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from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import StreamingResponse, JSONResponse
from pydantic import BaseModel
from typing import List, Optional
import json
import time
import uuid
import logging
import g4f
from g4f.client import Client
# =====================================================
# LOGGING
# =====================================================
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
# =====================================================
# CONFIG
# =====================================================
API_KEY = "sk-your-secret-key"
# =====================================================
# FASTAPI
# =====================================================
app = FastAPI(
title="Universal AI Gateway",
version="5.3.0"
)
# =====================================================
# CORS
# =====================================================
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
# =====================================================
# MODELS
# =====================================================
class Message(BaseModel):
role: str
content: str
class ChatRequest(BaseModel):
model: str
messages: List[Message]
stream: bool = False
temperature: Optional[float] = 0.7
max_tokens: Optional[int] = 4096
# =====================================================
# AUTH
# =====================================================
def verify_api_key(req: Request):
auth = req.headers.get("Authorization")
# السماح بدون مفتاح للاختبار
if not auth:
return True
if not auth.startswith("Bearer "):
raise HTTPException(
status_code=401,
detail="Invalid Authorization Format"
)
token = auth.replace("Bearer ", "").strip()
if token != API_KEY:
raise HTTPException(
status_code=403,
detail="Invalid API Key"
)
return True
# =====================================================
# ROOT
# =====================================================
@app.get("/")
async def root():
return {
"status": "online",
"service": "Universal AI Gateway",
"version": "5.3.0"
}
# =====================================================
# MODELS
# =====================================================
@app.get("/v1/models")
async def get_models():
models_data = []
try:
if hasattr(g4f.models, "_all_models"):
all_models = list(g4f.models._all_models)
for model in all_models:
models_data.append({
"id": str(model),
"object": "model",
"created": int(time.time()),
"owned_by": "g4f"
})
except Exception as e:
logger.error(f"Models error: {e}")
return {
"object": "list",
"data": models_data
}
# =====================================================
# CHAT COMPLETIONS
# =====================================================
@app.post("/v1/chat/completions")
async def chat_completions(
req: Request,
body: ChatRequest
):
verify_api_key(req)
messages = [
{
"role": m.role,
"content": m.content
}
for m in body.messages
]
logger.info(
f"Request model={body.model} stream={body.stream}"
)
# =================================================
# STREAMING
# =================================================
if body.stream:
def generate_stream():
chunk_id = f"chatcmpl-{uuid.uuid4().hex}"
try:
client = Client()
response = client.chat.completions.create(
model=body.model,
messages=messages,
stream=True
)
has_content = False
for chunk in response:
try:
content = ""
if (
hasattr(chunk, "choices")
and chunk.choices
and len(chunk.choices) > 0
and hasattr(chunk.choices[0], "delta")
and chunk.choices[0].delta
and chunk.choices[0].delta.content
):
content = chunk.choices[0].delta.content
if not content:
continue
has_content = True
payload = {
"id": chunk_id,
"object": "chat.completion.chunk",
"created": int(time.time()),
"model": body.model,
"choices": [
{
"index": 0,
"delta": {
"content": content
},
"finish_reason": None
}
]
}
yield (
"data: "
+ json.dumps(
payload,
ensure_ascii=False
)
+ "\n\n"
)
except Exception as chunk_error:
logger.error(
f"Chunk error: {chunk_error}"
)
if not has_content:
error_payload = {
"error": {
"message": "Provider returned empty stream",
"type": "empty_stream"
}
}
yield (
"data: "
+ json.dumps(error_payload)
+ "\n\n"
)
final_payload = {
"id": chunk_id,
"object": "chat.completion.chunk",
"created": int(time.time()),
"model": body.model,
"choices": [
{
"index": 0,
"delta": {},
"finish_reason": "stop"
}
]
}
yield (
"data: "
+ json.dumps(final_payload)
+ "\n\n"
)
yield "data: [DONE]\n\n"
except Exception as e:
logger.error(
f"Streaming error: {e}"
)
error_payload = {
"error": {
"message": str(e),
"type": "server_error"
}
}
yield (
"data: "
+ json.dumps(error_payload)
+ "\n\n"
)
yield "data: [DONE]\n\n"
return StreamingResponse(
generate_stream(),
media_type="text/event-stream",
headers={
"Cache-Control": "no-cache",
"Connection": "keep-alive",
"X-Accel-Buffering": "no"
}
)
# =================================================
# NORMAL RESPONSE
# =================================================
try:
client = Client()
response = client.chat.completions.create(
model=body.model,
messages=messages,
stream=False
)
assistant_message = ""
try:
assistant_message = (
response
.choices[0]
.message
.content
)
except Exception:
assistant_message = str(response)
return JSONResponse({
"id": (
f"chatcmpl-{uuid.uuid4().hex}"
),
"object": "chat.completion",
"created": int(time.time()),
"model": body.model,
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": assistant_message
},
"finish_reason": "stop"
}
],
"usage": {
"prompt_tokens": 0,
"completion_tokens": 0,
"total_tokens": 0
}
})
except Exception as e:
logger.error(f"Chat error: {e}")
raise HTTPException(
status_code=500,
detail=str(e)
)
# =====================================================
# RUN
# =====================================================
if __name__ == "__main__":
import uvicorn
uvicorn.run(
app,
host="0.0.0.0",
port=7860,
log_level="info"
) |