error: %s",
                        _guardrail_exc,
                    )

                streaming: Final = ResponsesWebSocketStreaming(
                    websocket=websocket,
                    backend_ws=cast(ClientConnection, backend_ws),
                    logging_obj=logging_obj,
                    user_api_key_dict=user_api_key_dict,
                    request_data=_request_data,
                    first_message=first_message,
                    guardrail_callbacks=_ws_guardrail_callbacks,
                    output_guardrail_callbacks=_ws_output_guardrail_callbacks,
                    quota_callbacks=_ws_quota_callbacks,
                    authorized_model=model,
                )
                await streaming.bidirectional_forward()

        except websockets.exceptions.InvalidStatusCode as e:
            verbose_logger.exception("Error connecting to responses WS backend: %s", e)
            await websocket.close(code=e.status_code, reason=_redact_string(str(e)))
        except Exception as e:
            verbose_logger.exception("Error in responses WS: %s", e)
            try:
                await websocket.close(code=1011, reason=_redact_string(f"Internal server error: {e}"))
            except RuntimeError as close_error:
                if "already completed" in str(close_error) or "websocket.close" in str(close_error):
                    pass
                else:
                    raise Exception(f"Unexpected error while closing WebSocket: {close_error}")

    def image_edit_handler(
        self,
        model: str,
        image: Any,
        prompt: str | None,
        image_edit_provider_config: BaseImageEditConfig,
        image_edit_optional_request_params: dict,
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        timeout: float | httpx.Timeout,
        extra_headers: dict[str, object] | None = None,
        extra_body: dict[str, object] | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
        fake_stream: bool = False,
        litellm_metadata: dict[str, object] | None = None,
    ) -> ImageResponse | Coroutine[object, object, ImageResponse]:
        """

        Handles image edit requests.
        When _is_async=True, returns a coroutine instead of making the call directly.
        """
        if _is_async:
            # Return the async coroutine if called with _is_async=True
            return self.async_image_edit_handler(
                model=model,
                image=image,
                prompt=prompt,
                image_edit_provider_config=image_edit_provider_config,
                image_edit_optional_request_params=image_edit_optional_request_params,
                custom_llm_provider=custom_llm_provider,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                extra_body=extra_body,
                timeout=timeout,
                client=client if isinstance(client, AsyncHTTPHandler) else None,
                fake_stream=fake_stream,
                litellm_metadata=litellm_metadata,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = image_edit_provider_config.validate_environment(
            api_key=litellm_params.api_key,
            headers=image_edit_optional_request_params.get("extra_headers", {}) or {},
            model=model,
            litellm_params=dict(litellm_params),
            api_base=litellm_params.api_base,
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = image_edit_provider_config.get_complete_url(
            model=model,
            api_base=litellm_params.api_base,
            litellm_params=dict(litellm_params),
        )

        data, files = image_edit_provider_config.transform_image_edit_request(
            model=model,
            image=image,
            prompt=prompt,
            image_edit_optional_request_params=image_edit_optional_request_params,
            litellm_params=litellm_params,
            headers=headers,
        )
        data = image_edit_provider_config.finalize_image_edit_request_data(data, api_base)

        ## LOGGING
        logging_obj.pre_call(
            input=prompt,
            api_key="",
            additional_args={
                "complete_input_dict": files,
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            # Check if provider uses multipart/form-data or JSON
            if image_edit_provider_config.use_multipart_form_data():
                # Use form-data (OpenAI style)
                response = sync_httpx_client.post(
                    url=api_base,
                    headers=headers,
                    data=data,
                    files=files,
                    timeout=timeout,
                )
            else:
                # Use JSON (Gemini style)
                response = sync_httpx_client.post(
                    url=api_base,
                    headers=headers,
                    json=data,
                    timeout=timeout,
                )

        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=image_edit_provider_config,
            )

        return image_edit_provider_config.transform_image_edit_response(
            model=model,
            raw_response=response,
            logging_obj=logging_obj,
        )

    async def async_image_edit_handler(
        self,
        model: str,
        image: FileTypes,
        prompt: str | None,
        image_edit_provider_config: BaseImageEditConfig,
        image_edit_optional_request_params: dict,
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        timeout: float | httpx.Timeout,
        extra_headers: dict[str, object] | None = None,
        extra_body: dict[str, object] | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        fake_stream: bool = False,
        litellm_metadata: dict[str, object] | None = None,
    ) -> ImageResponse:
        """
        Async version of the image edit handler.
        Uses async HTTP client to make requests.
        """
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = image_edit_provider_config.validate_environment(
            api_key=litellm_params.api_key,
            headers=image_edit_optional_request_params.get("extra_headers", {}) or {},
            model=model,
            litellm_params=dict(litellm_params),
            api_base=litellm_params.api_base,
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = image_edit_provider_config.get_complete_url(
            model=model,
            api_base=litellm_params.api_base,
            litellm_params=dict(litellm_params),
        )

        data, files = image_edit_provider_config.transform_image_edit_request(
            model=model,
            image=image,
            prompt=prompt,
            image_edit_optional_request_params=image_edit_optional_request_params,
            litellm_params=litellm_params,
            headers=headers,
        )
        data = image_edit_provider_config.finalize_image_edit_request_data(data, api_base)

        ## LOGGING
        logging_obj.pre_call(
            input=prompt,
            api_key="",
            additional_args={
                "complete_input_dict": data,
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            # Check if provider uses multipart/form-data or JSON
            if image_edit_provider_config.use_multipart_form_data():
                # Use form-data (OpenAI style)
                response = await async_httpx_client.post(
                    url=api_base,
                    headers=headers,
                    data=data,
                    files=files,
                    timeout=timeout,
                )
            else:
                # Use JSON (Gemini style)
                response = await async_httpx_client.post(
                    url=api_base,
                    headers=headers,
                    json=data,
                    timeout=timeout,
                )

        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=image_edit_provider_config,
            )

        return image_edit_provider_config.transform_image_edit_response(
            model=model,
            raw_response=response,
            logging_obj=logging_obj,
        )

    def image_generation_handler(
        self,
        model: str,
        prompt: str,
        image_generation_provider_config: BaseImageGenerationConfig,
        image_generation_optional_request_params: dict,
        custom_llm_provider: str,
        litellm_params: dict,
        logging_obj: LiteLLMLoggingObj,
        timeout: float | httpx.Timeout,
        extra_headers: dict[str, object] | None = None,
        extra_body: dict[str, object] | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
        fake_stream: bool = False,
        litellm_metadata: dict[str, object] | None = None,
        api_key: str | None = None,
    ) -> ImageResponse | Coroutine[object, object, ImageResponse]:
        """
        Handles image generation requests.
        When _is_async=True, returns a coroutine instead of making the call directly.
        """
        if _is_async:
            # Return the async coroutine if called with _is_async=True
            return self.async_image_generation_handler(
                model=model,
                prompt=prompt,
                image_generation_provider_config=image_generation_provider_config,
                image_generation_optional_request_params=image_generation_optional_request_params,
                custom_llm_provider=custom_llm_provider,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                extra_body=extra_body,
                timeout=timeout,
                client=client if isinstance(client, AsyncHTTPHandler) else None,
                fake_stream=fake_stream,
                litellm_metadata=litellm_metadata,
                api_key=api_key,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = image_generation_provider_config.validate_environment(
            api_key=api_key,
            headers=image_generation_optional_request_params.get("extra_headers", {}) or {},
            model=model,
            messages=[],
            optional_params=image_generation_optional_request_params,
            litellm_params=dict(litellm_params),
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = image_generation_provider_config.get_complete_url(
            model=model,
            api_base=litellm_params.get("api_base", None),
            api_key=litellm_params.get("api_key", None),
            optional_params=image_generation_optional_request_params,
            litellm_params=dict(litellm_params),
        )

        data: Final = image_generation_provider_config.transform_image_generation_request(
            model=model,
            prompt=prompt,
            optional_params=image_generation_optional_request_params,
            litellm_params=dict(litellm_params),
            headers=headers,
        )

        ## LOGGING
        logging_obj.pre_call(
            input=prompt,
            api_key="",
            additional_args={
                "complete_input_dict": data,
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            # Check if provider requires multipart/form-data (e.g., Stability AI)
            if image_generation_provider_config.use_multipart_form_data():
                # Use form-data: pass files={} to force multipart encoding
                response = sync_httpx_client.post(
                    url=api_base,
                    headers=headers,
                    data=data,
                    files={"none": ""},  # Forces multipart/form-data
                    timeout=timeout,
                )
            else:
                # Use JSON (default)
                response = sync_httpx_client.post(
                    url=api_base,
                    headers=headers,
                    json=data,
                    timeout=timeout,
                )

        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=image_generation_provider_config,
            )

        model_response: Final[ImageResponse] = image_generation_provider_config.transform_image_generation_response(
            model=model,
            raw_response=response,
            model_response=litellm.ImageResponse(),
            logging_obj=logging_obj,
            request_data=data,
            optional_params=image_generation_optional_request_params,
            litellm_params=dict(litellm_params),
            encoding=None,
        )

        return model_response

    async def async_image_generation_handler(
        self,
        model: str,
        prompt: str,
        image_generation_provider_config: BaseImageGenerationConfig,
        image_generation_optional_request_params: dict,
        custom_llm_provider: str,
        litellm_params: dict,
        logging_obj: LiteLLMLoggingObj,
        timeout: float | httpx.Timeout,
        extra_headers: dict[str, object] | None = None,
        extra_body: dict[str, object] | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        fake_stream: bool = False,
        litellm_metadata: dict[str, object] | None = None,
        api_key: str | None = None,
    ) -> ImageResponse:
        """
        Async version of the image generation handler.
        Uses async HTTP client to make requests.
        """
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = image_generation_provider_config.validate_environment(
            api_key=api_key,
            headers=image_generation_optional_request_params.get("extra_headers", {}) or {},
            model=model,
            messages=[],
            optional_params=image_generation_optional_request_params,
            litellm_params=dict(litellm_params),
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = image_generation_provider_config.get_complete_url(
            model=model,
            api_base=litellm_params.get("api_base", None),
            api_key=litellm_params.get("api_key", None),
            optional_params=image_generation_optional_request_params,
            litellm_params=dict(litellm_params),
        )

        data: Final = image_generation_provider_config.transform_image_generation_request(
            model=model,
            prompt=prompt,
            optional_params=image_generation_optional_request_params,
            litellm_params=dict(litellm_params),
            headers=headers,
        )

        ## LOGGING
        logging_obj.pre_call(
            input=prompt,
            api_key="",
            additional_args={
                "complete_input_dict": data,
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            # Check if provider requires multipart/form-data (e.g., Stability AI)
            if image_generation_provider_config.use_multipart_form_data():
                # Use form-data: pass files={} to force multipart encoding
                response = await async_httpx_client.post(
                    url=api_base,
                    headers=headers,
                    data=data,
                    files={"none": ""},  # Forces multipart/form-data
                    timeout=timeout,
                )
            else:
                # Use JSON (default)
                response = await async_httpx_client.post(
                    url=api_base,
                    headers=headers,
                    json=data,
                    timeout=timeout,
                )

        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=image_generation_provider_config,
            )

        model_response: Final[ImageResponse] = image_generation_provider_config.transform_image_generation_response(
            model=model,
            raw_response=response,
            model_response=litellm.ImageResponse(),
            logging_obj=logging_obj,
            request_data=data,
            optional_params=image_generation_optional_request_params,
            litellm_params=dict(litellm_params),
            encoding=None,
        )

        return model_response

    ###### VIDEO GENERATION HANDLER ######
    def video_generation_handler(
        self,
        model: str,
        prompt: str,
        video_generation_provider_config: BaseVideoConfig,
        video_generation_optional_request_params: dict,
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        timeout: float | httpx.Timeout,
        extra_headers: dict[str, object] | None = None,
        extra_body: dict[str, object] | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
        fake_stream: bool = False,
        litellm_metadata: dict[str, object] | None = None,
        api_key: str | None = None,
    ) -> VideoObject | Coroutine[object, object, VideoObject]:
        """
        Handles video generation requests.
        When _is_async=True, returns a coroutine instead of making the call directly.
        """
        if _is_async:
            # Return the async coroutine if called with _is_async=True
            return self.async_video_generation_handler(
                model=model,
                prompt=prompt,
                video_generation_provider_config=video_generation_provider_config,
                video_generation_optional_request_params=video_generation_optional_request_params,
                custom_llm_provider=custom_llm_provider,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                extra_body=extra_body,
                timeout=timeout,
                client=client if isinstance(client, AsyncHTTPHandler) else None,
                fake_stream=fake_stream,
                litellm_metadata=litellm_metadata,
                api_key=api_key,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = video_generation_provider_config.validate_environment(
            api_key=api_key or litellm_params.get("api_key", None),
            headers=video_generation_optional_request_params.get("extra_headers", {}) or {},
            model=model,
            litellm_params=litellm_params,
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base = video_generation_provider_config.get_complete_url(
            model=model,
            api_base=litellm_params.get("api_base", None),
            litellm_params=dict(litellm_params),
        )

        (
            data,
            files,
            api_base,
        ) = video_generation_provider_config.transform_video_create_request(
            model=model,
            prompt=prompt,
            video_create_optional_request_params=video_generation_optional_request_params,
            litellm_params=litellm_params,
            headers=headers,
            api_base=api_base,
        )

        ## LOGGING
        logging_obj.pre_call(
            input=prompt,
            api_key="",
            additional_args={
                "complete_input_dict": data,
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            if files and len(files) > 0:
                response = sync_httpx_client.post(
                    url=api_base,
                    headers=headers,
                    data=data,
                    files=files,
                    timeout=timeout,
                )
            elif video_generation_provider_config.use_multipart_form_data():
                response = sync_httpx_client.post(  # rebind-ok: one of three mutually-exclusive branches
                    url=api_base,
                    headers=headers,
                    files=serialize_multipart_form_fields(data),
                    timeout=timeout,
                )
            else:
                response = sync_httpx_client.post(
                    url=api_base,
                    headers=headers,
                    json=data,
                    timeout=timeout,
                )

        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=video_generation_provider_config,
            )

        return video_generation_provider_config.transform_video_create_response(
            model=model,
            raw_response=response,
            logging_obj=logging_obj,
            custom_llm_provider=custom_llm_provider,
            request_data=data,
        )

    async def async_video_generation_handler(
        self,
        model: str,
        prompt: str,
        video_generation_provider_config: "BaseVideoConfig",
        video_generation_optional_request_params: dict,
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        timeout: float | httpx.Timeout,
        extra_headers: dict[str, object] | None = None,
        extra_body: dict[str, object] | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        fake_stream: bool = False,
        litellm_metadata: dict[str, object] | None = None,
        api_key: str | None = None,
    ) -> VideoObject:
        """
        Async version of the video generation handler.
        Uses async HTTP client to make requests.
        """
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = video_generation_provider_config.validate_environment(
            api_key=api_key or litellm_params.get("api_key", None),
            headers=video_generation_optional_request_params.get("extra_headers", {}) or {},
            model=model,
            litellm_params=litellm_params,
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base = video_generation_provider_config.get_complete_url(
            model=model,
            api_base=litellm_params.get("api_base", None),
            litellm_params=dict(litellm_params),
        )

        (
            data,
            files,
            api_base,
        ) = video_generation_provider_config.transform_video_create_request(
            model=model,
            prompt=prompt,
            api_base=api_base,
            video_create_optional_request_params=video_generation_optional_request_params,
            litellm_params=litellm_params,
            headers=headers,
        )

        ## LOGGING
        logging_obj.pre_call(
            input=prompt,
            api_key="",
            additional_args={
                "complete_input_dict": data,
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            if files and len(files) > 0:
                response = await async_httpx_client.post(
                    url=api_base,
                    headers=headers,
                    data=data,
                    files=files,
                    timeout=timeout,
                )
            elif video_generation_provider_config.use_multipart_form_data():
                response = await async_httpx_client.post(  # rebind-ok: one of three mutually-exclusive branches
                    url=api_base,
                    headers=headers,
                    files=serialize_multipart_form_fields(data),
                    timeout=timeout,
                )
            else:
                response = await async_httpx_client.post(
                    url=api_base,
                    headers=headers,
                    json=data,
                    timeout=timeout,
                )

        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=video_generation_provider_config,
            )

        return video_generation_provider_config.transform_video_create_response(
            model=model,
            raw_response=response,
            logging_obj=logging_obj,
            custom_llm_provider=custom_llm_provider,
            request_data=data,
        )

    ###### VIDEO CONTENT HANDLER ######
    def video_content_handler(
        self,
        video_id: str,
        video_content_provider_config: BaseVideoConfig,
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        timeout: float | httpx.Timeout,
        extra_headers: dict[str, object] | None = None,
        api_key: str | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
        variant: str | None = None,
    ) -> bytes | Coroutine[object, object, bytes]:
        """
        Handle video content download requests.
        """
        if _is_async:
            return self.async_video_content_handler(
                video_id=video_id,
                video_content_provider_config=video_content_provider_config,
                custom_llm_provider=custom_llm_provider,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                timeout=timeout,
                extra_headers=extra_headers,
                api_key=api_key,
                client=client,
                variant=variant,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = video_content_provider_config.validate_environment(
            headers=extra_headers or {},
            model="",
            api_key=api_key,
            litellm_params=litellm_params,
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = video_content_provider_config.get_complete_url(
            model="",
            api_base=litellm_params.get("api_base", None),
            litellm_params=dict(litellm_params),
        )

        # Transform the request using the provider config
        url, data = video_content_provider_config.transform_video_content_request(
            video_id=video_id,
            api_base=api_base,
            litellm_params=litellm_params,
            headers=headers,
            variant=variant,
        )

        try:
            # Use POST if params contains data (e.g., Vertex AI fetchPredictOperation)
            # Otherwise use GET (e.g., OpenAI video content download)
            if data:
                response = sync_httpx_client.post(
                    url=url,
                    headers=headers,
                    json=data,
                )
            else:
                # Otherwise it's a GET request with query params
                response = sync_httpx_client.get(
                    url=url,
                    headers=headers,
                    params=data,
                )

            # Transform the response using the provider config
            return video_content_provider_config.transform_video_content_response(
                raw_response=response,
                logging_obj=logging_obj,
            )

        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=video_content_provider_config,
            )

    async def async_video_content_handler(
        self,
        video_id: str,
        video_content_provider_config: BaseVideoConfig,
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        timeout: float | httpx.Timeout,
        extra_headers: dict[str, object] | None = None,
        api_key: str | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        variant: str | None = None,
    ) -> bytes:
        """
        Async version of the video content download handler.
        """
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = video_content_provider_config.validate_environment(
            headers=extra_headers or {},
            model="",
            api_key=api_key,
            litellm_params=litellm_params,
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = video_content_provider_config.get_complete_url(
            model="",
            api_base=litellm_params.get("api_base", None),
            litellm_params=dict(litellm_params),
        )

        # Transform the request using the provider config
        url, data = video_content_provider_config.transform_video_content_request(
            video_id=video_id,
            api_base=api_base,
            litellm_params=litellm_params,
            headers=headers,
            variant=variant,
        )

        try:
            # Use POST if params contains data (e.g., Vertex AI fetchPredictOperation)
            # Otherwise use GET (e.g., OpenAI video content download)
            if data:
                response = await async_httpx_client.post(
                    url=url,
                    headers=headers,
                    json=data,
                )
            else:
                # Otherwise it's a GET request with query params
                response = await async_httpx_client.get(
                    url=url,
                    headers=headers,
                    params=data,
                )

            # Transform the response using the provider config
            return await video_content_provider_config.async_transform_video_content_response(
                raw_response=response,
                logging_obj=logging_obj,
            )

        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=video_content_provider_config,
            )

    def video_remix_handler(
        self,
        video_id: str,
        prompt: str,
        video_remix_provider_config: BaseVideoConfig,
        custom_llm_provider: str,
        litellm_params,
        logging_obj,
        extra_headers: dict[str, object] | None = None,
        extra_body: dict[str, object] | None = None,
        timeout: float | None = None,
        _is_async: bool = False,
        client=None,
        api_key: str | None = None,
    ):
        """
        Handler for video remix requests.
        When _is_async=True, returns a coroutine instead of making the call directly.
        """
        if _is_async:
            # Return the async coroutine if called with _is_async=True
            return self.async_video_remix_handler(
                video_id=video_id,
                prompt=prompt,
                video_remix_provider_config=video_remix_provider_config,
                custom_llm_provider=custom_llm_provider,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                extra_body=extra_body,
                timeout=timeout,
                client=client,
                api_key=api_key,
            )

        # For sync calls, use sync HTTP client directly (like video_generation does)
        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = video_remix_provider_config.validate_environment(
            api_key=api_key or litellm_params.get("api_key", None),
            headers=extra_headers or {},
            model="",
            litellm_params=litellm_params,
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = video_remix_provider_config.get_complete_url(
            model="",
            api_base=litellm_params.get("api_base", None),
            litellm_params=dict(litellm_params),
        )

        # Transform the request using the provider config
        url, data = video_remix_provider_config.transform_video_remix_request(
            video_id=video_id,
            prompt=prompt,
            api_base=api_base,
            litellm_params=litellm_params,
            headers=headers,
            extra_body=extra_body,
        )

        ## LOGGING
        logging_obj.pre_call(
            input=prompt,
            api_key="",
            additional_args={
                "complete_input_dict": data,
                "api_base": url,
                "headers": headers,
                "video_id": video_id,
            },
        )

        try:
            response: Final = sync_httpx_client.post(
                url=url,
                headers=headers,
                json=data,
                timeout=timeout,
            )

            return video_remix_provider_config.transform_video_remix_response(
                raw_response=response,
                logging_obj=logging_obj,
                custom_llm_provider=custom_llm_provider,
            )

        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=video_remix_provider_config,
            )

    async def async_video_remix_handler(
        self,
        video_id: str,
        prompt: str,
        video_remix_provider_config: BaseVideoConfig,
        custom_llm_provider: str,
        litellm_params,
        logging_obj,
        extra_headers: dict[str, object] | None = None,
        extra_body: dict[str, object] | None = None,
        timeout: float | None = None,
        client=None,
        api_key: str | None = None,
    ):
        """
        Async version of the video remix handler.
        """
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = video_remix_provider_config.validate_environment(
            api_key=api_key or litellm_params.get("api_key", None),
            headers=extra_headers or {},
            model="",
            litellm_params=litellm_params,
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = video_remix_provider_config.get_complete_url(
            model="",
            api_base=litellm_params.get("api_base", None),
            litellm_params=dict(litellm_params),
        )

        # Transform the request using the provider config
        url, data = video_remix_provider_config.transform_video_remix_request(
            video_id=video_id,
            prompt=prompt,
            api_base=api_base,
            litellm_params=litellm_params,
            headers=headers,
            extra_body=extra_body,
        )

        ## LOGGING
        logging_obj.pre_call(
            input=prompt,
            api_key="",
            additional_args={
                "complete_input_dict": data,
                "api_base": url,
                "headers": headers,
                "video_id": video_id,
            },
        )

        try:
            response: Final = await async_httpx_client.post(
                url=url,
                headers=headers,
                json=data,
                timeout=timeout,
            )

            return video_remix_provider_config.transform_video_remix_response(
                raw_response=response,
                logging_obj=logging_obj,
                custom_llm_provider=custom_llm_provider,
            )

        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=video_remix_provider_config,
            )

    def video_create_character_handler(
        self,
        name: str,
        video: Any,
        video_provider_config: BaseVideoConfig,
        custom_llm_provider: str,
        litellm_params,
        logging_obj,
        extra_headers: dict[str, object] | None = None,
        timeout: float | None = None,
        _is_async: bool = False,
        client=None,
        api_key: str | None = None,
    ):
        if _is_async:
            return self.async_video_create_character_handler(
                name=name,
                video=video,
                video_provider_config=video_provider_config,
                custom_llm_provider=custom_llm_provider,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                timeout=timeout,
                client=client,
                api_key=api_key,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = video_provider_config.validate_environment(
            api_key=api_key or litellm_params.get("api_key", None),
            headers=extra_headers or {},
            model="",
            litellm_params=litellm_params,
        )
        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = video_provider_config.get_complete_url(
            model="",
            api_base=litellm_params.get("api_base", None),
            litellm_params=dict(litellm_params),
        )

        (
            url,
            files_list,
        ) = video_provider_config.transform_video_create_character_request(
            name=name,
            video=video,
            api_base=api_base,
            litellm_params=litellm_params,
            headers=headers,
        )

        logging_obj.pre_call(
            input=name,
            api_key="",
            additional_args={
                "complete_input_dict": {"name": name},
                "api_base": url,
                "headers": headers,
            },
        )

        try:
            response: Final = sync_httpx_client.post(
                url=url,
                headers=headers,
                files=files_list,
                timeout=timeout,
            )
            response.raise_for_status()
            return video_provider_config.transform_video_create_character_response(
                raw_response=response,
                logging_obj=logging_obj,
            )
        except Exception as e:
            raise self._handle_error(e=e, provider_config=video_provider_config)

    async def async_video_create_character_handler(
        self,
        name: str,
        video: Any,
        video_provider_config: BaseVideoConfig,
        custom_llm_provider: str,
        litellm_params,
        logging_obj,
        extra_headers: dict[str, object] | None = None,
        timeout: float | None = None,
        client=None,
        api_key: str | None = None,
    ):
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = video_provider_config.validate_environment(
            api_key=api_key or litellm_params.get("api_key", None),
            headers=extra_headers or {},
            model="",
            litellm_params=litellm_params,
        )
        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = video_provider_config.get_complete_url(
            model="",
            api_base=litellm_params.get("api_base", None),
            litellm_params=dict(litellm_params),
        )

        (
            url,
            files_list,
        ) = video_provider_config.transform_video_create_character_request(
            name=name,
            video=video,
            api_base=api_base,
            litellm_params=litellm_params,
            headers=headers,
        )

        logging_obj.pre_call(
            input=name,
            api_key="",
            additional_args={
                "complete_input_dict": {"name": name},
                "api_base": url,
                "headers": headers,
            },
        )

        try:
            response: Final = await async_httpx_client.post(
                url=url,
                headers=headers,
                files=files_list,
                timeout=timeout,
            )
            response.raise_for_status()
            return video_provider_config.transform_video_create_character_response(
                raw_response=response,
                logging_obj=logging_obj,
            )
        except Exception as e:
            raise self._handle_error(e=e, provider_config=video_provider_config)

    def video_get_character_handler(
        self,
        character_id: str,
        video_provider_config: BaseVideoConfig,
        custom_llm_provider: str,
        litellm_params,
        logging_obj,
        extra_headers: dict[str, object] | None = None,
        timeout: float | None = None,
        _is_async: bool = False,
        client=None,
        api_key: str | None = None,
    ):
        if _is_async:
            return self.async_video_get_character_handler(
                character_id=character_id,
                video_provider_config=video_provider_config,
                custom_llm_provider=custom_llm_provider,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                timeout=timeout,
                client=client,
                api_key=api_key,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = video_provider_config.validate_environment(
            api_key=api_key or litellm_params.get("api_key", None),
            headers=extra_headers or {},
            model="",
            litellm_params=litellm_params,
        )
        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = video_provider_config.get_complete_url(
            model="",
            api_base=litellm_params.get("api_base", None),
            litellm_params=dict(litellm_params),
        )

        url, params = video_provider_config.transform_video_get_character_request(
            character_id=character_id,
            api_base=api_base,
            litellm_params=litellm_params,
            headers=headers,
        )

        logging_obj.pre_call(
            input=character_id,
            api_key="",
            additional_args={"api_base": url, "headers": headers},
        )

        try:
            response: Final = sync_httpx_client.get(url=url, headers=headers, params=params)
            response.raise_for_status()
            return video_provider_config.transform_video_get_character_response(
                raw_response=response,
                logging_obj=logging_obj,
            )
        except Exception as e:
            raise self._handle_error(e=e, provider_config=video_provider_config)

    async def async_video_get_character_handler(
        self,
        character_id: str,
        video_provider_config: BaseVideoConfig,
        custom_llm_provider: str,
        litellm_params,
        logging_obj,
        extra_headers: dict[str, object] | None = None,
        timeout: float | None = None,
        client=None,
        api_key: str | None = None,
    ):
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = video_provider_config.validate_environment(
            api_key=api_key or litellm_params.get("api_key", None),
            headers=extra_headers or {},
            model="",
            litellm_params=litellm_params,
        )
        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = video_provider_config.get_complete_url(
            model="",
            api_base=litellm_params.get("api_base", None),
            litellm_params=dict(litellm_params),
        )

        url, params = video_provider_config.transform_video_get_character_request(
            character_id=character_id,
            api_base=api_base,
            litellm_params=litellm_params,
            headers=headers,
        )

        logging_obj.pre_call(
            input=character_id,
            api_key="",
            additional_args={"api_base": url, "headers": headers},
        )

        try:
            response: Final = await async_httpx_client.get(url=url, headers=headers, params=params)
            response.raise_for_status()
            return video_provider_config.transform_video_get_character_response(
                raw_response=response,
                logging_obj=logging_obj,
            )
        except Exception as e:
            raise self._handle_error(e=e, provider_config=video_provider_config)

    def video_edit_handler(
        self,
        prompt: str,
        video_id: str,
        video_provider_config: BaseVideoConfig,
        custom_llm_provider: str,
        litellm_params,
        logging_obj,
        video_file: FileContent | None = None,
        extra_headers: dict[str, object] | None = None,
        extra_body: dict[str, object] | None = None,
        timeout: float | None = None,
        _is_async: bool = False,
        client=None,
        api_key: str | None = None,
    ):
        if _is_async:
            return self.async_video_edit_handler(
                prompt=prompt,
                video_id=video_id,
                video_file=video_file,
                video_provider_config=video_provider_config,
                custom_llm_provider=custom_llm_provider,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                extra_body=extra_body,
                timeout=timeout,
                client=client,
                api_key=api_key,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = video_provider_config.validate_environment(
            api_key=api_key or litellm_params.get("api_key", None),
            headers=extra_headers or {},
            model="",
            litellm_params=litellm_params,
        )
        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = video_provider_config.get_complete_url(
            model="",
            api_base=litellm_params.get("api_base", None),
            litellm_params=dict(litellm_params),
        )

        prefetched_source_data = None
        prefetch_params: Final = video_provider_config.get_video_edit_prefetch_params(
            video_id=video_id,
            api_base=api_base,
            litellm_params=litellm_params,
            headers=headers,
        )
        if prefetch_params is not None:
            prefetch_url, prefetch_body = prefetch_params
            try:
                prefetch_resp: Final = sync_httpx_client.post(
                    url=prefetch_url,
                    headers=headers,
                    json=prefetch_body,
                    timeout=timeout,
                )
                prefetch_resp.raise_for_status()
            except Exception as e:
                raise self._handle_error(e=e, provider_config=video_provider_config)
            prefetched_source_data = prefetch_resp.json()

        try:
            url, data, files = video_provider_config.transform_video_edit_request(
                prompt=prompt,
                video_id=video_id,
                video_file=video_file,
                api_base=api_base,
                litellm_params=litellm_params,
                headers=headers,
                extra_body=extra_body,
                prefetched_source_data=prefetched_source_data,
            )

            logging_obj.pre_call(
                input=prompt,
                api_key="",
                additional_args={
                    "complete_input_dict": data,
                    "api_base": url,
                    "headers": headers,
                    "video_id": video_id,
                },
            )

            response: Final = (
                sync_httpx_client.post(url=url, headers=headers, data=data, files=files, timeout=timeout)
                if files
                else sync_httpx_client.post(url=url, headers=headers, json=data, timeout=timeout)
            )
            response.raise_for_status()
            return video_provider_config.transform_video_edit_response(
                raw_response=response,
                logging_obj=logging_obj,
                custom_llm_provider=custom_llm_provider,
                request_data=data,
            )
        except Exception as e:
            raise self._handle_error(e=e, provider_config=video_provider_config)

    async def async_video_edit_handler(
        self,
        prompt: str,
        video_id: str,
        video_provider_config: BaseVideoConfig,
        custom_llm_provider: str,
        litellm_params,
        logging_obj,
        video_file: FileContent | None = None,
        extra_headers: dict[str, object] | None = None,
        extra_body: dict[str, object] | None = None,
        timeout: float | None = None,
        client=None,
        api_key: str | None = None,
    ):
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = video_provider_config.validate_environment(
            api_key=api_key or litellm_params.get("api_key", None),
            headers=extra_headers or {},
            model="",
            litellm_params=litellm_params,
        )
        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = video_provider_config.get_complete_url(
            model="",
            api_base=litellm_params.get("api_base", None),
            litellm_params=dict(litellm_params),
        )

        prefetched_source_data = None
        prefetch_params: Final = video_provider_config.get_video_edit_prefetch_params(
            video_id=video_id,
            api_base=api_base,
            litellm_params=litellm_params,
            headers=headers,
        )
        if prefetch_params is not None:
            prefetch_url, prefetch_body = prefetch_params
            try:
                prefetch_resp: Final = await async_httpx_client.post(
                    url=prefetch_url,
                    headers=headers,
                    json=prefetch_body,
                    timeout=timeout,
                )
                prefetch_resp.raise_for_status()
            except Exception as e:
                raise self._handle_error(e=e, provider_config=video_provider_config)
            prefetched_source_data = prefetch_resp.json()

        try:
            url, data, files = video_provider_config.transform_video_edit_request(
                prompt=prompt,
                video_id=video_id,
                video_file=video_file,
                api_base=api_base,
                litellm_params=litellm_params,
                headers=headers,
                extra_body=extra_body,
                prefetched_source_data=prefetched_source_data,
            )

            logging_obj.pre_call(
                input=prompt,
                api_key="",
                additional_args={
                    "complete_input_dict": data,
                    "api_base": url,
                    "headers": headers,
                    "video_id": video_id,
                },
            )

            response: Final = await (
                async_httpx_client.post(url=url, headers=headers, data=data, files=files, timeout=timeout)
                if files
                else async_httpx_client.post(url=url, headers=headers, json=data, timeout=timeout)
            )
            response.raise_for_status()
            return video_provider_config.transform_video_edit_response(
                raw_response=response,
                logging_obj=logging_obj,
                custom_llm_provider=custom_llm_provider,
                request_data=data,
            )
        except Exception as e:
            raise self._handle_error(e=e, provider_config=video_provider_config)

    def video_extension_handler(
        self,
        prompt: str,
        video_id: str,
        seconds: str,
        video_provider_config: BaseVideoConfig,
        custom_llm_provider: str,
        litellm_params,
        logging_obj,
        extra_headers: dict[str, object] | None = None,
        extra_body: dict[str, object] | None = None,
        timeout: float | None = None,
        _is_async: bool = False,
        client=None,
        api_key: str | None = None,
    ):
        if _is_async:
            return self.async_video_extension_handler(
                prompt=prompt,
                video_id=video_id,
                seconds=seconds,
                video_provider_config=video_provider_config,
                custom_llm_provider=custom_llm_provider,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                extra_body=extra_body,
                timeout=timeout,
                client=client,
                api_key=api_key,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = video_provider_config.validate_environment(
            api_key=api_key or litellm_params.get("api_key", None),
            headers=extra_headers or {},
            model="",
            litellm_params=litellm_params,
        )
        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = video_provider_config.get_complete_url(
            model="",
            api_base=litellm_params.get("api_base", None),
            litellm_params=dict(litellm_params),
        )

        url, data = video_provider_config.transform_video_extension_request(
            prompt=prompt,
            video_id=video_id,
            seconds=seconds,
            api_base=api_base,
            litellm_params=litellm_params,
            headers=headers,
            extra_body=extra_body,
        )

        logging_obj.pre_call(
            input=prompt,
            api_key="",
            additional_args={
                "complete_input_dict": data,
                "api_base": url,
                "headers": headers,
                "video_id": video_id,
            },
        )

        try:
            response: Final = sync_httpx_client.post(
                url=url,
                headers=headers,
                json=data,
                timeout=timeout,
            )
            response.raise_for_status()
            return video_provider_config.transform_video_extension_response(
                raw_response=response,
                logging_obj=logging_obj,
                custom_llm_provider=custom_llm_provider,
            )
        except Exception as e:
            raise self._handle_error(e=e, provider_config=video_provider_config)

    async def async_video_extension_handler(
        self,
        prompt: str,
        video_id: str,
        seconds: str,
        video_provider_config: BaseVideoConfig,
        custom_llm_provider: str,
        litellm_params,
        logging_obj,
        extra_headers: dict[str, object] | None = None,
        extra_body: dict[str, object] | None = None,
        timeout: float | None = None,
        client=None,
        api_key: str | None = None,
    ):
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = video_provider_config.validate_environment(
            api_key=api_key or litellm_params.get("api_key", None),
            headers=extra_headers or {},
            model="",
            litellm_params=litellm_params,
        )
        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = video_provider_config.get_complete_url(
            model="",
            api_base=litellm_params.get("api_base", None),
            litellm_params=dict(litellm_params),
        )

        url, data = video_provider_config.transform_video_extension_request(
            prompt=prompt,
            video_id=video_id,
            seconds=seconds,
            api_base=api_base,
            litellm_params=litellm_params,
            headers=headers,
            extra_body=extra_body,
        )

        logging_obj.pre_call(
            input=prompt,
            api_key="",
            additional_args={
                "complete_input_dict": data,
                "api_base": url,
                "headers": headers,
                "video_id": video_id,
            },
        )

        try:
            response: Final = await async_httpx_client.post(
                url=url,
                headers=headers,
                json=data,
                timeout=timeout,
            )
            response.raise_for_status()
            return video_provider_config.transform_video_extension_response(
                raw_response=response,
                logging_obj=logging_obj,
                custom_llm_provider=custom_llm_provider,
            )
        except Exception as e:
            raise self._handle_error(e=e, provider_config=video_provider_config)

    def video_list_handler(
        self,
        after: str | None,
        limit: int | None,
        order: str | None,
        video_list_provider_config,
        custom_llm_provider: str,
        litellm_params,
        logging_obj,
        extra_headers: dict[str, object] | None = None,
        extra_query: dict[str, object] | None = None,
        timeout: float | None = None,
        _is_async: bool = False,
        client=None,
        api_key: str | None = None,
    ):
        """
        Handler for video list requests.
        """
        if _is_async:
            return self.async_video_list_handler(
                after=after,
                limit=limit,
                order=order,
                video_list_provider_config=video_list_provider_config,
                custom_llm_provider=custom_llm_provider,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                extra_query=extra_query,
                timeout=timeout,
                client=client,
                api_key=api_key,
            )
        else:
            # For sync calls, we'll use the async handler in a sync context
            import asyncio

            return asyncio.run(
                self.async_video_list_handler(
                    after=after,
                    limit=limit,
                    order=order,
                    video_list_provider_config=video_list_provider_config,
                    custom_llm_provider=custom_llm_provider,
                    litellm_params=litellm_params,
                    logging_obj=logging_obj,
                    extra_headers=extra_headers,
                    extra_query=extra_query,
                    timeout=timeout,
                    client=client,
                )
            )

    async def async_video_list_handler(
        self,
        after: str | None,
        limit: int | None,
        order: str | None,
        video_list_provider_config: BaseVideoConfig,
        custom_llm_provider: str,
        litellm_params,
        logging_obj,
        extra_headers: dict[str, object] | None = None,
        extra_query: dict[str, object] | None = None,
        timeout: float | None = None,
        client=None,
        api_key: str | None = None,
    ):
        """
        Async version of the video list handler.
        """
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = video_list_provider_config.validate_environment(
            api_key=api_key,
            headers=extra_headers or {},
            model="",
            litellm_params=litellm_params,
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = video_list_provider_config.get_complete_url(
            model="",
            api_base=litellm_params.get("api_base", None),
            litellm_params=dict(litellm_params),
        )

        # Transform the request using the provider config
        url, params = video_list_provider_config.transform_video_list_request(
            api_base=api_base,
            litellm_params=litellm_params,
            headers=headers,
            after=after,
            limit=limit,
            order=order,
            extra_query=extra_query,
        )

        ## LOGGING
        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
                "params": params,
            },
        )

        try:
            response: Final = await async_httpx_client.get(
                url=url,
                headers=headers,
                params=params,
            )

            return video_list_provider_config.transform_video_list_response(
                raw_response=response,
                logging_obj=logging_obj,
                custom_llm_provider=custom_llm_provider,
            )

        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=video_list_provider_config,
            )

    async def async_video_delete_handler(
        self,
        video_id: str,
        video_delete_provider_config: BaseVideoConfig,
        custom_llm_provider: str,
        litellm_params,
        logging_obj,
        extra_headers: dict[str, object] | None = None,
        timeout: float | None = None,
        client=None,
        api_key: str | None = None,
    ):
        """
        Async version of the video delete handler.
        """
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = video_delete_provider_config.validate_environment(
            api_key=api_key,
            headers=extra_headers or {},
            model="",
            litellm_params=litellm_params,
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = video_delete_provider_config.get_complete_url(
            model="",
            api_base=litellm_params.get("api_base", None),
            litellm_params=dict(litellm_params),
        )

        # Transform the request using the provider config
        url, data = video_delete_provider_config.transform_video_delete_request(
            video_id=video_id,
            api_base=api_base,
            litellm_params=litellm_params,
            headers=headers,
        )

        ## LOGGING
        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
                "video_id": video_id,
            },
        )

        try:
            response: Final = await async_httpx_client.delete(
                url=url,
                headers=headers,
                timeout=timeout,
            )

            return video_delete_provider_config.transform_video_delete_response(
                raw_response=response,
                logging_obj=logging_obj,
            )

        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=video_delete_provider_config,
            )

    def video_status_handler(
        self,
        video_id: str,
        video_status_provider_config: BaseVideoConfig,
        custom_llm_provider: str,
        litellm_params,
        logging_obj,
        extra_headers: dict[str, object] | None = None,
        extra_body: dict[str, object] | None = None,
        timeout: float | None = None,
        _is_async: bool = False,
        client=None,
        api_key: str | None = None,
    ):
        """
        Handler for video status requests.
        When _is_async=True, returns a coroutine instead of making the call directly.
        """
        if _is_async:
            # Return the async coroutine if called with _is_async=True
            return self.async_video_status_handler(
                video_id=video_id,
                video_status_provider_config=video_status_provider_config,
                custom_llm_provider=custom_llm_provider,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                extra_body=extra_body,
                timeout=timeout,
                client=client,
                api_key=api_key,
            )

        # For sync calls, use sync HTTP client directly (like video_generation does)
        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = video_status_provider_config.validate_environment(
            api_key=api_key,
            headers=extra_headers or {},
            model="",
            litellm_params=litellm_params,
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = video_status_provider_config.get_complete_url(
            model="",
            api_base=litellm_params.get("api_base", None),
            litellm_params=dict(litellm_params),
        )

        # Transform the request using the provider config
        (
            url,
            data,
        ) = video_status_provider_config.transform_video_status_retrieve_request(
            video_id=video_id,
            api_base=api_base,
            litellm_params=litellm_params,
            headers=headers,
        )

        ## LOGGING
        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
                "video_id": video_id,
                "data": data,
            },
        )

        try:
            # Use POST if data is provided (e.g., Vertex AI fetchPredictOperation)
            # Otherwise use GET (e.g., OpenAI video status)
            if data:
                response = sync_httpx_client.post(
                    url=url,
                    headers=headers,
                    json=data,
                )
            else:
                response = sync_httpx_client.get(
                    url=url,
                    headers=headers,
                )

            return video_status_provider_config.transform_video_status_retrieve_response(
                raw_response=response,
                logging_obj=logging_obj,
                custom_llm_provider=custom_llm_provider,
            )

        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=video_status_provider_config,
            )

    async def async_video_status_handler(
        self,
        video_id: str,
        video_status_provider_config: BaseVideoConfig,
        custom_llm_provider: str,
        litellm_params,
        logging_obj,
        extra_headers: dict[str, object] | None = None,
        extra_body: dict[str, object] | None = None,
        timeout: float | None = None,
        client=None,
        api_key: str | None = None,
    ):
        """
        Async version of the video status handler.
        """
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = video_status_provider_config.validate_environment(
            api_key=api_key,
            headers=extra_headers or {},
            model="",
            litellm_params=litellm_params,
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = video_status_provider_config.get_complete_url(
            model="",
            api_base=litellm_params.get("api_base", None),
            litellm_params=dict(litellm_params),
        )

        # Transform the request using the provider config
        (
            url,
            data,
        ) = video_status_provider_config.transform_video_status_retrieve_request(
            video_id=video_id,
            api_base=api_base,
            litellm_params=litellm_params,
            headers=headers,
        )

        ## LOGGING
        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
                "video_id": video_id,
                "data": data,
            },
        )

        try:
            # Use POST if data is provided (e.g., Vertex AI fetchPredictOperation)
            # Otherwise use GET (e.g., OpenAI video status)
            if data:
                response = await async_httpx_client.post(
                    url=url,
                    headers=headers,
                    json=data,
                )
            else:
                response = await async_httpx_client.get(
                    url=url,
                    headers=headers,
                )
            return video_status_provider_config.transform_video_status_retrieve_response(
                raw_response=response,
                logging_obj=logging_obj,
                custom_llm_provider=custom_llm_provider,
            )

        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=video_status_provider_config,
            )

    ###### CONTAINER HANDLER ######
    def container_create_handler(
        self,
        name: str,
        container_create_request_params: dict,
        container_provider_config: "BaseContainerConfig",
        litellm_params: GenericLiteLLMParams,
        logging_obj: "LiteLLMLoggingObj",
        extra_headers: dict[str, object] | None = None,
        timeout: float | httpx.Timeout = 600,
        _is_async: bool = False,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
    ) -> Union["ContainerObject", Coroutine[object, object, "ContainerObject"]]:
        if _is_async:
            # Return the async coroutine if called with _is_async=True
            return self.async_container_create_handler(
                name=name,
                container_create_request_params=container_create_request_params,
                container_provider_config=container_provider_config,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                timeout=timeout,
                client=client,
            )

        # For sync calls, use sync HTTP client
        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        # Validate environment and get headers
        headers: Final = container_provider_config.validate_environment(
            headers=extra_headers or {},
            api_key=litellm_params.get("api_key", None),
        )

        # Add Content-Type header for JSON requests
        headers["Content-Type"] = "application/json"

        if extra_headers:
            headers.update(extra_headers)

        # Get the complete URL for the request
        api_base: Final = container_provider_config.get_complete_url(
            api_base=litellm_params.get("api_base", None),
            litellm_params=dict(litellm_params),
        )

        # Transform the request using the provider config
        data: Final = container_provider_config.transform_container_create_request(
            name=name,
            container_create_optional_request_params=container_create_request_params,
            litellm_params=litellm_params,
            headers=headers,
        )

        ## LOGGING
        logging_obj.pre_call(
            input=name,
            api_key="",
            additional_args={
                "complete_input_dict": data,
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            response: Final = sync_httpx_client.post(
                url=api_base,
                headers=headers,
                json=data,
                timeout=timeout,
            )

            return container_provider_config.transform_container_create_response(
                raw_response=response,
                logging_obj=logging_obj,
            )

        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=container_provider_config,
            )

    async def async_container_create_handler(
        self,
        name: str,
        container_create_request_params: dict,
        container_provider_config: "BaseContainerConfig",
        litellm_params: GenericLiteLLMParams,
        logging_obj: "LiteLLMLoggingObj",
        extra_headers: dict[str, object] | None = None,
        timeout: float | httpx.Timeout = 600,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
    ) -> "ContainerObject":
        # For async calls, use async HTTP client
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders.OPENAI,
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        # Validate environment and get headers
        headers: Final = container_provider_config.validate_environment(
            headers=extra_headers or {},
            api_key=litellm_params.get("api_key", None),
        )

        # Add Content-Type header for JSON requests
        headers["Content-Type"] = "application/json"

        if extra_headers:
            headers.update(extra_headers)

        # Get the complete URL for the request
        api_base: Final = container_provider_config.get_complete_url(
            api_base=litellm_params.get("api_base", None),
            litellm_params=dict(litellm_params),
        )

        # Transform the request using the provider config
        data: Final = container_provider_config.transform_container_create_request(
            name=name,
            container_create_optional_request_params=container_create_request_params,
            litellm_params=litellm_params,
            headers=headers,
        )

        ## LOGGING
        logging_obj.pre_call(
            input=name,
            api_key="",
            additional_args={
                "complete_input_dict": data,
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            response: Final = await async_httpx_client.post(
                url=api_base,
                headers=headers,
                json=data,
                timeout=timeout,
            )

            return container_provider_config.transform_container_create_response(
                raw_response=response,
                logging_obj=logging_obj,
            )

        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=container_provider_config,
            )

    def container_list_handler(
        self,
        container_provider_config: "BaseContainerConfig",
        litellm_params: GenericLiteLLMParams,
        logging_obj: "LiteLLMLoggingObj",
        after: str | None = None,
        limit: int | None = None,
        order: str | None = None,
        extra_headers: dict[str, object] | None = None,
        extra_query: dict[str, object] | None = None,
        timeout: float | httpx.Timeout = 600,
        _is_async: bool = False,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
    ) -> Union["ContainerListResponse", Coroutine[object, object, "ContainerListResponse"]]:
        if _is_async:
            # Return the async coroutine if called with _is_async=True
            return self.async_container_list_handler(
                container_provider_config=container_provider_config,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                after=after,
                limit=limit,
                order=order,
                extra_headers=extra_headers,
                extra_query=extra_query,
                timeout=timeout,
                client=client,
            )

        # For sync calls, use sync HTTP client
        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        # Validate environment and get headers
        headers: Final = container_provider_config.validate_environment(
            headers=extra_headers or {},
            api_key=litellm_params.get("api_key", None),
        )

        if extra_headers:
            headers.update(extra_headers)

        # Get the complete URL for the request
        api_base: Final = container_provider_config.get_complete_url(
            api_base=litellm_params.get("api_base", None),
            litellm_params=dict(litellm_params),
        )

        # Transform the request using the provider config
        url, params = container_provider_config.transform_container_list_request(
            api_base=api_base,
            litellm_params=litellm_params,
            headers=headers,
            after=after,
            limit=limit,
            order=order,
            extra_query=extra_query,
        )

        ## LOGGING
        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
                "params": params,
            },
        )

        try:
            response: Final = sync_httpx_client.get(
                url=url,
                headers=headers,
                params=params or None,
            )

            return container_provider_config.transform_container_list_response(
                raw_response=response,
                logging_obj=logging_obj,
            )

        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=container_provider_config,
            )

    async def async_container_list_handler(
        self,
        container_provider_config: "BaseContainerConfig",
        litellm_params: GenericLiteLLMParams,
        logging_obj: "LiteLLMLoggingObj",
        after: str | None = None,
        limit: int | None = None,
        order: str | None = None,
        extra_headers: dict[str, object] | None = None,
        extra_query: dict[str, object] | None = None,
        timeout: float | httpx.Timeout = 600,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
    ) -> "ContainerListResponse":
        # For async calls, use async HTTP client
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders.OPENAI,
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        # Validate environment and get headers
        headers: Final = container_provider_config.validate_environment(
            headers=extra_headers or {},
            api_key=litellm_params.get("api_key", None),
        )

        if extra_headers:
            headers.update(extra_headers)

        # Get the complete URL for the request
        api_base: Final = container_provider_config.get_complete_url(
            api_base=litellm_params.get("api_base", None),
            litellm_params=dict(litellm_params),
        )

        # Transform the request using the provider config
        url, params = container_provider_config.transform_container_list_request(
            api_base=api_base,
            litellm_params=litellm_params,
            headers=headers,
            after=after,
            limit=limit,
            order=order,
            extra_query=extra_query,
        )

        ## LOGGING
        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
                "params": params,
            },
        )

        try:
            response: Final = await async_httpx_client.get(
                url=url,
                headers=headers,
                params=params or None,
            )

            return container_provider_config.transform_container_list_response(
                raw_response=response,
                logging_obj=logging_obj,
            )

        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=container_provider_config,
            )

    def container_retrieve_handler(
        self,
        container_id: str,
        container_provider_config: "BaseContainerConfig",
        litellm_params: GenericLiteLLMParams,
        logging_obj: "LiteLLMLoggingObj",
        extra_headers: dict[str, object] | None = None,
        extra_query: dict[str, object] | None = None,
        timeout: float | httpx.Timeout = 600,
        _is_async: bool = False,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
    ) -> Union["ContainerObject", Coroutine[object, object, "ContainerObject"]]:
        if _is_async:
            # Return the async coroutine if called with _is_async=True
            return self.async_container_retrieve_handler(
                container_id=container_id,
                container_provider_config=container_provider_config,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                extra_query=extra_query,
                timeout=timeout,
                client=client,
            )

        # For sync calls, use sync HTTP client
        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        # Validate environment and get headers
        headers: Final = container_provider_config.validate_environment(
            headers=extra_headers or {},
            api_key=litellm_params.get("api_key", None),
        )

        if extra_headers:
            headers.update(extra_headers)

        # Get the complete URL for the request
        api_base: Final = container_provider_config.get_complete_url(
            api_base=litellm_params.get("api_base", None),
            litellm_params=dict(litellm_params),
        )

        # Transform the request using the provider config
        url, params = container_provider_config.transform_container_retrieve_request(
            container_id=container_id,
            api_base=api_base,
            litellm_params=litellm_params,
            headers=headers,
        )

        # Add any extra query parameters
        if extra_query:
            params.update(extra_query)

        ## LOGGING
        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
                "params": params,
                "container_id": container_id,
            },
        )

        try:
            response: Final = sync_httpx_client.get(
                url=url,
                headers=headers,
                params=params or None,
            )

            return container_provider_config.transform_container_retrieve_response(
                raw_response=response,
                logging_obj=logging_obj,
            )

        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=container_provider_config,
            )

    async def async_container_retrieve_handler(
        self,
        container_id: str,
        container_provider_config: "BaseContainerConfig",
        litellm_params: GenericLiteLLMParams,
        logging_obj: "LiteLLMLoggingObj",
        extra_headers: dict[str, object] | None = None,
        extra_query: dict[str, object] | None = None,
        timeout: float | httpx.Timeout = 600,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
    ) -> "ContainerObject":
        # For async calls, use async HTTP client
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders.OPENAI,
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        # Validate environment and get headers
        headers: Final = container_provider_config.validate_environment(
            headers=extra_headers or {},
            api_key=litellm_params.get("api_key", None),
        )

        if extra_headers:
            headers.update(extra_headers)

        # Get the complete URL for the request
        api_base: Final = container_provider_config.get_complete_url(
            api_base=litellm_params.get("api_base", None),
            litellm_params=dict(litellm_params),
        )

        # Transform the request using the provider config
        url, params = container_provider_config.transform_container_retrieve_request(
            container_id=container_id,
            api_base=api_base,
            litellm_params=litellm_params,
            headers=headers,
        )

        # Add any extra query parameters
        if extra_query:
            params.update(extra_query)

        ## LOGGING
        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
                "params": params,
                "container_id": container_id,
            },
        )

        try:
            response: Final = await async_httpx_client.get(
                url=url,
                headers=headers,
                params=params or None,
            )

            return container_provider_config.transform_container_retrieve_response(
                raw_response=response,
                logging_obj=logging_obj,
            )

        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=container_provider_config,
            )

    def container_delete_handler(
        self,
        container_id: str,
        container_provider_config: "BaseContainerConfig",
        litellm_params: GenericLiteLLMParams,
        logging_obj: "LiteLLMLoggingObj",
        extra_headers: dict[str, object] | None = None,
        extra_query: dict[str, object] | None = None,
        timeout: float | httpx.Timeout = 600,
        _is_async: bool = False,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
    ) -> Union["DeleteContainerResult", Coroutine[object, object, "DeleteContainerResult"]]:
        if _is_async:
            # Return the async coroutine if called with _is_async=True
            return self.async_container_delete_handler(
                container_id=container_id,
                container_provider_config=container_provider_config,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                extra_query=extra_query,
                timeout=timeout,
                client=client,
            )

        # For sync calls, use sync HTTP client
        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        # Validate environment and get headers
        headers: Final = container_provider_config.validate_environment(
            headers=extra_headers or {},
            api_key=litellm_params.get("api_key", None),
        )

        if extra_headers:
            headers.update(extra_headers)

        # Get the complete URL for the request
        api_base: Final = container_provider_config.get_complete_url(
            api_base=litellm_params.get("api_base", None),
            litellm_params=dict(litellm_params),
        )

        # Transform the request using the provider config
        url, params = container_provider_config.transform_container_delete_request(
            container_id=container_id,
            api_base=api_base,
            litellm_params=litellm_params,
            headers=headers,
        )

        # Add any extra query parameters
        if extra_query:
            params.update(extra_query)

        ## LOGGING
        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
                "params": params,
                "container_id": container_id,
            },
        )

        try:
            response: Final = sync_httpx_client.delete(
                url=url,
                headers=headers,
                params=params or None,
            )

            return container_provider_config.transform_container_delete_response(
                raw_response=response,
                logging_obj=logging_obj,
            )

        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=container_provider_config,
            )

    async def async_container_delete_handler(
        self,
        container_id: str,
        container_provider_config: "BaseContainerConfig",
        litellm_params: GenericLiteLLMParams,
        logging_obj: "LiteLLMLoggingObj",
        extra_headers: dict[str, object] | None = None,
        extra_query: dict[str, object] | None = None,
        timeout: float | httpx.Timeout = 600,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
    ) -> "DeleteContainerResult":
        # For async calls, use async HTTP client
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders.OPENAI,
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        # Validate environment and get headers
        headers: Final = container_provider_config.validate_environment(
            headers=extra_headers or {},
            api_key=litellm_params.get("api_key", None),
        )

        if extra_headers:
            headers.update(extra_headers)

        # Get the complete URL for the request
        api_base: Final = container_provider_config.get_complete_url(
            api_base=litellm_params.get("api_base", None),
            litellm_params=dict(litellm_params),
        )

        # Transform the request using the provider config
        url, params = container_provider_config.transform_container_delete_request(
            container_id=container_id,
            api_base=api_base,
            litellm_params=litellm_params,
            headers=headers,
        )

        # Add any extra query parameters
        if extra_query:
            params.update(extra_query)

        ## LOGGING
        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
                "params": params,
                "container_id": container_id,
            },
        )

        try:
            response: Final = await async_httpx_client.delete(
                url=url,
                headers=headers,
                params=params or None,
            )

            return container_provider_config.transform_container_delete_response(
                raw_response=response,
                logging_obj=logging_obj,
            )

        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=container_provider_config,
            )

    def container_file_list_handler(
        self,
        container_id: str,
        container_provider_config: "BaseContainerConfig",
        litellm_params: GenericLiteLLMParams,
        logging_obj: "LiteLLMLoggingObj",
        after: str | None = None,
        limit: int | None = None,
        order: str | None = None,
        extra_headers: dict[str, object] | None = None,
        extra_query: dict[str, object] | None = None,
        timeout: float | httpx.Timeout = 600,
        _is_async: bool = False,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
    ) -> Union["ContainerFileListResponse", Coroutine[object, object, "ContainerFileListResponse"]]:
        if _is_async:
            return self.async_container_file_list_handler(
                container_id=container_id,
                container_provider_config=container_provider_config,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                after=after,
                limit=limit,
                order=order,
                extra_headers=extra_headers,
                extra_query=extra_query,
                timeout=timeout,
                client=client,
            )

        # For sync calls, use sync HTTP client
        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        # Validate environment and get headers
        headers: Final = container_provider_config.validate_environment(
            headers=extra_headers or {},
            api_key=litellm_params.get("api_key", None),
        )

        if extra_headers:
            headers.update(extra_headers)

        # Get the complete URL for container files
        api_base: Final = container_provider_config.get_complete_url(
            api_base=litellm_params.get("api_base", None),
            litellm_params=dict(litellm_params),
        )

        # Transform the request using the provider config
        url, params = container_provider_config.transform_container_file_list_request(
            container_id=container_id,
            api_base=api_base,
            litellm_params=litellm_params,
            headers=headers,
            after=after,
            limit=limit,
            order=order,
            extra_query=extra_query,
        )

        ## LOGGING
        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
                "params": params,
            },
        )

        try:
            response: Final = sync_httpx_client.get(
                url=url,
                headers=headers,
                params=params or None,
            )

            return container_provider_config.transform_container_file_list_response(
                raw_response=response,
                logging_obj=logging_obj,
            )

        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=container_provider_config,
            )

    async def async_container_file_list_handler(
        self,
        container_id: str,
        container_provider_config: "BaseContainerConfig",
        litellm_params: GenericLiteLLMParams,
        logging_obj: "LiteLLMLoggingObj",
        after: str | None = None,
        limit: int | None = None,
        order: str | None = None,
        extra_headers: dict[str, object] | None = None,
        extra_query: dict[str, object] | None = None,
        timeout: float | httpx.Timeout = 600,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
    ) -> "ContainerFileListResponse":
        # For async calls, use async HTTP client
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders.OPENAI,
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        # Validate environment and get headers
        headers: Final = container_provider_config.validate_environment(
            headers=extra_headers or {},
            api_key=litellm_params.get("api_key", None),
        )

        if extra_headers:
            headers.update(extra_headers)

        # Get the complete URL for container files
        api_base: Final = container_provider_config.get_complete_url(
            api_base=litellm_params.get("api_base", None),
            litellm_params=dict(litellm_params),
        )

        # Transform the request using the provider config
        url, params = container_provider_config.transform_container_file_list_request(
            container_id=container_id,
            api_base=api_base,
            litellm_params=litellm_params,
            headers=headers,
            after=after,
            limit=limit,
            order=order,
            extra_query=extra_query,
        )

        ## LOGGING
        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
                "params": params,
            },
        )

        try:
            response: Final = await async_httpx_client.get(
                url=url,
                headers=headers,
                params=params or None,
            )

            return container_provider_config.transform_container_file_list_response(
                raw_response=response,
                logging_obj=logging_obj,
            )

        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=container_provider_config,
            )

    def container_file_content_handler(
        self,
        container_id: str,
        file_id: str,
        container_provider_config: "BaseContainerConfig",
        litellm_params: GenericLiteLLMParams,
        logging_obj: "LiteLLMLoggingObj",
        extra_headers: dict[str, object] | None = None,
        timeout: float | httpx.Timeout = 600,
        _is_async: bool = False,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
    ) -> bytes | Coroutine[object, object, bytes]:
        if _is_async:
            return self.async_container_file_content_handler(
                container_id=container_id,
                file_id=file_id,
                container_provider_config=container_provider_config,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                timeout=timeout,
                client=client,
            )

        # For sync calls, use sync HTTP client
        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        # Validate environment and get headers
        headers: Final = container_provider_config.validate_environment(
            headers=extra_headers or {},
            api_key=litellm_params.get("api_key", None),
        )

        if extra_headers:
            headers.update(extra_headers)

        # Get the complete URL for container files
        api_base: Final = container_provider_config.get_complete_url(
            api_base=litellm_params.get("api_base", None),
            litellm_params=dict(litellm_params),
        )

        # Transform the request using the provider config
        (
            url,
            params,
        ) = container_provider_config.transform_container_file_content_request(
            container_id=container_id,
            file_id=file_id,
            api_base=api_base,
            litellm_params=litellm_params,
            headers=headers,
        )

        ## LOGGING
        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
                "params": params,
            },
        )

        try:
            response: Final = sync_httpx_client.get(
                url=url,
                headers=headers,
                params=params or None,
            )

            return container_provider_config.transform_container_file_content_response(
                raw_response=response,
                logging_obj=logging_obj,
            )

        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=container_provider_config,
            )

    async def async_container_file_content_handler(
        self,
        container_id: str,
        file_id: str,
        container_provider_config: "BaseContainerConfig",
        litellm_params: GenericLiteLLMParams,
        logging_obj: "LiteLLMLoggingObj",
        extra_headers: dict[str, object] | None = None,
        timeout: float | httpx.Timeout = 600,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
    ) -> bytes:
        # For async calls, use async HTTP client
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders.OPENAI,
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        # Validate environment and get headers
        headers: Final = container_provider_config.validate_environment(
            headers=extra_headers or {},
            api_key=litellm_params.get("api_key", None),
        )

        if extra_headers:
            headers.update(extra_headers)

        # Get the complete URL for container files
        api_base: Final = container_provider_config.get_complete_url(
            api_base=litellm_params.get("api_base", None),
            litellm_params=dict(litellm_params),
        )

        # Transform the request using the provider config
        (
            url,
            params,
        ) = container_provider_config.transform_container_file_content_request(
            container_id=container_id,
            file_id=file_id,
            api_base=api_base,
            litellm_params=litellm_params,
            headers=headers,
        )

        ## LOGGING
        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
                "params": params,
            },
        )

        try:
            response: Final = await async_httpx_client.get(
                url=url,
                headers=headers,
                params=params or None,
            )

            return container_provider_config.transform_container_file_content_response(
                raw_response=response,
                logging_obj=logging_obj,
            )

        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=container_provider_config,
            )

    ###### VECTOR STORE HANDLER ######
    @staticmethod
    def _pre_call_direct_vector_store_search(
        logging_obj: LiteLLMLoggingObj,
        custom_llm_provider: str,
        vector_store_id: str,
        query: str | Sequence[str],
    ) -> None:
        """Direct providers have no HTTP request to echo, and an empty api_base makes the debug
        logger fall back to dumping model_call_details, which holds stored provider credentials."""
        endpoint: Final = f"{custom_llm_provider}://{vector_store_id}"
        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={  # mutable-ok: pre_call's additional_args contract is a dict
                "query": query,
                "vector_store_id": vector_store_id,
                "api_base": endpoint,
                "request_str": f"direct vector store search: {endpoint}",
            },
        )

    async def async_vector_store_search_handler(
        self,
        vector_store_id: str,
        query: str | list[str],
        vector_store_search_optional_params: VectorStoreSearchOptionalRequestParams,
        vector_store_provider_config: BaseVectorStoreConfig,
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        extra_body: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
    ) -> VectorStoreSearchResponse:
        if isinstance(vector_store_provider_config, BaseDirectVectorStoreConfig):
            self._pre_call_direct_vector_store_search(
                logging_obj=logging_obj,
                custom_llm_provider=custom_llm_provider,
                vector_store_id=vector_store_id,
                query=query,
            )
            return await vector_store_provider_config.aexecute_search_vector_store_request(
                vector_store_id=vector_store_id,
                query=query,
                vector_store_search_optional_params=vector_store_search_optional_params,
                litellm_logging_obj=logging_obj,
                litellm_params=dict(litellm_params),  # mutable-ok: snapshot GenericLiteLLMParams into the Mapping shape
                timeout=timeout,
            )

        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers = vector_store_provider_config.validate_environment(
            headers=extra_headers or {}, litellm_params=litellm_params
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = vector_store_provider_config.get_complete_url(
            api_base=litellm_params.api_base,
            litellm_params=dict(litellm_params),
        )

        # Check if provider has async transform method
        if hasattr(vector_store_provider_config, "atransform_search_vector_store_request"):
            (
                url,
                request_body,
            ) = await vector_store_provider_config.atransform_search_vector_store_request(
                vector_store_id=vector_store_id,
                query=query,
                vector_store_search_optional_params=vector_store_search_optional_params,
                api_base=api_base,
                litellm_logging_obj=logging_obj,
                litellm_params=dict(litellm_params),
                extra_body=extra_body,
            )
        else:
            (
                url,
                request_body,
            ) = vector_store_provider_config.transform_search_vector_store_request(
                vector_store_id=vector_store_id,
                query=query,
                vector_store_search_optional_params=vector_store_search_optional_params,
                api_base=api_base,
                litellm_logging_obj=logging_obj,
                litellm_params=dict(litellm_params),
                extra_body=extra_body,
            )
        all_optional_params: Final[dict[str, object]] = dict(litellm_params)
        all_optional_params.update(vector_store_search_optional_params or {})
        headers, signed_json_body = vector_store_provider_config.sign_request(
            headers=headers,
            optional_params=all_optional_params,
            request_data=request_body,
            api_base=url,
        )

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "complete_input_dict": request_body,
                "api_base": api_base,
                "headers": headers,
            },
        )

        request_data: Final = json.dumps(request_body) if signed_json_body is None else signed_json_body

        try:
            response: Final = await async_httpx_client.post(
                url=url,
                headers=headers,
                data=request_data,
                timeout=timeout,
            )
        except Exception as e:
            raise self._handle_error(e=e, provider_config=vector_store_provider_config)

        return vector_store_provider_config.transform_search_vector_store_response(
            response=response,
            litellm_logging_obj=logging_obj,
        )

    def vector_store_search_handler(
        self,
        vector_store_id: str,
        query: str | list[str],
        vector_store_search_optional_params: VectorStoreSearchOptionalRequestParams,
        vector_store_provider_config: BaseVectorStoreConfig,
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        extra_body: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
    ) -> VectorStoreSearchResponse | Coroutine[object, object, VectorStoreSearchResponse]:
        if _is_async:
            return self.async_vector_store_search_handler(
                vector_store_id=vector_store_id,
                query=query,
                vector_store_search_optional_params=vector_store_search_optional_params,
                vector_store_provider_config=vector_store_provider_config,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                custom_llm_provider=custom_llm_provider,
                extra_headers=extra_headers,
                extra_body=extra_body,
                timeout=timeout,
                client=client,
            )

        if isinstance(vector_store_provider_config, BaseDirectVectorStoreConfig):
            self._pre_call_direct_vector_store_search(
                logging_obj=logging_obj,
                custom_llm_provider=custom_llm_provider,
                vector_store_id=vector_store_id,
                query=query,
            )
            return vector_store_provider_config.execute_search_vector_store_request(
                vector_store_id=vector_store_id,
                query=query,
                vector_store_search_optional_params=vector_store_search_optional_params,
                litellm_logging_obj=logging_obj,
                litellm_params=dict(litellm_params),  # mutable-ok: snapshot GenericLiteLLMParams into the Mapping shape
                timeout=timeout,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers = vector_store_provider_config.validate_environment(
            headers=extra_headers or {}, litellm_params=litellm_params
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = vector_store_provider_config.get_complete_url(
            api_base=litellm_params.api_base,
            litellm_params=dict(litellm_params),
        )

        (
            url,
            request_body,
        ) = vector_store_provider_config.transform_search_vector_store_request(
            vector_store_id=vector_store_id,
            query=query,
            vector_store_search_optional_params=vector_store_search_optional_params,
            api_base=api_base,
            litellm_logging_obj=logging_obj,
            litellm_params=dict(litellm_params),
            extra_body=extra_body,
        )

        all_optional_params: Final[dict[str, object]] = dict(litellm_params)
        all_optional_params.update(vector_store_search_optional_params or {})

        headers, signed_json_body = vector_store_provider_config.sign_request(
            headers=headers,
            optional_params=all_optional_params,
            request_data=request_body,
            api_base=url,
        )

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "complete_input_dict": request_body,
                "api_base": api_base,
                "headers": headers,
            },
        )

        request_data: Final = json.dumps(request_body) if signed_json_body is None else signed_json_body

        try:
            response: Final = sync_httpx_client.post(
                url=url,
                headers=headers,
                data=request_data,
            )
        except Exception as e:
            raise self._handle_error(e=e, provider_config=vector_store_provider_config)

        return vector_store_provider_config.transform_search_vector_store_response(
            response=response,
            litellm_logging_obj=logging_obj,
        )

    async def async_vector_store_create_handler(
        self,
        vector_store_create_optional_params: VectorStoreCreateOptionalRequestParams,
        vector_store_provider_config: BaseVectorStoreConfig,
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        extra_body: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
    ) -> VectorStoreCreateResponse:
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = vector_store_provider_config.validate_environment(
            headers=extra_headers or {}, litellm_params=litellm_params
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = vector_store_provider_config.get_complete_url(
            api_base=litellm_params.api_base,
            litellm_params=dict(litellm_params),
        )

        (
            url,
            request_body,
        ) = vector_store_provider_config.transform_create_vector_store_request(
            vector_store_create_optional_params=vector_store_create_optional_params,
            api_base=api_base,
        )

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "complete_input_dict": request_body,
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            response = await async_httpx_client.post(url=url, headers=headers, json=request_body, timeout=timeout)
        except Exception as e:
            raise self._handle_error(e=e, provider_config=vector_store_provider_config)

        return vector_store_provider_config.transform_create_vector_store_response(
            response=response,
        )

    def vector_store_create_handler(
        self,
        vector_store_create_optional_params: VectorStoreCreateOptionalRequestParams,
        vector_store_provider_config: BaseVectorStoreConfig,
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        extra_body: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
    ) -> VectorStoreCreateResponse | Coroutine[object, object, VectorStoreCreateResponse]:
        if _is_async:
            return self.async_vector_store_create_handler(
                vector_store_create_optional_params=vector_store_create_optional_params,
                vector_store_provider_config=vector_store_provider_config,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                custom_llm_provider=custom_llm_provider,
                extra_headers=extra_headers,
                extra_body=extra_body,
                timeout=timeout,
                client=client,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = vector_store_provider_config.validate_environment(
            headers=extra_headers or {}, litellm_params=litellm_params
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = vector_store_provider_config.get_complete_url(
            api_base=litellm_params.api_base,
            litellm_params=dict(litellm_params),
        )

        (
            url,
            request_body,
        ) = vector_store_provider_config.transform_create_vector_store_request(
            vector_store_create_optional_params=vector_store_create_optional_params,
            api_base=api_base,
        )

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "complete_input_dict": request_body,
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            response: Final = sync_httpx_client.post(url=url, headers=headers, json=request_body)
        except Exception as e:
            raise self._handle_error(e=e, provider_config=vector_store_provider_config)

        return vector_store_provider_config.transform_create_vector_store_response(
            response=response,
        )

    async def async_vector_store_retrieve_handler(
        self,
        vector_store_id: str,
        vector_store_provider_config: BaseVectorStoreConfig,
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        extra_body: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
    ) -> VectorStoreCreateResponse:
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = vector_store_provider_config.validate_environment(
            headers=extra_headers or {}, litellm_params=litellm_params
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = vector_store_provider_config.get_complete_url(
            api_base=litellm_params.api_base,
            litellm_params=dict(litellm_params),
        )

        encoded_vector_store_id: Final = encode_url_path_segment(vector_store_id, field_name="vector_store_id")
        url: Final = f"{api_base}/{encoded_vector_store_id}"

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            response: Final = await async_httpx_client.get(url=url, headers=headers)
        except Exception as e:
            raise self._handle_error(e=e, provider_config=vector_store_provider_config)

        return vector_store_provider_config.transform_create_vector_store_response(
            response=response,
        )

    def vector_store_retrieve_handler(
        self,
        vector_store_id: str,
        vector_store_provider_config: BaseVectorStoreConfig,
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        extra_body: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
    ) -> VectorStoreCreateResponse | Coroutine[object, object, VectorStoreCreateResponse]:
        if _is_async:
            return self.async_vector_store_retrieve_handler(
                vector_store_id=vector_store_id,
                vector_store_provider_config=vector_store_provider_config,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                custom_llm_provider=custom_llm_provider,
                extra_headers=extra_headers,
                extra_body=extra_body,
                timeout=timeout,
                client=client,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = vector_store_provider_config.validate_environment(
            headers=extra_headers or {}, litellm_params=litellm_params
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = vector_store_provider_config.get_complete_url(
            api_base=litellm_params.api_base,
            litellm_params=dict(litellm_params),
        )

        encoded_vector_store_id: Final = encode_url_path_segment(vector_store_id, field_name="vector_store_id")
        url: Final = f"{api_base}/{encoded_vector_store_id}"

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            response: Final = sync_httpx_client.get(url=url, headers=headers)
        except Exception as e:
            raise self._handle_error(e=e, provider_config=vector_store_provider_config)

        return vector_store_provider_config.transform_create_vector_store_response(
            response=response,
        )

    async def async_vector_store_list_handler(
        self,
        after: str | None,
        before: str | None,
        limit: int | None,
        order: str | None,
        vector_store_provider_config: BaseVectorStoreConfig,
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        extra_body: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
    ):
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = vector_store_provider_config.validate_environment(
            headers=extra_headers or {}, litellm_params=litellm_params
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = vector_store_provider_config.get_complete_url(
            api_base=litellm_params.api_base,
            litellm_params=dict(litellm_params),
        )

        url: Final = api_base

        params: Final[dict[str, object]] = {}
        if after is not None:
            params["after"] = after
        if before is not None:
            params["before"] = before
        if limit is not None:
            params["limit"] = limit
        if order is not None:
            params["order"] = order

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": api_base,
                "headers": headers,
                "params": params,
            },
        )

        try:
            response: Final = await async_httpx_client.get(url=url, headers=headers, params=params)
        except Exception as e:
            raise self._handle_error(e=e, provider_config=vector_store_provider_config)

        return response.json()

    def vector_store_list_handler(
        self,
        after: str | None,
        before: str | None,
        limit: int | None,
        order: str | None,
        vector_store_provider_config: BaseVectorStoreConfig,
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        extra_body: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
    ):
        if _is_async:
            return self.async_vector_store_list_handler(
                after=after,
                before=before,
                limit=limit,
                order=order,
                vector_store_provider_config=vector_store_provider_config,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                custom_llm_provider=custom_llm_provider,
                extra_headers=extra_headers,
                extra_body=extra_body,
                timeout=timeout,
                client=client,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = vector_store_provider_config.validate_environment(
            headers=extra_headers or {}, litellm_params=litellm_params
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = vector_store_provider_config.get_complete_url(
            api_base=litellm_params.api_base,
            litellm_params=dict(litellm_params),
        )

        url: Final = api_base

        params: Final[dict[str, object]] = {}
        if after is not None:
            params["after"] = after
        if before is not None:
            params["before"] = before
        if limit is not None:
            params["limit"] = limit
        if order is not None:
            params["order"] = order

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": api_base,
                "headers": headers,
                "params": params,
            },
        )

        try:
            response: Final = sync_httpx_client.get(url=url, headers=headers, params=params)
        except Exception as e:
            raise self._handle_error(e=e, provider_config=vector_store_provider_config)

        return response.json()

    async def async_vector_store_update_handler(
        self,
        vector_store_id: str,
        vector_store_update_optional_params: VectorStoreCreateOptionalRequestParams,
        vector_store_provider_config: BaseVectorStoreConfig,
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        extra_body: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
    ) -> VectorStoreCreateResponse:
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = vector_store_provider_config.validate_environment(
            headers=extra_headers or {}, litellm_params=litellm_params
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = vector_store_provider_config.get_complete_url(
            api_base=litellm_params.api_base,
            litellm_params=dict(litellm_params),
        )

        encoded_vector_store_id: Final = encode_url_path_segment(vector_store_id, field_name="vector_store_id")
        url: Final = f"{api_base}/{encoded_vector_store_id}"

        request_body: Final[dict[str, Any]] = dict(vector_store_update_optional_params)

        # Clean metadata to only include string values (OpenAI requirement)
        if "metadata" in request_body and request_body["metadata"] is not None:
            from litellm.utils import add_openai_metadata

            request_body["metadata"] = add_openai_metadata(request_body["metadata"])

        if extra_body:
            request_body.update(extra_body)

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "complete_input_dict": request_body,
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            response = await async_httpx_client.post(url=url, headers=headers, json=request_body, timeout=timeout)
        except Exception as e:
            raise self._handle_error(e=e, provider_config=vector_store_provider_config)

        return vector_store_provider_config.transform_create_vector_store_response(
            response=response,
        )

    def vector_store_update_handler(
        self,
        vector_store_id: str,
        vector_store_update_optional_params: VectorStoreCreateOptionalRequestParams,
        vector_store_provider_config: BaseVectorStoreConfig,
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        extra_body: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
    ) -> VectorStoreCreateResponse | Coroutine[object, object, VectorStoreCreateResponse]:
        if _is_async:
            return self.async_vector_store_update_handler(
                vector_store_id=vector_store_id,
                vector_store_update_optional_params=vector_store_update_optional_params,
                vector_store_provider_config=vector_store_provider_config,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                custom_llm_provider=custom_llm_provider,
                extra_headers=extra_headers,
                extra_body=extra_body,
                timeout=timeout,
                client=client,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = vector_store_provider_config.validate_environment(
            headers=extra_headers or {}, litellm_params=litellm_params
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = vector_store_provider_config.get_complete_url(
            api_base=litellm_params.api_base,
            litellm_params=dict(litellm_params),
        )

        encoded_vector_store_id: Final = encode_url_path_segment(vector_store_id, field_name="vector_store_id")
        url: Final = f"{api_base}/{encoded_vector_store_id}"

        request_body: Final[dict[str, Any]] = dict(vector_store_update_optional_params)

        # Clean metadata to only include string values (OpenAI requirement)
        if "metadata" in request_body and request_body["metadata"] is not None:
            from litellm.utils import add_openai_metadata

            request_body["metadata"] = add_openai_metadata(request_body["metadata"])

        if extra_body:
            request_body.update(extra_body)

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "complete_input_dict": request_body,
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            response: Final = sync_httpx_client.post(url=url, headers=headers, json=request_body)
        except Exception as e:
            raise self._handle_error(e=e, provider_config=vector_store_provider_config)

        return vector_store_provider_config.transform_create_vector_store_response(
            response=response,
        )

    async def async_vector_store_delete_handler(
        self,
        vector_store_id: str,
        vector_store_provider_config: BaseVectorStoreConfig,
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        extra_body: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
    ):
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = vector_store_provider_config.validate_environment(
            headers=extra_headers or {}, litellm_params=litellm_params
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = vector_store_provider_config.get_complete_url(
            api_base=litellm_params.api_base,
            litellm_params=dict(litellm_params),
        )

        encoded_vector_store_id: Final = encode_url_path_segment(vector_store_id, field_name="vector_store_id")
        url: Final = f"{api_base}/{encoded_vector_store_id}"

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            response: Final = await async_httpx_client.delete(url=url, headers=headers, timeout=timeout)
        except Exception as e:
            raise self._handle_error(e=e, provider_config=vector_store_provider_config)

        return response.json()

    def vector_store_delete_handler(
        self,
        vector_store_id: str,
        vector_store_provider_config: BaseVectorStoreConfig,
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        extra_body: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
    ):
        if _is_async:
            return self.async_vector_store_delete_handler(
                vector_store_id=vector_store_id,
                vector_store_provider_config=vector_store_provider_config,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                custom_llm_provider=custom_llm_provider,
                extra_headers=extra_headers,
                extra_body=extra_body,
                timeout=timeout,
                client=client,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = vector_store_provider_config.validate_environment(
            headers=extra_headers or {}, litellm_params=litellm_params
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = vector_store_provider_config.get_complete_url(
            api_base=litellm_params.api_base,
            litellm_params=dict(litellm_params),
        )

        encoded_vector_store_id: Final = encode_url_path_segment(vector_store_id, field_name="vector_store_id")
        url: Final = f"{api_base}/{encoded_vector_store_id}"

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            response: Final = sync_httpx_client.delete(url=url, headers=headers)
        except Exception as e:
            raise self._handle_error(e=e, provider_config=vector_store_provider_config)

        return response.json()

    #####################################################################
    ################ Vector Store Files HANDLERS ########################
    #####################################################################
    async def async_vector_store_file_create_handler(
        self,
        *,
        vector_store_id: str,
        create_request: VectorStoreFileCreateRequest,
        vector_store_files_provider_config: BaseVectorStoreFilesConfig,
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, str] | None = None,
        extra_body: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
    ) -> VectorStoreFileObject:
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = vector_store_files_provider_config.validate_environment(
            headers=extra_headers or {}, litellm_params=litellm_params
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = vector_store_files_provider_config.get_complete_url(
            api_base=litellm_params.api_base,
            vector_store_id=vector_store_id,
            litellm_params=dict(litellm_params),
        )

        request_dict: Final = dict(create_request)
        if extra_body:
            request_dict.update(extra_body)

        (
            url,
            request_body,
        ) = vector_store_files_provider_config.transform_create_vector_store_file_request(
            vector_store_id=vector_store_id,
            create_request=cast(VectorStoreFileCreateRequest, request_dict),
            api_base=api_base,
        )

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "complete_input_dict": request_body,
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            response = await async_httpx_client.post(url=url, headers=headers, json=request_body, timeout=timeout)
        except Exception as e:
            raise self._handle_error(e=e, provider_config=vector_store_files_provider_config)

        return vector_store_files_provider_config.transform_create_vector_store_file_response(response=response)

    def vector_store_file_create_handler(
        self,
        *,
        vector_store_id: str,
        create_request: VectorStoreFileCreateRequest,
        vector_store_files_provider_config: BaseVectorStoreFilesConfig,
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, str] | None = None,
        extra_body: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
    ) -> VectorStoreFileObject | Coroutine[object, object, VectorStoreFileObject]:
        if _is_async:
            return self.async_vector_store_file_create_handler(
                vector_store_id=vector_store_id,
                create_request=create_request,
                vector_store_files_provider_config=vector_store_files_provider_config,
                custom_llm_provider=custom_llm_provider,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                extra_body=extra_body,
                timeout=timeout,
                client=client if isinstance(client, AsyncHTTPHandler) else None,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = vector_store_files_provider_config.validate_environment(
            headers=extra_headers or {}, litellm_params=litellm_params
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = vector_store_files_provider_config.get_complete_url(
            api_base=litellm_params.api_base,
            vector_store_id=vector_store_id,
            litellm_params=dict(litellm_params),
        )

        request_dict: Final = dict(create_request)
        if extra_body:
            request_dict.update(extra_body)

        (
            url,
            request_body,
        ) = vector_store_files_provider_config.transform_create_vector_store_file_request(
            vector_store_id=vector_store_id,
            create_request=cast(VectorStoreFileCreateRequest, request_dict),
            api_base=api_base,
        )

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "complete_input_dict": request_body,
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            response: Final = sync_httpx_client.post(url=url, headers=headers, json=request_body, timeout=timeout)
        except Exception as e:
            raise self._handle_error(e=e, provider_config=vector_store_files_provider_config)

        return vector_store_files_provider_config.transform_create_vector_store_file_response(response=response)

    async def async_vector_store_file_list_handler(
        self,
        *,
        vector_store_id: str,
        query_params: VectorStoreFileListQueryParams,
        vector_store_files_provider_config: BaseVectorStoreFilesConfig,
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, str] | None = None,
        extra_query: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
    ) -> VectorStoreFileListResponse:
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = vector_store_files_provider_config.validate_environment(
            headers=extra_headers or {}, litellm_params=litellm_params
        )
        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = vector_store_files_provider_config.get_complete_url(
            api_base=litellm_params.api_base,
            vector_store_id=vector_store_id,
            litellm_params=dict(litellm_params),
        )

        params_dict: Final = dict(query_params)
        if extra_query:
            params_dict.update(extra_query)

        (
            url,
            request_params,
        ) = vector_store_files_provider_config.transform_list_vector_store_files_request(
            vector_store_id=vector_store_id,
            query_params=cast(VectorStoreFileListQueryParams, params_dict),
            api_base=api_base,
        )

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "complete_input_dict": request_params,
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            response: Final = await async_httpx_client.get(url=url, headers=headers, params=request_params)
        except Exception as e:
            raise self._handle_error(e=e, provider_config=vector_store_files_provider_config)

        return vector_store_files_provider_config.transform_list_vector_store_files_response(response=response)

    def vector_store_file_list_handler(
        self,
        *,
        vector_store_id: str,
        query_params: VectorStoreFileListQueryParams,
        vector_store_files_provider_config: BaseVectorStoreFilesConfig,
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, str] | None = None,
        extra_query: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
    ) -> VectorStoreFileListResponse | Coroutine[object, object, VectorStoreFileListResponse]:
        if _is_async:
            return self.async_vector_store_file_list_handler(
                vector_store_id=vector_store_id,
                query_params=query_params,
                vector_store_files_provider_config=vector_store_files_provider_config,
                custom_llm_provider=custom_llm_provider,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                extra_query=extra_query,
                timeout=timeout,
                client=client if isinstance(client, AsyncHTTPHandler) else None,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = vector_store_files_provider_config.validate_environment(
            headers=extra_headers or {}, litellm_params=litellm_params
        )
        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = vector_store_files_provider_config.get_complete_url(
            api_base=litellm_params.api_base,
            vector_store_id=vector_store_id,
            litellm_params=dict(litellm_params),
        )

        params_dict: Final = dict(query_params)
        if extra_query:
            params_dict.update(extra_query)

        (
            url,
            request_params,
        ) = vector_store_files_provider_config.transform_list_vector_store_files_request(
            vector_store_id=vector_store_id,
            query_params=cast(VectorStoreFileListQueryParams, params_dict),
            api_base=api_base,
        )

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "complete_input_dict": request_params,
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            response: Final = sync_httpx_client.get(url=url, headers=headers, params=request_params)
        except Exception as e:
            raise self._handle_error(e=e, provider_config=vector_store_files_provider_config)

        return vector_store_files_provider_config.transform_list_vector_store_files_response(response=response)

    async def async_vector_store_file_retrieve_handler(
        self,
        *,
        vector_store_id: str,
        file_id: str,
        vector_store_files_provider_config: BaseVectorStoreFilesConfig,
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, str] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
    ) -> VectorStoreFileObject:
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = vector_store_files_provider_config.validate_environment(
            headers=extra_headers or {}, litellm_params=litellm_params
        )
        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = vector_store_files_provider_config.get_complete_url(
            api_base=litellm_params.api_base,
            vector_store_id=vector_store_id,
            litellm_params=dict(litellm_params),
        )

        (
            url,
            request_params,
        ) = vector_store_files_provider_config.transform_retrieve_vector_store_file_request(
            vector_store_id=vector_store_id,
            file_id=file_id,
            api_base=api_base,
        )

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "complete_input_dict": request_params,
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            response: Final = await async_httpx_client.get(url=url, headers=headers, params=request_params)
        except Exception as e:
            raise self._handle_error(e=e, provider_config=vector_store_files_provider_config)

        return vector_store_files_provider_config.transform_retrieve_vector_store_file_response(response=response)

    def vector_store_file_retrieve_handler(
        self,
        *,
        vector_store_id: str,
        file_id: str,
        vector_store_files_provider_config: BaseVectorStoreFilesConfig,
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, str] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
    ) -> VectorStoreFileObject | Coroutine[object, object, VectorStoreFileObject]:
        if _is_async:
            return self.async_vector_store_file_retrieve_handler(
                vector_store_id=vector_store_id,
                file_id=file_id,
                vector_store_files_provider_config=vector_store_files_provider_config,
                custom_llm_provider=custom_llm_provider,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                timeout=timeout,
                client=client if isinstance(client, AsyncHTTPHandler) else None,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = vector_store_files_provider_config.validate_environment(
            headers=extra_headers or {}, litellm_params=litellm_params
        )
        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = vector_store_files_provider_config.get_complete_url(
            api_base=litellm_params.api_base,
            vector_store_id=vector_store_id,
            litellm_params=dict(litellm_params),
        )

        (
            url,
            request_params,
        ) = vector_store_files_provider_config.transform_retrieve_vector_store_file_request(
            vector_store_id=vector_store_id,
            file_id=file_id,
            api_base=api_base,
        )

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "complete_input_dict": request_params,
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            response: Final = sync_httpx_client.get(url=url, headers=headers, params=request_params)
        except Exception as e:
            raise self._handle_error(e=e, provider_config=vector_store_files_provider_config)

        return vector_store_files_provider_config.transform_retrieve_vector_store_file_response(response=response)

    async def async_vector_store_file_content_handler(
        self,
        *,
        vector_store_id: str,
        file_id: str,
        vector_store_files_provider_config: BaseVectorStoreFilesConfig,
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, str] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
    ) -> VectorStoreFileContentResponse:
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = vector_store_files_provider_config.validate_environment(
            headers=extra_headers or {}, litellm_params=litellm_params
        )
        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = vector_store_files_provider_config.get_complete_url(
            api_base=litellm_params.api_base,
            vector_store_id=vector_store_id,
            litellm_params=dict(litellm_params),
        )

        (
            url,
            request_params,
        ) = vector_store_files_provider_config.transform_retrieve_vector_store_file_content_request(
            vector_store_id=vector_store_id,
            file_id=file_id,
            api_base=api_base,
        )

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "complete_input_dict": request_params,
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            response: Final = await async_httpx_client.get(url=url, headers=headers, params=request_params)
        except Exception as e:
            raise self._handle_error(e=e, provider_config=vector_store_files_provider_config)

        return vector_store_files_provider_config.transform_retrieve_vector_store_file_content_response(
            response=response
        )

    def vector_store_file_content_handler(
        self,
        *,
        vector_store_id: str,
        file_id: str,
        vector_store_files_provider_config: BaseVectorStoreFilesConfig,
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, str] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
    ) -> VectorStoreFileContentResponse | Coroutine[object, object, VectorStoreFileContentResponse]:
        if _is_async:
            return self.async_vector_store_file_content_handler(
                vector_store_id=vector_store_id,
                file_id=file_id,
                vector_store_files_provider_config=vector_store_files_provider_config,
                custom_llm_provider=custom_llm_provider,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                timeout=timeout,
                client=client if isinstance(client, AsyncHTTPHandler) else None,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = vector_store_files_provider_config.validate_environment(
            headers=extra_headers or {}, litellm_params=litellm_params
        )
        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = vector_store_files_provider_config.get_complete_url(
            api_base=litellm_params.api_base,
            vector_store_id=vector_store_id,
            litellm_params=dict(litellm_params),
        )

        (
            url,
            request_params,
        ) = vector_store_files_provider_config.transform_retrieve_vector_store_file_content_request(
            vector_store_id=vector_store_id,
            file_id=file_id,
            api_base=api_base,
        )

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "complete_input_dict": request_params,
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            response: Final = sync_httpx_client.get(url=url, headers=headers, params=request_params)
        except Exception as e:
            raise self._handle_error(e=e, provider_config=vector_store_files_provider_config)

        return vector_store_files_provider_config.transform_retrieve_vector_store_file_content_response(
            response=response
        )

    async def async_vector_store_file_update_handler(
        self,
        *,
        vector_store_id: str,
        file_id: str,
        update_request: VectorStoreFileUpdateRequest,
        vector_store_files_provider_config: BaseVectorStoreFilesConfig,
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, str] | None = None,
        extra_body: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
    ) -> VectorStoreFileObject:
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = vector_store_files_provider_config.validate_environment(
            headers=extra_headers or {}, litellm_params=litellm_params
        )
        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = vector_store_files_provider_config.get_complete_url(
            api_base=litellm_params.api_base,
            vector_store_id=vector_store_id,
            litellm_params=dict(litellm_params),
        )

        request_dict: Final = dict(update_request)
        if extra_body:
            request_dict.update(extra_body)

        (
            url,
            request_body,
        ) = vector_store_files_provider_config.transform_update_vector_store_file_request(
            vector_store_id=vector_store_id,
            file_id=file_id,
            update_request=cast(VectorStoreFileUpdateRequest, request_dict),
            api_base=api_base,
        )

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "complete_input_dict": request_body,
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            response = await async_httpx_client.post(url=url, headers=headers, json=request_body, timeout=timeout)
        except Exception as e:
            raise self._handle_error(e=e, provider_config=vector_store_files_provider_config)

        return vector_store_files_provider_config.transform_update_vector_store_file_response(response=response)

    def vector_store_file_update_handler(
        self,
        *,
        vector_store_id: str,
        file_id: str,
        update_request: VectorStoreFileUpdateRequest,
        vector_store_files_provider_config: BaseVectorStoreFilesConfig,
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, str] | None = None,
        extra_body: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
    ) -> VectorStoreFileObject | Coroutine[object, object, VectorStoreFileObject]:
        if _is_async:
            return self.async_vector_store_file_update_handler(
                vector_store_id=vector_store_id,
                file_id=file_id,
                update_request=update_request,
                vector_store_files_provider_config=vector_store_files_provider_config,
                custom_llm_provider=custom_llm_provider,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                extra_body=extra_body,
                timeout=timeout,
                client=client if isinstance(client, AsyncHTTPHandler) else None,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = vector_store_files_provider_config.validate_environment(
            headers=extra_headers or {}, litellm_params=litellm_params
        )
        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = vector_store_files_provider_config.get_complete_url(
            api_base=litellm_params.api_base,
            vector_store_id=vector_store_id,
            litellm_params=dict(litellm_params),
        )

        request_dict: Final = dict(update_request)
        if extra_body:
            request_dict.update(extra_body)

        (
            url,
            request_body,
        ) = vector_store_files_provider_config.transform_update_vector_store_file_request(
            vector_store_id=vector_store_id,
            file_id=file_id,
            update_request=cast(VectorStoreFileUpdateRequest, request_dict),
            api_base=api_base,
        )

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "complete_input_dict": request_body,
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            response: Final = sync_httpx_client.post(url=url, headers=headers, json=request_body, timeout=timeout)
        except Exception as e:
            raise self._handle_error(e=e, provider_config=vector_store_files_provider_config)

        return vector_store_files_provider_config.transform_update_vector_store_file_response(response=response)

    async def async_vector_store_file_delete_handler(
        self,
        *,
        vector_store_id: str,
        file_id: str,
        vector_store_files_provider_config: BaseVectorStoreFilesConfig,
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, str] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
    ) -> VectorStoreFileDeleteResponse:
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = vector_store_files_provider_config.validate_environment(
            headers=extra_headers or {}, litellm_params=litellm_params
        )
        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = vector_store_files_provider_config.get_complete_url(
            api_base=litellm_params.api_base,
            vector_store_id=vector_store_id,
            litellm_params=dict(litellm_params),
        )

        (
            url,
            request_params,
        ) = vector_store_files_provider_config.transform_delete_vector_store_file_request(
            vector_store_id=vector_store_id,
            file_id=file_id,
            api_base=api_base,
        )

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "complete_input_dict": request_params,
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            response = await async_httpx_client.delete(url=url, headers=headers, params=request_params, timeout=timeout)
        except Exception as e:
            raise self._handle_error(e=e, provider_config=vector_store_files_provider_config)

        return vector_store_files_provider_config.transform_delete_vector_store_file_response(response=response)

    def vector_store_file_delete_handler(
        self,
        *,
        vector_store_id: str,
        file_id: str,
        vector_store_files_provider_config: BaseVectorStoreFilesConfig,
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, str] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
    ) -> VectorStoreFileDeleteResponse | Coroutine[object, object, VectorStoreFileDeleteResponse]:
        if _is_async:
            return self.async_vector_store_file_delete_handler(
                vector_store_id=vector_store_id,
                file_id=file_id,
                vector_store_files_provider_config=vector_store_files_provider_config,
                custom_llm_provider=custom_llm_provider,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                timeout=timeout,
                client=client if isinstance(client, AsyncHTTPHandler) else None,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = vector_store_files_provider_config.validate_environment(
            headers=extra_headers or {}, litellm_params=litellm_params
        )
        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = vector_store_files_provider_config.get_complete_url(
            api_base=litellm_params.api_base,
            vector_store_id=vector_store_id,
            litellm_params=dict(litellm_params),
        )

        (
            url,
            request_params,
        ) = vector_store_files_provider_config.transform_delete_vector_store_file_request(
            vector_store_id=vector_store_id,
            file_id=file_id,
            api_base=api_base,
        )

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "complete_input_dict": request_params,
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            response: Final = sync_httpx_client.delete(url=url, headers=headers, params=request_params, timeout=timeout)
        except Exception as e:
            raise self._handle_error(e=e, provider_config=vector_store_files_provider_config)

        return vector_store_files_provider_config.transform_delete_vector_store_file_response(response=response)

    #####################################################################
    ################ Google GenAI GENERATE CONTENT HANDLER ###########################
    #####################################################################
    def generate_content_handler(
        self,
        model: str,
        contents: Any,
        generate_content_provider_config: BaseGoogleGenAIGenerateContentConfig,
        generate_content_config_dict: dict,
        tools: Any,
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        extra_body: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        _is_async: bool = False,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        stream: bool = False,
        litellm_metadata: dict[str, object] | None = None,
        system_instruction: object | None = None,
    ) -> Any:
        """
        Handles Google GenAI generate content requests.
        When _is_async=True, returns a coroutine instead of making the call directly.
        """
        from litellm.google_genai.streaming_iterator import (
            GoogleGenAIGenerateContentStreamingIterator,
        )

        if _is_async:
            return self.async_generate_content_handler(
                model=model,
                contents=contents,
                generate_content_provider_config=generate_content_provider_config,
                generate_content_config_dict=generate_content_config_dict,
                tools=tools,
                custom_llm_provider=custom_llm_provider,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                extra_body=extra_body,
                timeout=timeout,
                client=client if isinstance(client, AsyncHTTPHandler) else None,
                stream=stream,
                litellm_metadata=litellm_metadata,
                system_instruction=system_instruction,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        # Get headers and URL from the provider config
        (
            headers,
            api_base,
        ) = generate_content_provider_config.sync_get_auth_token_and_url(
            api_base=litellm_params.api_base,
            model=model,
            litellm_params=dict(litellm_params),
            stream=stream,
        )

        if extra_headers:
            headers.update(extra_headers)

        # Get the request body from the provider config
        data: Final = generate_content_provider_config.transform_generate_content_request(
            model=model,
            contents=contents,
            tools=tools,
            generate_content_config_dict=generate_content_config_dict,
            system_instruction=system_instruction,
        )

        if extra_body:
            data.update(extra_body)

        ## LOGGING
        logging_obj.pre_call(
            input=contents,
            api_key="",
            additional_args={
                "complete_input_dict": data,
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            if stream:
                response = sync_httpx_client.post(
                    url=api_base,
                    headers=headers,
                    json=data,
                    timeout=timeout,
                    stream=True,
                )
                # Return streaming iterator
                return GoogleGenAIGenerateContentStreamingIterator(
                    response=response,
                    model=model,
                    logging_obj=logging_obj,
                    generate_content_provider_config=generate_content_provider_config,
                    litellm_metadata=litellm_metadata or {},
                    custom_llm_provider=custom_llm_provider,
                    request_body=data,
                    hidden_params=_google_genai_streaming_hidden_params(
                        api_base=api_base,
                        litellm_params=litellm_params,
                        logging_obj=logging_obj,
                        response_headers=response.headers,
                    ),
                )
            else:
                response = sync_httpx_client.post(
                    url=api_base,
                    headers=headers,
                    json=data,
                    timeout=timeout,
                )
        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=generate_content_provider_config,
            )

        return generate_content_provider_config.transform_generate_content_response(
            model=model,
            raw_response=response,
            logging_obj=logging_obj,
        )

    async def async_generate_content_handler(
        self,
        model: str,
        contents: Any,
        generate_content_provider_config: BaseGoogleGenAIGenerateContentConfig,
        generate_content_config_dict: dict,
        tools: Any,
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        extra_body: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: AsyncHTTPHandler | None = None,
        stream: bool = False,
        litellm_metadata: dict[str, object] | None = None,
        system_instruction: object | None = None,
    ) -> Any:
        """
        Async version of the generate content handler.
        Uses async HTTP client to make requests.
        """
        from litellm.google_genai.streaming_iterator import (
            AsyncGoogleGenAIGenerateContentStreamingIterator,
        )

        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        # Get headers and URL from the provider config
        (
            headers,
            api_base,
        ) = await generate_content_provider_config.get_auth_token_and_url(
            model=model,
            litellm_params=dict(litellm_params),
            stream=stream,
            api_base=litellm_params.api_base,
        )

        if extra_headers:
            headers.update(extra_headers)

        # Get the request body from the provider config
        data: Final = generate_content_provider_config.transform_generate_content_request(
            model=model,
            contents=contents,
            tools=tools,
            generate_content_config_dict=generate_content_config_dict,
            system_instruction=system_instruction,
        )

        if extra_body:
            data.update(extra_body)

        ## LOGGING
        logging_obj.pre_call(
            input=contents,
            api_key="",
            additional_args={
                "complete_input_dict": data,
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            if stream:
                response = await async_httpx_client.post(
                    url=api_base,
                    headers=headers,
                    json=data,
                    timeout=timeout,
                    stream=True,
                )
                # Return async streaming iterator
                return AsyncGoogleGenAIGenerateContentStreamingIterator(
                    response=response,
                    model=model,
                    logging_obj=logging_obj,
                    generate_content_provider_config=generate_content_provider_config,
                    litellm_metadata=litellm_metadata or {},
                    custom_llm_provider=custom_llm_provider,
                    request_body=data,
                    hidden_params=_google_genai_streaming_hidden_params(
                        api_base=api_base,
                        litellm_params=litellm_params,
                        logging_obj=logging_obj,
                        response_headers=response.headers,
                    ),
                )
            else:
                response = await async_httpx_client.post(
                    url=api_base,
                    headers=headers,
                    json=data,
                    timeout=timeout,
                )
        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=generate_content_provider_config,
            )

        return generate_content_provider_config.transform_generate_content_response(
            model=model,
            raw_response=response,
            logging_obj=logging_obj,
        )

    #####################################################################
    ################ TEXT TO SPEECH HANDLER ###########################
    #####################################################################
    def text_to_speech_handler(
        self,
        model: str,
        input: str,
        voice: str | None,
        text_to_speech_provider_config: BaseTextToSpeechConfig,
        text_to_speech_optional_params: dict,
        custom_llm_provider: str,
        litellm_params: dict,
        logging_obj: LiteLLMLoggingObj,
        timeout: float | httpx.Timeout,
        extra_headers: dict[str, object] | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
    ) -> Union[
        "HttpxBinaryResponseContent",
        Coroutine[object, object, "HttpxBinaryResponseContent"],
    ]:
        """
        Handles text-to-speech requests.
        When _is_async=True, returns a coroutine instead of making the call directly.
        """
        if _is_async:
            return self.async_text_to_speech_handler(
                model=model,
                input=input,
                voice=voice,
                text_to_speech_provider_config=text_to_speech_provider_config,
                text_to_speech_optional_params=text_to_speech_optional_params,
                custom_llm_provider=custom_llm_provider,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                timeout=timeout,
                client=client if isinstance(client, AsyncHTTPHandler) else None,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = text_to_speech_provider_config.validate_environment(
            api_key=litellm_params.get("api_key"),
            headers=extra_headers or {},
            model=model,
            api_base=litellm_params.get("api_base"),
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = text_to_speech_provider_config.get_complete_url(
            model=model,
            api_base=litellm_params.get("api_base"),
            litellm_params=litellm_params,
        )

        request_data: Final = text_to_speech_provider_config.transform_text_to_speech_request(
            model=model,
            input=input,
            voice=voice,
            optional_params=text_to_speech_optional_params,
            litellm_params=litellm_params,
            headers=headers,
        )

        # Merge provider-specific headers
        if "headers" in request_data:
            headers.update(request_data["headers"])

        ## LOGGING
        logging_obj.pre_call(
            input=input,
            api_key="",
            additional_args={
                "complete_input_dict": request_data,
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            # Determine request body type and send appropriately
            if "dict_body" in request_data:
                response = sync_httpx_client.post(
                    url=api_base,
                    headers=headers,
                    json=request_data["dict_body"],
                    timeout=timeout,
                )
            elif "ssml_body" in request_data:
                response = sync_httpx_client.post(
                    url=api_base,
                    headers=headers,
                    data=request_data["ssml_body"],
                    timeout=timeout,
                )
            else:
                raise ValueError(
                    "No body found in request_data. Must provide one of: dict_body, ssml_body, text_body, binary_body"
                )

        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=text_to_speech_provider_config,
            )

        return text_to_speech_provider_config.transform_text_to_speech_response(
            model=model,
            raw_response=response,
            logging_obj=logging_obj,
        )

    async def async_text_to_speech_handler(
        self,
        model: str,
        input: str,
        voice: str | None,
        text_to_speech_provider_config: BaseTextToSpeechConfig,
        text_to_speech_optional_params: dict,
        custom_llm_provider: str,
        litellm_params: dict,
        logging_obj: LiteLLMLoggingObj,
        timeout: float | httpx.Timeout,
        extra_headers: dict[str, object] | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
    ) -> "HttpxBinaryResponseContent":
        """
        Async version of the text-to-speech handler.
        Uses async HTTP client to make requests.
        """
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = text_to_speech_provider_config.validate_environment(
            api_key=litellm_params.get("api_key"),
            headers=extra_headers or {},
            model=model,
            api_base=litellm_params.get("api_base"),
        )

        if extra_headers:
            headers.update(extra_headers)

        api_base: Final = text_to_speech_provider_config.get_complete_url(
            model=model,
            api_base=litellm_params.get("api_base"),
            litellm_params=litellm_params,
        )

        request_data: Final = text_to_speech_provider_config.transform_text_to_speech_request(
            model=model,
            input=input,
            voice=voice,
            optional_params=text_to_speech_optional_params,
            litellm_params=litellm_params,
            headers=headers,
        )

        # Merge provider-specific headers
        if "headers" in request_data:
            headers.update(request_data["headers"])

        ## LOGGING
        logging_obj.pre_call(
            input=input,
            api_key="",
            additional_args={
                "complete_input_dict": request_data,
                "api_base": api_base,
                "headers": headers,
            },
        )

        try:
            # Determine request body type and send appropriately
            if "dict_body" in request_data:
                response = await async_httpx_client.post(
                    url=api_base,
                    headers=headers,
                    json=request_data["dict_body"],
                    timeout=timeout,
                )
            elif "ssml_body" in request_data:
                response = await async_httpx_client.post(
                    url=api_base,
                    headers=headers,
                    data=request_data["ssml_body"],
                    timeout=timeout,
                )
            else:
                raise ValueError(
                    "No body found in request_data. Must provide one of: dict_body, ssml_body, text_body, binary_body"
                )

        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=text_to_speech_provider_config,
            )

        return text_to_speech_provider_config.transform_text_to_speech_response(
            model=model,
            raw_response=response,
            logging_obj=logging_obj,
        )

    #########################################################
    ########## SKILLS API HANDLERS ##########################
    #########################################################

    def _prepare_skill_multipart_request(
        self,
        request_body: dict,
        headers: dict,
    ) -> tuple[dict | None, list | None]:
        """
        Helper to prepare multipart/form-data request for skills API.

        Args:
            request_body: Request body containing files and other fields
            headers: Request headers

        Returns:
            Tuple of (data_dict, files_list) for multipart request, or (None, None) if no files
        """
        if "files" not in request_body or not request_body["files"]:
            return None, None

        # Remove content-type header if present - httpx will set it automatically for multipart
        headers.pop("content-type", None)

        # Prepare files for multipart upload
        files: Final = []
        for file_obj in request_body["files"]:
            files.append(("files[]", file_obj))

        # Prepare data (non-file fields)
        data: Final = {k: v for k, v in request_body.items() if k != "files"}

        return data, files

    def create_skill_handler(
        self,
        url: str,
        request_body: dict,
        skills_api_provider_config: "BaseSkillsAPIConfig",
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
        shared_session: Optional["ClientSession"] = None,
    ) -> Union["Skill", Coroutine[object, object, "Skill"]]:
        """Create a skill"""
        if _is_async:
            return self.async_create_skill_handler(
                url=url,
                request_body=request_body,
                skills_api_provider_config=skills_api_provider_config,
                custom_llm_provider=custom_llm_provider,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                timeout=timeout,
                client=client,
                shared_session=shared_session,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = extra_headers or {}

        logging_obj.pre_call(
            input=request_body.get("display_title", ""),
            api_key="",
            additional_args={
                "complete_input_dict": request_body,
                "api_base": url,
                "headers": headers,
            },
        )

        try:
            # Check if files are present - use multipart/form-data
            data, files = self._prepare_skill_multipart_request(request_body=request_body, headers=headers)

            if files is not None:
                response = sync_httpx_client.post(url=url, headers=headers, data=data, files=files, timeout=timeout)
            else:
                # No files - send as JSON
                response = sync_httpx_client.post(url=url, headers=headers, json=request_body, timeout=timeout)
        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=skills_api_provider_config,
            )

        return skills_api_provider_config.transform_create_skill_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    async def async_create_skill_handler(
        self,
        url: str,
        request_body: dict,
        skills_api_provider_config: "BaseSkillsAPIConfig",
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        shared_session: Optional["ClientSession"] = None,
    ) -> "Skill":
        """Async create a skill"""
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = extra_headers or {}

        logging_obj.pre_call(
            input=request_body.get("display_title", ""),
            api_key="",
            additional_args={
                "complete_input_dict": request_body,
                "api_base": url,
                "headers": headers,
            },
        )

        try:
            # Check if files are present - use multipart/form-data
            data, files = self._prepare_skill_multipart_request(request_body=request_body, headers=headers)

            if files is not None:
                response = await async_httpx_client.post(
                    url=url, headers=headers, data=data, files=files, timeout=timeout
                )
            else:
                # No files - send as JSON
                response = await async_httpx_client.post(url=url, headers=headers, json=request_body, timeout=timeout)
        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=skills_api_provider_config,
            )

        return skills_api_provider_config.transform_create_skill_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    def list_skills_handler(
        self,
        url: str,
        query_params: dict,
        skills_api_provider_config: "BaseSkillsAPIConfig",
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
        shared_session: Optional["ClientSession"] = None,
    ) -> Union["ListSkillsResponse", Coroutine[object, object, "ListSkillsResponse"]]:
        """List skills"""
        if _is_async:
            return self.async_list_skills_handler(
                url=url,
                query_params=query_params,
                skills_api_provider_config=skills_api_provider_config,
                custom_llm_provider=custom_llm_provider,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                timeout=timeout,
                client=client,
                shared_session=shared_session,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = extra_headers or {}

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "complete_input_dict": query_params,
                "api_base": url,
                "headers": headers,
            },
        )

        try:
            response: Final = sync_httpx_client.get(url=url, headers=headers, params=query_params)
        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=skills_api_provider_config,
            )

        return skills_api_provider_config.transform_list_skills_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    async def async_list_skills_handler(
        self,
        url: str,
        query_params: dict,
        skills_api_provider_config: "BaseSkillsAPIConfig",
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        shared_session: Optional["ClientSession"] = None,
    ) -> "ListSkillsResponse":
        """Async list skills"""
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = extra_headers or {}

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "complete_input_dict": query_params,
                "api_base": url,
                "headers": headers,
            },
        )

        try:
            response: Final = await async_httpx_client.get(url=url, headers=headers, params=query_params)
        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=skills_api_provider_config,
            )

        return skills_api_provider_config.transform_list_skills_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    def get_skill_handler(
        self,
        url: str,
        skills_api_provider_config: "BaseSkillsAPIConfig",
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
        shared_session: Optional["ClientSession"] = None,
    ) -> Union["Skill", Coroutine[object, object, "Skill"]]:
        """Get a skill"""
        if _is_async:
            return self.async_get_skill_handler(
                url=url,
                skills_api_provider_config=skills_api_provider_config,
                custom_llm_provider=custom_llm_provider,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                timeout=timeout,
                client=client,
                shared_session=shared_session,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = extra_headers or {}

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
            },
        )

        try:
            response: Final = sync_httpx_client.get(url=url, headers=headers)
        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=skills_api_provider_config,
            )

        return skills_api_provider_config.transform_get_skill_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    async def async_get_skill_handler(
        self,
        url: str,
        skills_api_provider_config: "BaseSkillsAPIConfig",
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        shared_session: Optional["ClientSession"] = None,
    ) -> "Skill":
        """Async get a skill"""
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = extra_headers or {}

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
            },
        )

        try:
            response: Final = await async_httpx_client.get(url=url, headers=headers)
        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=skills_api_provider_config,
            )

        return skills_api_provider_config.transform_get_skill_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    def delete_skill_handler(
        self,
        url: str,
        skills_api_provider_config: "BaseSkillsAPIConfig",
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
        shared_session: Optional["ClientSession"] = None,
    ) -> Union["DeleteSkillResponse", Coroutine[object, object, "DeleteSkillResponse"]]:
        """Delete a skill"""
        if _is_async:
            return self.async_delete_skill_handler(
                url=url,
                skills_api_provider_config=skills_api_provider_config,
                custom_llm_provider=custom_llm_provider,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                timeout=timeout,
                client=client,
                shared_session=shared_session,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = extra_headers or {}

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
            },
        )

        try:
            response: Final = sync_httpx_client.delete(url=url, headers=headers, timeout=timeout)
        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=skills_api_provider_config,
            )

        return skills_api_provider_config.transform_delete_skill_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    async def async_delete_skill_handler(
        self,
        url: str,
        skills_api_provider_config: "BaseSkillsAPIConfig",
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        shared_session: Optional["ClientSession"] = None,
    ) -> "DeleteSkillResponse":
        """Async delete a skill"""
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = extra_headers or {}

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
            },
        )

        try:
            response: Final = await async_httpx_client.delete(url=url, headers=headers, timeout=timeout)
        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=skills_api_provider_config,
            )

        return skills_api_provider_config.transform_delete_skill_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    # ===================================
    # Evals API Handlers
    # ===================================

    def create_eval_handler(
        self,
        url: str,
        request_body: dict,
        evals_api_provider_config: "BaseEvalsAPIConfig",
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
        shared_session: Optional["ClientSession"] = None,
    ) -> Union["Eval", Coroutine[object, object, "Eval"]]:
        """Create an eval"""
        if _is_async:
            return self.async_create_eval_handler(
                url=url,
                request_body=request_body,
                evals_api_provider_config=evals_api_provider_config,
                custom_llm_provider=custom_llm_provider,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                timeout=timeout,
                client=client,
                shared_session=shared_session,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = extra_headers or {}

        logging_obj.pre_call(
            input=request_body.get("display_name", ""),
            api_key="",
            additional_args={
                "complete_input_dict": request_body,
                "api_base": url,
                "headers": headers,
            },
        )

        try:
            response: Final = sync_httpx_client.post(url=url, headers=headers, json=request_body, timeout=timeout)
        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=evals_api_provider_config,
            )

        return evals_api_provider_config.transform_create_eval_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    async def async_create_eval_handler(
        self,
        url: str,
        request_body: dict,
        evals_api_provider_config: "BaseEvalsAPIConfig",
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        shared_session: Optional["ClientSession"] = None,
    ) -> "Eval":
        """Async create an eval"""
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = extra_headers or {}

        logging_obj.pre_call(
            input=request_body.get("name", ""),
            api_key="",
            additional_args={
                "complete_input_dict": request_body,
                "api_base": url,
                "headers": headers,
            },
        )

        try:
            response = await async_httpx_client.post(url=url, headers=headers, json=request_body, timeout=timeout)
        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=evals_api_provider_config,
            )

        return evals_api_provider_config.transform_create_eval_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    def list_evals_handler(
        self,
        url: str,
        query_params: dict,
        evals_api_provider_config: "BaseEvalsAPIConfig",
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
        shared_session: Optional["ClientSession"] = None,
    ) -> Union["ListEvalsResponse", Coroutine[object, object, "ListEvalsResponse"]]:
        """List evals"""
        if _is_async:
            return self.async_list_evals_handler(
                url=url,
                query_params=query_params,
                evals_api_provider_config=evals_api_provider_config,
                custom_llm_provider=custom_llm_provider,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                timeout=timeout,
                client=client,
                shared_session=shared_session,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = extra_headers or {}

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "complete_input_dict": query_params,
                "api_base": url,
                "headers": headers,
            },
        )

        try:
            response: Final = sync_httpx_client.get(url=url, headers=headers, params=query_params)
        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=evals_api_provider_config,
            )

        return evals_api_provider_config.transform_list_evals_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    async def async_list_evals_handler(
        self,
        url: str,
        query_params: dict,
        evals_api_provider_config: "BaseEvalsAPIConfig",
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        shared_session: Optional["ClientSession"] = None,
    ) -> "ListEvalsResponse":
        """Async list evals"""
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = extra_headers or {}

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "complete_input_dict": query_params,
                "api_base": url,
                "headers": headers,
            },
        )

        try:
            response: Final = await async_httpx_client.get(url=url, headers=headers, params=query_params)
        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=evals_api_provider_config,
            )

        return evals_api_provider_config.transform_list_evals_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    def get_eval_handler(
        self,
        url: str,
        evals_api_provider_config: "BaseEvalsAPIConfig",
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
        shared_session: Optional["ClientSession"] = None,
    ) -> Union["Eval", Coroutine[object, object, "Eval"]]:
        """Get an eval"""
        if _is_async:
            return self.async_get_eval_handler(
                url=url,
                evals_api_provider_config=evals_api_provider_config,
                custom_llm_provider=custom_llm_provider,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                timeout=timeout,
                client=client,
                shared_session=shared_session,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = extra_headers or {}

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
            },
        )

        try:
            response: Final = sync_httpx_client.get(url=url, headers=headers)
        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=evals_api_provider_config,
            )

        return evals_api_provider_config.transform_get_eval_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    async def async_get_eval_handler(
        self,
        url: str,
        evals_api_provider_config: "BaseEvalsAPIConfig",
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        shared_session: Optional["ClientSession"] = None,
    ) -> "Eval":
        """Async get an eval"""
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = extra_headers or {}

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
            },
        )

        try:
            response: Final = await async_httpx_client.get(url=url, headers=headers)
        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=evals_api_provider_config,
            )

        return evals_api_provider_config.transform_get_eval_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    def update_eval_handler(
        self,
        url: str,
        request_body: dict,
        evals_api_provider_config: "BaseEvalsAPIConfig",
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
        shared_session: Optional["ClientSession"] = None,
    ) -> Union["Eval", Coroutine[object, object, "Eval"]]:
        """Update an eval"""
        if _is_async:
            return self.async_update_eval_handler(
                url=url,
                request_body=request_body,
                evals_api_provider_config=evals_api_provider_config,
                custom_llm_provider=custom_llm_provider,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                timeout=timeout,
                client=client,
                shared_session=shared_session,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = extra_headers or {}

        logging_obj.pre_call(
            input=request_body.get("display_name", ""),
            api_key="",
            additional_args={
                "complete_input_dict": request_body,
                "api_base": url,
                "headers": headers,
            },
        )

        try:
            response: Final = sync_httpx_client.post(url=url, headers=headers, json=request_body, timeout=timeout)
        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=evals_api_provider_config,
            )

        return evals_api_provider_config.transform_update_eval_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    async def async_update_eval_handler(
        self,
        url: str,
        request_body: dict,
        evals_api_provider_config: "BaseEvalsAPIConfig",
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        shared_session: Optional["ClientSession"] = None,
    ) -> "Eval":
        """Async update an eval"""
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = extra_headers or {}

        logging_obj.pre_call(
            input=request_body.get("display_name", ""),
            api_key="",
            additional_args={
                "complete_input_dict": request_body,
                "api_base": url,
                "headers": headers,
            },
        )

        try:
            response = await async_httpx_client.post(url=url, headers=headers, json=request_body, timeout=timeout)
        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=evals_api_provider_config,
            )

        return evals_api_provider_config.transform_update_eval_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    def delete_eval_handler(
        self,
        url: str,
        evals_api_provider_config: "BaseEvalsAPIConfig",
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
        shared_session: Optional["ClientSession"] = None,
    ) -> Union["DeleteEvalResponse", Coroutine[object, object, "DeleteEvalResponse"]]:
        """Delete an eval"""
        if _is_async:
            return self.async_delete_eval_handler(
                url=url,
                evals_api_provider_config=evals_api_provider_config,
                custom_llm_provider=custom_llm_provider,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                timeout=timeout,
                client=client,
                shared_session=shared_session,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = extra_headers or {}

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
            },
        )

        try:
            response: Final = sync_httpx_client.delete(url=url, headers=headers, timeout=timeout)
        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=evals_api_provider_config,
            )

        return evals_api_provider_config.transform_delete_eval_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    async def async_delete_eval_handler(
        self,
        url: str,
        evals_api_provider_config: "BaseEvalsAPIConfig",
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        shared_session: Optional["ClientSession"] = None,
    ) -> "DeleteEvalResponse":
        """Async delete an eval"""
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = extra_headers or {}

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
            },
        )

        try:
            response: Final = await async_httpx_client.delete(url=url, headers=headers, timeout=timeout)
        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=evals_api_provider_config,
            )

        return evals_api_provider_config.transform_delete_eval_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    def cancel_eval_handler(
        self,
        url: str,
        evals_api_provider_config: "BaseEvalsAPIConfig",
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
        shared_session: Optional["ClientSession"] = None,
    ) -> Union["CancelEvalResponse", Coroutine[object, object, "CancelEvalResponse"]]:
        """Cancel an eval"""
        if _is_async:
            return self.async_cancel_eval_handler(
                url=url,
                evals_api_provider_config=evals_api_provider_config,
                custom_llm_provider=custom_llm_provider,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                timeout=timeout,
                client=client,
                shared_session=shared_session,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = extra_headers or {}

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
            },
        )

        try:
            response: Final = sync_httpx_client.post(url=url, headers=headers, json={}, timeout=timeout)
        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=evals_api_provider_config,
            )

        return evals_api_provider_config.transform_cancel_eval_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    async def async_cancel_eval_handler(
        self,
        url: str,
        evals_api_provider_config: "BaseEvalsAPIConfig",
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        shared_session: Optional["ClientSession"] = None,
    ) -> "CancelEvalResponse":
        """Async cancel an eval"""
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = extra_headers or {}

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
            },
        )

        try:
            response: Final = await async_httpx_client.post(url=url, headers=headers, json={}, timeout=timeout)
        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=evals_api_provider_config,
            )

        return evals_api_provider_config.transform_cancel_eval_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    # ===================================
    # Eval Runs API Handlers
    # ===================================

    def create_run_handler(
        self,
        url: str,
        request_body: dict,
        evals_api_provider_config: "BaseEvalsAPIConfig",
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
        shared_session: Optional["ClientSession"] = None,
    ) -> Union["Run", Coroutine[object, object, "Run"]]:
        """Create a run"""
        if _is_async:
            return self.async_create_run_handler(
                url=url,
                request_body=request_body,
                evals_api_provider_config=evals_api_provider_config,
                custom_llm_provider=custom_llm_provider,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                timeout=timeout,
                client=client,
                shared_session=shared_session,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = extra_headers or {}

        logging_obj.pre_call(
            input=request_body.get("name", ""),
            api_key="",
            additional_args={
                "complete_input_dict": request_body,
                "api_base": url,
                "headers": headers,
            },
        )

        try:
            response: Final = sync_httpx_client.post(url=url, headers=headers, json=request_body, timeout=timeout)
        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=evals_api_provider_config,
            )

        return evals_api_provider_config.transform_create_run_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    async def async_create_run_handler(
        self,
        url: str,
        request_body: dict,
        evals_api_provider_config: "BaseEvalsAPIConfig",
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        shared_session: Optional["ClientSession"] = None,
    ) -> "Run":
        """Async create a run"""
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = extra_headers or {}

        logging_obj.pre_call(
            input=request_body.get("name", ""),
            api_key="",
            additional_args={
                "complete_input_dict": request_body,
                "api_base": url,
                "headers": headers,
            },
        )

        try:
            response = await async_httpx_client.post(url=url, headers=headers, json=request_body, timeout=timeout)
        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=evals_api_provider_config,
            )

        return evals_api_provider_config.transform_create_run_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    def list_runs_handler(
        self,
        url: str,
        query_params: dict,
        evals_api_provider_config: "BaseEvalsAPIConfig",
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
        shared_session: Optional["ClientSession"] = None,
    ) -> Union["ListRunsResponse", Coroutine[object, object, "ListRunsResponse"]]:
        """List runs"""
        if _is_async:
            return self.async_list_runs_handler(
                url=url,
                query_params=query_params,
                evals_api_provider_config=evals_api_provider_config,
                custom_llm_provider=custom_llm_provider,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                timeout=timeout,
                client=client,
                shared_session=shared_session,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = extra_headers or {}

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
                "params": query_params,
            },
        )

        try:
            response: Final = sync_httpx_client.get(url=url, headers=headers, params=query_params)
        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=evals_api_provider_config,
            )

        return evals_api_provider_config.transform_list_runs_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    async def async_list_runs_handler(
        self,
        url: str,
        query_params: dict,
        evals_api_provider_config: "BaseEvalsAPIConfig",
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        shared_session: Optional["ClientSession"] = None,
    ) -> "ListRunsResponse":
        """Async list runs"""
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = extra_headers or {}

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
                "params": query_params,
            },
        )

        try:
            response: Final = await async_httpx_client.get(url=url, headers=headers, params=query_params)
        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=evals_api_provider_config,
            )

        return evals_api_provider_config.transform_list_runs_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    def get_run_handler(
        self,
        url: str,
        evals_api_provider_config: "BaseEvalsAPIConfig",
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
        shared_session: Optional["ClientSession"] = None,
    ) -> Union["Run", Coroutine[object, object, "Run"]]:
        """Get a run"""
        if _is_async:
            return self.async_get_run_handler(
                url=url,
                evals_api_provider_config=evals_api_provider_config,
                custom_llm_provider=custom_llm_provider,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                timeout=timeout,
                client=client,
                shared_session=shared_session,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = extra_headers or {}

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
            },
        )

        try:
            response: Final = sync_httpx_client.get(url=url, headers=headers)
        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=evals_api_provider_config,
            )

        return evals_api_provider_config.transform_get_run_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    async def async_get_run_handler(
        self,
        url: str,
        evals_api_provider_config: "BaseEvalsAPIConfig",
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        shared_session: Optional["ClientSession"] = None,
    ) -> "Run":
        """Async get a run"""
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = extra_headers or {}

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
            },
        )

        try:
            response: Final = await async_httpx_client.get(url=url, headers=headers)
        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=evals_api_provider_config,
            )

        return evals_api_provider_config.transform_get_run_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    def cancel_run_handler(
        self,
        url: str,
        evals_api_provider_config: "BaseEvalsAPIConfig",
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
        shared_session: Optional["ClientSession"] = None,
    ) -> Union["CancelRunResponse", Coroutine[object, object, "CancelRunResponse"]]:
        """Cancel a run"""
        if _is_async:
            return self.async_cancel_run_handler(
                url=url,
                evals_api_provider_config=evals_api_provider_config,
                custom_llm_provider=custom_llm_provider,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                timeout=timeout,
                client=client,
                shared_session=shared_session,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = extra_headers or {}

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
            },
        )

        try:
            response: Final = sync_httpx_client.post(url=url, headers=headers, json={}, timeout=timeout)
        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=evals_api_provider_config,
            )

        return evals_api_provider_config.transform_cancel_run_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    async def async_cancel_run_handler(
        self,
        url: str,
        evals_api_provider_config: "BaseEvalsAPIConfig",
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        shared_session: Optional["ClientSession"] = None,
    ) -> "CancelRunResponse":
        """Async cancel a run"""
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = extra_headers or {}

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
            },
        )

        try:
            response: Final = await async_httpx_client.post(url=url, headers=headers, json={}, timeout=timeout)
        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=evals_api_provider_config,
            )

        return evals_api_provider_config.transform_cancel_run_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    def delete_run_handler(
        self,
        url: str,
        evals_api_provider_config: "BaseEvalsAPIConfig",
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        _is_async: bool = False,
        shared_session: Optional["ClientSession"] = None,
    ) -> Union["RunDeleteResponse", Coroutine[object, object, "RunDeleteResponse"]]:
        """Delete a run"""
        if _is_async:
            return self.async_delete_run_handler(
                url=url,
                evals_api_provider_config=evals_api_provider_config,
                custom_llm_provider=custom_llm_provider,
                litellm_params=litellm_params,
                logging_obj=logging_obj,
                extra_headers=extra_headers,
                timeout=timeout,
                client=client,
                shared_session=shared_session,
            )

        if client is None or not isinstance(client, HTTPHandler):
            sync_httpx_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
        else:
            sync_httpx_client = client

        headers: Final = extra_headers or {}

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
            },
        )

        try:
            response: Final = sync_httpx_client.delete(url=url, headers=headers, timeout=timeout)
        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=evals_api_provider_config,
            )

        return evals_api_provider_config.transform_delete_run_response(
            raw_response=response,
            logging_obj=logging_obj,
        )

    async def async_delete_run_handler(
        self,
        url: str,
        evals_api_provider_config: "BaseEvalsAPIConfig",
        custom_llm_provider: str,
        litellm_params: GenericLiteLLMParams,
        logging_obj: LiteLLMLoggingObj,
        extra_headers: dict[str, object] | None = None,
        timeout: float | httpx.Timeout | None = None,
        client: HTTPHandler | AsyncHTTPHandler | None = None,
        shared_session: Optional["ClientSession"] = None,
    ) -> "RunDeleteResponse":
        """Async delete a run"""
        if client is None or not isinstance(client, AsyncHTTPHandler):
            async_httpx_client = get_async_httpx_client(
                llm_provider=litellm.LlmProviders(custom_llm_provider),
                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
            )
        else:
            async_httpx_client = client

        headers: Final = extra_headers or {}

        logging_obj.pre_call(
            input="",
            api_key="",
            additional_args={
                "api_base": url,
                "headers": headers,
            },
        )

        try:
            response: Final = await async_httpx_client.delete(url=url, headers=headers, timeout=timeout)
        except Exception as e:
            raise self._handle_error(
                e=e,
                provider_config=evals_api_provider_config,
            )

        return evals_api_provider_config.transform_delete_run_response(
            raw_response=response,
            logging_obj=logging_obj,
        )