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Support aws_session_token for bedrock client. https://github.com/BerriAI/litellm/issues/4346
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commit
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2 changed files with 68 additions and 60 deletions
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@ -2176,13 +2176,23 @@ def completion(
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# boto3 reads keys from .env
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custom_prompt_dict = custom_prompt_dict or litellm.custom_prompt_dict
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if (
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"aws_bedrock_client" in optional_params
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): # use old bedrock flow for aws_bedrock_client users.
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response = bedrock.completion(
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if ("aws_bedrock_client" in optional_params):
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# Extract credentials for legacy boto3 client and pass thru to httpx
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aws_bedrock_client = optional_params.pop("aws_bedrock_client")
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creds = aws_bedrock_client._get_credentials().get_frozen_credentials()
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if creds.access_key:
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optional_params["aws_access_key_id"] = creds.access_key
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if creds.secret_key:
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optional_params["aws_secret_access_key"] = creds.secret_key
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if creds.token:
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optional_params["aws_session_token"] = creds.token
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if model.startswith("anthropic"):
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response = bedrock_converse_chat_completion.completion(
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model=model,
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messages=messages,
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custom_prompt_dict=litellm.custom_prompt_dict,
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custom_prompt_dict=custom_prompt_dict,
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model_response=model_response,
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print_verbose=print_verbose,
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optional_params=optional_params,
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@ -2192,63 +2202,27 @@ def completion(
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logging_obj=logging,
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extra_headers=extra_headers,
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timeout=timeout,
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acompletion=acompletion,
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client=client,
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)
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else:
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response = bedrock_chat_completion.completion(
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model=model,
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messages=messages,
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custom_prompt_dict=custom_prompt_dict,
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model_response=model_response,
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print_verbose=print_verbose,
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optional_params=optional_params,
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litellm_params=litellm_params,
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logger_fn=logger_fn,
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encoding=encoding,
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logging_obj=logging,
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extra_headers=extra_headers,
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timeout=timeout,
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acompletion=acompletion,
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client=client,
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)
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if (
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"stream" in optional_params
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and optional_params["stream"] == True
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and not isinstance(response, CustomStreamWrapper)
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):
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# don't try to access stream object,
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if "ai21" in model:
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response = CustomStreamWrapper(
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response,
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model,
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custom_llm_provider="bedrock",
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logging_obj=logging,
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)
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else:
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response = CustomStreamWrapper(
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iter(response),
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model,
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custom_llm_provider="bedrock",
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logging_obj=logging,
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)
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else:
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if model.startswith("anthropic"):
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response = bedrock_converse_chat_completion.completion(
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model=model,
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messages=messages,
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custom_prompt_dict=custom_prompt_dict,
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model_response=model_response,
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print_verbose=print_verbose,
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optional_params=optional_params,
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litellm_params=litellm_params,
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logger_fn=logger_fn,
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encoding=encoding,
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logging_obj=logging,
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extra_headers=extra_headers,
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timeout=timeout,
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acompletion=acompletion,
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client=client,
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)
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else:
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response = bedrock_chat_completion.completion(
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model=model,
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messages=messages,
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custom_prompt_dict=custom_prompt_dict,
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model_response=model_response,
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print_verbose=print_verbose,
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optional_params=optional_params,
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litellm_params=litellm_params,
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logger_fn=logger_fn,
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encoding=encoding,
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logging_obj=logging,
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extra_headers=extra_headers,
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timeout=timeout,
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acompletion=acompletion,
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client=client,
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)
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if optional_params.get("stream", False):
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## LOGGING
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logging.post_call(
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