Create app.py

app.py

@@ -1,104 +1 @@
-from fastapi import FastAPI, HTTPException, Depends, Header, Request
-from fastapi.responses import StreamingResponse
-from pydantic import BaseModel
-from typing import List
-from g4f import ChatCompletion
-from slowapi import Limiter
-from slowapi.util import get_remote_address
-
-app = FastAPI()
-
-# Initialize the rate limiter
-limiter = Limiter(key_func=get_remote_address)
-
-# List of available models
-models = [
-    "gpt-4o", "gpt-4o-mini", "gpt-4",
-    "gpt-4-turbo", "gpt-3.5-turbo",
-    "claude-3.7-sonnet", "o3-mini", "o1", "claude-3.5", "llama-3.1-405b", "gemini-flash", "blackboxai-pro", "openchat-3.5", "glm-4-9B", "blackboxai"
-]
-
-# Request model
-class Message(BaseModel):
-    role: str
-    content: str
-
-class ChatRequest(BaseModel):
-    model: str
-    messages: List[Message]
-    streaming: bool = True  # Add streaming support
-
-class ChatResponse(BaseModel):
-    role: str
-    content: str
-
-# Dependency to check API key
-async def verify_api_key(x_api_key: str = Header(...)):
-    if x_api_key != "your-api-key":  # Replace with your actual API key
-        raise HTTPException(status_code=403, detail="Invalid API key")
-
-@app.get("/v1/models", tags=["Models"])
-async def get_models():
-    """Endpoint to get the list of available models."""
-    return {"models": models}
-
-@app.post("/v1/chat/completions", tags=["Chat Completion"])
-@limiter.limit("10/minute")  # Rate limit to 10 requests per minute
-async def chat_completion(
-    request: Request,
-    chat_request: ChatRequest,
-    api_key: str = Depends(verify_api_key)
-):
-    # Validate model
-    if chat_request.model not in models:
-        raise HTTPException(status_code=400, detail="Invalid model selected.")
-
-    # Check if messages are provided
-    if not chat_request.messages:
-        raise HTTPException(status_code=400, detail="Messages cannot be empty.")
-
-    # Convert messages to the format expected by ChatCompletion
-    formatted_messages = [{"role": msg.role, "content": msg.content} for msg in chat_request.messages]
-
-    try:
-        if chat_request.streaming:
-            # Stream the response
-            def event_stream():
-                response = ChatCompletion.create(
-                    model=chat_request.model,
-                    messages=formatted_messages,
-                    stream=True  # Enable streaming
-                )
-                
-                for chunk in response:
-                    if isinstance(chunk, dict) and 'choices' in chunk:
-                        for choice in chunk['choices']:
-                            if 'message' in choice:
-                                yield f"data: {choice['message']['content']}\n\n"
-                    else:
-                        yield f"data: {chunk}\n\n"  # Fallback if chunk is not as expected
-
-            return StreamingResponse(event_stream(), media_type="text/event-stream")
-        else:
-            # Non-streaming response
-            response = ChatCompletion.create(
-                model=chat_request.model,
-                messages=formatted_messages
-            )
-
-            if isinstance(response, str):
-                response_content = response  # Directly use if it's a string
-            else:
-                try:
-                    response_content = response['choices'][0]['message']['content']
-                except (IndexError, KeyError):
-                    raise HTTPException(status_code=500, detail="Unexpected response structure.")
-
-            return ChatResponse(role="assistant", content=response_content)
-
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=str(e))
-
-if __name__ == "__main__":
-    import uvicorn
-    uvicorn.run(app, host="0.0.0.0", port=7860)
+import module