structure saas with tools
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"""
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Support for OpenAI's `/v1/chat/completions` endpoint.
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Calls done in OpenAI/openai.py as OpenRouter is openai-compatible.
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Docs: https://openrouter.ai/docs/parameters
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"""
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from typing import Any, AsyncIterator, Iterator, List, Optional, Union
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import httpx
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from litellm.llms.base_llm.base_model_iterator import BaseModelResponseIterator
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from litellm.llms.base_llm.chat.transformation import BaseLLMException
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from litellm.types.llms.openai import AllMessageValues
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from litellm.types.llms.openrouter import OpenRouterErrorMessage
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from litellm.types.utils import ModelResponse, ModelResponseStream
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from ...openai.chat.gpt_transformation import OpenAIGPTConfig
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from ..common_utils import OpenRouterException
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class OpenrouterConfig(OpenAIGPTConfig):
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def map_openai_params(
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self,
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non_default_params: dict,
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optional_params: dict,
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model: str,
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drop_params: bool,
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) -> dict:
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mapped_openai_params = super().map_openai_params(
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non_default_params, optional_params, model, drop_params
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)
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# OpenRouter-only parameters
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extra_body = {}
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transforms = non_default_params.pop("transforms", None)
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models = non_default_params.pop("models", None)
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route = non_default_params.pop("route", None)
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if transforms is not None:
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extra_body["transforms"] = transforms
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if models is not None:
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extra_body["models"] = models
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if route is not None:
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extra_body["route"] = route
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mapped_openai_params[
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"extra_body"
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] = extra_body # openai client supports `extra_body` param
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return mapped_openai_params
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def transform_request(
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self,
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model: str,
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messages: List[AllMessageValues],
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optional_params: dict,
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litellm_params: dict,
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headers: dict,
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) -> dict:
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"""
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Transform the overall request to be sent to the API.
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Returns:
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dict: The transformed request. Sent as the body of the API call.
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"""
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extra_body = optional_params.pop("extra_body", {})
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response = super().transform_request(
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model, messages, optional_params, litellm_params, headers
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)
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response.update(extra_body)
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return response
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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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return OpenRouterException(
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message=error_message,
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status_code=status_code,
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headers=headers,
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)
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def get_model_response_iterator(
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self,
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streaming_response: Union[Iterator[str], AsyncIterator[str], ModelResponse],
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sync_stream: bool,
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json_mode: Optional[bool] = False,
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) -> Any:
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return OpenRouterChatCompletionStreamingHandler(
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streaming_response=streaming_response,
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sync_stream=sync_stream,
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json_mode=json_mode,
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)
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class OpenRouterChatCompletionStreamingHandler(BaseModelResponseIterator):
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def chunk_parser(self, chunk: dict) -> ModelResponseStream:
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try:
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## HANDLE ERROR IN CHUNK ##
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if "error" in chunk:
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error_chunk = chunk["error"]
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error_message = OpenRouterErrorMessage(
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message="Message: {}, Metadata: {}, User ID: {}".format(
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error_chunk["message"],
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error_chunk.get("metadata", {}),
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error_chunk.get("user_id", ""),
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),
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code=error_chunk["code"],
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metadata=error_chunk.get("metadata", {}),
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)
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raise OpenRouterException(
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message=error_message["message"],
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status_code=error_message["code"],
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headers=error_message["metadata"].get("headers", {}),
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)
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new_choices = []
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for choice in chunk["choices"]:
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choice["delta"]["reasoning_content"] = choice["delta"].get("reasoning")
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new_choices.append(choice)
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return ModelResponseStream(
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id=chunk["id"],
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object="chat.completion.chunk",
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created=chunk["created"],
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model=chunk["model"],
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choices=new_choices,
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)
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except KeyError as e:
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raise OpenRouterException(
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message=f"KeyError: {e}, Got unexpected response from OpenRouter: {chunk}",
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status_code=400,
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headers={"Content-Type": "application/json"},
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)
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except Exception as e:
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raise e
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