open-webui/backend/open_webui/routers/openai.py

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import asyncio
import hashlib
import json
import logging
from typing import Optional
import aiohttp
from aiocache import cached
import requests
from urllib.parse import quote
from azure.identity import DefaultAzureCredential, get_bearer_token_provider
from fastapi import Depends, HTTPException, Request, APIRouter
from fastapi.responses import (
FileResponse,
StreamingResponse,
JSONResponse,
PlainTextResponse,
)
from pydantic import BaseModel
from starlette.background import BackgroundTask
from open_webui.models.models import Models
from open_webui.config import (
CACHE_DIR,
)
from open_webui.env import (
MODELS_CACHE_TTL,
AIOHTTP_CLIENT_SESSION_SSL,
AIOHTTP_CLIENT_TIMEOUT,
AIOHTTP_CLIENT_TIMEOUT_MODEL_LIST,
ENABLE_FORWARD_USER_INFO_HEADERS,
BYPASS_MODEL_ACCESS_CONTROL,
)
from open_webui.models.users import UserModel
from open_webui.memory.cross_window_memory import last_process_payload
from open_webui.utils.misc import extract_timestamped_messages
from open_webui.constants import ERROR_MESSAGES
from open_webui.env import SRC_LOG_LEVELS
from open_webui.utils.payload import (
apply_model_params_to_body_openai,
apply_system_prompt_to_body,
)
from open_webui.utils.misc import (
convert_logit_bias_input_to_json,
)
from open_webui.utils.auth import get_admin_user, get_verified_user
from open_webui.utils.access_control import has_access
log = logging.getLogger(__name__)
log.setLevel(SRC_LOG_LEVELS["OPENAI"])
##########################################
#
# Utility functions
#
##########################################
async def send_get_request(url, key=None, user: UserModel = None):
timeout = aiohttp.ClientTimeout(total=AIOHTTP_CLIENT_TIMEOUT_MODEL_LIST)
try:
async with aiohttp.ClientSession(timeout=timeout, trust_env=True) as session:
async with session.get(
url,
headers={
**({"Authorization": f"Bearer {key}"} if key else {}),
**(
{
"X-OpenWebUI-User-Name": quote(user.name, safe=" "),
"X-OpenWebUI-User-Id": user.id,
"X-OpenWebUI-User-Email": user.email,
"X-OpenWebUI-User-Role": user.role,
}
if ENABLE_FORWARD_USER_INFO_HEADERS and user
else {}
),
},
ssl=AIOHTTP_CLIENT_SESSION_SSL,
) as response:
return await response.json()
except Exception as e:
# Handle connection error here
log.error(f"Connection error: {e}")
return None
async def cleanup_response(
response: Optional[aiohttp.ClientResponse],
session: Optional[aiohttp.ClientSession],
):
if response:
response.close()
if session:
await session.close()
def openai_reasoning_model_handler(payload):
"""
Handle reasoning model specific parameters
"""
if "max_tokens" in payload:
# Convert "max_tokens" to "max_completion_tokens" for all reasoning models
payload["max_completion_tokens"] = payload["max_tokens"]
del payload["max_tokens"]
# Handle system role conversion based on model type
if payload["messages"][0]["role"] == "system":
model_lower = payload["model"].lower()
# Legacy models use "user" role instead of "system"
if model_lower.startswith("o1-mini") or model_lower.startswith("o1-preview"):
payload["messages"][0]["role"] = "user"
else:
payload["messages"][0]["role"] = "developer"
return payload
async def get_headers_and_cookies(
request: Request,
url,
key=None,
config=None,
metadata: Optional[dict] = None,
user: UserModel = None,
):
cookies = {}
headers = {
"Content-Type": "application/json",
**(
{
"HTTP-Referer": "https://openwebui.com/",
"X-Title": "CyberLover",
}
if "openrouter.ai" in url
else {}
),
**(
{
"X-OpenWebUI-User-Name": quote(user.name, safe=" "),
"X-OpenWebUI-User-Id": user.id,
"X-OpenWebUI-User-Email": user.email,
"X-OpenWebUI-User-Role": user.role,
**(
{"X-OpenWebUI-Chat-Id": metadata.get("chat_id")}
if metadata and metadata.get("chat_id")
else {}
),
}
if ENABLE_FORWARD_USER_INFO_HEADERS
else {}
),
}
token = None
auth_type = config.get("auth_type")
if auth_type == "bearer" or auth_type is None:
# Default to bearer if not specified
token = f"{key}"
elif auth_type == "none":
token = None
elif auth_type == "session":
cookies = request.cookies
token = request.state.token.credentials
elif auth_type == "system_oauth":
cookies = request.cookies
oauth_token = None
try:
if request.cookies.get("oauth_session_id", None):
oauth_token = await request.app.state.oauth_manager.get_oauth_token(
user.id,
request.cookies.get("oauth_session_id", None),
)
except Exception as e:
log.error(f"Error getting OAuth token: {e}")
if oauth_token:
token = f"{oauth_token.get('access_token', '')}"
elif auth_type in ("azure_ad", "microsoft_entra_id"):
token = get_microsoft_entra_id_access_token()
if token:
headers["Authorization"] = f"Bearer {token}"
if config.get("headers") and isinstance(config.get("headers"), dict):
headers = {**headers, **config.get("headers")}
return headers, cookies
def get_microsoft_entra_id_access_token():
"""
Get Microsoft Entra ID access token using DefaultAzureCredential for Azure OpenAI.
Returns the token string or None if authentication fails.
"""
try:
token_provider = get_bearer_token_provider(
DefaultAzureCredential(), "https://cognitiveservices.azure.com/.default"
)
return token_provider()
except Exception as e:
log.error(f"Error getting Microsoft Entra ID access token: {e}")
return None
##########################################
#
# API routes
#
##########################################
router = APIRouter()
@router.get("/config")
async def get_config(request: Request, user=Depends(get_admin_user)):
return {
"ENABLE_OPENAI_API": request.app.state.config.ENABLE_OPENAI_API,
"OPENAI_API_BASE_URLS": request.app.state.config.OPENAI_API_BASE_URLS,
"OPENAI_API_KEYS": request.app.state.config.OPENAI_API_KEYS,
"OPENAI_API_CONFIGS": request.app.state.config.OPENAI_API_CONFIGS,
}
class OpenAIConfigForm(BaseModel):
ENABLE_OPENAI_API: Optional[bool] = None
OPENAI_API_BASE_URLS: list[str]
OPENAI_API_KEYS: list[str]
OPENAI_API_CONFIGS: dict
@router.post("/config/update")
async def update_config(
request: Request, form_data: OpenAIConfigForm, user=Depends(get_admin_user)
):
request.app.state.config.ENABLE_OPENAI_API = form_data.ENABLE_OPENAI_API
request.app.state.config.OPENAI_API_BASE_URLS = form_data.OPENAI_API_BASE_URLS
request.app.state.config.OPENAI_API_KEYS = form_data.OPENAI_API_KEYS
# Check if API KEYS length is same than API URLS length
if len(request.app.state.config.OPENAI_API_KEYS) != len(
request.app.state.config.OPENAI_API_BASE_URLS
):
if len(request.app.state.config.OPENAI_API_KEYS) > len(
request.app.state.config.OPENAI_API_BASE_URLS
):
request.app.state.config.OPENAI_API_KEYS = (
request.app.state.config.OPENAI_API_KEYS[
: len(request.app.state.config.OPENAI_API_BASE_URLS)
]
)
else:
request.app.state.config.OPENAI_API_KEYS += [""] * (
len(request.app.state.config.OPENAI_API_BASE_URLS)
- len(request.app.state.config.OPENAI_API_KEYS)
)
request.app.state.config.OPENAI_API_CONFIGS = form_data.OPENAI_API_CONFIGS
# Remove the API configs that are not in the API URLS
keys = list(map(str, range(len(request.app.state.config.OPENAI_API_BASE_URLS))))
request.app.state.config.OPENAI_API_CONFIGS = {
key: value
for key, value in request.app.state.config.OPENAI_API_CONFIGS.items()
if key in keys
}
return {
"ENABLE_OPENAI_API": request.app.state.config.ENABLE_OPENAI_API,
"OPENAI_API_BASE_URLS": request.app.state.config.OPENAI_API_BASE_URLS,
"OPENAI_API_KEYS": request.app.state.config.OPENAI_API_KEYS,
"OPENAI_API_CONFIGS": request.app.state.config.OPENAI_API_CONFIGS,
}
@router.post("/audio/speech")
async def speech(request: Request, user=Depends(get_verified_user)):
idx = None
try:
idx = request.app.state.config.OPENAI_API_BASE_URLS.index(
"https://api.openai.com/v1"
)
body = await request.body()
name = hashlib.sha256(body).hexdigest()
SPEECH_CACHE_DIR = CACHE_DIR / "audio" / "speech"
SPEECH_CACHE_DIR.mkdir(parents=True, exist_ok=True)
file_path = SPEECH_CACHE_DIR.joinpath(f"{name}.mp3")
file_body_path = SPEECH_CACHE_DIR.joinpath(f"{name}.json")
# Check if the file already exists in the cache
if file_path.is_file():
return FileResponse(file_path)
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
)
headers, cookies = await get_headers_and_cookies(
request, url, key, api_config, user=user
)
r = None
try:
r = requests.post(
url=f"{url}/audio/speech",
data=body,
headers=headers,
cookies=cookies,
stream=True,
)
r.raise_for_status()
# Save the streaming content to a file
with open(file_path, "wb") as f:
for chunk in r.iter_content(chunk_size=8192):
f.write(chunk)
with open(file_body_path, "w") as f:
json.dump(json.loads(body.decode("utf-8")), f)
# 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 "CyberLover: Server Connection Error",
)
except ValueError:
raise HTTPException(status_code=401, detail=ERROR_MESSAGES.OPENAI_NOT_FOUND)
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="CyberLover: 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="CyberLover: Server Connection Error"
)
except Exception as e:
log.exception(f"Unexpected error: {e}")
raise HTTPException(
status_code=500, detail="CyberLover: 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. 权限检查配置 ===
if BYPASS_MODEL_ACCESS_CONTROL:
bypass_filter = True
idx = 0 # 用于标识使用哪个 OPENAI_API_BASE_URL
# === 2. 准备 Payload 和提取元数据 ===
payload = {**form_data}
metadata = payload.pop("metadata", None) # 移除内部元数据,不发送给上游 API
model_id = form_data.get("model")
model_info = Models.get_model_by_id(model_id)
# === 3. 应用模型配置和权限检查 ===
# Check model info and override the payload
if model_info:
# 3.1 如果配置了 base_model_id替换为底层模型 ID
# 例如:自定义模型 "my-gpt4" → 实际调用 "gpt-4-turbo"
if model_info.base_model_id:
payload["model"] = model_info.base_model_id
model_id = model_info.base_model_id
# 3.2 应用模型参数temperature, max_tokens 等)
params = model_info.params.model_dump()
if params:
system = params.pop("system", None) # 提取 system prompt
# 应用模型参数到 payload覆盖用户传入的参数
payload = apply_model_params_to_body_openai(params, payload)
# 注入或替换 system prompt
payload = apply_system_prompt_to_body(system, payload, metadata, user)
# 3.3 权限检查:验证用户是否有权限访问该模型
# Check if user has access to the model
if not bypass_filter and user.role == "user":
if not (
user.id == model_info.user_id # 用户是模型创建者
or has_access(
user.id, type="read", access_control=model_info.access_control
) # 或用户在访问控制列表中
):
raise HTTPException(
status_code=403,
detail="Model not found",
)
elif not bypass_filter:
# 如果模型信息不存在且未绕过过滤器,只有管理员可访问
if user.role != "admin":
raise HTTPException(
status_code=403,
detail="Model not found",
)
# === 4. 查找 OpenAI API 配置 ===
await get_all_models(request, user=user) # 刷新模型列表
model = request.app.state.OPENAI_MODELS.get(model_id)
if model:
idx = model["urlIdx"] # 获取 API 基础 URL 索引
else:
raise HTTPException(
status_code=404,
detail="Model not found",
)
# === 5. 获取 API 配置并处理 prefix_id ===
# Get the API config for the model
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
)
# 移除模型 ID 前缀(如果配置了 prefix_id
# 例如:模型 ID "custom.gpt-4" → 发送给 API 的是 "gpt-4"
prefix_id = api_config.get("prefix_id", None)
if prefix_id:
payload["model"] = payload["model"].replace(f"{prefix_id}.", "")
# === 6. Pipeline 模式:注入用户信息 ===
# Add user info to the payload if the model is a pipeline
if "pipeline" in model and model.get("pipeline"):
payload["user"] = {
"name": user.name,
"id": user.id,
"email": user.email,
"role": user.role,
}
url = request.app.state.config.OPENAI_API_BASE_URLS[idx]
key = request.app.state.config.OPENAI_API_KEYS[idx]
# === 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}")
payload = json.dumps(payload) # 序列化为 JSON 字符串
# === 11. 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:直接转发 SSE 流
streaming = True
return StreamingResponse(
r.content,
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:
if isinstance(response, (dict, list)):
return JSONResponse(status_code=r.status, content=response)
else:
return PlainTextResponse(status_code=r.status, content=response)
return response # 成功响应
except Exception as e:
log.exception(e)
raise HTTPException(
status_code=r.status if r else 500,
detail="CyberLover: 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="CyberLover: 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="CyberLover: Server Connection Error",
)
finally:
if not streaming:
await cleanup_response(r, session)