litellm-mirror/litellm/responses/main.py
2025-03-11 22:03:48 -07:00

164 lines
6.3 KiB
Python

from typing import Any, Dict, Iterable, List, Literal, Optional, Union, get_type_hints
import httpx
import litellm
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.utils import (
ResponsesAPIRequestParams,
get_optional_params_responses_api,
)
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 ResponsesAPIStreamingIterator
####### ENVIRONMENT VARIABLES ###################
# Initialize any necessary instances or variables here
base_llm_http_handler = BaseLLMHTTPHandler()
#################################################
def get_requested_response_api_optional_param(
params: Dict[str, Any]
) -> ResponsesAPIOptionalRequestParams:
"""
Filter parameters to only include those defined in ResponsesAPIOptionalRequestParams.
Args:
params: Dictionary of parameters to filter
Returns:
ResponsesAPIOptionalRequestParams instance with only the valid parameters
"""
valid_keys = get_type_hints(ResponsesAPIOptionalRequestParams).keys()
filtered_params = {k: v for k, v in params.items() if k in valid_keys}
return ResponsesAPIOptionalRequestParams(**filtered_params)
@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,
**kwargs,
) -> Union[ResponsesAPIResponse, ResponsesAPIStreamingIterator]:
litellm_logging_obj: LiteLLMLoggingObj = kwargs.get("litellm_logging_obj") # type: ignore
litellm_call_id: Optional[str] = kwargs.get("litellm_call_id", None)
# 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=kwargs.get("custom_llm_provider", None),
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),
)
)
if responses_api_provider_config is None:
raise litellm.BadRequestError(
model=model,
llm_provider=custom_llm_provider,
message=f"Responses API not available for custom_llm_provider={custom_llm_provider}, model: {model}",
)
# Get all parameters using locals() and combine with kwargs
local_vars = locals()
local_vars.update(kwargs)
# Get ResponsesAPIOptionalRequestParams with only valid parameters
response_api_optional_params: ResponsesAPIOptionalRequestParams = (
get_requested_response_api_optional_param(local_vars)
)
# Get optional parameters for the responses API
responses_api_request_params: Dict = get_optional_params_responses_api(
model=model,
responses_api_provider_config=responses_api_provider_config,
response_api_optional_params=response_api_optional_params,
)
response = await base_llm_http_handler.async_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,
)
return response
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,
):
pass