new mcp servers format
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@@ -95,6 +95,35 @@ class AzureOpenAIResponsesAPIConfig(OpenAIResponsesAPIConfig):
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#########################################################
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########## DELETE RESPONSE API TRANSFORMATION ##############
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#########################################################
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def _construct_url_for_response_id_in_path(
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self, api_base: str, response_id: str
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) -> str:
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"""
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Constructs a URL for the API request with the response_id in the path.
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"""
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from urllib.parse import urlparse, urlunparse
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# Parse the URL to separate its components
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parsed_url = urlparse(api_base)
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# Insert the response_id at the end of the path component
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# Remove trailing slash if present to avoid double slashes
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path = parsed_url.path.rstrip("/")
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new_path = f"{path}/{response_id}"
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# Reconstruct the URL with all original components but with the modified path
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constructed_url = urlunparse(
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(
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parsed_url.scheme, # http, https
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parsed_url.netloc, # domain name, port
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new_path, # path with response_id added
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parsed_url.params, # parameters
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parsed_url.query, # query string
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parsed_url.fragment, # fragment
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)
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)
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return constructed_url
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def transform_delete_response_api_request(
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self,
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response_id: str,
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@@ -111,28 +140,33 @@ class AzureOpenAIResponsesAPIConfig(OpenAIResponsesAPIConfig):
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This function handles URLs with query parameters by inserting the response_id
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at the correct location (before any query parameters).
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"""
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from urllib.parse import urlparse, urlunparse
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# Parse the URL to separate its components
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parsed_url = urlparse(api_base)
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# Insert the response_id at the end of the path component
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# Remove trailing slash if present to avoid double slashes
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path = parsed_url.path.rstrip("/")
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new_path = f"{path}/{response_id}"
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# Reconstruct the URL with all original components but with the modified path
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delete_url = urlunparse(
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(
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parsed_url.scheme, # http, https
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parsed_url.netloc, # domain name, port
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new_path, # path with response_id added
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parsed_url.params, # parameters
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parsed_url.query, # query string
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parsed_url.fragment, # fragment
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)
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delete_url = self._construct_url_for_response_id_in_path(
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api_base=api_base, response_id=response_id
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)
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data: Dict = {}
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verbose_logger.debug(f"delete response url={delete_url}")
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return delete_url, data
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#########################################################
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########## GET RESPONSE API TRANSFORMATION ###############
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#########################################################
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def transform_get_response_api_request(
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self,
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response_id: str,
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api_base: str,
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litellm_params: GenericLiteLLMParams,
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headers: dict,
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) -> Tuple[str, Dict]:
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"""
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Transform the get response API request into a URL and data
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OpenAI API expects the following request
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- GET /v1/responses/{response_id}
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"""
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get_url = self._construct_url_for_response_id_in_path(
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api_base=api_base, response_id=response_id
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)
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data: Dict = {}
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verbose_logger.debug(f"get response url={get_url}")
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return get_url, data
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@@ -141,9 +141,34 @@ class BaseResponsesAPIConfig(ABC):
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pass
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#########################################################
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########## END DELETE RESPONSE API TRANSFORMATION ##########
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########## END DELETE RESPONSE API TRANSFORMATION #######
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#########################################################
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#########################################################
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########## GET RESPONSE API TRANSFORMATION ###############
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#########################################################
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@abstractmethod
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def transform_get_response_api_request(
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self,
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response_id: str,
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api_base: str,
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litellm_params: GenericLiteLLMParams,
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headers: dict,
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) -> Tuple[str, Dict]:
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pass
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@abstractmethod
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def transform_get_response_api_response(
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self,
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raw_response: httpx.Response,
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logging_obj: LiteLLMLoggingObj,
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) -> ResponsesAPIResponse:
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pass
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#########################################################
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########## END GET RESPONSE API TRANSFORMATION ##########
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#########################################################
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def get_error_class(
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self, error_message: str, status_code: int, headers: Union[dict, httpx.Headers]
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) -> BaseLLMException:
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@@ -107,6 +107,15 @@ class AmazonConverseConfig(BaseConfig):
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"response_format",
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]
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if (
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"arn" in model
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): # we can't infer the model from the arn, so just add all params
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supported_params.append("tools")
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supported_params.append("tool_choice")
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supported_params.append("thinking")
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supported_params.append("reasoning_effort")
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return supported_params
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## Filter out 'cross-region' from model name
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base_model = BedrockModelInfo.get_base_model(model)
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