litellm-mirror/litellm/responses/main.py

import asyncio
import contextvars
from functools import partial
from typing import Any, Dict, Iterable, List, Literal, Optional, Union

import httpx

import litellm
from litellm.constants import request_timeout
from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
from litellm.llms.base_llm.responses.transformation import BaseResponsesAPIConfig
from litellm.llms.custom_httpx.llm_http_handler import BaseLLMHTTPHandler
from litellm.responses.litellm_completion_transformation.handler import (
    LiteLLMCompletionTransformationHandler,
)
from litellm.responses.utils import ResponsesAPIRequestUtils
from litellm.types.llms.openai import (
    Reasoning,
    ResponseIncludable,
    ResponseInputParam,
    ResponsesAPIOptionalRequestParams,
    ResponsesAPIResponse,
    ResponseTextConfigParam,
    ToolChoice,
    ToolParam,
)
from litellm.types.router import GenericLiteLLMParams
from litellm.utils import ProviderConfigManager, client

from .streaming_iterator import BaseResponsesAPIStreamingIterator

####### ENVIRONMENT VARIABLES ###################
# Initialize any necessary instances or variables here
base_llm_http_handler = BaseLLMHTTPHandler()
litellm_completion_transformation_handler = LiteLLMCompletionTransformationHandler()
#################################################


@client
async def aresponses(
    input: Union[str, ResponseInputParam],
    model: str,
    include: Optional[List[ResponseIncludable]] = None,
    instructions: Optional[str] = None,
    max_output_tokens: Optional[int] = None,
    metadata: Optional[Dict[str, Any]] = None,
    parallel_tool_calls: Optional[bool] = None,
    previous_response_id: Optional[str] = None,
    reasoning: Optional[Reasoning] = None,
    store: Optional[bool] = None,
    stream: Optional[bool] = None,
    temperature: Optional[float] = None,
    text: Optional[ResponseTextConfigParam] = None,
    tool_choice: Optional[ToolChoice] = None,
    tools: Optional[Iterable[ToolParam]] = None,
    top_p: Optional[float] = None,
    truncation: Optional[Literal["auto", "disabled"]] = None,
    user: Optional[str] = None,
    # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
    # The extra values given here take precedence over values defined on the client or passed to this method.
    extra_headers: Optional[Dict[str, Any]] = None,
    extra_query: Optional[Dict[str, Any]] = None,
    extra_body: Optional[Dict[str, Any]] = None,
    timeout: Optional[Union[float, httpx.Timeout]] = None,
    # LiteLLM specific params,
    custom_llm_provider: Optional[str] = None,
    **kwargs,
) -> Union[ResponsesAPIResponse, BaseResponsesAPIStreamingIterator]:
    """
    Async: Handles responses API requests by reusing the synchronous function
    """
    local_vars = locals()
    try:
        loop = asyncio.get_event_loop()
        kwargs["aresponses"] = True

        # get custom llm provider so we can use this for mapping exceptions
        if custom_llm_provider is None:
            _, custom_llm_provider, _, _ = litellm.get_llm_provider(
                model=model, api_base=local_vars.get("base_url", None)
            )

        func = partial(
            responses,
            input=input,
            model=model,
            include=include,
            instructions=instructions,
            max_output_tokens=max_output_tokens,
            metadata=metadata,
            parallel_tool_calls=parallel_tool_calls,
            previous_response_id=previous_response_id,
            reasoning=reasoning,
            store=store,
            stream=stream,
            temperature=temperature,
            text=text,
            tool_choice=tool_choice,
            tools=tools,
            top_p=top_p,
            truncation=truncation,
            user=user,
            extra_headers=extra_headers,
            extra_query=extra_query,
            extra_body=extra_body,
            timeout=timeout,
            custom_llm_provider=custom_llm_provider,
            **kwargs,
        )

        ctx = contextvars.copy_context()
        func_with_context = partial(ctx.run, func)
        init_response = await loop.run_in_executor(None, func_with_context)

        if asyncio.iscoroutine(init_response):
            response = await init_response
        else:
            response = init_response
        return response
    except Exception as e:
        raise litellm.exception_type(
            model=model,
            custom_llm_provider=custom_llm_provider,
            original_exception=e,
            completion_kwargs=local_vars,
            extra_kwargs=kwargs,
        )


@client
def responses(
    input: Union[str, ResponseInputParam],
    model: str,
    include: Optional[List[ResponseIncludable]] = None,
    instructions: Optional[str] = None,
    max_output_tokens: Optional[int] = None,
    metadata: Optional[Dict[str, Any]] = None,
    parallel_tool_calls: Optional[bool] = None,
    previous_response_id: Optional[str] = None,
    reasoning: Optional[Reasoning] = None,
    store: Optional[bool] = None,
    stream: Optional[bool] = None,
    temperature: Optional[float] = None,
    text: Optional[ResponseTextConfigParam] = None,
    tool_choice: Optional[ToolChoice] = None,
    tools: Optional[Iterable[ToolParam]] = None,
    top_p: Optional[float] = None,
    truncation: Optional[Literal["auto", "disabled"]] = None,
    user: Optional[str] = None,
    # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
    # The extra values given here take precedence over values defined on the client or passed to this method.
    extra_headers: Optional[Dict[str, Any]] = None,
    extra_query: Optional[Dict[str, Any]] = None,
    extra_body: Optional[Dict[str, Any]] = None,
    timeout: Optional[Union[float, httpx.Timeout]] = None,
    # LiteLLM specific params,
    custom_llm_provider: Optional[str] = None,
    **kwargs,
):
    """
    Synchronous version of the Responses API.
    Uses the synchronous HTTP handler to make requests.
    """
    local_vars = locals()
    try:
        litellm_logging_obj: LiteLLMLoggingObj = kwargs.get("litellm_logging_obj")  # type: ignore
        litellm_call_id: Optional[str] = kwargs.get("litellm_call_id", None)
        _is_async = kwargs.pop("aresponses", False) is True

        # get llm provider logic
        litellm_params = GenericLiteLLMParams(**kwargs)
        (
            model,
            custom_llm_provider,
            dynamic_api_key,
            dynamic_api_base,
        ) = litellm.get_llm_provider(
            model=model,
            custom_llm_provider=custom_llm_provider,
            api_base=litellm_params.api_base,
            api_key=litellm_params.api_key,
        )

        # get provider config
        responses_api_provider_config: Optional[BaseResponsesAPIConfig] = (
            ProviderConfigManager.get_provider_responses_api_config(
                model=model,
                provider=litellm.LlmProviders(custom_llm_provider),
            )
        )

        local_vars.update(kwargs)
        # Get ResponsesAPIOptionalRequestParams with only valid parameters
        response_api_optional_params: ResponsesAPIOptionalRequestParams = (
            ResponsesAPIRequestUtils.get_requested_response_api_optional_param(
                local_vars
            )
        )

        if responses_api_provider_config is None:
            return litellm_completion_transformation_handler.response_api_handler(
                model=model,
                input=input,
                responses_api_request=response_api_optional_params,
                custom_llm_provider=custom_llm_provider,
                _is_async=_is_async,
                stream=stream,
                **kwargs,
            )

        # Get optional parameters for the responses API
        responses_api_request_params: Dict = (
            ResponsesAPIRequestUtils.get_optional_params_responses_api(
                model=model,
                responses_api_provider_config=responses_api_provider_config,
                response_api_optional_params=response_api_optional_params,
            )
        )

        # Pre Call logging
        litellm_logging_obj.update_environment_variables(
            model=model,
            user=user,
            optional_params=dict(responses_api_request_params),
            litellm_params={
                "litellm_call_id": litellm_call_id,
                **responses_api_request_params,
            },
            custom_llm_provider=custom_llm_provider,
        )

        # Call the handler with _is_async flag instead of directly calling the async handler
        response = base_llm_http_handler.response_api_handler(
            model=model,
            input=input,
            responses_api_provider_config=responses_api_provider_config,
            response_api_optional_request_params=responses_api_request_params,
            custom_llm_provider=custom_llm_provider,
            litellm_params=litellm_params,
            logging_obj=litellm_logging_obj,
            extra_headers=extra_headers,
            extra_body=extra_body,
            timeout=timeout or request_timeout,
            _is_async=_is_async,
            client=kwargs.get("client"),
            fake_stream=responses_api_provider_config.should_fake_stream(
                model=model, stream=stream, custom_llm_provider=custom_llm_provider
            ),
        )

        return response
    except Exception as e:
        raise litellm.exception_type(
            model=model,
            custom_llm_provider=custom_llm_provider,
            original_exception=e,
            completion_kwargs=local_vars,
            extra_kwargs=kwargs,
        )