chore: initial snapshot for gitea/github upload
This commit is contained in:
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@@ -0,0 +1,414 @@
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#### Container Endpoints #####
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from typing import Any, Dict
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from fastapi import APIRouter, Depends, Request, Response
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from fastapi.responses import ORJSONResponse
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from litellm.proxy._types import *
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from litellm.proxy.auth.user_api_key_auth import UserAPIKeyAuth, user_api_key_auth
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from litellm.proxy.common_request_processing import ProxyBaseLLMRequestProcessing
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from litellm.proxy.common_utils.http_parsing_utils import _read_request_body
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from litellm.proxy.common_utils.openai_endpoint_utils import (
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get_custom_llm_provider_from_request_body,
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get_custom_llm_provider_from_request_headers,
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get_custom_llm_provider_from_request_query,
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)
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router = APIRouter()
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@router.post(
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"/v1/containers",
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dependencies=[Depends(user_api_key_auth)],
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response_class=ORJSONResponse,
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tags=["containers"],
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)
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@router.post(
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"/containers",
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dependencies=[Depends(user_api_key_auth)],
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response_class=ORJSONResponse,
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tags=["containers"],
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)
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async def create_container(
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request: Request,
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fastapi_response: Response,
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user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth),
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):
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"""
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Container creation endpoint for creating new containers.
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Follows the OpenAI Containers API spec:
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https://platform.openai.com/docs/api-reference/containers
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Example:
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```bash
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curl -X POST "http://localhost:4000/v1/containers" \
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-H "Authorization: Bearer sk-1234" \
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-H "Content-Type: application/json" \
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-d '{
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"name": "My Container",
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"expires_after": {
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"anchor": "last_active_at",
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"minutes": 20
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}
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}'
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```
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Or specify provider via header:
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```bash
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curl -X POST "http://localhost:4000/v1/containers" \
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-H "Authorization: Bearer sk-1234" \
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-H "custom-llm-provider: azure" \
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-H "Content-Type: application/json" \
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-d '{
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"name": "My Container"
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}'
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```
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"""
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from litellm.proxy.proxy_server import (
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general_settings,
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llm_router,
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proxy_config,
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proxy_logging_obj,
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select_data_generator,
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user_api_base,
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user_max_tokens,
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user_model,
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user_request_timeout,
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user_temperature,
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version,
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)
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# Read request body
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data = await _read_request_body(request=request)
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# Extract custom_llm_provider using priority chain
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# Priority: headers > query params > request body > default
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custom_llm_provider = (
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get_custom_llm_provider_from_request_headers(request=request)
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or get_custom_llm_provider_from_request_query(request=request)
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or await get_custom_llm_provider_from_request_body(request=request)
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or "openai"
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)
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# Add custom_llm_provider to data
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data["custom_llm_provider"] = custom_llm_provider
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# Process request using ProxyBaseLLMRequestProcessing
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processor = ProxyBaseLLMRequestProcessing(data=data)
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try:
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return await processor.base_process_llm_request(
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request=request,
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fastapi_response=fastapi_response,
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user_api_key_dict=user_api_key_dict,
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route_type="acreate_container",
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proxy_logging_obj=proxy_logging_obj,
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llm_router=llm_router,
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general_settings=general_settings,
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proxy_config=proxy_config,
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select_data_generator=select_data_generator,
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model=None,
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user_model=user_model,
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user_temperature=user_temperature,
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user_request_timeout=user_request_timeout,
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user_max_tokens=user_max_tokens,
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user_api_base=user_api_base,
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version=version,
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)
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except Exception as e:
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raise await processor._handle_llm_api_exception(
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e=e,
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user_api_key_dict=user_api_key_dict,
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proxy_logging_obj=proxy_logging_obj,
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version=version,
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)
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@router.get(
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"/v1/containers",
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dependencies=[Depends(user_api_key_auth)],
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response_class=ORJSONResponse,
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tags=["containers"],
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)
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@router.get(
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"/containers",
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dependencies=[Depends(user_api_key_auth)],
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response_class=ORJSONResponse,
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tags=["containers"],
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)
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async def list_containers(
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request: Request,
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fastapi_response: Response,
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user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth),
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):
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"""
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Container list endpoint for retrieving a list of containers.
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Follows the OpenAI Containers API spec:
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https://platform.openai.com/docs/api-reference/containers
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Example:
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```bash
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curl -X GET "http://localhost:4000/v1/containers?limit=20&order=desc" \
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-H "Authorization: Bearer sk-1234"
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```
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Or specify provider via header or query param:
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```bash
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curl -X GET "http://localhost:4000/v1/containers?custom_llm_provider=azure" \
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-H "Authorization: Bearer sk-1234"
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```
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"""
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from litellm.proxy.proxy_server import (
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general_settings,
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llm_router,
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proxy_config,
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proxy_logging_obj,
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select_data_generator,
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user_api_base,
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user_max_tokens,
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user_model,
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user_request_timeout,
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user_temperature,
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version,
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)
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# Read query parameters
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query_params = dict(request.query_params)
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data: Dict[str, Any] = {"query_params": query_params}
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# Extract custom_llm_provider using priority chain
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custom_llm_provider = (
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get_custom_llm_provider_from_request_headers(request=request)
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or get_custom_llm_provider_from_request_query(request=request)
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or "openai"
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)
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# Add custom_llm_provider to data
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data["custom_llm_provider"] = custom_llm_provider
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# Process request using ProxyBaseLLMRequestProcessing
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processor = ProxyBaseLLMRequestProcessing(data=data)
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try:
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return await processor.base_process_llm_request(
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request=request,
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fastapi_response=fastapi_response,
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user_api_key_dict=user_api_key_dict,
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route_type="alist_containers",
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proxy_logging_obj=proxy_logging_obj,
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llm_router=llm_router,
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general_settings=general_settings,
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proxy_config=proxy_config,
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select_data_generator=select_data_generator,
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model=None,
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user_model=user_model,
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user_temperature=user_temperature,
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user_request_timeout=user_request_timeout,
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user_max_tokens=user_max_tokens,
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user_api_base=user_api_base,
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version=version,
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)
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except Exception as e:
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raise await processor._handle_llm_api_exception(
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e=e,
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user_api_key_dict=user_api_key_dict,
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proxy_logging_obj=proxy_logging_obj,
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version=version,
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)
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@router.get(
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"/v1/containers/{container_id}",
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dependencies=[Depends(user_api_key_auth)],
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response_class=ORJSONResponse,
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tags=["containers"],
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)
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@router.get(
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"/containers/{container_id}",
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dependencies=[Depends(user_api_key_auth)],
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response_class=ORJSONResponse,
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tags=["containers"],
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)
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async def retrieve_container(
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request: Request,
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container_id: str,
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fastapi_response: Response,
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user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth),
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):
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"""
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Container retrieve endpoint for getting details of a specific container.
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Follows the OpenAI Containers API spec:
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https://platform.openai.com/docs/api-reference/containers
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Example:
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```bash
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curl -X GET "http://localhost:4000/v1/containers/cntr_123" \
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-H "Authorization: Bearer sk-1234"
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```
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Or specify provider via header:
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```bash
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curl -X GET "http://localhost:4000/v1/containers/cntr_123" \
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-H "Authorization: Bearer sk-1234" \
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-H "custom-llm-provider: azure"
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```
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"""
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from litellm.proxy.proxy_server import (
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general_settings,
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llm_router,
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proxy_config,
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proxy_logging_obj,
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select_data_generator,
|
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user_api_base,
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user_max_tokens,
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user_model,
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user_request_timeout,
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user_temperature,
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version,
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)
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# Include container_id in request data
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data: Dict[str, Any] = {"container_id": container_id}
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# Extract custom_llm_provider using priority chain
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custom_llm_provider = (
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get_custom_llm_provider_from_request_headers(request=request)
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or get_custom_llm_provider_from_request_query(request=request)
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or "openai"
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)
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# Add custom_llm_provider to data
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data["custom_llm_provider"] = custom_llm_provider
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# Process request using ProxyBaseLLMRequestProcessing
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processor = ProxyBaseLLMRequestProcessing(data=data)
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try:
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return await processor.base_process_llm_request(
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request=request,
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fastapi_response=fastapi_response,
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user_api_key_dict=user_api_key_dict,
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route_type="aretrieve_container",
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proxy_logging_obj=proxy_logging_obj,
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llm_router=llm_router,
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general_settings=general_settings,
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proxy_config=proxy_config,
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select_data_generator=select_data_generator,
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model=None,
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user_model=user_model,
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user_temperature=user_temperature,
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user_request_timeout=user_request_timeout,
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user_max_tokens=user_max_tokens,
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user_api_base=user_api_base,
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version=version,
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)
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except Exception as e:
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raise await processor._handle_llm_api_exception(
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e=e,
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user_api_key_dict=user_api_key_dict,
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proxy_logging_obj=proxy_logging_obj,
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version=version,
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)
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@router.delete(
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"/v1/containers/{container_id}",
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dependencies=[Depends(user_api_key_auth)],
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response_class=ORJSONResponse,
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tags=["containers"],
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)
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@router.delete(
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"/containers/{container_id}",
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dependencies=[Depends(user_api_key_auth)],
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response_class=ORJSONResponse,
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tags=["containers"],
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)
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async def delete_container(
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request: Request,
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container_id: str,
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fastapi_response: Response,
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user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth),
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):
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"""
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Container delete endpoint for deleting a specific container.
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Follows the OpenAI Containers API spec:
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https://platform.openai.com/docs/api-reference/containers
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Example:
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```bash
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curl -X DELETE "http://localhost:4000/v1/containers/cntr_123" \
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-H "Authorization: Bearer sk-1234"
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```
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Or specify provider via header:
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```bash
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curl -X DELETE "http://localhost:4000/v1/containers/cntr_123" \
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-H "Authorization: Bearer sk-1234" \
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-H "custom-llm-provider: azure"
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```
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"""
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from litellm.proxy.proxy_server import (
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general_settings,
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llm_router,
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proxy_config,
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proxy_logging_obj,
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select_data_generator,
|
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user_api_base,
|
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user_max_tokens,
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user_model,
|
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user_request_timeout,
|
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user_temperature,
|
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version,
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)
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# Include container_id in request data
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data: Dict[str, Any] = {"container_id": container_id}
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# Extract custom_llm_provider using priority chain
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custom_llm_provider = (
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get_custom_llm_provider_from_request_headers(request=request)
|
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or get_custom_llm_provider_from_request_query(request=request)
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or "openai"
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||||
)
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# Add custom_llm_provider to data
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data["custom_llm_provider"] = custom_llm_provider
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# Process request using ProxyBaseLLMRequestProcessing
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processor = ProxyBaseLLMRequestProcessing(data=data)
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try:
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return await processor.base_process_llm_request(
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request=request,
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fastapi_response=fastapi_response,
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user_api_key_dict=user_api_key_dict,
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route_type="adelete_container",
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proxy_logging_obj=proxy_logging_obj,
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llm_router=llm_router,
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general_settings=general_settings,
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proxy_config=proxy_config,
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select_data_generator=select_data_generator,
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model=None,
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user_model=user_model,
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user_temperature=user_temperature,
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user_request_timeout=user_request_timeout,
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user_max_tokens=user_max_tokens,
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user_api_base=user_api_base,
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version=version,
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)
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except Exception as e:
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raise await processor._handle_llm_api_exception(
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e=e,
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user_api_key_dict=user_api_key_dict,
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proxy_logging_obj=proxy_logging_obj,
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version=version,
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)
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# Register JSON-configured container file endpoints
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from litellm.proxy.container_endpoints.handler_factory import (
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register_container_file_endpoints,
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)
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register_container_file_endpoints(router)
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Reference in New Issue
Block a user