Update main.py

main.py

@@ -1,14 +1,12 @@
 from __future__ import annotations
-
 import re
 import random
 import string
-import uuid  # Already added
-from datetime import datetime  # Add this line
 from aiohttp import ClientSession
 from fastapi import FastAPI, HTTPException
 from pydantic import BaseModel
-from typing import List, Dict, Any, Optional
+from typing import List, Dict, Any, Optional, Union
+import asyncio
 
 # Mock implementations for ImageResponse and to_data_uri
 class ImageResponse:
@@ -17,7 +15,6 @@ class ImageResponse:
         self.alt = alt
 
 def to_data_uri(image: Any) -> str:
-    # Placeholder for actual image encoding
     return "data:image/png;base64,..."  # Replace with actual base64 data
 
 class AsyncGeneratorProvider:
@@ -29,10 +26,6 @@ class ProviderModelMixin:
 class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):
     url = "https://www.blackbox.ai"
     api_endpoint = "https://www.blackbox.ai/api/chat"
-    working = True
-    supports_stream = True
-    supports_system_message = True
-    supports_message_history = True
     
     default_model = 'blackbox'
     models = [
@@ -47,39 +40,11 @@ class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):
         'claude-sonnet-3.5',
     ]
 
-    agentMode = {
-        'ImageGenerationLV45LJp': {'mode': True, 'id': "ImageGenerationLV45LJp", 'name': "Image Generation"},
-    }
-
-    trendingAgentMode = {
-        "blackbox": {},
-        "gemini-1.5-flash": {'mode': True, 'id': 'Gemini'},
-        "llama-3.1-8b": {'mode': True, 'id': "llama-3.1-8b"},
-        'llama-3.1-70b': {'mode': True, 'id': "llama-3.1-70b"},
-        'llama-3.1-405b': {'mode': True, 'id': "llama-3.1-405b"},
-    }
-    
-    userSelectedModel = {
-        "gpt-4o": "gpt-4o",
-        "gemini-pro": "gemini-pro",
-        'claude-sonnet-3.5': "claude-sonnet-3.5",
-    }
-    
-    model_aliases = {
-        "gemini-flash": "gemini-1.5-flash",
-        "flux": "ImageGenerationLV45LJp",
-    }
-
     @classmethod
     def get_model(cls, model: str) -> str:
         if model in cls.models:
             return model
-        elif model in cls.userSelectedModel:
-            return model
-        elif model in cls.model_aliases:
-            return cls.model_aliases[model]
-        else:
-            return cls.default_model
+        return cls.default_model
 
     @classmethod
     async def create_async_generator(
@@ -89,89 +54,38 @@ class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):
         proxy: Optional[str] = None,
         image: Optional[Any] = None,
         image_name: Optional[str] = None,
+        stream: bool = False,
         **kwargs
-    ) -> Any:
+    ) -> Union[Dict[str, Any], AsyncGenerator[str, None]]:
         model = cls.get_model(model)
-        
+
         headers = {
-            "accept": "*/*",
-            "accept-language": "en-US,en;q=0.9",
-            "cache-control": "no-cache",
-            "content-type": "application/json",
-            "origin": cls.url,
-            "pragma": "no-cache",
-            "referer": f"{cls.url}/",
-            "sec-ch-ua": '"Not;A=Brand";v="24", "Chromium";v="128"',
-            "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/128.0.0.0 Safari/537.36"
+            "Content-Type": "application/json",
+            "User-Agent": "Mozilla/5.0"
         }
 
-        if model in cls.userSelectedModel:
-            prefix = f"@{cls.userSelectedModel[model]}"
-            if not messages[0]['content'].startswith(prefix):
-                messages[0]['content'] = f"{prefix} {messages[0]['content']}"
-        
         async with ClientSession(headers=headers) as session:
             if image is not None:
                 messages[-1]["data"] = {
                     "fileText": image_name,
                     "imageBase64": to_data_uri(image)
                 }
-            
-            random_id = ''.join(random.choices(string.ascii_letters + string.digits, k=7))
 
             data = {
+                "model": model,
                 "messages": messages,
-                "id": random_id,
-                "previewToken": None,
-                "userId": None,
-                "codeModelMode": True,
-                "agentMode": {},
-                "trendingAgentMode": {},
-                "userSelectedModel": None,
-                "userSystemPrompt": None,
-                "isMicMode": False,
-                "maxTokens": 1024,
-                "playgroundTopP": 0.9,
-                "playgroundTemperature": 0.5,
-                "isChromeExt": False,
-                "githubToken": None,
-                "clickedAnswer2": False,
-                "clickedAnswer3": False,
-                "clickedForceWebSearch": False,
-                "visitFromDelta": False,
-                "mobileClient": False,
-                "webSearchMode": False,
+                "max_tokens": 1024,
+                "temperature": 0.7,
+                "stream": stream
             }
 
-            if model in cls.agentMode:
-                data["agentMode"] = cls.agentMode[model]
-            elif model in cls.trendingAgentMode:
-                data["trendingAgentMode"] = cls.trendingAgentMode[model]
-            elif model in cls.userSelectedModel:
-                data["userSelectedModel"] = cls.userSelectedModel[model]
-            
             async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response:
                 response.raise_for_status()
-                if model == 'ImageGenerationLV45LJp':
-                    response_text = await response.text()
-                    url_match = re.search(r'https://storage\.googleapis\.com/[^\s\)]+', response_text)
-                    if url_match:
-                        image_url = url_match.group(0)
-                        yield ImageResponse(image_url, alt=messages[-1]['content'])
-                    else:
-                        raise Exception("Image URL not found in the response")
-                else:
+                if stream:
                     async for chunk in response.content.iter_any():
-                        if chunk:
-                            decoded_chunk = chunk.decode()
-                            decoded_chunk = re.sub(r'\$@\$v=[^$]+\$@\$', '', decoded_chunk)
-                            if decoded_chunk.strip():
-                                yield decoded_chunk
+                        yield chunk.decode()
+                else:
+                    return await response.json()
 
 # FastAPI app setup
 app = FastAPI()
@@ -183,8 +97,7 @@ class Message(BaseModel):
 class ChatRequest(BaseModel):
     model: str
     messages: List[Message]
-
-from fastapi.responses import Response
+    stream: Optional[bool] = False  # Add stream option
 
 @app.post("/v1/chat/completions")
 async def chat_completions(request: ChatRequest):
@@ -192,19 +105,22 @@ async def chat_completions(request: ChatRequest):
 
     async_generator = Blackbox.create_async_generator(
         model=request.model,
-        messages=messages
+        messages=messages,
+        stream=request.stream  # Pass the stream flag
     )
 
-    response_content = ""
-    async for chunk in async_generator:
-        if isinstance(chunk, str):
-            response_content += chunk
-        else:
-            response_content += chunk.content
+    if request.stream:
+        async def event_stream():
+            async for chunk in async_generator:
+                # If chunk is a string, it should be processed as needed
+                yield {"choices": [{"text": chunk.strip()}]}
 
-    # Clean up the response to get only the plain text content
-    start = response_content.find('"content": "') + len('"content": "')
-    end = response_content.find('"', start)
-    clean_content = response_content[start:end].replace('\\n', '\n')  # Handle newline characters
+        return app.streaming_response(event_stream(), media_type="application/json")
+    
+    # Handle non-streaming response
+    response = await async_generator
+    if "choices" in response and len(response["choices"]) > 0:
+        clean_content = response["choices"][0]["message"]["content"]
+        return {"choices": [{"text": clean_content.strip()}]}
 
-    return Response(content=clean_content.strip(), media_type="text/plain")  # Return plain text
+    raise HTTPException(status_code=500, detail="No valid response received.")