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Same trust rules as ``get_configured_s3_bucket_name``: only the immutable credential snapshot or the environment, never a request param. rAWS_S3_OUTPUT_BUCKET_NAMEc3&K|] }|s| ywrEr`).0buckets rG z1get_configured_s3_bucket_names..s(fF_e(fs) rrrrrtuplerFfromkeysrr)rtrusted input_bucket output_bucketbucketss rGget_configured_s3_bucket_namesrst3>BG!00SBII>R4SL"88bBIIFa[(ffgG 233 NrIs3_uriconfigured_bucket_namesallow_legacy_cloud_file_idscdtdtttfffd }|ddD]$}tt5||cdddcS||dS#1swY;xYw)Nconfigured_bucket_namerCc,td|tS)Nr)rschemerallowed_object_prefixesr)r$r)rrrs rGvalidate_againstzF_validate_file_id_against_configured_buckets..validate_againsts-#9$?(C   rI)r\rrr)rrrrcandidate_bucket_names` ` rG,_validate_file_id_against_configured_bucketsrsu   sCx "9"!=; j ! ;#$9: ; ;; 3B7 88 ; ;s AA# raw_responsec|jt}t|tr|S|jjdd}|j r t|SdS)z S3 answers PutObject with an empty body, so the stored object size comes from the signed request recorded by `transform_create_file_request`, not the response headers. zContent-Length0r)rrArr^headersisdigit)rr uploaded_sizeresponse_content_lengths rG_uploaded_object_sizers] *--.IJM-%%1%9%9%=%=>NPS%T+B+J+J+L3& 'SRSSrIceZdZdZfdZedefdZedefdZ dQde ee fded e e d ed e ee fd edzd edzdefdZdedefdZdeedefdZdededefdZd edzd edzded ed ededefdZdede efdZded edededef dZdZdZdZdZ e!d ede"fd!Z#d"Z$d#Z%d$Z&e!dedefd%Z'e!d&ed'ededzfd(Z(e!dRd)e)dzdedefd*Z*d+e+dedeee ffd,Z,e!d+e+de-ee ffd-Z.e!d+e+de-ee ffd.Z/e!d+e+d/e"de-ee ffd0Z0 dSd+e-ee1fded1edzdeee ffd2Z2d3ed4ede3ee4dzffd5Z5 dRdeed4ede e6fd6Z7ded7ed ed ede8ezezf d8Z9 dSd9ed ed ed:edzde3eeff d;Z:def d@Z?dAedBe@deeAzdeBfdCZCdDed ed ede3eeffdEZDd>eEjxd?e=d ede>fdFZFdDed ed ede3eeffdGZGd>eEjxd?e=d edeHfdHZIdedzd ed ede3eeffdIZJd>eEjxd?e=d ede e>fdJZKdKeLd e-ee fd e ee fde3eeeefffdLZMd edMedNeNdeeeffdOZOd>eEjxd?e=d edePfdPZQxZRS)TBedrockFilesConfigzT Config for Bedrock Files - handles S3 uploads for Bedrock batch processing c@t|_t| yrE)BedrockJsonlFilesTransformationjsonl_transformationsuper__init__)self __class__s rGrzBedrockFilesConfig.__init__ s$C$E! rIrCc"tjSrE)r6BEDROCKrs rGrLz&BedrockFilesConfig.custom_llm_providers###rIcy)zO Bedrock files are uploaded to S3, which requires PUT requests PUTr`rs rGfile_upload_http_methodz*BedrockFilesConfig.file_upload_http_methods rINrrJmessagesoptional_paramsrapi_keyapi_baseci}|j||jtd} t| tr|j| |SrE)rpopr?rr) rrrJrrrrrresultsigned_headerss rGvalidate_environmentz'BedrockFilesConfig.validate_environmentsD,. g . 2 23NPT U ng . 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Precedence (strict - any recognized `url` short-circuits): 1. A `url` matching a supported endpoint wins. Authoritative per the OpenAI Batch API spec, which requires it on every record. 2. Any other non-empty `url` -> chat. We trust the caller's explicit signal rather than re-deriving it from the body, and an unexpectedly-shaped body fails cleanly inside the chat transformer instead of being silently misrouted. 3. `url` missing/empty -> fall back to body shape. `messages` wins over the other keys so a malformed record carrying several of them keeps its conversation instead of having it dropped, and a bare `input` stays an embedding for backwards compatibility (that ambiguity with `/v1/responses` is only resolvable from `url`). rerrfrrVrW) rrOPENAI_EMBEDDINGS_URLr* EMBEDDINGOPENAI_TEXT_COMPLETIONS_URLTEXT_COMPLETIONOPENAI_RESPONSES_URL RESPONSESCHATrr)r.rfs rG_classify_batch_recordz)BedrockFilesConfig._classify_batch_records&"%%e,9#99-777?#??-===8#88-777-222*--f5$().. .  ).. . t )99 9 d?)33 3%***rItitan_v2ztitan-embed-text-v2bedrock_invocation_schemacNtj|tj}||tjk(S|j }|j d}tj }|j|}|dkry|t|z}|t|k(xs||dvS)a True iff `model` refers to Amazon Titan Text Embeddings V2. Resolution order: 1. `model_prices_and_context_window.json` via `get_model_info`. The Titan v2 registry entry carries an explicit `provider_specific_entry.bedrock_invocation_schema` discriminator (`"titan_v2"`). When the registry resolves the id we trust that field as the source of truth - no hardcoded model-id comparison needed. 2. Substring fallback (`titan-embed-text-v2` followed by `:`, `/`, or end-of-string) for ids the registry can't normalize. This catches cross-region inference profile prefixes (`us.amazon.titan-embed-text-v2:0`) and Bedrock ARN forms; the marker boundary check rejects lookalikes like `titan-embed-text-v20` or `titan-embed-text-v2-experimental`. Tolerant of common id shapes: - "amazon.titan-embed-text-v2:0" - "bedrock/amazon.titan-embed-text-v2:0" - "us.amazon.titan-embed-text-v2:0" (cross-region inference profile) - ARN forms ending in ".../amazon.titan-embed-text-v2:0" rrF)rr) r_lookup_provider_specific_field _BEDROCK_INVOCATION_SCHEMA_FIELD_TITAN_V2_INVOCATION_SCHEMAlowerr_TITAN_V2_EMBED_MODEL_MARKERfindr)rJregistry_schema normalizedmarkeridxends rG_is_titan_v2_embed_modelz+BedrockFilesConfig._is_titan_v2_embed_models:"4!S!S %FF"   &"&8&T&TT T[[] ,,Z8 *GG__V, 73v;&c*o%FCJ)FFrImodel_idfieldc ddlm}||}t|tsy|j d}t|tsy|j |}t|t r|r|SdS#t$rYywxYw)aw Read a nested string field from the registry entry's `provider_specific_entry` dict via `litellm.get_model_info`. Returns the field's string value when: - the registry resolves `model_id`, - the entry exposes `provider_specific_entry` as a dict, and - that dict has `field` mapped to a non-empty string. Otherwise returns `None`. Isolating this means feature detectors (Titan v2 today, future Cohere Embed / Nova Multimodal branches) share one defensive try/except shape instead of duplicating it. The `None` return covers every realistic failure mode: `get_model_info` raises (cross-region profile prefixes, Bedrock ARN forms, unreleased models), returns a non-dict, has no `provider_specific_entry`, or the requested field is missing / non-string / empty. r)get_model_infoNprovider_specific_entry)litellmrJrMrrFrr\)rGrHrJinfoprovider_specificrs rGr;z2BedrockFilesConfig._lookup_provider_specific_field-s{(  .(2D$%#'88,E#F+T2(,,U3"5#.5uBdB  sA** A65A6 raw_inputc\|td|t|tr/t|dk(r|d}ntdt|d|d|}t|ttfrt d|dt|t s%td t|jd |d |S) a Normalize an OpenAI /v1/embeddings `input` field into the single string that Bedrock Titan v2 InvokeModel expects in `inputText`. Accepts: a string, or a single-element list containing one string. Rejects (with actionable messages): - None / missing -> ValueError - Multi-element string lists -> ValueError, prompts caller to emit one JSONL line per input - Pre-tokenized inputs (List[int], List[List[int]]) -> NotImplementedError - Any other type -> ValueError Extracted so the validation can be exercised in isolation and so future embedding-provider branches (Titan G1, Cohere) can reuse it without duplicating the type-shaping logic. z@Embedding batch record is missing required `input` field: model=rrzMBedrock batch embedding requires one input per JSONL record. Got a list with z items for model=z/; emit one JSONL line per input string instead.zpBedrock Titan v2 batch embedding does not support pre-tokenized integer inputs. Pass `input` as a string (model=z).zaBedrock batch embedding `input` must be a string (or a single-element list of strings). Got type z for model=r) rrlistrr^NotImplementedErrorr\typerY)rOrJ candidates rG!_coerce_embedding_input_to_stringz4BedrockFilesConfig._coerce_embedding_input_to_stringOs$  _`e_fgh h i &9~"%aL  /9~&&7w?;;"I i$ -%$  )S)= ?++,KwaA  rIopenai_request_bodycZddlm}|j|std|d|j |j d|}|j Dcic] \}}|dvs ||}}}|}|j|i} t|j|| Scc}}w) a Transform an OpenAI /v1/embeddings request body into the Bedrock InvokeModel `modelInput` for embedding models that AWS supports via batch inference (CreateModelInvocationJob). Currently routes Amazon Titan Text Embeddings V2 only; other embedding providers (Titan G1, Titan Multimodal, Cohere Embed, Nova Multimodal Embeddings) raise NotImplementedError until they get a dedicated branch. Splitting them keeps PR scope tight and lets each model's request schema be exercised by its own tests. AWS docs (Titan v2 InvokeModel body): https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-titan-embed-text.html r)AmazonTitanV2ConfigzBedrock batch embedding currently supports only Amazon Titan Text Embeddings V2 (model id contains 'titan-embed-text-v2'). Got model=zL. Track other embedding models in https://github.com/BerriAI/litellm/issues.rW)rJrJrW)r)r)rWinference_params) 9litellm.llms.bedrock.embed.amazon_titan_v2_transformationrXrFrRrUrrBr,rF_transform_request) rrVrJrX input_textkvr) titan_configrZs rG'_map_openai_embedding_to_bedrock_paramsz:BedrockFilesConfig._map_openai_embedding_to_bedrock_paramss& ,,U3 &55:I>QQ !BBCVCZCZ[bCckpBq 7J6O6O6Q$qdaUV^pUpQT$q$q13 "."@"@1#A# L33*Wg3hii %rs  B')B'c |jd}|td|jddttd|j Ddt |ffS)aE Rewrite an OpenAI `/v1/completions` batch body as a Chat Completions body. Bedrock batch `modelInput` is the model's InvokeModel/Converse body, and no Bedrock batch model takes a bare `prompt`, so the wrapping that `litellm.text_completion` does in real time has to happen here too. rVzKBatch record for /v1/completions is missing required `prompt` field: model=rJrc36K|]\}}|dk7s ||fyw)rVNr`rkeyrs rGrzRBedrockFilesConfig._transform_text_completion_body_to_chat_body..s_*#usV^#u_s  r)rrrHr rBr&)rVrVs rG,_transform_text_completion_body_to_chat_bodyz?BedrockFilesConfig._transform_text_completion_body_to_chat_bodys~,//9 >,00"=>@  _0C0I0I0K_@HIK   rIc ddlm}|jd}|td|jdd|j |jddt j |tj td|jD|jd }td |jDS) a  Rewrite an OpenAI `/v1/responses` batch body as a Chat Completions body. Delegates to the same Responses-to-Chat bridge the real-time path uses for providers without a native Responses API (which is every Bedrock model), so `input`, `instructions`, `max_output_tokens` and the tool params translate identically in batch and real time. The bridge always emits a `tools` key; an empty one is dropped rather than shipped as an empty array inside `modelInput`. r) LiteLLMCompletionResponsesConfigrWzHBatch record for /v1/responses is missing required `input` field: model=rJrc34K|]\}}|dvs ||fyw)rYNr`rds rGrzLBedrockFilesConfig._transform_responses_body_to_chat_body..s&$)3eVYasVse $s  rX)rJrWresponses_api_requestrXc3:K|]\}}|dk7s|s||fyw)toolsNr`rds rGrzLBedrockFilesConfig._transform_responses_body_to_chat_body..s$k USVZaSaejU|ks ) Blitellm.responses.litellm_completion_transformation.transformationrhrr:transform_responses_api_request_to_chat_completion_requestrqvalidate_pythonrsrHrB)rVrhresponses_input chat_bodys rG&_transform_responses_body_to_chat_bodyz9BedrockFilesConfig._transform_responses_body_to_chat_bodys "5!8!8!A  ",00"=>@  - g g)--gr:.0@@Q&@&B&R&R#$7J7P7P7R$' -00< h  kioo>OkkkrI record_kindc|xtjk(rtj|Sxtjk(rtj |Sxtj k(r|Stjk(r tdy)z Normalize a non-embedding batch body to the Chat Completions shape the per-provider Bedrock transformations expect. z@Embedding batch records do not have a chat-completion equivalentN) r*r3rrfr5rrr6r1r)rVrss rG"_transform_batch_body_to_chat_bodyz5BedrockFilesConfig._transform_batch_body_to_chat_bodyso7'77)VVWjkk1'11)PPQdee,',,**'11 !cdd2rIprovidercddlm}|jdg}|jDcic] \}}|dvs ||}}}||jk(r8ddlm} | } | ji||d} | j||| iiS||jvr8dd l m } | } | j|i|d} | j||| iiSd|i|Scc}}w) a5 Transform OpenAI request body to Bedrock-compatible modelInput parameters using existing transformation logic. Routes to the correct per-provider transformation so that the resulting dict matches the InvokeModel body that Bedrock expects for batch inference. r)r6r)rJr)AmazonAnthropicClaudeConfigF)r)rrJr*)rJrrrr)AmazonConverseConfig) litellm.types.utilsr6rrB ANTHROPICQlitellm.llms.bedrock.chat.invoke_transformations.anthropic_claude3_transformationrxr,transform_requestCONVERSE_INVOKE_PROVIDERS1litellm.llms.bedrock.chat.converse_transformationry)rrVrJrvr6rr^r_rrxconfig mapped_paramsryconverse_configs rG_map_openai_to_bedrock_paramsz0BedrockFilesConfig._map_openai_to_bedrock_paramss8 5-11*bA3F3L3L3N!q41aRS[pRp!Q$!q!q |-- - 89F"44#% /! 5M ++! -! ,  t55 5 &:%;O+==#2 "! >M #44! -! 5     a"rs CC record_model target_modelc|jt|}||s||fS|jt|}|||fS||fSrE)get_bedrock_invoke_providerrR)rrrrecord_providertarget_providers rG(_resolve_batch_record_model_and_providerz;BedrockFilesConfig._resolve_batch_record_model_and_providerLsa "&!A!AB[\hBi!j  &l0 0!%!A!AB[\hBi!j  "0 0_,,rIc ddl}g}t|D]\}}|jdi}|jdd}|jj||} |j | |\} } |j |} | t jur|j|| } n$|j|j|| | | } |jd d t|jd }|| d }|j||S) aI Transforms OpenAI JSONL content to Bedrock batch format Bedrock batch format: { "recordId": "alphanumeric string", "modelInput": {JSON body} } Example: { "recordId": "CALL0000001", "modelInput": { "anthropic_version": "bedrock-2023-05-31", "max_tokens": 1024, "messages": [ { "role": "user", "content": [{"type": "text", "text": "Hello"}] } ] } } rNrfrJr)rr)rVrJ)rVrJrvrdCALL)rirj)rL enumeratermodel_alias_maprr7r*r1rarrur\zfillappend)rrrrLbedrock_jsonl_contentrD_openai_jsonl_content openai_bodyrresolved_modelmodel_for_transformrvrs model_input record_idbedrock_records rG8_transform_openai_jsonl_content_to_bedrock_jsonl_contentzKBedrockFilesConfig._transform_openai_jsonl_content_to_bedrock_jsonl_contentYs;. ')*34H*I 9 &C&/33FB?K&??7B7L$4488|TN,0,Y,Y+,-Z- ) 556KLK4>>>"JJ(3;NK #@@(,(O(OP[]h(i-%A .11+c#hnnUVFWEX?YZI*3;ON ! ( ( 8= 9>%$rIcreate_file_datac |jd}| tdt|}|jd}| tdtj||r|j |}|j D cgc](} | jstj| *} } |jd} |xst| tr| nd} |j| | } d jd | D}n@t|tr|jd }nt|tr|}n td |j!dd||||}t#||}|jdxs|jd}|ri|d|in|}|j%|||t'||\}}||d<t)|j+d }||t,<d|||xs|dScc} w)z Transform file request and return a pre-signed request for S3. This keeps the HTTP handler clean by doing all the signing here. rNrrr )rr rJr)r c3FK|]}tj|ywrErdumpsritems rGrzCBedrockFilesConfig.transform_create_file_request..s$X$TZZ%5$X!rzUnsupported file content type)rrrJrrrrr|)rr)rrrs3_encryption_key_id upload_urlr)methodrerr)rrr%ris_batch_jsonl_filerrrrrrr\rjoinrrr&r<_sign_s3_requestr=rencoderA)rrJrrrr$r roriginal_file_contentrrlitellm_params_modelrrrr merged_paramsrr"r signed_bodyupload_content_lengths rGtransform_create_file_requestz0BedrockFilesConfig.transform_create_file_requests>,//7  /0 0%6y%A-@-D-DY-O# & .78 8  , ,- 3 ,0+M+MNi+j !AVAaAaAc#tgkgqgqgsDJJt$4#t #t*8*<*+>w+G'H6K23%/<   e$us G/G/rrc  ddl}ddl}ddlm}ddlm}|j|d} |j|jd|jd |jd | |jd |jd |jd |jd|jd } |j|jdj} |rtd|dn ti} td| ddd| } |jd||| }|j}||j |j"|j$|j&}|j)| }|| d|j+||j$}t-|t.r|j1d}n||}t3|j&|fS#t $r t dwxYw)z Sign S3 PUT request using the same proven logic as S3Logger. Reuses the exact pattern from litellm/integrations/s3_v2.py rN S3SigV4Auth AWSRequest7Missing boto3 to call bedrock. Run 'pip install boto3'.rrrJryrzr{r}r~rrr ryrzr{r|r}r~rrrrzaws:kms)zx-amz-server-side-encryptionz+x-amz-server-side-encryption-aws-kms-key-idzapplication/jsonenz0private, immutable, max-age=31536000, s-maxage=0)z Content-Typex-amz-content-sha256zContent-Languagez Cache-Controlr)rr)rrerr)r|s3)hashlibrequests botocore.authrbotocore.awsrequestr ImportErrorr get_credentialsrsha256r hexdigestr Requestpreparerrerfr)get_aws_region_name_for_non_llm_api_callsadd_authrrrrF)rrrrrrrrrr| credentials content_hash sse_headersrequest_headersreqprepped aws_requestsigning_regionrs rGrz#BedrockFilesConfig._sign_s3_requests Y   1 6 "&!:!:?bd!:!e!11-112EF"1"5"56M"N-112EF+,001CD,001CD)--o>#2#6#67O#P,001CD2  &nnW^^G-DEOOQ $ 4=CW ""% "2 2(4$(!S     " %%eXG_%](>> OO  !% N N_n N oK~6?? L"&& k5 )%,,W5K  !KK''(+55C YWX X Ys G##G8 https_urlc$ddl}d}d}|j||}|j||}|r(|j\}}} t| } d|d| } n|r(|j\}}} t| } d|d| } nsddlm} | |} | j jdjdd} t| d k\r| d| d} }t| } d|d| } ntd |d| vr| jdd n| }| |fS) a Convert HTTPS S3 URL to s3:// URI format. Args: https_url: HTTPS S3 URL (e.g., "https://s3.us-west-2.amazonaws.com/bucket/key") Returns: Tuple of (s3_uri, filename) Example: Input: "https://s3.us-west-2.amazonaws.com/litellm-proxy/file.jsonl" Output: ("s3://litellm-proxy/file.jsonl", "file.jsonl") rNz0https://s3\.([^.]+)\.amazonaws\.com/([^/]+)/(.+)z1https://([^.]+)\.s3\.([^.]+)\.amazonaws\.com/(.+)rr)urlparserr9zUnable to parse S3 URL: r) rematchgroupsr urllib.parserpathlstriprrr)rrrpattern1pattern2match1match2regionrrerrparsed path_partsrs rG_convert_https_url_to_s3_uriz/BedrockFilesConfig._convert_https_url_to_s3_uri<s6  NN9595 "(--/ FFC#,CVHAcU+F "(--/ FFC#,CVHAcU+F .$Y/F & 2 23 7 = =c1 EJ:!#(mZ]cl #/ #;I;!GHH14s #))C.,xrIr logging_objc |jd}d}d}|r|j|\}}td||tt jdt ||dS)zP Transform S3 File upload response into OpenAI-style FileObject rrruploaded)rrrr idr created_atstatusrr_)rrr1r^timer)rrJrrrrrrs rGtransform_create_file_responsez1BedrockFilesConfig.transform_create_file_responsersk+..|<   $ A A* M GX499;''~T`a  rI error_message status_codect|||S)Nrmessager)r;)rrrrs rGget_error_classz"BedrockFilesConfig.get_error_classs ]T[\\rIrctdNz2BedrockFilesConfig does not support file retrievalrRrrrrs rGtransform_retrieve_file_requestz2BedrockFilesConfig.transform_retrieve_file_request ""VWWrIctdrrrrrrs rG transform_retrieve_file_responsez3BedrockFilesConfig.transform_retrieve_file_responserrIctdNz1BedrockFilesConfig does not support file deletionrrs rGtransform_delete_file_requestz0BedrockFilesConfig.transform_delete_file_request ""UVVrIctdrrrs rGtransform_delete_file_responsez1BedrockFilesConfig.transform_delete_file_responserrIctdNz0BedrockFilesConfig does not support file listingr)rr rrs rGtransform_list_files_requestz/BedrockFilesConfig.transform_list_files_request ""TUUrIctdrrrs rGtransform_list_files_responsez0BedrockFilesConfig.transform_list_files_responserrIfile_content_requestc.|jd}|s tdt|}t|t |t |\}}i}|j ||j |tj|} | jxs | j} d| i} |j| d} | jxsd| dt| jd } | d |d t|}|j!|| | |t"<|ifS) a) Build a SigV4-signed S3 GetObject request for a Bedrock batch file. Bedrock batch file ids are `s3://bucket/key` URIs (or unified ids that decode to one); the bucket and key are validated against the server-configured bucket before any request is signed. rz6file_id is required for Bedrock file content retrieval)rrrr|rrrrr)rr|r")rrrrrr"rrurrr|r rrr!r _sign_s3_get_requestr?)rrrrrrr object_keyrr"region_preference region_paramsr|rres rGtransform_file_content_requestz1BedrockFilesConfig.transform_file_content_requests?.11)<UV V3G<"N$B>$R(J>(Z#  Z35 ^,_- 7 F F} U#1#@#@#bNDbDb7HJ[6\ !%!:!:=`b!:!c  * * s O;LAN`apNqMr.s &+ ((+a8TU_8`7ab6:6O6O+)7P7 23 BwrIr|r"c  ddl}ddlm}ddlm}|j |j|j|j||j|j|j|j|j }|jdj!}|d|d |i } ||d |} | j#| t%| j&S#t $r t dwxYw) zY SigV4-sign an S3 GetObject request, mirroring `_sign_s3_request` (PUT). rNrrrrrIGETr)rrerr)rrrrrrrryrzr{r}r~rrrrrrrFr) rrr|r"rrrrempty_body_hashrauths rGrz'BedrockFilesConfig._sign_s3_get_requests Y  1 6"11,>>"0"F"F,>>++<<+<<(66#1#H#H+<<2  ")!4!>!>!@'+_= "+t_E k"K''((/ YWX X Ys CC-c|jdk\r,t|j|j|jt |S)Nir)response)rr;textrr/rs rGtransform_file_content_responsez2BedrockFilesConfig.transform_file_content_responsesG  # #s *(44$))$,,  *<@@rI)NN)rrE)SrYrZr[rrpropertyr6rLr\rrr_rQr+rFrr.rrrcr r5rr,r&r0r(boolr,r~r0r2r4 staticmethodr*r7r=r?r<rFr;rSrUrUrarrfrrrur rrrrrhrrrrrrr)r1rr^rr'rrhttpxrrrrrrr-r rurr/r __classcell__)rs@rGrrs-$\$$##V ,'(    'sF{3 t* $##s#J&'9: $ 3D s WZ 4)H*)Ht)H )H  )H  )H )H )HV>c9d      !* -"3*'+4F'+Ka'+'+\#- $9 (C$*G*G*G*GXC#CcCcDjCCB55ID5P5Y\5fi55n.j3.j.j c6k  .j` 3 f   .!lDZ!l_fgjlrgr_s!l!lFe3e+e f ee, $ D $S#X.D D * D c6k  D L - - - s4t;; < -WY9%$,-?$@9%PS9% ! "9%vR R ,R  R  R t  R r,0 R6R6R6 R6 "Dj R6 tSy  R6h4 c4 eCHo4 l Tz  '      8]S]s]TT[^]`p]XXX X sDy  XXnnX'X X  XWWW W sDy  WWnnW'W W  WVtVV V sDy  VVnnV'V V   V/0/!f-/'sF{3 / sDcN" # /b%)%)%)0 %) c3h %)N Ann A' A A $ ArIrceZdZdZ d dedzdeeeffdZdee fdZ dee defdZ dedefd Z d e d edefd Zy)rz` Transforms OpenAI /v1/files/* requests to Bedrock S3 file uploads for batch processing NrrCcH| td|j|}|jDcgc](}|jst j |*}}|j |}djd|D}|j|}||fScc}w)zP Transforms OpenAI FileContentRequest to Bedrock S3 file format zcontents of file are Nonerc3FK|]}tj|ywrErrs rGrzhBedrockJsonlFilesTransformation.transform_openai_file_content_to_bedrock_file_content..<s/cT 40@/cr)r) rrrrrrrr_get_s3_object_name)rrrrrrbedrock_jsonl_stringrs rG5transform_openai_file_content_to_bedrock_file_contentzUBedrockJsonlFilesTransformation.transform_openai_file_content_to_bedrock_file_content-s  &89 9"@@ATU EQD[D[D]&nDaeakakamtzz$'7&n&n $ ] ]^r s&*ii/cMb/c&c!55K_5` #[00 'os BBrc8t}|j|S)zO Delegate to the main BedrockFilesConfig transformation method )rr)rrrs rGrzXBedrockJsonlFilesTransformation._transform_openai_jsonl_content_to_bedrock_jsonl_content@s +,NNOcddrIc|djdijdd}|jd}t|jddd}t|dt j d }|S) z Gets a unique S3 object name for the Bedrock batch processing job named as: litellm-bedrock-files-{model}-{uuid} rrfrJrrrrrrrrs rGrz3BedrockJsonlFilesTransformation._get_s3_object_nameIsu&a(,,VR8<r=s GG"33 #177&+>-G   G>   NM*%gg &>U=&AU@)8E#v+$67)GCK Th T[^ T`A_`AF!k k rI