""" Anthropic Skills API configuration and transformations """ from typing import Final import httpx from pydantic import TypeAdapter from litellm._logging import verbose_logger from litellm.litellm_core_utils.url_utils import encode_url_path_segment from litellm.llms.base_llm.skills.transformation import ( BaseSkillsAPIConfig, LiteLLMLoggingObj, ) from litellm.types.llms.anthropic_skills import ( CreateSkillRequest, DeleteSkillResponse, ListSkillsParams, ListSkillsResponse, Skill, ) from litellm.types.router import GenericLiteLLMParams from litellm.types.utils import LlmProviders _RAW_JSON_PAYLOAD: Final = TypeAdapter(object) class AnthropicSkillsConfig(BaseSkillsAPIConfig): """Anthropic-specific Skills API configuration""" @property def custom_llm_provider(self) -> LlmProviders: return LlmProviders.ANTHROPIC def validate_environment(self, headers: dict, litellm_params: GenericLiteLLMParams | None) -> dict: """Add Anthropic-specific headers""" from litellm.llms.anthropic.common_utils import AnthropicModelInfo # Get API key from litellm_params if available api_key = None api_base = None if litellm_params is not None: api_key = litellm_params.api_key api_base = litellm_params.api_base auth_header: Final = AnthropicModelInfo.get_auth_header(api_key, api_base) if auth_header is None: raise ValueError("ANTHROPIC_API_KEY or ANTHROPIC_AUTH_TOKEN is required for Skills API") headers.update(auth_header) headers["anthropic-version"] = "2023-06-01" # Add beta header for skills API from litellm.constants import ANTHROPIC_SKILLS_API_BETA_VERSION if "anthropic-beta" not in headers: headers["anthropic-beta"] = ANTHROPIC_SKILLS_API_BETA_VERSION elif isinstance(headers["anthropic-beta"], list): if ANTHROPIC_SKILLS_API_BETA_VERSION not in headers["anthropic-beta"]: headers["anthropic-beta"].append(ANTHROPIC_SKILLS_API_BETA_VERSION) elif isinstance(headers["anthropic-beta"], str): if ANTHROPIC_SKILLS_API_BETA_VERSION not in headers["anthropic-beta"]: headers["anthropic-beta"] = [ headers["anthropic-beta"], ANTHROPIC_SKILLS_API_BETA_VERSION, ] headers["content-type"] = "application/json" return headers def get_complete_url( self, api_base: str | None, endpoint: str, skill_id: str | None = None, ) -> str: """Get complete URL for Anthropic Skills API""" from litellm.llms.anthropic.common_utils import AnthropicModelInfo if api_base is None: api_base = AnthropicModelInfo.get_api_base() if skill_id: encoded_skill_id: Final = encode_url_path_segment(skill_id, field_name="skill_id") return f"{api_base}/v1/skills/{encoded_skill_id}" return f"{api_base}/v1/{endpoint}" def transform_create_skill_request( self, create_request: CreateSkillRequest, litellm_params: GenericLiteLLMParams, headers: dict, ) -> dict: """Transform create skill request for Anthropic""" verbose_logger.debug("Transforming create skill request: %s", create_request) # Anthropic expects the request body directly request_body: Final = {k: v for k, v in create_request.items() if v is not None} return request_body def transform_create_skill_response( self, raw_response: httpx.Response, logging_obj: LiteLLMLoggingObj, ) -> Skill: """Transform Anthropic response to Skill object""" response_json: Final = _RAW_JSON_PAYLOAD.validate_python(raw_response.json()) verbose_logger.debug("Transforming create skill response: %s", response_json) return Skill.model_validate(response_json) def transform_list_skills_request( self, list_params: ListSkillsParams, litellm_params: GenericLiteLLMParams, headers: dict, ) -> tuple[str, dict]: """Transform list skills request for Anthropic""" from litellm.llms.anthropic.common_utils import AnthropicModelInfo api_base: Final = AnthropicModelInfo.get_api_base(litellm_params.api_base if litellm_params else None) url: Final = self.get_complete_url(api_base=api_base, endpoint="skills") # Build query parameters limit: Final = list_params.get("limit") page: Final = list_params.get("page") source: Final = list_params.get("source") query_params: Final[dict[str, int | str]] = { key: value for key, value in (("limit", limit), ("page", page), ("source", source)) if value } verbose_logger.debug( "List skills request made to Anthropic Skills endpoint with params: %s", query_params, ) return url, query_params def transform_list_skills_response( self, raw_response: httpx.Response, logging_obj: LiteLLMLoggingObj, ) -> ListSkillsResponse: """Transform Anthropic response to ListSkillsResponse""" response_json: Final = _RAW_JSON_PAYLOAD.validate_python(raw_response.json()) verbose_logger.debug("Transforming list skills response: %s", response_json) return ListSkillsResponse.model_validate(response_json) def transform_get_skill_request( self, skill_id: str, api_base: str, litellm_params: GenericLiteLLMParams, headers: dict, ) -> tuple[str, dict]: """Transform get skill request for Anthropic""" url: Final = self.get_complete_url(api_base=api_base, endpoint="skills", skill_id=skill_id) verbose_logger.debug("Get skill request - URL: %s", url) return url, headers def transform_get_skill_response( self, raw_response: httpx.Response, logging_obj: LiteLLMLoggingObj, ) -> Skill: """Transform Anthropic response to Skill object""" response_json: Final = _RAW_JSON_PAYLOAD.validate_python(raw_response.json()) verbose_logger.debug("Transforming get skill response: %s", response_json) return Skill.model_validate(response_json) def transform_delete_skill_request( self, skill_id: str, api_base: str, litellm_params: GenericLiteLLMParams, headers: dict, ) -> tuple[str, dict]: """Transform delete skill request for Anthropic""" url: Final = self.get_complete_url(api_base=api_base, endpoint="skills", skill_id=skill_id) verbose_logger.debug("Delete skill request - URL: %s", url) return url, headers def transform_delete_skill_response( self, raw_response: httpx.Response, logging_obj: LiteLLMLoggingObj, ) -> DeleteSkillResponse: """Transform Anthropic response to DeleteSkillResponse""" response_json: Final = _RAW_JSON_PAYLOAD.validate_python(raw_response.json()) verbose_logger.debug("Transforming delete skill response: %s", response_json) return DeleteSkillResponse.model_validate(response_json)