mirror of
https://github.com/open-webui/open-webui
synced 2024-11-16 13:40:55 +00:00
454 lines
14 KiB
Python
454 lines
14 KiB
Python
from fastapi import FastAPI, Request, Response, HTTPException, Depends
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from fastapi.middleware.cors import CORSMiddleware
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from fastapi.responses import StreamingResponse, JSONResponse, FileResponse
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import requests
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import aiohttp
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import asyncio
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import json
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import logging
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from pydantic import BaseModel
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from apps.web.models.models import Models
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from apps.web.models.users import Users
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from constants import ERROR_MESSAGES
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from utils.utils import (
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decode_token,
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get_current_user,
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get_verified_user,
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get_admin_user,
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)
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from config import (
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SRC_LOG_LEVELS,
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ENABLE_OPENAI_API,
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OPENAI_API_BASE_URLS,
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OPENAI_API_KEYS,
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CACHE_DIR,
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ENABLE_MODEL_FILTER,
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MODEL_FILTER_LIST,
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AppConfig,
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)
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from typing import List, Optional
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import hashlib
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from pathlib import Path
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log = logging.getLogger(__name__)
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log.setLevel(SRC_LOG_LEVELS["OPENAI"])
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app = FastAPI()
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["*"],
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allow_credentials=True,
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allow_methods=["*"],
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allow_headers=["*"],
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)
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app.state.config = AppConfig()
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app.state.config.ENABLE_MODEL_FILTER = ENABLE_MODEL_FILTER
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app.state.config.MODEL_FILTER_LIST = MODEL_FILTER_LIST
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app.state.config.ENABLE_OPENAI_API = ENABLE_OPENAI_API
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app.state.config.OPENAI_API_BASE_URLS = OPENAI_API_BASE_URLS
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app.state.config.OPENAI_API_KEYS = OPENAI_API_KEYS
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app.state.MODELS = {}
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@app.middleware("http")
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async def check_url(request: Request, call_next):
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if len(app.state.MODELS) == 0:
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await get_all_models()
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else:
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pass
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response = await call_next(request)
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return response
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@app.get("/config")
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async def get_config(user=Depends(get_admin_user)):
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return {"ENABLE_OPENAI_API": app.state.config.ENABLE_OPENAI_API}
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class OpenAIConfigForm(BaseModel):
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enable_openai_api: Optional[bool] = None
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@app.post("/config/update")
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async def update_config(form_data: OpenAIConfigForm, user=Depends(get_admin_user)):
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app.state.config.ENABLE_OPENAI_API = form_data.enable_openai_api
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return {"ENABLE_OPENAI_API": app.state.config.ENABLE_OPENAI_API}
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class UrlsUpdateForm(BaseModel):
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urls: List[str]
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class KeysUpdateForm(BaseModel):
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keys: List[str]
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@app.get("/urls")
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async def get_openai_urls(user=Depends(get_admin_user)):
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return {"OPENAI_API_BASE_URLS": app.state.config.OPENAI_API_BASE_URLS}
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@app.post("/urls/update")
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async def update_openai_urls(form_data: UrlsUpdateForm, user=Depends(get_admin_user)):
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await get_all_models()
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app.state.config.OPENAI_API_BASE_URLS = form_data.urls
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return {"OPENAI_API_BASE_URLS": app.state.config.OPENAI_API_BASE_URLS}
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@app.get("/keys")
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async def get_openai_keys(user=Depends(get_admin_user)):
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return {"OPENAI_API_KEYS": app.state.config.OPENAI_API_KEYS}
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@app.post("/keys/update")
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async def update_openai_key(form_data: KeysUpdateForm, user=Depends(get_admin_user)):
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app.state.config.OPENAI_API_KEYS = form_data.keys
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return {"OPENAI_API_KEYS": app.state.config.OPENAI_API_KEYS}
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@app.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 = app.state.config.OPENAI_API_BASE_URLS.index("https://api.openai.com/v1")
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body = await request.body()
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name = hashlib.sha256(body).hexdigest()
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SPEECH_CACHE_DIR = Path(CACHE_DIR).joinpath("./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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headers = {}
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headers["Authorization"] = f"Bearer {app.state.config.OPENAI_API_KEYS[idx]}"
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headers["Content-Type"] = "application/json"
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if "openrouter.ai" in app.state.config.OPENAI_API_BASE_URLS[idx]:
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headers["HTTP-Referer"] = "https://openwebui.com/"
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headers["X-Title"] = "Open WebUI"
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r = None
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try:
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r = requests.post(
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url=f"{app.state.config.OPENAI_API_BASE_URLS[idx]}/audio/speech",
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data=body,
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headers=headers,
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stream=True,
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)
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r.raise_for_status()
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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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# Return the saved file
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return FileResponse(file_path)
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except Exception as e:
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log.exception(e)
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error_detail = "Open WebUI: Server Connection Error"
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if r is not None:
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try:
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res = r.json()
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if "error" in res:
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error_detail = f"External: {res['error']}"
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except:
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error_detail = f"External: {e}"
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raise HTTPException(
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status_code=r.status_code if r else 500, detail=error_detail
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)
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except ValueError:
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raise HTTPException(status_code=401, detail=ERROR_MESSAGES.OPENAI_NOT_FOUND)
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async def fetch_url(url, key):
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timeout = aiohttp.ClientTimeout(total=5)
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try:
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if key != "":
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headers = {"Authorization": f"Bearer {key}"}
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async with aiohttp.ClientSession(timeout=timeout) as session:
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async with session.get(url, headers=headers) as response:
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return await response.json()
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else:
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return None
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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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def merge_models_lists(model_lists):
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log.info(f"merge_models_lists {model_lists}")
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merged_list = []
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for idx, models in enumerate(model_lists):
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if models is not None and "error" not in models:
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merged_list.extend(
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[
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{
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**model,
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"name": model.get("name", model["id"]),
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"owned_by": "openai",
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"openai": model,
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"urlIdx": idx,
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}
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for model in models
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if "api.openai.com"
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not in app.state.config.OPENAI_API_BASE_URLS[idx]
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or "gpt" in model["id"]
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]
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)
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return merged_list
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async def get_all_models():
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log.info("get_all_models()")
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if (
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len(app.state.config.OPENAI_API_KEYS) == 1
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and app.state.config.OPENAI_API_KEYS[0] == ""
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) or not app.state.config.ENABLE_OPENAI_API:
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models = {"data": []}
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else:
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tasks = [
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fetch_url(f"{url}/models", app.state.config.OPENAI_API_KEYS[idx])
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for idx, url in enumerate(app.state.config.OPENAI_API_BASE_URLS)
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]
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responses = await asyncio.gather(*tasks)
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log.info(f"get_all_models:responses() {responses}")
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models = {
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"data": merge_models_lists(
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list(
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map(
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lambda response: (
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response["data"]
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if (response and "data" in response)
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else (response if isinstance(response, list) else None)
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),
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responses,
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)
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)
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)
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}
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log.info(f"models: {models}")
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app.state.MODELS = {model["id"]: model for model in models["data"]}
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return models
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@app.get("/models")
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@app.get("/models/{url_idx}")
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async def get_models(url_idx: Optional[int] = None, user=Depends(get_current_user)):
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if url_idx == None:
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models = await get_all_models()
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if app.state.config.ENABLE_MODEL_FILTER:
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if user.role == "user":
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models["data"] = list(
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filter(
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lambda model: model["id"] in app.state.config.MODEL_FILTER_LIST,
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models["data"],
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)
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)
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return models
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return models
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else:
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url = app.state.config.OPENAI_API_BASE_URLS[url_idx]
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r = None
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try:
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r = requests.request(method="GET", url=f"{url}/models")
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r.raise_for_status()
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response_data = r.json()
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if "api.openai.com" in url:
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response_data["data"] = list(
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filter(lambda model: "gpt" in model["id"], response_data["data"])
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)
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return response_data
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except Exception as e:
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log.exception(e)
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error_detail = "Open WebUI: Server Connection Error"
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if r is not None:
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try:
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res = r.json()
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if "error" in res:
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error_detail = f"External: {res['error']}"
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except:
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error_detail = f"External: {e}"
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raise HTTPException(
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status_code=r.status_code if r else 500,
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detail=error_detail,
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)
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@app.api_route("/{path:path}", methods=["GET", "POST", "PUT", "DELETE"])
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async def proxy(path: str, request: Request, user=Depends(get_verified_user)):
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idx = 0
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body = await request.body()
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# TODO: Remove below after gpt-4-vision fix from Open AI
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# Try to decode the body of the request from bytes to a UTF-8 string (Require add max_token to fix gpt-4-vision)
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payload = None
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try:
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if "chat/completions" in path:
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body = body.decode("utf-8")
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body = json.loads(body)
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payload = {**body}
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model_id = body.get("model")
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model_info = Models.get_model_by_id(model_id)
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if model_info:
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print(model_info)
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if model_info.base_model_id:
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payload["model"] = model_info.base_model_id
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model_info.params = model_info.params.model_dump()
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if model_info.params:
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payload["temperature"] = model_info.params.get("temperature", None)
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payload["top_p"] = model_info.params.get("top_p", None)
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payload["max_tokens"] = model_info.params.get("max_tokens", None)
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payload["frequency_penalty"] = model_info.params.get(
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"frequency_penalty", None
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)
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payload["seed"] = model_info.params.get("seed", None)
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payload["stop"] = (
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[
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bytes(stop, "utf-8").decode("unicode_escape")
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for stop in model_info.params["stop"]
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]
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if model_info.params.get("stop", None)
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else None
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)
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if model_info.params.get("system", None):
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# Check if the payload already has a system message
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# If not, add a system message to the payload
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if payload.get("messages"):
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for message in payload["messages"]:
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if message.get("role") == "system":
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message["content"] = (
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model_info.params.get("system", None)
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+ message["content"]
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)
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break
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else:
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payload["messages"].insert(
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0,
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{
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"role": "system",
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"content": model_info.params.get("system", None),
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},
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)
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else:
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pass
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print(app.state.MODELS)
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model = app.state.MODELS[payload.get("model")]
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idx = model["urlIdx"]
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if "pipeline" in model and model.get("pipeline"):
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payload["user"] = {"name": user.name, "id": user.id}
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payload["title"] = (
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True
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if payload["stream"] == False and payload["max_tokens"] == 50
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else False
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)
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# Check if the model is "gpt-4-vision-preview" and set "max_tokens" to 4000
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# This is a workaround until OpenAI fixes the issue with this model
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if payload.get("model") == "gpt-4-vision-preview":
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if "max_tokens" not in payload:
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payload["max_tokens"] = 4000
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log.debug("Modified payload:", payload)
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# Convert the modified body back to JSON
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payload = json.dumps(payload)
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except json.JSONDecodeError as e:
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log.error("Error loading request body into a dictionary:", e)
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print(payload)
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url = app.state.config.OPENAI_API_BASE_URLS[idx]
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key = app.state.config.OPENAI_API_KEYS[idx]
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target_url = f"{url}/{path}"
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if key == "":
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raise HTTPException(status_code=401, detail=ERROR_MESSAGES.API_KEY_NOT_FOUND)
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headers = {}
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headers["Authorization"] = f"Bearer {key}"
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headers["Content-Type"] = "application/json"
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r = None
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try:
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r = requests.request(
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method=request.method,
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url=target_url,
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data=payload if payload else body,
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headers=headers,
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stream=True,
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)
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r.raise_for_status()
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# Check if response is SSE
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if "text/event-stream" in r.headers.get("Content-Type", ""):
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return StreamingResponse(
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r.iter_content(chunk_size=8192),
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status_code=r.status_code,
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headers=dict(r.headers),
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)
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else:
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response_data = r.json()
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return response_data
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except Exception as e:
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log.exception(e)
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error_detail = "Open WebUI: Server Connection Error"
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if r is not None:
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try:
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res = r.json()
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if "error" in res:
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error_detail = f"External: {res['error']['message'] if 'message' in res['error'] else res['error']}"
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except:
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error_detail = f"External: {e}"
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raise HTTPException(
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status_code=r.status_code if r else 500, detail=error_detail
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)
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