Update main.py
Browse files
main.py
CHANGED
@@ -11,7 +11,7 @@ from collections import defaultdict
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from typing import List, Dict, Any, Optional, AsyncGenerator, Union
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from datetime import datetime
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from aiohttp import ClientSession, ClientTimeout, ClientError
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from fastapi import FastAPI, HTTPException, Request, Depends, Header
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from fastapi.responses import StreamingResponse, JSONResponse, RedirectResponse
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from pydantic import BaseModel
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@@ -46,68 +46,17 @@ rate_limit_store = defaultdict(lambda: {"count": 0, "timestamp": time.time()})
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CLEANUP_INTERVAL = 60 # seconds
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RATE_LIMIT_WINDOW = 60 # seconds
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async def cleanup_rate_limit_stores():
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"""
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Periodically cleans up stale entries in the rate_limit_store to prevent memory bloat.
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"""
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while True:
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current_time = time.time()
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ips_to_delete = [ip for ip, value in rate_limit_store.items() if current_time - value["timestamp"] > RATE_LIMIT_WINDOW * 2]
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for ip in ips_to_delete:
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del rate_limit_store[ip]
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logger.debug(f"Cleaned up rate_limit_store for IP: {ip}")
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await asyncio.sleep(CLEANUP_INTERVAL)
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async def rate_limiter_per_ip(request: Request):
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"""
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Rate limiter that enforces a limit based on the client's IP address.
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"""
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client_ip = request.client.host
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current_time = time.time()
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# Initialize or update the count and timestamp
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if current_time - rate_limit_store[client_ip]["timestamp"] > RATE_LIMIT_WINDOW:
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rate_limit_store[client_ip] = {"count": 1, "timestamp": current_time}
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else:
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if rate_limit_store[client_ip]["count"] >= RATE_LIMIT:
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logger.warning(f"Rate limit exceeded for IP address: {client_ip}")
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raise HTTPException(status_code=429, detail='Rate limit exceeded for IP address | NiansuhAI')
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rate_limit_store[client_ip]["count"] += 1
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async def get_api_key(request: Request, authorization: str = Header(None)) -> str:
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"""
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Dependency to extract and validate the API key from the Authorization header.
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"""
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client_ip = request.client.host
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if authorization is None or not authorization.startswith('Bearer '):
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logger.warning(f"Invalid or missing authorization header from IP: {client_ip}")
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raise HTTPException(status_code=401, detail='Invalid authorization header format')
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api_key = authorization[7:]
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if api_key not in API_KEYS:
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logger.warning(f"Invalid API key attempted: {api_key} from IP: {client_ip}")
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raise HTTPException(status_code=401, detail='Invalid API key')
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return api_key
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# Custom exception for model not working
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class ModelNotWorkingException(Exception):
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def __init__(self, model: str):
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self.model = model
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self.message = f"The model '{model}' is currently not working. Please try another model or wait for it to be fixed."
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super().__init__(self.message)
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# Mock implementations for ImageResponse and to_data_uri
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class ImageResponse:
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def __init__(self,
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self.
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self.alt = alt
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def to_data_uri(image: Any) -> str:
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return "data:image/png;base64,..." # Replace with actual base64 data
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class Blackbox:
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url = "https://www.blackbox.ai"
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api_endpoint = "https://www.blackbox.ai/api/chat"
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working = True
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supports_stream = True
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supports_system_message = True
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supports_message_history = True
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@@ -117,6 +66,7 @@ class Blackbox:
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models = [
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default_model,
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'blackboxai-pro',
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"llama-3.1-8b",
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'llama-3.1-70b',
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'llama-3.1-405b',
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'ReactAgent',
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'XcodeAgent',
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'AngularJSAgent',
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*image_models,
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'Niansuh',
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]
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# Filter models based on AVAILABLE_MODELS
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if AVAILABLE_MODELS:
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models = [model for model in models if model in AVAILABLE_MODELS]
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agentMode = {
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'ImageGeneration': {'mode': True, 'id': "ImageGenerationLV45LJp", 'name': "Image Generation"},
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'Niansuh': {'mode': True, 'id': "NiansuhAIk1HgESy", 'name': "Niansuh"},
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}
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trendingAgentMode = {
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"blackboxai": {},
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"gemini-1.5-flash": {'mode': True, 'id': 'Gemini'},
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'AngularJSAgent': '@AngularJS Agent',
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'blackboxai-pro': '@BLACKBOXAI-PRO',
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'ImageGeneration': '@Image Generation',
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'Niansuh': '@Niansuh',
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}
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model_referers = {
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"blackboxai":
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"gpt-4o":
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"gemini-pro":
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"claude-sonnet-3.5":
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}
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model_aliases = {
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"gemini-flash": "gemini-1.5-flash",
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"claude-3.5-sonnet": "claude-sonnet-3.5",
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"flux": "ImageGeneration",
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"niansuh": "Niansuh",
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}
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@classmethod
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def get_model(cls, model: str) ->
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if model in cls.models:
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return model
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elif model in cls.
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return model
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elif model in cls.model_aliases and cls.model_aliases[model] in cls.models:
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return cls.model_aliases[model]
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else:
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return cls.default_model
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@classmethod
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async def create_async_generator(
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@@ -230,73 +206,88 @@ class Blackbox:
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model: str,
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messages: List[Dict[str, str]],
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proxy: Optional[str] = None,
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image_name: Optional[str] = None,
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webSearchMode: bool = False,
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**kwargs
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) -> AsyncGenerator[
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model = cls.get_model(model)
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if model is None:
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logger.error(f"Model {model} is not available.")
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raise ModelNotWorkingException(model)
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raise ModelNotWorkingException(model)
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headers = {
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"accept": "*/*",
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"accept-language": "en-US,en;q=0.9",
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"cache-control": "no-cache",
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"content-type": "application/json",
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"origin": cls.url,
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"pragma": "no-cache",
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"priority": "u=1, i",
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"referer": cls.model_referers.get(model, cls.url),
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"sec-ch-ua": '"Chromium";v="129", "Not=A?Brand";v="8"',
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"sec-ch-ua-mobile": "?0",
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"sec-ch-ua-platform": '"Linux"',
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"sec-fetch-dest": "empty",
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"sec-fetch-mode": "cors",
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"sec-fetch-site": "same-origin",
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"user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/129.0.0.0 Safari/537.36",
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}
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prefix = cls.model_prefixes[model]
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if not messages[0]['content'].startswith(prefix):
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logger.debug(f"Adding prefix '{prefix}' to the first message.")
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messages[0]['content'] = f"{prefix} {messages[0]['content']}"
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if image is not None:
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messages[-1]['data'] = {
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'fileText': '',
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'imageBase64': to_data_uri(image),
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'title': image_name
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}
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messages[-1]['content'] = 'FILE:BB\n$#$\n\n$#$\n' + messages[-1]['content']
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logger.debug("Image data added to the message.")
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"
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"previewToken": None,
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"userId": None,
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"codeModelMode": True,
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"agentMode":
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"trendingAgentMode":
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"isMicMode": False,
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"userSystemPrompt": None,
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"maxTokens":
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"playgroundTopP": 0.9,
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"playgroundTemperature": 0.5,
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"isChromeExt": False,
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"clickedForceWebSearch": False,
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"visitFromDelta": False,
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"mobileClient": False,
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"
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"
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}
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retry_attempts = 10 # Set the number of retry attempts
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try:
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async with
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else:
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raise Exception("Image URL not found in the response")
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else:
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raise HTTPException(status_code=504, detail="External API request timed out.")
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except Exception as e:
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# FastAPI app setup
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app = FastAPI()
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frequency_penalty: Optional[float] = 0.0
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logit_bias: Optional[Dict[str, float]] = None
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user: Optional[str] = None
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def create_response(content: str, model: str, finish_reason: Optional[str] = None) -> Dict[str, Any]:
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return {
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async_generator = Blackbox.create_async_generator(
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model=request.model,
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messages=[{"role": msg.role, "content": msg.content} for msg in request.messages], # Actual message content used here
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image_name=None,
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webSearchMode=request.webSearchMode
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)
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if request.stream:
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try:
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async for chunk in async_generator:
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if isinstance(chunk, ImageResponse):
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image_markdown = f"
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else:
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response_chunk = create_response(chunk, request.model)
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response_content = ""
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async for chunk in async_generator:
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if isinstance(chunk, ImageResponse):
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response_content += f"
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raise HTTPException(status_code=500, detail=str(e))
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# Re-added endpoints without API key authentication
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# Endpoint: POST /v1/tokenizer
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class TokenizerRequest(BaseModel):
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text: str
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from typing import List, Dict, Any, Optional, AsyncGenerator, Union
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from datetime import datetime
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from aiohttp import ClientSession, ClientTimeout, ClientError, ClientResponseError
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from fastapi import FastAPI, HTTPException, Request, Depends, Header
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from fastapi.responses import StreamingResponse, JSONResponse, RedirectResponse
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from pydantic import BaseModel
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CLEANUP_INTERVAL = 60 # seconds
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RATE_LIMIT_WINDOW = 60 # seconds
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class ImageResponse:
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def __init__(self, images: str, alt: str):
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self.images = images
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self.alt = alt
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class Blackbox:
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label = "Blackbox AI"
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url = "https://www.blackbox.ai"
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api_endpoint = "https://www.blackbox.ai/api/chat"
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working = True
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supports_gpt_4 = True
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supports_stream = True
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supports_system_message = True
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supports_message_history = True
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models = [
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default_model,
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'blackboxai-pro',
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*image_models,
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"llama-3.1-8b",
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'llama-3.1-70b',
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'llama-3.1-405b',
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'ReactAgent',
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'XcodeAgent',
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'AngularJSAgent',
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]
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agentMode = {
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'ImageGeneration': {'mode': True, 'id': "ImageGenerationLV45LJp", 'name': "Image Generation"},
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}
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trendingAgentMode = {
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"blackboxai": {},
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"gemini-1.5-flash": {'mode': True, 'id': 'Gemini'},
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'AngularJSAgent': '@AngularJS Agent',
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'blackboxai-pro': '@BLACKBOXAI-PRO',
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'ImageGeneration': '@Image Generation',
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}
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model_referers = {
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"blackboxai": "/?model=blackboxai",
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"gpt-4o": "/?model=gpt-4o",
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"gemini-pro": "/?model=gemini-pro",
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"claude-sonnet-3.5": "/?model=claude-sonnet-3.5"
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}
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model_aliases = {
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"gemini-flash": "gemini-1.5-flash",
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"claude-3.5-sonnet": "claude-sonnet-3.5",
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"flux": "ImageGeneration",
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}
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|
158 |
@classmethod
|
159 |
+
def get_model(cls, model: str) -> str:
|
160 |
if model in cls.models:
|
161 |
return model
|
162 |
+
elif model in cls.model_aliases:
|
|
|
|
|
163 |
return cls.model_aliases[model]
|
164 |
else:
|
165 |
+
return cls.default_model
|
166 |
+
|
167 |
+
@staticmethod
|
168 |
+
def generate_random_string(length: int = 7) -> str:
|
169 |
+
characters = string.ascii_letters + string.digits
|
170 |
+
return ''.join(random.choices(characters, k=length))
|
171 |
+
|
172 |
+
@staticmethod
|
173 |
+
def generate_next_action() -> str:
|
174 |
+
return uuid.uuid4().hex
|
175 |
+
|
176 |
+
@staticmethod
|
177 |
+
def generate_next_router_state_tree() -> str:
|
178 |
+
router_state = [
|
179 |
+
"",
|
180 |
+
{
|
181 |
+
"children": [
|
182 |
+
"(chat)",
|
183 |
+
{
|
184 |
+
"children": [
|
185 |
+
"__PAGE__",
|
186 |
+
{}
|
187 |
+
]
|
188 |
+
}
|
189 |
+
]
|
190 |
+
},
|
191 |
+
None,
|
192 |
+
None,
|
193 |
+
True
|
194 |
+
]
|
195 |
+
return json.dumps(router_state)
|
196 |
+
|
197 |
+
@staticmethod
|
198 |
+
def clean_response(text: str) -> str:
|
199 |
+
pattern = r'^\$\@\$v=undefined-rv1\$\@\$'
|
200 |
+
cleaned_text = re.sub(pattern, '', text)
|
201 |
+
return cleaned_text
|
202 |
|
203 |
@classmethod
|
204 |
async def create_async_generator(
|
|
|
206 |
model: str,
|
207 |
messages: List[Dict[str, str]],
|
208 |
proxy: Optional[str] = None,
|
209 |
+
web_search_mode: bool = False,
|
|
|
|
|
210 |
**kwargs
|
211 |
+
) -> AsyncGenerator[Union[str, ImageResponse], None]:
|
212 |
+
"""
|
213 |
+
Creates an asynchronous generator for streaming responses from Blackbox AI.
|
214 |
+
Parameters:
|
215 |
+
model (str): Model to use for generating responses.
|
216 |
+
messages (List[Dict[str, str]]): Message history.
|
217 |
+
proxy (Optional[str]): Proxy URL, if needed.
|
218 |
+
web_search_mode (bool): Enables or disables web search mode.
|
219 |
+
**kwargs: Additional keyword arguments.
|
220 |
+
Yields:
|
221 |
+
Union[str, ImageResponse]: Segments of the generated response or ImageResponse objects.
|
222 |
+
"""
|
223 |
model = cls.get_model(model)
|
224 |
if model is None:
|
225 |
logger.error(f"Model {model} is not available.")
|
226 |
raise ModelNotWorkingException(model)
|
227 |
|
228 |
+
chat_id = cls.generate_random_string()
|
229 |
+
next_action = cls.generate_next_action()
|
230 |
+
next_router_state_tree = cls.generate_next_router_state_tree()
|
231 |
|
232 |
+
agent_mode = cls.agentMode.get(model, {})
|
233 |
+
trending_agent_mode = cls.trendingAgentMode.get(model, {})
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
234 |
|
235 |
+
prefix = cls.model_prefixes.get(model, "")
|
|
|
|
|
|
|
|
|
236 |
|
237 |
+
formatted_prompt = ""
|
238 |
+
for message in messages:
|
239 |
+
role = message.get('role', '').capitalize()
|
240 |
+
content = message.get('content', '')
|
241 |
+
if role and content:
|
242 |
+
formatted_prompt += f"{role}: {content}\n"
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
243 |
|
244 |
+
if prefix:
|
245 |
+
formatted_prompt = f"{prefix} {formatted_prompt}".strip()
|
246 |
+
|
247 |
+
referer_path = cls.model_referers.get(model, f"/?model={model}")
|
248 |
+
referer_url = f"{cls.url}{referer_path}"
|
249 |
+
|
250 |
+
common_headers = {
|
251 |
+
'accept': '*/*',
|
252 |
+
'accept-language': 'en-US,en;q=0.9',
|
253 |
+
'cache-control': 'no-cache',
|
254 |
+
'origin': cls.url,
|
255 |
+
'pragma': 'no-cache',
|
256 |
+
'priority': 'u=1, i',
|
257 |
+
'sec-ch-ua': '"Chromium";v="129", "Not=A?Brand";v="8"',
|
258 |
+
'sec-ch-ua-mobile': '?0',
|
259 |
+
'sec-ch-ua-platform': '"Linux"',
|
260 |
+
'sec-fetch-dest': 'empty',
|
261 |
+
'sec-fetch-mode': 'cors',
|
262 |
+
'sec-fetch-site': 'same-origin',
|
263 |
+
'user-agent': 'Mozilla/5.0 (X11; Linux x86_64) '
|
264 |
+
'AppleWebKit/537.36 (KHTML, like Gecko) '
|
265 |
+
'Chrome/129.0.0.0 Safari/537.36'
|
266 |
+
}
|
267 |
+
|
268 |
+
headers_api_chat = {
|
269 |
+
'Content-Type': 'application/json',
|
270 |
+
'Referer': referer_url
|
271 |
+
}
|
272 |
+
headers_api_chat_combined = {**common_headers, **headers_api_chat}
|
273 |
+
|
274 |
+
payload_api_chat = {
|
275 |
+
"messages": [
|
276 |
+
{
|
277 |
+
"id": chat_id,
|
278 |
+
"content": formatted_prompt,
|
279 |
+
"role": "user"
|
280 |
+
}
|
281 |
+
],
|
282 |
+
"id": chat_id,
|
283 |
"previewToken": None,
|
284 |
"userId": None,
|
285 |
"codeModelMode": True,
|
286 |
+
"agentMode": agent_mode,
|
287 |
+
"trendingAgentMode": trending_agent_mode,
|
288 |
"isMicMode": False,
|
289 |
"userSystemPrompt": None,
|
290 |
+
"maxTokens": 1024,
|
291 |
"playgroundTopP": 0.9,
|
292 |
"playgroundTemperature": 0.5,
|
293 |
"isChromeExt": False,
|
|
|
297 |
"clickedForceWebSearch": False,
|
298 |
"visitFromDelta": False,
|
299 |
"mobileClient": False,
|
300 |
+
"webSearchMode": web_search_mode,
|
301 |
+
"userSelectedModel": cls.userSelectedModel.get(model, model)
|
302 |
}
|
303 |
|
304 |
+
headers_chat = {
|
305 |
+
'Accept': 'text/x-component',
|
306 |
+
'Content-Type': 'text/plain;charset=UTF-8',
|
307 |
+
'Referer': f'{cls.url}/chat/{chat_id}?model={model}',
|
308 |
+
'next-action': next_action,
|
309 |
+
'next-router-state-tree': next_router_state_tree,
|
310 |
+
'next-url': '/'
|
311 |
+
}
|
312 |
+
headers_chat_combined = {**common_headers, **headers_chat}
|
313 |
|
314 |
+
data_chat = '[]'
|
|
|
315 |
|
316 |
+
async with ClientSession(headers=common_headers) as session:
|
317 |
try:
|
318 |
+
async with session.post(
|
319 |
+
cls.api_endpoint,
|
320 |
+
headers=headers_api_chat_combined,
|
321 |
+
json=payload_api_chat,
|
322 |
+
proxy=proxy
|
323 |
+
) as response_api_chat:
|
324 |
+
response_api_chat.raise_for_status()
|
325 |
+
text = await response_api_chat.text()
|
326 |
+
cleaned_response = cls.clean_response(text)
|
327 |
+
|
328 |
+
if model in cls.image_models:
|
329 |
+
match = re.search(r'!\[.*?\]\((https?://[^\)]+)\)', cleaned_response)
|
330 |
+
if match:
|
331 |
+
image_url = match.group(1)
|
332 |
+
image_response = ImageResponse(images=image_url, alt="Generated Image")
|
333 |
+
yield image_response
|
334 |
+
else:
|
335 |
+
yield cleaned_response
|
336 |
+
else:
|
337 |
+
if web_search_mode:
|
338 |
+
match = re.search(r'\$~~~\$(.*?)\$~~~\$', cleaned_response, re.DOTALL)
|
339 |
+
if match:
|
340 |
+
source_part = match.group(1).strip()
|
341 |
+
answer_part = cleaned_response[match.end():].strip()
|
342 |
+
try:
|
343 |
+
sources = json.loads(source_part)
|
344 |
+
source_formatted = "**Source:**\n"
|
345 |
+
for item in sources:
|
346 |
+
title = item.get('title', 'No Title')
|
347 |
+
link = item.get('link', '#')
|
348 |
+
position = item.get('position', '')
|
349 |
+
source_formatted += f"{position}. [{title}]({link})\n"
|
350 |
+
final_response = f"{answer_part}\n\n{source_formatted}"
|
351 |
+
except json.JSONDecodeError:
|
352 |
+
final_response = f"{answer_part}\n\nSource information is unavailable."
|
353 |
else:
|
354 |
+
final_response = cleaned_response
|
|
|
355 |
else:
|
356 |
+
if '$~~~$' in cleaned_response:
|
357 |
+
final_response = cleaned_response.split('$~~~$')[0].strip()
|
358 |
+
else:
|
359 |
+
final_response = cleaned_response
|
360 |
+
|
361 |
+
yield final_response
|
362 |
+
except ClientResponseError as e:
|
363 |
+
error_text = f"Error {e.status}: {e.message}"
|
364 |
+
try:
|
365 |
+
error_response = await e.response.text()
|
366 |
+
cleaned_error = cls.clean_response(error_response)
|
367 |
+
error_text += f" - {cleaned_error}"
|
368 |
+
except Exception:
|
369 |
+
pass
|
370 |
+
yield error_text
|
371 |
+
except Exception as e:
|
372 |
+
yield f"Unexpected error during /api/chat request: {str(e)}"
|
373 |
+
|
374 |
+
chat_url = f'{cls.url}/chat/{chat_id}?model={model}'
|
375 |
+
|
376 |
+
try:
|
377 |
+
async with session.post(
|
378 |
+
chat_url,
|
379 |
+
headers=headers_chat_combined,
|
380 |
+
data=data_chat,
|
381 |
+
proxy=proxy
|
382 |
+
) as response_chat:
|
383 |
+
response_chat.raise_for_status()
|
384 |
+
pass
|
385 |
+
except ClientResponseError as e:
|
386 |
+
error_text = f"Error {e.status}: {e.message}"
|
387 |
+
try:
|
388 |
+
error_response = await e.response.text()
|
389 |
+
cleaned_error = cls.clean_response(error_response)
|
390 |
+
error_text += f" - {cleaned_error}"
|
391 |
+
except Exception:
|
392 |
+
pass
|
393 |
+
yield error_text
|
|
|
394 |
except Exception as e:
|
395 |
+
yield f"Unexpected error during /chat/{chat_id} request: {str(e)}"
|
396 |
+
|
397 |
+
# Custom exception for model not working
|
398 |
+
class ModelNotWorkingException(Exception):
|
399 |
+
def __init__(self, model: str):
|
400 |
+
self.model = model
|
401 |
+
self.message = f"The model '{model}' is currently not working. Please try another model or wait for it to be fixed."
|
402 |
+
super().__init__(self.message)
|
403 |
+
|
404 |
+
async def cleanup_rate_limit_stores():
|
405 |
+
"""
|
406 |
+
Periodically cleans up stale entries in the rate_limit_store to prevent memory bloat.
|
407 |
+
"""
|
408 |
+
while True:
|
409 |
+
current_time = time.time()
|
410 |
+
ips_to_delete = [ip for ip, value in rate_limit_store.items() if current_time - value["timestamp"] > RATE_LIMIT_WINDOW * 2]
|
411 |
+
for ip in ips_to_delete:
|
412 |
+
del rate_limit_store[ip]
|
413 |
+
logger.debug(f"Cleaned up rate_limit_store for IP: {ip}")
|
414 |
+
await asyncio.sleep(CLEANUP_INTERVAL)
|
415 |
+
|
416 |
+
async def rate_limiter_per_ip(request: Request):
|
417 |
+
"""
|
418 |
+
Rate limiter that enforces a limit based on the client's IP address.
|
419 |
+
"""
|
420 |
+
client_ip = request.client.host
|
421 |
+
current_time = time.time()
|
422 |
+
|
423 |
+
# Initialize or update the count and timestamp
|
424 |
+
if current_time - rate_limit_store[client_ip]["timestamp"] > RATE_LIMIT_WINDOW:
|
425 |
+
rate_limit_store[client_ip] = {"count": 1, "timestamp": current_time}
|
426 |
+
else:
|
427 |
+
if rate_limit_store[client_ip]["count"] >= RATE_LIMIT:
|
428 |
+
logger.warning(f"Rate limit exceeded for IP address: {client_ip}")
|
429 |
+
raise HTTPException(status_code=429, detail='Rate limit exceeded for IP address | NiansuhAI')
|
430 |
+
rate_limit_store[client_ip]["count"] += 1
|
431 |
+
|
432 |
+
async def get_api_key(request: Request, authorization: str = Header(None)) -> str:
|
433 |
+
"""
|
434 |
+
Dependency to extract and validate the API key from the Authorization header.
|
435 |
+
"""
|
436 |
+
client_ip = request.client.host
|
437 |
+
if authorization is None or not authorization.startswith('Bearer '):
|
438 |
+
logger.warning(f"Invalid or missing authorization header from IP: {client_ip}")
|
439 |
+
raise HTTPException(status_code=401, detail='Invalid authorization header format')
|
440 |
+
api_key = authorization[7:]
|
441 |
+
if api_key not in API_KEYS:
|
442 |
+
logger.warning(f"Invalid API key attempted: {api_key} from IP: {client_ip}")
|
443 |
+
raise HTTPException(status_code=401, detail='Invalid API key')
|
444 |
+
return api_key
|
445 |
|
446 |
# FastAPI app setup
|
447 |
app = FastAPI()
|
|
|
493 |
frequency_penalty: Optional[float] = 0.0
|
494 |
logit_bias: Optional[Dict[str, float]] = None
|
495 |
user: Optional[str] = None
|
496 |
+
web_search_mode: Optional[bool] = False # Custom parameter
|
497 |
|
498 |
def create_response(content: str, model: str, finish_reason: Optional[str] = None) -> Dict[str, Any]:
|
499 |
return {
|
|
|
529 |
async_generator = Blackbox.create_async_generator(
|
530 |
model=request.model,
|
531 |
messages=[{"role": msg.role, "content": msg.content} for msg in request.messages], # Actual message content used here
|
532 |
+
web_search_mode=request.web_search_mode
|
|
|
|
|
533 |
)
|
534 |
|
535 |
if request.stream:
|
|
|
537 |
try:
|
538 |
async for chunk in async_generator:
|
539 |
if isinstance(chunk, ImageResponse):
|
540 |
+
image_markdown = f""
|
541 |
response_chunk = create_response(image_markdown, request.model)
|
542 |
else:
|
543 |
response_chunk = create_response(chunk, request.model)
|
|
|
558 |
response_content = ""
|
559 |
async for chunk in async_generator:
|
560 |
if isinstance(chunk, ImageResponse):
|
561 |
+
response_content += f"\n"
|
562 |
else:
|
563 |
response_content += chunk
|
564 |
|
|
|
594 |
logger.exception(f"An unexpected error occurred while processing the chat completions request from IP: {client_ip}.")
|
595 |
raise HTTPException(status_code=500, detail=str(e))
|
596 |
|
|
|
|
|
597 |
# Endpoint: POST /v1/tokenizer
|
598 |
class TokenizerRequest(BaseModel):
|
599 |
text: str
|