Update main.py

main.py

@@ -1,38 +1,26 @@
-from __future__ import annotations
-
+from fastapi import FastAPI
+from fastapi.responses import StreamingResponse
+from pydantic import BaseModel
+import json
 import re
 import random
 import string
 from aiohttp import ClientSession
-from fastapi import FastAPI, HTTPException
-from pydantic import BaseModel
-from typing import List, Dict, Any, Optional
 
-# Mock implementations for ImageResponse and to_data_uri
-class ImageResponse:
-    def __init__(self, url: str, alt: str):
-        self.url = url
-        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:
-    pass
+# Pydantic models for request
+class Message(BaseModel):
+    role: str
+    content: str
 
-class ProviderModelMixin:
-    pass
+class ChatRequest(BaseModel):
+    model: str
+    messages: list[Message]
 
-class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):
+# Blackbox class
+class Blackbox:
     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 = [
         'blackbox',
         'gemini-1.5-flash',
@@ -45,170 +33,50 @@ 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 model if model in cls.models else 'blackbox'
 
     @classmethod
-    async def create_async_generator(
-        cls,
-        model: str,
-        messages: List[Dict[str, str]],
-        proxy: Optional[str] = None,
-        image: Optional[Any] = None,
-        image_name: Optional[str] = None,
-        **kwargs
-    ) -> Any:
+    async def create_async_generator(cls, model: str, messages: list) -> str:
         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"
+            "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 = {
                 "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,
             }
 
-            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:
+            async with session.post(cls.api_endpoint, json=data) 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:
-                    async for chunk in response.content.iter_any():
-                        if chunk:
-                            decoded_chunk = chunk.decode()
-                            decoded_chunk = re.sub(r'\$@\$v=[^$]+\$@\$', '', decoded_chunk)
-                            if decoded_chunk.strip():
-                                yield decoded_chunk
+                async for chunk in response.content.iter_any():
+                    if chunk:
+                        decoded_chunk = chunk.decode()
+                        decoded_chunk = re.sub(r'\$@\$v=[^$]+\$@\$', '', decoded_chunk)
+                        yield decoded_chunk.strip()
 
-# FastAPI app setup
+# FastAPI app
 app = FastAPI()
 
-class Message(BaseModel):
-    role: str
-    content: str
-
-class ChatRequest(BaseModel):
-    model: str
-    messages: List[Message]
-
 @app.post("/v1/chat/completions")
 async def chat_completions(request: ChatRequest):
     messages = [{"role": msg.role, "content": msg.content} for msg in request.messages]
 
-    # Use an async generator to get the response
     async_generator = Blackbox.create_async_generator(
         model=request.model,
         messages=messages
     )
 
-    response_content = ""
-    async for chunk in async_generator:
-        response_content += chunk if isinstance(chunk, str) else chunk.content  # Concatenate response
+    async def event_stream():
+        async for chunk in async_generator:
+            yield f"data: {json.dumps({'choices': [{'message': {'role': 'assistant', 'content': chunk}}]}})}\n\n"
 
-    return {
-        "id": "chatcmpl-1234",  # Example ID, generate as needed
-        "object": "chat.completion",
-        "created": 1690000000,  # Replace with actual timestamp
-        "model": request.model,
-        "choices": [
-            {
-                "message": {
-                    "role": "assistant",
-                    "content": response_content
-                },
-                "finish_reason": "stop",
-                "index": 0
-            }
-        ]
-    }
+    return StreamingResponse(event_stream(), media_type="text/event-stream")