litellm-mirror/litellm/responses/main.py
Krish Dholakia 9b7ebb6a7d
build(pyproject.toml): add new dev dependencies - for type checking (#9631)
* build(pyproject.toml): add new dev dependencies - for type checking

* build: reformat files to fit black

* ci: reformat to fit black

* ci(test-litellm.yml): make tests run clear

* build(pyproject.toml): add ruff

* fix: fix ruff checks

* build(mypy/): fix mypy linting errors

* fix(hashicorp_secret_manager.py): fix passing cert for tls auth

* build(mypy/): resolve all mypy errors

* test: update test

* fix: fix black formatting

* build(pre-commit-config.yaml): use poetry run black

* fix(proxy_server.py): fix linting error

* fix: fix ruff safe representation error
2025-03-29 11:02:13 -07:00

251 lines
9.3 KiB
Python

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