mirror of
https://github.com/open-webui/open-webui.git
synced 2025-12-13 21:05:19 +00:00
1439 lines
54 KiB
Python
1439 lines
54 KiB
Python
import asyncio
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import hashlib
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import json
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import logging
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from typing import Optional
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import aiohttp
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from aiocache import cached
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import requests
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from urllib.parse import quote
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from azure.identity import DefaultAzureCredential, get_bearer_token_provider
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from fastapi import Depends, HTTPException, Request, APIRouter
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from fastapi.responses import (
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FileResponse,
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StreamingResponse,
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JSONResponse,
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PlainTextResponse,
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)
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from pydantic import BaseModel
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from starlette.background import BackgroundTask
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from open_webui.models.models import Models
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from open_webui.config import (
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CACHE_DIR,
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)
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from open_webui.env import (
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MODELS_CACHE_TTL,
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AIOHTTP_CLIENT_SESSION_SSL,
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AIOHTTP_CLIENT_TIMEOUT,
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AIOHTTP_CLIENT_TIMEOUT_MODEL_LIST,
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ENABLE_FORWARD_USER_INFO_HEADERS,
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BYPASS_MODEL_ACCESS_CONTROL,
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)
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from open_webui.models.users import UserModel
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from open_webui.memory.cross_window_memory import last_process_payload
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from open_webui.utils.misc import extract_timestamped_messages
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from open_webui.constants import ERROR_MESSAGES
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from open_webui.env import SRC_LOG_LEVELS
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from open_webui.utils.payload import (
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apply_model_params_to_body_openai,
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apply_system_prompt_to_body,
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)
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from open_webui.utils.misc import (
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convert_logit_bias_input_to_json,
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)
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from open_webui.utils.auth import get_admin_user, get_verified_user
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from open_webui.utils.access_control import has_access
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log = logging.getLogger(__name__)
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log.setLevel(SRC_LOG_LEVELS["OPENAI"])
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##########################################
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#
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# Utility functions
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#
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##########################################
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async def send_get_request(url, key=None, user: UserModel = None):
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timeout = aiohttp.ClientTimeout(total=AIOHTTP_CLIENT_TIMEOUT_MODEL_LIST)
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try:
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async with aiohttp.ClientSession(timeout=timeout, trust_env=True) as session:
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async with session.get(
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url,
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headers={
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**({"Authorization": f"Bearer {key}"} if key else {}),
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**(
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{
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"X-OpenWebUI-User-Name": quote(user.name, safe=" "),
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"X-OpenWebUI-User-Id": user.id,
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"X-OpenWebUI-User-Email": user.email,
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"X-OpenWebUI-User-Role": user.role,
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}
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if ENABLE_FORWARD_USER_INFO_HEADERS and user
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else {}
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),
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},
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ssl=AIOHTTP_CLIENT_SESSION_SSL,
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) as response:
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return await response.json()
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except Exception as e:
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# Handle connection error here
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log.error(f"Connection error: {e}")
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return None
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async def cleanup_response(
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response: Optional[aiohttp.ClientResponse],
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session: Optional[aiohttp.ClientSession],
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):
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if response:
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response.close()
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if session:
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await session.close()
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def openai_reasoning_model_handler(payload):
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"""
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Handle reasoning model specific parameters
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"""
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if "max_tokens" in payload:
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# Convert "max_tokens" to "max_completion_tokens" for all reasoning models
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payload["max_completion_tokens"] = payload["max_tokens"]
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del payload["max_tokens"]
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# Handle system role conversion based on model type
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if payload["messages"][0]["role"] == "system":
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model_lower = payload["model"].lower()
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# Legacy models use "user" role instead of "system"
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if model_lower.startswith("o1-mini") or model_lower.startswith("o1-preview"):
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payload["messages"][0]["role"] = "user"
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else:
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payload["messages"][0]["role"] = "developer"
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return payload
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async def get_headers_and_cookies(
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request: Request,
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url,
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key=None,
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config=None,
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metadata: Optional[dict] = None,
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user: UserModel = None,
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):
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cookies = {}
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headers = {
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"Content-Type": "application/json",
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**(
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{
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"HTTP-Referer": "https://openwebui.com/",
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"X-Title": "Cakumi",
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}
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if "openrouter.ai" in url
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else {}
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),
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**(
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{
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"X-OpenWebUI-User-Name": quote(user.name, safe=" "),
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"X-OpenWebUI-User-Id": user.id,
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"X-OpenWebUI-User-Email": user.email,
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"X-OpenWebUI-User-Role": user.role,
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**(
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{"X-OpenWebUI-Chat-Id": metadata.get("chat_id")}
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if metadata and metadata.get("chat_id")
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else {}
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),
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}
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if ENABLE_FORWARD_USER_INFO_HEADERS
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else {}
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),
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}
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token = None
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auth_type = config.get("auth_type")
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if auth_type == "bearer" or auth_type is None:
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# Default to bearer if not specified
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token = f"{key}"
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elif auth_type == "none":
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token = None
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elif auth_type == "session":
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cookies = request.cookies
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token = request.state.token.credentials
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elif auth_type == "system_oauth":
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cookies = request.cookies
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oauth_token = None
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try:
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if request.cookies.get("oauth_session_id", None):
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oauth_token = await request.app.state.oauth_manager.get_oauth_token(
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user.id,
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request.cookies.get("oauth_session_id", None),
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)
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except Exception as e:
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log.error(f"Error getting OAuth token: {e}")
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if oauth_token:
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token = f"{oauth_token.get('access_token', '')}"
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elif auth_type in ("azure_ad", "microsoft_entra_id"):
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token = get_microsoft_entra_id_access_token()
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if token:
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headers["Authorization"] = f"Bearer {token}"
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if config.get("headers") and isinstance(config.get("headers"), dict):
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headers = {**headers, **config.get("headers")}
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return headers, cookies
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def get_microsoft_entra_id_access_token():
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"""
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Get Microsoft Entra ID access token using DefaultAzureCredential for Azure OpenAI.
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Returns the token string or None if authentication fails.
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"""
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try:
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token_provider = get_bearer_token_provider(
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DefaultAzureCredential(), "https://cognitiveservices.azure.com/.default"
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)
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return token_provider()
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except Exception as e:
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log.error(f"Error getting Microsoft Entra ID access token: {e}")
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return None
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##########################################
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#
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# API routes
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#
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##########################################
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router = APIRouter()
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@router.get("/config")
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async def get_config(request: Request, user=Depends(get_admin_user)):
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return {
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"ENABLE_OPENAI_API": request.app.state.config.ENABLE_OPENAI_API,
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"OPENAI_API_BASE_URLS": request.app.state.config.OPENAI_API_BASE_URLS,
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"OPENAI_API_KEYS": request.app.state.config.OPENAI_API_KEYS,
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"OPENAI_API_CONFIGS": request.app.state.config.OPENAI_API_CONFIGS,
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}
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class OpenAIConfigForm(BaseModel):
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ENABLE_OPENAI_API: Optional[bool] = None
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OPENAI_API_BASE_URLS: list[str]
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OPENAI_API_KEYS: list[str]
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OPENAI_API_CONFIGS: dict
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@router.post("/config/update")
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async def update_config(
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request: Request, form_data: OpenAIConfigForm, user=Depends(get_admin_user)
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):
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request.app.state.config.ENABLE_OPENAI_API = form_data.ENABLE_OPENAI_API
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request.app.state.config.OPENAI_API_BASE_URLS = form_data.OPENAI_API_BASE_URLS
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request.app.state.config.OPENAI_API_KEYS = form_data.OPENAI_API_KEYS
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# Check if API KEYS length is same than API URLS length
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if len(request.app.state.config.OPENAI_API_KEYS) != len(
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request.app.state.config.OPENAI_API_BASE_URLS
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):
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if len(request.app.state.config.OPENAI_API_KEYS) > len(
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request.app.state.config.OPENAI_API_BASE_URLS
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):
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request.app.state.config.OPENAI_API_KEYS = (
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request.app.state.config.OPENAI_API_KEYS[
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: len(request.app.state.config.OPENAI_API_BASE_URLS)
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]
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)
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else:
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request.app.state.config.OPENAI_API_KEYS += [""] * (
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len(request.app.state.config.OPENAI_API_BASE_URLS)
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- len(request.app.state.config.OPENAI_API_KEYS)
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)
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request.app.state.config.OPENAI_API_CONFIGS = form_data.OPENAI_API_CONFIGS
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# Remove the API configs that are not in the API URLS
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keys = list(map(str, range(len(request.app.state.config.OPENAI_API_BASE_URLS))))
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request.app.state.config.OPENAI_API_CONFIGS = {
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key: value
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for key, value in request.app.state.config.OPENAI_API_CONFIGS.items()
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if key in keys
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}
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return {
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"ENABLE_OPENAI_API": request.app.state.config.ENABLE_OPENAI_API,
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"OPENAI_API_BASE_URLS": request.app.state.config.OPENAI_API_BASE_URLS,
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"OPENAI_API_KEYS": request.app.state.config.OPENAI_API_KEYS,
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"OPENAI_API_CONFIGS": request.app.state.config.OPENAI_API_CONFIGS,
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}
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@router.post("/audio/speech")
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async def speech(request: Request, user=Depends(get_verified_user)):
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idx = None
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try:
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idx = request.app.state.config.OPENAI_API_BASE_URLS.index(
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"https://api.openai.com/v1"
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)
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body = await request.body()
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name = hashlib.sha256(body).hexdigest()
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SPEECH_CACHE_DIR = CACHE_DIR / "audio" / "speech"
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SPEECH_CACHE_DIR.mkdir(parents=True, exist_ok=True)
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file_path = SPEECH_CACHE_DIR.joinpath(f"{name}.mp3")
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file_body_path = SPEECH_CACHE_DIR.joinpath(f"{name}.json")
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# Check if the file already exists in the cache
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if file_path.is_file():
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return FileResponse(file_path)
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url = request.app.state.config.OPENAI_API_BASE_URLS[idx]
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key = request.app.state.config.OPENAI_API_KEYS[idx]
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api_config = request.app.state.config.OPENAI_API_CONFIGS.get(
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str(idx),
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request.app.state.config.OPENAI_API_CONFIGS.get(url, {}), # Legacy support
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)
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headers, cookies = await get_headers_and_cookies(
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request, url, key, api_config, user=user
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)
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r = None
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try:
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r = requests.post(
|
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url=f"{url}/audio/speech",
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data=body,
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headers=headers,
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cookies=cookies,
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stream=True,
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)
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r.raise_for_status()
|
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|
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# Save the streaming content to a file
|
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with open(file_path, "wb") as f:
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for chunk in r.iter_content(chunk_size=8192):
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f.write(chunk)
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with open(file_body_path, "w") as f:
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json.dump(json.loads(body.decode("utf-8")), f)
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|
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# Return the saved file
|
||
return FileResponse(file_path)
|
||
|
||
except Exception as e:
|
||
log.exception(e)
|
||
|
||
detail = None
|
||
if r is not None:
|
||
try:
|
||
res = r.json()
|
||
if "error" in res:
|
||
detail = f"External: {res['error']}"
|
||
except Exception:
|
||
detail = f"External: {e}"
|
||
|
||
raise HTTPException(
|
||
status_code=r.status_code if r else 500,
|
||
detail=detail if detail else "Cakumi: Server Connection Error",
|
||
)
|
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|
||
except ValueError:
|
||
raise HTTPException(status_code=401, detail=ERROR_MESSAGES.OPENAI_NOT_FOUND)
|
||
|
||
|
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async def get_all_models_responses(request: Request, user: UserModel) -> list:
|
||
if not request.app.state.config.ENABLE_OPENAI_API:
|
||
return []
|
||
|
||
# Check if API KEYS length is same than API URLS length
|
||
num_urls = len(request.app.state.config.OPENAI_API_BASE_URLS)
|
||
num_keys = len(request.app.state.config.OPENAI_API_KEYS)
|
||
|
||
if num_keys != num_urls:
|
||
# if there are more keys than urls, remove the extra keys
|
||
if num_keys > num_urls:
|
||
new_keys = request.app.state.config.OPENAI_API_KEYS[:num_urls]
|
||
request.app.state.config.OPENAI_API_KEYS = new_keys
|
||
# if there are more urls than keys, add empty keys
|
||
else:
|
||
request.app.state.config.OPENAI_API_KEYS += [""] * (num_urls - num_keys)
|
||
|
||
request_tasks = []
|
||
for idx, url in enumerate(request.app.state.config.OPENAI_API_BASE_URLS):
|
||
if (str(idx) not in request.app.state.config.OPENAI_API_CONFIGS) and (
|
||
url not in request.app.state.config.OPENAI_API_CONFIGS # Legacy support
|
||
):
|
||
request_tasks.append(
|
||
send_get_request(
|
||
f"{url}/models",
|
||
request.app.state.config.OPENAI_API_KEYS[idx],
|
||
user=user,
|
||
)
|
||
)
|
||
else:
|
||
api_config = request.app.state.config.OPENAI_API_CONFIGS.get(
|
||
str(idx),
|
||
request.app.state.config.OPENAI_API_CONFIGS.get(
|
||
url, {}
|
||
), # Legacy support
|
||
)
|
||
|
||
enable = api_config.get("enable", True)
|
||
model_ids = api_config.get("model_ids", [])
|
||
|
||
if enable:
|
||
if len(model_ids) == 0:
|
||
request_tasks.append(
|
||
send_get_request(
|
||
f"{url}/models",
|
||
request.app.state.config.OPENAI_API_KEYS[idx],
|
||
user=user,
|
||
)
|
||
)
|
||
else:
|
||
model_list = {
|
||
"object": "list",
|
||
"data": [
|
||
{
|
||
"id": model_id,
|
||
"name": model_id,
|
||
"owned_by": "openai",
|
||
"openai": {"id": model_id},
|
||
"urlIdx": idx,
|
||
}
|
||
for model_id in model_ids
|
||
],
|
||
}
|
||
|
||
request_tasks.append(
|
||
asyncio.ensure_future(asyncio.sleep(0, model_list))
|
||
)
|
||
else:
|
||
request_tasks.append(asyncio.ensure_future(asyncio.sleep(0, None)))
|
||
|
||
responses = await asyncio.gather(*request_tasks)
|
||
|
||
for idx, response in enumerate(responses):
|
||
if response:
|
||
url = request.app.state.config.OPENAI_API_BASE_URLS[idx]
|
||
api_config = request.app.state.config.OPENAI_API_CONFIGS.get(
|
||
str(idx),
|
||
request.app.state.config.OPENAI_API_CONFIGS.get(
|
||
url, {}
|
||
), # Legacy support
|
||
)
|
||
|
||
connection_type = api_config.get("connection_type", "external")
|
||
prefix_id = api_config.get("prefix_id", None)
|
||
tags = api_config.get("tags", [])
|
||
|
||
model_list = (
|
||
response if isinstance(response, list) else response.get("data", [])
|
||
)
|
||
if not isinstance(model_list, list):
|
||
# Catch non-list responses
|
||
model_list = []
|
||
|
||
for model in model_list:
|
||
# Remove name key if its value is None #16689
|
||
if "name" in model and model["name"] is None:
|
||
del model["name"]
|
||
|
||
if prefix_id:
|
||
model["id"] = (
|
||
f"{prefix_id}.{model.get('id', model.get('name', ''))}"
|
||
)
|
||
|
||
if tags:
|
||
model["tags"] = tags
|
||
|
||
if connection_type:
|
||
model["connection_type"] = connection_type
|
||
|
||
log.debug(f"get_all_models:responses() {responses}")
|
||
return responses
|
||
|
||
|
||
async def get_filtered_models(models, user):
|
||
# Filter models based on user access control
|
||
filtered_models = []
|
||
for model in models.get("data", []):
|
||
model_info = Models.get_model_by_id(model["id"])
|
||
if model_info:
|
||
if user.id == model_info.user_id or has_access(
|
||
user.id, type="read", access_control=model_info.access_control
|
||
):
|
||
filtered_models.append(model)
|
||
return filtered_models
|
||
|
||
|
||
@cached(
|
||
ttl=MODELS_CACHE_TTL,
|
||
key=lambda _, user: f"openai_all_models_{user.id}" if user else "openai_all_models",
|
||
)
|
||
async def get_all_models(request: Request, user: UserModel) -> dict[str, list]:
|
||
log.info("get_all_models()")
|
||
|
||
if not request.app.state.config.ENABLE_OPENAI_API:
|
||
return {"data": []}
|
||
|
||
responses = await get_all_models_responses(request, user=user)
|
||
|
||
def extract_data(response):
|
||
if response and "data" in response:
|
||
return response["data"]
|
||
if isinstance(response, list):
|
||
return response
|
||
return None
|
||
|
||
def merge_models_lists(model_lists):
|
||
log.debug(f"merge_models_lists {model_lists}")
|
||
merged_list = []
|
||
|
||
for idx, models in enumerate(model_lists):
|
||
if models is not None and "error" not in models:
|
||
|
||
merged_list.extend(
|
||
[
|
||
{
|
||
**model,
|
||
"name": model.get("name", model["id"]),
|
||
"owned_by": "openai",
|
||
"openai": model,
|
||
"connection_type": model.get("connection_type", "external"),
|
||
"urlIdx": idx,
|
||
}
|
||
for model in models
|
||
if (model.get("id") or model.get("name"))
|
||
and (
|
||
"api.openai.com"
|
||
not in request.app.state.config.OPENAI_API_BASE_URLS[idx]
|
||
or not any(
|
||
name in model["id"]
|
||
for name in [
|
||
"babbage",
|
||
"dall-e",
|
||
"davinci",
|
||
"embedding",
|
||
"tts",
|
||
"whisper",
|
||
]
|
||
)
|
||
)
|
||
]
|
||
)
|
||
|
||
return merged_list
|
||
|
||
models = {"data": merge_models_lists(map(extract_data, responses))}
|
||
log.debug(f"models: {models}")
|
||
|
||
request.app.state.OPENAI_MODELS = {model["id"]: model for model in models["data"]}
|
||
return models
|
||
|
||
|
||
@router.get("/models")
|
||
@router.get("/models/{url_idx}")
|
||
async def get_models(
|
||
request: Request, url_idx: Optional[int] = None, user=Depends(get_verified_user)
|
||
):
|
||
models = {
|
||
"data": [],
|
||
}
|
||
|
||
if url_idx is None:
|
||
models = await get_all_models(request, user=user)
|
||
else:
|
||
url = request.app.state.config.OPENAI_API_BASE_URLS[url_idx]
|
||
key = request.app.state.config.OPENAI_API_KEYS[url_idx]
|
||
|
||
api_config = request.app.state.config.OPENAI_API_CONFIGS.get(
|
||
str(url_idx),
|
||
request.app.state.config.OPENAI_API_CONFIGS.get(url, {}), # Legacy support
|
||
)
|
||
|
||
r = None
|
||
async with aiohttp.ClientSession(
|
||
trust_env=True,
|
||
timeout=aiohttp.ClientTimeout(total=AIOHTTP_CLIENT_TIMEOUT_MODEL_LIST),
|
||
) as session:
|
||
try:
|
||
headers, cookies = await get_headers_and_cookies(
|
||
request, url, key, api_config, user=user
|
||
)
|
||
|
||
if api_config.get("azure", False):
|
||
models = {
|
||
"data": api_config.get("model_ids", []) or [],
|
||
"object": "list",
|
||
}
|
||
else:
|
||
async with session.get(
|
||
f"{url}/models",
|
||
headers=headers,
|
||
cookies=cookies,
|
||
ssl=AIOHTTP_CLIENT_SESSION_SSL,
|
||
) as r:
|
||
if r.status != 200:
|
||
# Extract response error details if available
|
||
error_detail = f"HTTP Error: {r.status}"
|
||
res = await r.json()
|
||
if "error" in res:
|
||
error_detail = f"External Error: {res['error']}"
|
||
raise Exception(error_detail)
|
||
|
||
response_data = await r.json()
|
||
|
||
# Check if we're calling OpenAI API based on the URL
|
||
if "api.openai.com" in url:
|
||
# Filter models according to the specified conditions
|
||
response_data["data"] = [
|
||
model
|
||
for model in response_data.get("data", [])
|
||
if not any(
|
||
name in model["id"]
|
||
for name in [
|
||
"babbage",
|
||
"dall-e",
|
||
"davinci",
|
||
"embedding",
|
||
"tts",
|
||
"whisper",
|
||
]
|
||
)
|
||
]
|
||
|
||
models = response_data
|
||
except aiohttp.ClientError as e:
|
||
# ClientError covers all aiohttp requests issues
|
||
log.exception(f"Client error: {str(e)}")
|
||
raise HTTPException(
|
||
status_code=500, detail="Cakumi: Server Connection Error"
|
||
)
|
||
except Exception as e:
|
||
log.exception(f"Unexpected error: {e}")
|
||
error_detail = f"Unexpected error: {str(e)}"
|
||
raise HTTPException(status_code=500, detail=error_detail)
|
||
|
||
if user.role == "user" and not BYPASS_MODEL_ACCESS_CONTROL:
|
||
models["data"] = await get_filtered_models(models, user)
|
||
|
||
return models
|
||
|
||
|
||
class ConnectionVerificationForm(BaseModel):
|
||
url: str
|
||
key: str
|
||
|
||
config: Optional[dict] = None
|
||
|
||
|
||
@router.post("/verify")
|
||
async def verify_connection(
|
||
request: Request,
|
||
form_data: ConnectionVerificationForm,
|
||
user=Depends(get_admin_user),
|
||
):
|
||
url = form_data.url
|
||
key = form_data.key
|
||
|
||
api_config = form_data.config or {}
|
||
|
||
async with aiohttp.ClientSession(
|
||
trust_env=True,
|
||
timeout=aiohttp.ClientTimeout(total=AIOHTTP_CLIENT_TIMEOUT_MODEL_LIST),
|
||
) as session:
|
||
try:
|
||
headers, cookies = await get_headers_and_cookies(
|
||
request, url, key, api_config, user=user
|
||
)
|
||
|
||
if api_config.get("azure", False):
|
||
# Only set api-key header if not using Azure Entra ID authentication
|
||
auth_type = api_config.get("auth_type", "bearer")
|
||
if auth_type not in ("azure_ad", "microsoft_entra_id"):
|
||
headers["api-key"] = key
|
||
|
||
api_version = api_config.get("api_version", "") or "2023-03-15-preview"
|
||
async with session.get(
|
||
url=f"{url}/openai/models?api-version={api_version}",
|
||
headers=headers,
|
||
cookies=cookies,
|
||
ssl=AIOHTTP_CLIENT_SESSION_SSL,
|
||
) as r:
|
||
try:
|
||
response_data = await r.json()
|
||
except Exception:
|
||
response_data = await r.text()
|
||
|
||
if r.status != 200:
|
||
if isinstance(response_data, (dict, list)):
|
||
return JSONResponse(
|
||
status_code=r.status, content=response_data
|
||
)
|
||
else:
|
||
return PlainTextResponse(
|
||
status_code=r.status, content=response_data
|
||
)
|
||
|
||
return response_data
|
||
else:
|
||
async with session.get(
|
||
f"{url}/models",
|
||
headers=headers,
|
||
cookies=cookies,
|
||
ssl=AIOHTTP_CLIENT_SESSION_SSL,
|
||
) as r:
|
||
try:
|
||
response_data = await r.json()
|
||
except Exception:
|
||
response_data = await r.text()
|
||
|
||
if r.status != 200:
|
||
if isinstance(response_data, (dict, list)):
|
||
return JSONResponse(
|
||
status_code=r.status, content=response_data
|
||
)
|
||
else:
|
||
return PlainTextResponse(
|
||
status_code=r.status, content=response_data
|
||
)
|
||
|
||
return response_data
|
||
|
||
except aiohttp.ClientError as e:
|
||
# ClientError covers all aiohttp requests issues
|
||
log.exception(f"Client error: {str(e)}")
|
||
raise HTTPException(
|
||
status_code=500, detail="Cakumi: Server Connection Error"
|
||
)
|
||
except Exception as e:
|
||
log.exception(f"Unexpected error: {e}")
|
||
raise HTTPException(
|
||
status_code=500, detail="Cakumi: Server Connection Error"
|
||
)
|
||
|
||
|
||
def get_azure_allowed_params(api_version: str) -> set[str]:
|
||
allowed_params = {
|
||
"messages",
|
||
"temperature",
|
||
"role",
|
||
"content",
|
||
"contentPart",
|
||
"contentPartImage",
|
||
"enhancements",
|
||
"dataSources",
|
||
"n",
|
||
"stream",
|
||
"stop",
|
||
"max_tokens",
|
||
"presence_penalty",
|
||
"frequency_penalty",
|
||
"logit_bias",
|
||
"user",
|
||
"function_call",
|
||
"functions",
|
||
"tools",
|
||
"tool_choice",
|
||
"top_p",
|
||
"log_probs",
|
||
"top_logprobs",
|
||
"response_format",
|
||
"seed",
|
||
"max_completion_tokens",
|
||
}
|
||
|
||
try:
|
||
if api_version >= "2024-09-01-preview":
|
||
allowed_params.add("stream_options")
|
||
except ValueError:
|
||
log.debug(
|
||
f"Invalid API version {api_version} for Azure OpenAI. Defaulting to allowed parameters."
|
||
)
|
||
|
||
return allowed_params
|
||
|
||
|
||
def is_openai_reasoning_model(model: str) -> bool:
|
||
return model.lower().startswith(("o1", "o3", "o4", "gpt-5"))
|
||
|
||
|
||
def convert_to_azure_payload(url, payload: dict, api_version: str):
|
||
model = payload.get("model", "")
|
||
|
||
# Filter allowed parameters based on Azure OpenAI API
|
||
allowed_params = get_azure_allowed_params(api_version)
|
||
|
||
# Special handling for o-series models
|
||
if is_openai_reasoning_model(model):
|
||
# Convert max_tokens to max_completion_tokens for o-series models
|
||
if "max_tokens" in payload:
|
||
payload["max_completion_tokens"] = payload["max_tokens"]
|
||
del payload["max_tokens"]
|
||
|
||
# Remove temperature if not 1 for o-series models
|
||
if "temperature" in payload and payload["temperature"] != 1:
|
||
log.debug(
|
||
f"Removing temperature parameter for o-series model {model} as only default value (1) is supported"
|
||
)
|
||
del payload["temperature"]
|
||
|
||
# Filter out unsupported parameters
|
||
payload = {k: v for k, v in payload.items() if k in allowed_params}
|
||
|
||
url = f"{url}/openai/deployments/{model}"
|
||
return url, payload
|
||
|
||
|
||
@router.post("/chat/completions")
|
||
async def generate_chat_completion(
|
||
request: Request,
|
||
form_data: dict,
|
||
user=Depends(get_verified_user),
|
||
bypass_filter: Optional[bool] = False,
|
||
chatting_completion: bool = False
|
||
):
|
||
"""
|
||
OpenAI 兼容的聊天完成端点 - 直接转发请求到 OpenAI API 或兼容服务
|
||
|
||
这是 OpenAI router 中的底层 API 调用函数，负责：
|
||
1. 应用模型配置（base_model_id, system prompt, 参数覆盖）
|
||
2. 验证用户权限（模型访问控制）
|
||
3. 处理 Azure OpenAI 特殊格式转换
|
||
4. 处理推理模型（reasoning model）特殊逻辑
|
||
5. 转发 HTTP 请求到上游 API（支持流式和非流式）
|
||
|
||
Args:
|
||
request: FastAPI Request 对象
|
||
form_data: OpenAI 格式的聊天请求
|
||
- model: 模型 ID
|
||
- messages: 消息列表
|
||
- stream: 是否流式响应
|
||
- temperature, max_tokens 等参数
|
||
user: 已验证的用户对象
|
||
bypass_filter: 是否绕过权限检查
|
||
|
||
Returns:
|
||
- 流式: StreamingResponse (SSE)
|
||
- 非流式: dict (OpenAI JSON 格式)
|
||
|
||
Raises:
|
||
HTTPException 403: 无权限访问模型
|
||
HTTPException 404: 模型不存在
|
||
HTTPException 500: 上游 API 连接失败
|
||
"""
|
||
|
||
# print("user:", user)
|
||
# user:
|
||
# id='55f85fb0-4aca-48bc-aea1-afce50ac989e'
|
||
# name='gaofeng1'
|
||
# email='h.summit1628935449@gmail.com'
|
||
# username=None
|
||
# role='user'
|
||
# profile_image_url='data:image/png;base64,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'
|
||
# bio=None
|
||
# gender=None
|
||
# date_of_birth=None
|
||
# info=None
|
||
# settings=UserSettings(ui={'memory': True})
|
||
# api_key=None
|
||
# oauth_sub=None
|
||
# last_active_at=1763997832
|
||
# updated_at=1763971141
|
||
# created_at=1763874812
|
||
|
||
# === 1. 准备 Payload 和清理内部参数 ===
|
||
payload = {**form_data}
|
||
metadata = payload.pop("metadata", None)
|
||
|
||
# 清理掉上游 API 不认识的、仅供后端内部逻辑使用的参数，避免请求被拒绝
|
||
payload.pop("is_user_model", None)
|
||
payload.pop("model_item", None)
|
||
|
||
model_id = form_data.get("model")
|
||
|
||
# === 2. 动态凭据和配置选择 ===
|
||
# 初始化所有后续逻辑需要用到的变量
|
||
url, key, api_config, model, model_info = None, None, {}, None, None
|
||
|
||
# 通过检查 request.state.direct 标志，来区分是“私有模型”还是“普通模型”
|
||
if getattr(request.state, "direct", False) and hasattr(request.state, "model"):
|
||
# --- 私有模型路径 ---
|
||
# 对于私有模型（由上游函数识别并标记），直接从 request.state 中提取其独立的凭据和配置
|
||
direct_model_config = request.state.model
|
||
url = direct_model_config.get("base_url")
|
||
key = direct_model_config.get("api_key")
|
||
api_config = direct_model_config.get("config") or {} # 保证 api_config 始终是字典，避免 NoneType 错误
|
||
|
||
# 私有模型没有数据库中的 model_info 记录，但其本身（direct_model_config）就是完整的模型定义
|
||
model_info = None
|
||
model = direct_model_config
|
||
|
||
# 健壮性检查：如果私有模型未提供 URL，则回退到使用第一个全局配置的 URL
|
||
if not url:
|
||
url = request.app.state.config.OPENAI_API_BASE_URLS[0]
|
||
# 如果私有模型也未提供 Key，则同时回退到使用全局 Key
|
||
if not key:
|
||
key = request.app.state.config.OPENAI_API_KEYS[0]
|
||
else:
|
||
# --- 普通平台模型路径 ---
|
||
# 保持原始逻辑，从数据库和全局配置中获取模型的凭据和设置
|
||
model_info = Models.get_model_by_id(model_id)
|
||
if model_info:
|
||
# 如果模型配置了 base_model_id，则实际请求时使用基础模型
|
||
if model_info.base_model_id:
|
||
payload["model"] = model_info.base_model_id
|
||
model_id = model_info.base_model_id
|
||
|
||
# 应用数据库中为该模型保存的特定参数（如 temperature, system_prompt 等）
|
||
params = model_info.params.model_dump()
|
||
if params:
|
||
system = params.pop("system", None)
|
||
payload = apply_model_params_to_body_openai(params, payload)
|
||
payload = apply_system_prompt_to_body(system, payload, metadata, user)
|
||
|
||
# 权限检查
|
||
if not bypass_filter and user.role == "user":
|
||
if not (user.id == model_info.user_id or has_access(user.id, type="read", access_control=model_info.access_control)):
|
||
raise HTTPException(status_code=403, detail="Model not found")
|
||
elif not bypass_filter and user.role != "admin":
|
||
raise HTTPException(status_code=403, detail="Model not found")
|
||
|
||
# 从缓存的平台模型列表中查找模型，以确定其所属的 API (urlIdx)
|
||
await get_all_models(request, user=user)
|
||
model = request.app.state.OPENAI_MODELS.get(model_id)
|
||
if model:
|
||
idx = model["urlIdx"]
|
||
else:
|
||
raise HTTPException(status_code=404, detail=f"Model not found: {model_id}")
|
||
|
||
# 根据索引从全局配置中获取 url, key 和 api_config
|
||
url = request.app.state.config.OPENAI_API_BASE_URLS[idx]
|
||
key = request.app.state.config.OPENAI_API_KEYS[idx]
|
||
api_config = request.app.state.config.OPENAI_API_CONFIGS.get(
|
||
str(idx),
|
||
request.app.state.config.OPENAI_API_CONFIGS.get(url, {}), # Legacy support
|
||
)
|
||
|
||
# === 3. 应用通用配置和特殊处理 ===
|
||
# 移除模型 ID 的前缀（如果配置了）
|
||
prefix_id = api_config.get("prefix_id", None)
|
||
if prefix_id:
|
||
payload["model"] = payload["model"].replace(f"{prefix_id}.", "")
|
||
|
||
# 如果是 Pipeline 类型的模型，注入用户信息
|
||
if model and "pipeline" in model and model.get("pipeline"):
|
||
payload["user"] = {
|
||
"name": user.name,
|
||
"id": user.id,
|
||
"email": user.email,
|
||
"role": user.role,
|
||
}
|
||
|
||
# === 7. 推理模型特殊处理 ===
|
||
# Check if model is a reasoning model that needs special handling
|
||
if is_openai_reasoning_model(payload["model"]):
|
||
# 推理模型（如 o1）使用 max_completion_tokens 而非 max_tokens
|
||
payload = openai_reasoning_model_handler(payload)
|
||
elif "api.openai.com" not in url:
|
||
# 非 OpenAI 官方 API：向后兼容，将 max_completion_tokens 转为 max_tokens
|
||
# Remove "max_completion_tokens" from the payload for backward compatibility
|
||
if "max_completion_tokens" in payload:
|
||
payload["max_tokens"] = payload["max_completion_tokens"]
|
||
del payload["max_completion_tokens"]
|
||
|
||
# 避免同时存在 max_tokens 和 max_completion_tokens
|
||
if "max_tokens" in payload and "max_completion_tokens" in payload:
|
||
del payload["max_tokens"]
|
||
|
||
# === 8. 转换 logit_bias 格式 ===
|
||
# Convert the modified body back to JSON
|
||
if "logit_bias" in payload:
|
||
payload["logit_bias"] = json.loads(
|
||
convert_logit_bias_input_to_json(payload["logit_bias"])
|
||
)
|
||
|
||
# === 9. 准备请求头和 Cookies ===
|
||
headers, cookies = await get_headers_and_cookies(
|
||
request, url, key, api_config, metadata, user=user
|
||
)
|
||
|
||
# === 10. Azure OpenAI 特殊处理 ===
|
||
if api_config.get("azure", False):
|
||
api_version = api_config.get("api_version", "2023-03-15-preview")
|
||
request_url, payload = convert_to_azure_payload(url, payload, api_version)
|
||
|
||
# 只有在非 Azure Entra ID 认证时才设置 api-key header
|
||
# Only set api-key header if not using Azure Entra ID authentication
|
||
auth_type = api_config.get("auth_type", "bearer")
|
||
if auth_type not in ("azure_ad", "microsoft_entra_id"):
|
||
headers["api-key"] = key
|
||
|
||
headers["api-version"] = api_version
|
||
request_url = f"{request_url}/chat/completions?api-version={api_version}"
|
||
else:
|
||
# 标准 OpenAI 兼容 API
|
||
request_url = f"{url}/chat/completions"
|
||
|
||
if chatting_completion:
|
||
try:
|
||
# 可选钩子：在发送到上游前记录/审计 payload，需自行实现 last_process_payload
|
||
log.debug(
|
||
f"chatting_completion hook user={user.id} chat_id={metadata.get('chat_id')} model={payload.get('model')}"
|
||
)
|
||
except Exception as e:
|
||
log.debug(f"chatting_completion 钩子执行失败: {e}")
|
||
|
||
|
||
# 移除上游不识别的内部参数
|
||
for key in [
|
||
"is_user_model",
|
||
"variables",
|
||
"model_item",
|
||
"background_tasks",
|
||
"chat_id",
|
||
"id",
|
||
"message_id",
|
||
"session_id",
|
||
"filter_ids",
|
||
"tool_servers",
|
||
]:
|
||
payload.pop(key, None)
|
||
|
||
payload = json.dumps(payload) # 序列化为 JSON 字符串
|
||
|
||
# === 11. 预扣费：流式请求启动前 ===
|
||
precharge_id = None
|
||
estimated_prompt = 0
|
||
if form_data.get("stream", False): # 只对流式请求预扣费
|
||
from open_webui.utils.billing import estimate_prompt_tokens, precharge_balance
|
||
|
||
try:
|
||
# 1. tiktoken预估prompt tokens
|
||
messages = form_data.get("messages", [])
|
||
estimated_prompt = estimate_prompt_tokens(messages, model_id)
|
||
|
||
# 2. 获取max_tokens参数（默认4096）
|
||
max_completion = form_data.get("max_completion_tokens") or form_data.get("max_tokens", 4096)
|
||
|
||
# 3. 预扣费
|
||
precharge_id, precharged_cost, balance_after = precharge_balance(
|
||
user_id=user.id,
|
||
model_id=model_id,
|
||
estimated_prompt_tokens=estimated_prompt,
|
||
max_completion_tokens=max_completion
|
||
)
|
||
|
||
log.info(
|
||
f"预扣费成功: user={user.id} model={model_id} "
|
||
f"estimated={estimated_prompt}+{max_completion}tokens "
|
||
f"cost={precharged_cost / 10000:.4f}元 precharge_id={precharge_id}"
|
||
)
|
||
except HTTPException as e:
|
||
# 余额不足或账户冻结，直接抛出阻止请求
|
||
raise e
|
||
except Exception as e:
|
||
# 预扣费失败（如数据库错误、计费服务异常），降级为后付费
|
||
log.error(
|
||
f"预扣费失败，降级为后付费: user={user.id} model={model_id} "
|
||
f"estimated={estimated_prompt}+{max_completion}tokens "
|
||
f"error={type(e).__name__}: {str(e)}",
|
||
exc_info=True # 打印完整堆栈
|
||
)
|
||
precharge_id = None
|
||
|
||
# === 12. 初始化请求状态变量 ===
|
||
r = None
|
||
session = None
|
||
streaming = False
|
||
response = None
|
||
|
||
try:
|
||
# === 12. 发起 HTTP 请求到上游 API ===
|
||
session = aiohttp.ClientSession(
|
||
trust_env=True, timeout=aiohttp.ClientTimeout(total=AIOHTTP_CLIENT_TIMEOUT)
|
||
)
|
||
|
||
r = await session.request(
|
||
method="POST",
|
||
url=request_url,
|
||
data=payload,
|
||
headers=headers,
|
||
cookies=cookies,
|
||
ssl=AIOHTTP_CLIENT_SESSION_SSL,
|
||
)
|
||
|
||
# === 13. 处理响应 ===
|
||
# Check if response is SSE
|
||
if "text/event-stream" in r.headers.get("Content-Type", ""):
|
||
# 流式响应：添加计费包装器
|
||
streaming = True
|
||
|
||
# 创建计费包装的流式生成器
|
||
async def stream_with_billing(
|
||
user_id: str,
|
||
model_id: str,
|
||
stream,
|
||
precharge_id: Optional[str],
|
||
estimated_prompt: int = 0
|
||
):
|
||
"""
|
||
流式响应计费包装器：预扣费模式下精确结算
|
||
|
||
Args:
|
||
precharge_id: 预扣费事务ID（None表示降级为后付费）
|
||
estimated_prompt: 预估的prompt tokens（用于fallback）
|
||
"""
|
||
import asyncio
|
||
from open_webui.utils.billing import deduct_balance, settle_precharge
|
||
|
||
accumulated = {"prompt": 0, "completion": 0}
|
||
has_usage_data = False
|
||
|
||
try:
|
||
# 1. 转发流式数据，累积 tokens
|
||
async for chunk in stream:
|
||
if b"data: " in chunk:
|
||
try:
|
||
data_str = chunk.decode().replace("data: ", "").strip()
|
||
if data_str and data_str != "[DONE]":
|
||
data = json.loads(data_str)
|
||
if "usage" in data:
|
||
has_usage_data = True
|
||
# 修复bug：使用max()避免覆盖
|
||
accumulated["prompt"] = max(
|
||
accumulated["prompt"],
|
||
data["usage"].get("prompt_tokens", 0)
|
||
)
|
||
accumulated["completion"] += data["usage"].get("completion_tokens", 0)
|
||
except Exception:
|
||
pass
|
||
yield chunk
|
||
|
||
except asyncio.CancelledError:
|
||
# 客户端断开连接（用户取消）
|
||
log.info(f"流式请求被取消: user={user_id} model={model_id}")
|
||
raise # 继续抛出，确保finally块执行
|
||
|
||
finally:
|
||
# 2. 精确结算（无论正常结束还是中断）
|
||
try:
|
||
if precharge_id:
|
||
# === 预扣费模式：精确结算 ===
|
||
|
||
# Fallback：如果没有收到usage，使用预估值
|
||
if not has_usage_data or accumulated["prompt"] == 0:
|
||
log.warning(f"未收到usage信息，使用预估值: precharge_id={precharge_id}")
|
||
accumulated["prompt"] = estimated_prompt
|
||
|
||
# 结算
|
||
actual_cost, refund, balance_after = settle_precharge(
|
||
precharge_id=precharge_id,
|
||
actual_prompt_tokens=accumulated["prompt"],
|
||
actual_completion_tokens=accumulated["completion"]
|
||
)
|
||
|
||
log.info(
|
||
f"结算完成: user={user_id} precharge_id={precharge_id} "
|
||
f"actual={accumulated['prompt']}+{accumulated['completion']}tokens "
|
||
f"cost={actual_cost / 10000:.4f}元 refund={refund / 10000:.4f}元"
|
||
)
|
||
|
||
elif accumulated["prompt"] > 0 or accumulated["completion"] > 0:
|
||
# === 降级后付费模式：直接扣费 ===
|
||
# 注意：此分支说明预扣费失败，使用后付费降级方案
|
||
cost, balance_after = deduct_balance(
|
||
user_id=user_id,
|
||
model_id=model_id,
|
||
prompt_tokens=accumulated["prompt"],
|
||
completion_tokens=accumulated["completion"],
|
||
log_type="deduct"
|
||
)
|
||
log.warning(
|
||
f"降级后付费扣费（预扣费失败）: user={user_id} model={model_id} "
|
||
f"actual={accumulated['prompt']}+{accumulated['completion']}tokens "
|
||
f"cost={cost / 10000:.4f}元 balance={balance_after / 10000:.4f}元"
|
||
)
|
||
|
||
except Exception as e:
|
||
log.error(f"计费结算异常: {e}", exc_info=True)
|
||
|
||
return StreamingResponse(
|
||
stream_with_billing(
|
||
user.id,
|
||
form_data.get("model", "unknown"),
|
||
r.content,
|
||
precharge_id,
|
||
estimated_prompt
|
||
),
|
||
status_code=r.status,
|
||
headers=dict(r.headers),
|
||
background=BackgroundTask(
|
||
cleanup_response, response=r, session=session
|
||
),
|
||
)
|
||
else:
|
||
# 非流式响应：解析 JSON
|
||
try:
|
||
response = await r.json()
|
||
except Exception as e:
|
||
log.error(e)
|
||
response = await r.text() # 如果 JSON 解析失败，返回纯文本
|
||
|
||
# 处理错误响应
|
||
if r.status >= 400:
|
||
# 回滚预扣费（如果已预扣）
|
||
if precharge_id:
|
||
from open_webui.utils.billing import settle_precharge
|
||
try:
|
||
settle_precharge(precharge_id, 0, 0) # 全额退款
|
||
log.info(f"API错误，预扣费已退款: precharge_id={precharge_id}")
|
||
except Exception as e:
|
||
log.error(f"预扣费回滚失败: {e}")
|
||
|
||
if isinstance(response, (dict, list)):
|
||
return JSONResponse(status_code=r.status, content=response)
|
||
else:
|
||
return PlainTextResponse(status_code=r.status, content=response)
|
||
|
||
# === 计费：非流式响应 ===
|
||
if isinstance(response, dict) and "usage" in response:
|
||
try:
|
||
from open_webui.utils.billing import deduct_balance
|
||
|
||
usage = response["usage"]
|
||
cost, balance = deduct_balance(
|
||
user_id=user.id,
|
||
model_id=form_data.get("model", "unknown"),
|
||
prompt_tokens=usage.get("prompt_tokens", 0),
|
||
completion_tokens=usage.get("completion_tokens", 0),
|
||
)
|
||
# 添加计费信息到响应（可选）
|
||
response["billing"] = {
|
||
"cost": float(cost),
|
||
"balance": float(balance),
|
||
}
|
||
log.info(
|
||
f"非流式请求计费成功: user={user.id} model={form_data.get('model')} "
|
||
f"tokens={usage.get('prompt_tokens', 0)}+{usage.get('completion_tokens', 0)} "
|
||
f"cost={cost / 10000:.4f}元 balance={balance / 10000:.4f}元"
|
||
)
|
||
except HTTPException as e:
|
||
# 余额不足等错误直接抛出，中断响应
|
||
log.error(f"非流式请求计费失败（业务异常）: {e.detail}")
|
||
raise e
|
||
except Exception as e:
|
||
# 其他计费错误仅记录日志，不中断响应
|
||
log.error(
|
||
f"非流式请求计费异常（系统异常）: user={user.id} model={form_data.get('model')} "
|
||
f"error={type(e).__name__}: {str(e)}",
|
||
exc_info=True
|
||
)
|
||
|
||
return response # 成功响应
|
||
|
||
except Exception as e:
|
||
log.exception(e)
|
||
|
||
raise HTTPException(
|
||
status_code=r.status if r else 500,
|
||
detail="Cakumi: Server Connection Error",
|
||
)
|
||
finally:
|
||
# === 14. 清理资源 ===
|
||
# 非流式响应需要手动关闭连接（流式响应在 BackgroundTask 中处理）
|
||
if not streaming:
|
||
await cleanup_response(r, session)
|
||
|
||
|
||
async def embeddings(request: Request, form_data: dict, user):
|
||
"""
|
||
Calls the embeddings endpoint for OpenAI-compatible providers.
|
||
|
||
Args:
|
||
request (Request): The FastAPI request context.
|
||
form_data (dict): OpenAI-compatible embeddings payload.
|
||
user (UserModel): The authenticated user.
|
||
|
||
Returns:
|
||
dict: OpenAI-compatible embeddings response.
|
||
"""
|
||
idx = 0
|
||
# Prepare payload/body
|
||
body = json.dumps(form_data)
|
||
# Find correct backend url/key based on model
|
||
await get_all_models(request, user=user)
|
||
model_id = form_data.get("model")
|
||
models = request.app.state.OPENAI_MODELS
|
||
if model_id in models:
|
||
idx = models[model_id]["urlIdx"]
|
||
|
||
url = request.app.state.config.OPENAI_API_BASE_URLS[idx]
|
||
key = request.app.state.config.OPENAI_API_KEYS[idx]
|
||
api_config = request.app.state.config.OPENAI_API_CONFIGS.get(
|
||
str(idx),
|
||
request.app.state.config.OPENAI_API_CONFIGS.get(url, {}), # Legacy support
|
||
)
|
||
|
||
r = None
|
||
session = None
|
||
streaming = False
|
||
|
||
headers, cookies = await get_headers_and_cookies(
|
||
request, url, key, api_config, user=user
|
||
)
|
||
try:
|
||
session = aiohttp.ClientSession(trust_env=True)
|
||
r = await session.request(
|
||
method="POST",
|
||
url=f"{url}/embeddings",
|
||
data=body,
|
||
headers=headers,
|
||
cookies=cookies,
|
||
)
|
||
|
||
if "text/event-stream" in r.headers.get("Content-Type", ""):
|
||
streaming = True
|
||
return StreamingResponse(
|
||
r.content,
|
||
status_code=r.status,
|
||
headers=dict(r.headers),
|
||
background=BackgroundTask(
|
||
cleanup_response, response=r, session=session
|
||
),
|
||
)
|
||
else:
|
||
try:
|
||
response_data = await r.json()
|
||
except Exception:
|
||
response_data = await r.text()
|
||
|
||
if r.status >= 400:
|
||
if isinstance(response_data, (dict, list)):
|
||
return JSONResponse(status_code=r.status, content=response_data)
|
||
else:
|
||
return PlainTextResponse(
|
||
status_code=r.status, content=response_data
|
||
)
|
||
|
||
return response_data
|
||
except Exception as e:
|
||
log.exception(e)
|
||
raise HTTPException(
|
||
status_code=r.status if r else 500,
|
||
detail="Cakumi: Server Connection Error",
|
||
)
|
||
finally:
|
||
if not streaming:
|
||
await cleanup_response(r, session)
|
||
|
||
|
||
@router.api_route("/{path:path}", methods=["GET", "POST", "PUT", "DELETE"])
|
||
async def proxy(path: str, request: Request, user=Depends(get_verified_user)):
|
||
"""
|
||
Deprecated: proxy all requests to OpenAI API
|
||
"""
|
||
|
||
body = await request.body()
|
||
|
||
idx = 0
|
||
url = request.app.state.config.OPENAI_API_BASE_URLS[idx]
|
||
key = request.app.state.config.OPENAI_API_KEYS[idx]
|
||
api_config = request.app.state.config.OPENAI_API_CONFIGS.get(
|
||
str(idx),
|
||
request.app.state.config.OPENAI_API_CONFIGS.get(
|
||
request.app.state.config.OPENAI_API_BASE_URLS[idx], {}
|
||
), # Legacy support
|
||
)
|
||
|
||
r = None
|
||
session = None
|
||
streaming = False
|
||
|
||
try:
|
||
headers, cookies = await get_headers_and_cookies(
|
||
request, url, key, api_config, user=user
|
||
)
|
||
|
||
if api_config.get("azure", False):
|
||
api_version = api_config.get("api_version", "2023-03-15-preview")
|
||
|
||
# Only set api-key header if not using Azure Entra ID authentication
|
||
auth_type = api_config.get("auth_type", "bearer")
|
||
if auth_type not in ("azure_ad", "microsoft_entra_id"):
|
||
headers["api-key"] = key
|
||
|
||
headers["api-version"] = api_version
|
||
|
||
payload = json.loads(body)
|
||
url, payload = convert_to_azure_payload(url, payload, api_version)
|
||
body = json.dumps(payload).encode()
|
||
|
||
request_url = f"{url}/{path}?api-version={api_version}"
|
||
else:
|
||
request_url = f"{url}/{path}"
|
||
|
||
session = aiohttp.ClientSession(trust_env=True)
|
||
r = await session.request(
|
||
method=request.method,
|
||
url=request_url,
|
||
data=body,
|
||
headers=headers,
|
||
cookies=cookies,
|
||
ssl=AIOHTTP_CLIENT_SESSION_SSL,
|
||
)
|
||
|
||
# Check if response is SSE
|
||
if "text/event-stream" in r.headers.get("Content-Type", ""):
|
||
streaming = True
|
||
return StreamingResponse(
|
||
r.content,
|
||
status_code=r.status,
|
||
headers=dict(r.headers),
|
||
background=BackgroundTask(
|
||
cleanup_response, response=r, session=session
|
||
),
|
||
)
|
||
else:
|
||
try:
|
||
response_data = await r.json()
|
||
except Exception:
|
||
response_data = await r.text()
|
||
|
||
if r.status >= 400:
|
||
if isinstance(response_data, (dict, list)):
|
||
return JSONResponse(status_code=r.status, content=response_data)
|
||
else:
|
||
return PlainTextResponse(
|
||
status_code=r.status, content=response_data
|
||
)
|
||
|
||
return response_data
|
||
|
||
except Exception as e:
|
||
log.exception(e)
|
||
raise HTTPException(
|
||
status_code=r.status if r else 500,
|
||
detail="Cakumi: Server Connection Error",
|
||
)
|
||
finally:
|
||
if not streaming:
|
||
await cleanup_response(r, session)
|