Update main.py

main.py

@@ -12,7 +12,7 @@ from typing import List, Dict, Any, Optional, Union, AsyncGenerator
 
 from aiohttp import ClientSession, ClientResponseError
 from fastapi import FastAPI, HTTPException, Request, Depends, Header
-from fastapi.responses import JSONResponse
+from fastapi.responses import JSONResponse, StreamingResponse
 from pydantic import BaseModel
 from datetime import datetime
 
@@ -44,6 +44,30 @@ class ImageResponse(BaseModel):
     images: str
     alt: str
 
+# Request Models
+class Message(BaseModel):
+    role: str
+    content: str
+
+class ChatRequest(BaseModel):
+    model: str
+    messages: List[Message]
+    temperature: Optional[float] = 1.0
+    top_p: Optional[float] = 1.0
+    n: Optional[int] = 1
+    max_tokens: Optional[int] = None
+    presence_penalty: Optional[float] = 0.0
+    frequency_penalty: Optional[float] = 0.0
+    logit_bias: Optional[Dict[str, float]] = None
+    user: Optional[str] = None
+
+# Custom exception for model not working
+class ModelNotWorkingException(Exception):
+    def __init__(self, model: str):
+        self.model = model
+        self.message = f"The model '{model}' is currently not working. Please try another model or wait for it to be fixed."
+        super().__init__(self.message)
+
 # Updated Blackbox class with new models and functionalities
 class Blackbox:
     label = "Blackbox AI"
@@ -192,7 +216,12 @@ class Blackbox:
     def clean_response(text: str) -> str:
         pattern = r'^\$\@\$v=undefined-rv1\$\@\$'
         cleaned_text = re.sub(pattern, '', text)
-        return cleaned_text
+        try:
+            response_json = json.loads(cleaned_text)
+            # Assuming the response is in {"response": "Your answer here."} format
+            return response_json.get("response", cleaned_text)
+        except json.JSONDecodeError:
+            return cleaned_text
 
     @classmethod
     async def generate_response(
@@ -307,12 +336,234 @@ class Blackbox:
                 logger.exception(f"Unexpected error during /api/chat request: {str(e)}")
                 return f"Unexpected error during /api/chat request: {str(e)}"
 
-    # Custom exception for model not working
-    class ModelNotWorkingException(Exception):
-        def __init__(self, model: str):
-            self.model = model
-            self.message = f"The model '{model}' is currently not working. Please try another model or wait for it to be fixed."
-            super().__init__(self.message)
+    @classmethod
+    async def create_async_generator(
+        cls,
+        model: str,
+        messages: List[Dict[str, str]],
+        proxy: Optional[str] = None,
+        websearch: bool = False,
+        **kwargs
+    ) -> AsyncGenerator[Union[str, ImageResponse], None]:
+        """
+        Creates an asynchronous generator for streaming responses from Blackbox AI.
+
+        Parameters:
+            model (str): Model to use for generating responses.
+            messages (List[Dict[str, str]]): Message history.
+            proxy (Optional[str]): Proxy URL, if needed.
+            websearch (bool): Enables or disables web search mode.
+            **kwargs: Additional keyword arguments.
+
+        Yields:
+            Union[str, ImageResponse]: Segments of the generated response or ImageResponse objects.
+        """
+        model = cls.get_model(model)
+
+        chat_id = cls.generate_random_string()
+        next_action = cls.generate_next_action()
+        next_router_state_tree = cls.generate_next_router_state_tree()
+
+        agent_mode = cls.agentMode.get(model, {})
+        trending_agent_mode = cls.trendingAgentMode.get(model, {})
+
+        prefix = cls.model_prefixes.get(model, "")
+        
+        formatted_prompt = ""
+        for message in messages:
+            role = message.get('role', '').capitalize()
+            content = message.get('content', '')
+            if role and content:
+                formatted_prompt += f"{role}: {content}\n"
+        
+        if prefix:
+            formatted_prompt = f"{prefix} {formatted_prompt}".strip()
+
+        referer_path = cls.model_referers.get(model, f"/?model={model}")
+        referer_url = f"{cls.url}{referer_path}"
+
+        common_headers = {
+            'accept': '*/*',
+            'accept-language': 'en-US,en;q=0.9',
+            'cache-control': 'no-cache',
+            'origin': cls.url,
+            'pragma': 'no-cache',
+            'priority': 'u=1, i',
+            'sec-ch-ua': '"Chromium";v="129", "Not=A?Brand";v="8"',
+            'sec-ch-ua-mobile': '?0',
+            'sec-ch-ua-platform': '"Linux"',
+            'sec-fetch-dest': 'empty',
+            'sec-fetch-mode': 'cors',
+            'sec-fetch-site': 'same-origin',
+            'user-agent': 'Mozilla/5.0 (X11; Linux x86_64) '
+                          'AppleWebKit/537.36 (KHTML, like Gecko) '
+                          'Chrome/129.0.0.0 Safari/537.36'
+        }
+
+        headers_api_chat = {
+            'Content-Type': 'application/json',
+            'Referer': referer_url
+        }
+        headers_api_chat_combined = {**common_headers, **headers_api_chat}
+
+        payload_api_chat = {
+            "messages": [
+                {
+                    "id": chat_id,
+                    "content": formatted_prompt,
+                    "role": "user"
+                }
+            ],
+            "id": chat_id,
+            "previewToken": None,
+            "userId": None,
+            "codeModelMode": True,
+            "agentMode": agent_mode,
+            "trendingAgentMode": trending_agent_mode,
+            "isMicMode": False,
+            "userSystemPrompt": None,
+            "maxTokens": 1024,
+            "playgroundTopP": 0.9,
+            "playgroundTemperature": 0.5,
+            "isChromeExt": False,
+            "githubToken": None,
+            "clickedAnswer2": False,
+            "clickedAnswer3": False,
+            "clickedForceWebSearch": False,
+            "visitFromDelta": False,
+            "mobileClient": False,
+            "webSearchMode": False,
+            "userSelectedModel": cls.userSelectedModel.get(model, model)
+        }
+
+        headers_chat = {
+            'Accept': 'text/x-component',
+            'Content-Type': 'text/plain;charset=UTF-8',
+            'Referer': f'{cls.url}/chat/{chat_id}?model={model}',
+            'next-action': next_action,
+            'next-router-state-tree': next_router_state_tree,
+            'next-url': '/'
+        }
+        headers_chat_combined = {**common_headers, **headers_chat}
+
+        data_chat = '[]'
+
+        async with ClientSession(headers=common_headers) as session:
+            try:
+                async with session.post(
+                    cls.api_endpoint,
+                    headers=headers_api_chat_combined,
+                    json=payload_api_chat,
+                    proxy=proxy
+                ) as response_api_chat:
+                    response_api_chat.raise_for_status()
+                    text = await response_api_chat.text()
+                    logger.debug(f"Raw response from Blackbox API: {text}")  # Log raw response
+                    cleaned_response = cls.clean_response(text)
+                    logger.debug(f"Cleaned response: {cleaned_response}")  # Log cleaned response
+
+                    if model in cls.image_models:
+                        match = re.search(r'!\[.*?\]\((https?://[^\)]+)\)', cleaned_response)
+                        if match:
+                            image_url = match.group(1)
+                            image_response = ImageResponse(images=image_url, alt="Generated Image")
+                            yield image_response
+                        else:
+                            yield cleaned_response
+                    else:
+                        if websearch:
+                            match = re.search(r'\$~~~\$(.*?)\$~~~\$', cleaned_response, re.DOTALL)
+                            if match:
+                                source_part = match.group(1).strip()
+                                answer_part = cleaned_response[match.end():].strip()
+                                try:
+                                    sources = json.loads(source_part)
+                                    source_formatted = "**Source:**\n"
+                                    for item in sources:
+                                        title = item.get('title', 'No Title')
+                                        link = item.get('link', '#')
+                                        position = item.get('position', '')
+                                        source_formatted += f"{position}. [{title}]({link})\n"
+                                    final_response = f"{answer_part}\n\n{source_formatted}"
+                                except json.JSONDecodeError:
+                                    final_response = f"{answer_part}\n\nSource information is unavailable."
+                            else:
+                                final_response = cleaned_response
+                        else:
+                            if '$~~~$' in cleaned_response:
+                                final_response = cleaned_response.split('$~~~$')[0].strip()
+                            else:
+                                final_response = cleaned_response
+
+                        yield final_response
+            except ClientResponseError as e:
+                error_text = f"Error {e.status}: {e.message}"
+                try:
+                    error_response = await e.response.text()
+                    cleaned_error = cls.clean_response(error_response)
+                    error_text += f" - {cleaned_error}"
+                    logger.error(f"Blackbox API ClientResponseError: {error_text}")
+                except Exception:
+                    pass
+                yield error_text
+            except Exception as e:
+                yield f"Unexpected error during /api/chat request: {str(e)}"
+
+            chat_url = f'{cls.url}/chat/{chat_id}?model={model}'
+
+            try:
+                async with session.post(
+                    chat_url,
+                    headers=headers_chat_combined,
+                    data=data_chat,
+                    proxy=proxy
+                ) as response_chat:
+                    response_chat.raise_for_status()
+                    pass
+            except ClientResponseError as e:
+                error_text = f"Error {e.status}: {e.message}"
+                try:
+                    error_response = await e.response.text()
+                    cleaned_error = cls.clean_response(error_response)
+                    error_text += f" - {cleaned_error}"
+                    logger.error(f"Blackbox API ClientResponseError during chat URL request: {error_text}")
+                except Exception:
+                    pass
+                yield error_text
+            except Exception as e:
+                yield f"Unexpected error during /chat/{chat_id} request: {str(e)}"
+
+    # FastAPI app setup
+    app = FastAPI()
+
+    # Add the cleanup task when the app starts
+    @app.on_event("startup")
+    async def startup_event():
+        asyncio.create_task(cleanup_rate_limit_stores())
+        logger.info("Started rate limit store cleanup task.")
+
+    # Middleware to enhance security and enforce Content-Type for specific endpoints
+    @app.middleware("http")
+    async def security_middleware(request: Request, call_next):
+        client_ip = request.client.host
+        # Enforce that POST requests to /v1/chat/completions must have Content-Type: application/json
+        if request.method == "POST" and request.url.path == "/v1/chat/completions":
+            content_type = request.headers.get("Content-Type")
+            if content_type != "application/json":
+                logger.warning(f"Invalid Content-Type from IP: {client_ip} for path: {request.url.path}")
+                return JSONResponse(
+                    status_code=400,
+                    content={
+                        "error": {
+                            "message": "Content-Type must be application/json",
+                            "type": "invalid_request_error",
+                            "param": None,
+                            "code": None
+                        }
+                    },
+                )
+        response = await call_next(request)
+        return response
 
     async def cleanup_rate_limit_stores():
         """
@@ -356,55 +607,6 @@ class Blackbox:
             raise HTTPException(status_code=401, detail='Invalid API key')
         return api_key
 
-    # FastAPI app setup
-    app = FastAPI()
-
-    # Add the cleanup task when the app starts
-    @app.on_event("startup")
-    async def startup_event():
-        asyncio.create_task(cleanup_rate_limit_stores())
-        logger.info("Started rate limit store cleanup task.")
-
-    # Middleware to enhance security and enforce Content-Type for specific endpoints
-    @app.middleware("http")
-    async def security_middleware(request: Request, call_next):
-        client_ip = request.client.host
-        # Enforce that POST requests to /v1/chat/completions must have Content-Type: application/json
-        if request.method == "POST" and request.url.path == "/v1/chat/completions":
-            content_type = request.headers.get("Content-Type")
-            if content_type != "application/json":
-                logger.warning(f"Invalid Content-Type from IP: {client_ip} for path: {request.url.path}")
-                return JSONResponse(
-                    status_code=400,
-                    content={
-                        "error": {
-                            "message": "Content-Type must be application/json",
-                            "type": "invalid_request_error",
-                            "param": None,
-                            "code": None
-                        }
-                    },
-                )
-        response = await call_next(request)
-        return response
-
-    # Request Models
-    class Message(BaseModel):
-        role: str
-        content: str
-
-    class ChatRequest(BaseModel):
-        model: str
-        messages: List[Message]
-        temperature: Optional[float] = 1.0
-        top_p: Optional[float] = 1.0
-        n: Optional[int] = 1
-        max_tokens: Optional[int] = None
-        presence_penalty: Optional[float] = 0.0
-        frequency_penalty: Optional[float] = 0.0
-        logit_bias: Optional[Dict[str, float]] = None
-        user: Optional[str] = None
-
     @app.post("/v1/chat/completions", dependencies=[Depends(rate_limiter_per_ip)])
     async def chat_completions(request: ChatRequest, req: Request, api_key: str = Depends(get_api_key)):
         client_ip = req.client.host
@@ -459,14 +661,12 @@ class Blackbox:
             logger.exception(f"An unexpected error occurred while processing the chat completions request from IP: {client_ip}.")
             raise HTTPException(status_code=500, detail=str(e))
 
-    # Endpoint: GET /v1/models
     @app.get("/v1/models", dependencies=[Depends(rate_limiter_per_ip)])
     async def get_models(req: Request):
         client_ip = req.client.host
         logger.info(f"Fetching available models from IP: {client_ip}")
         return {"data": [{"id": model, "object": "model"} for model in Blackbox.models]}
 
-    # Endpoint: GET /v1/health
     @app.get("/v1/health", dependencies=[Depends(rate_limiter_per_ip)])
     async def health_check(req: Request):
         client_ip = req.client.host
@@ -490,6 +690,44 @@ class Blackbox:
             },
         )
 
+    # Optional: Additional Endpoint for Streaming Responses (Using create_async_generator)
+    # This endpoint leverages the new create_async_generator method for streaming responses.
+    # Note: Streaming responses may require clients that support Server-Sent Events (SSE) or WebSockets.
+
+    @app.post("/v1/chat/completions/stream", dependencies=[Depends(rate_limiter_per_ip)])
+    async def chat_completions_stream(request: ChatRequest, req: Request, api_key: str = Depends(get_api_key)):
+        client_ip = req.client.host
+        # Redact user messages only for logging purposes
+        redacted_messages = [{"role": msg.role, "content": "[redacted]"} for msg in request.messages]
+
+        logger.info(f"Received streaming chat completions request from API key: {api_key} | IP: {client_ip} | Model: {request.model} | Messages: {redacted_messages}")
+
+        try:
+            # Validate that the requested model is available
+            if request.model not in Blackbox.models and request.model not in Blackbox.model_aliases:
+                logger.warning(f"Attempt to use unavailable model: {request.model} from IP: {client_ip}")
+                raise HTTPException(status_code=400, detail="Requested model is not available.")
+
+            # Create an asynchronous generator for the response
+            async_generator = Blackbox.create_async_generator(
+                model=request.model,
+                messages=[{"role": msg.role, "content": msg.content} for msg in request.messages],
+                temperature=request.temperature,
+                max_tokens=request.max_tokens
+            )
+
+            logger.info(f"Started streaming response for API key: {api_key} | IP: {client_ip}")
+            return StreamingResponse(async_generator, media_type="text/event-stream")
+        except ModelNotWorkingException as e:
+            logger.warning(f"Model not working: {e} | IP: {client_ip}")
+            raise HTTPException(status_code=503, detail=str(e))
+        except HTTPException as he:
+            logger.warning(f"HTTPException: {he.detail} | IP: {client_ip}")
+            raise he
+        except Exception as e:
+            logger.exception(f"An unexpected error occurred while processing the streaming chat completions request from IP: {client_ip}.")
+            raise HTTPException(status_code=500, detail=str(e))
+
     if __name__ == "__main__":
         import uvicorn
         uvicorn.run(app, host="0.0.0.0", port=8000)