mirror of
https://github.com/xtekky/gpt4free.git
synced 2025-12-06 02:30:41 -08:00
649 lines
30 KiB
Python
649 lines
30 KiB
Python
from __future__ import annotations
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from aiohttp import ClientSession
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import os
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import re
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import json
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import random
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import string
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import base64
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from pathlib import Path
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from typing import Optional
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from datetime import datetime, timedelta
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from ..typing import AsyncResult, Messages, MediaListType
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from ..requests.raise_for_status import raise_for_status
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from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
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from ..image import to_data_uri
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from ..cookies import get_cookies_dir
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from .helper import format_prompt, format_image_prompt
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from ..providers.response import JsonConversation, ImageResponse
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from ..errors import ModelNotSupportedError
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from .. import debug
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class Conversation(JsonConversation):
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validated_value: str = None
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chat_id: str = None
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message_history: Messages = []
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def __init__(self, model: str):
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self.model = model
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class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):
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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_stream = True
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supports_system_message = True
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supports_message_history = True
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default_model = "blackboxai"
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default_vision_model = default_model
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default_image_model = 'flux'
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# Completely free models
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fallback_models = [
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"blackboxai",
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"gpt-4o-mini",
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"GPT-4o",
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"o1",
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"o3-mini",
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"Claude-sonnet-3.7",
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"DeepSeek-V3",
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"DeepSeek-R1",
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"DeepSeek-LLM-Chat-(67B)",
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# Image models
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"flux",
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# Trending agent modes
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'Python Agent',
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'HTML Agent',
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'Builder Agent',
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'Java Agent',
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'JavaScript Agent',
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'React Agent',
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'Android Agent',
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'Flutter Agent',
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'Next.js Agent',
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'AngularJS Agent',
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'Swift Agent',
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'MongoDB Agent',
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'PyTorch Agent',
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'Xcode Agent',
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'Azure Agent',
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'Bitbucket Agent',
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'DigitalOcean Agent',
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'Docker Agent',
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'Electron Agent',
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'Erlang Agent',
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'FastAPI Agent',
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'Firebase Agent',
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'Flask Agent',
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'Git Agent',
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'Gitlab Agent',
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'Go Agent',
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'Godot Agent',
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'Google Cloud Agent',
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'Heroku Agent'
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]
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image_models = [default_image_model]
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vision_models = [default_vision_model, 'GPT-4o', 'o1', 'o3-mini', 'Gemini-PRO', 'Gemini Agent', 'llama-3.1-8b Agent', 'llama-3.1-70b Agent', 'llama-3.1-405 Agent', 'Gemini-Flash-2.0', 'DeepSeek-V3']
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userSelectedModel = ['GPT-4o', 'o1', 'o3-mini', 'Gemini-PRO', 'Claude-sonnet-3.7', 'DeepSeek-V3', 'DeepSeek-R1', 'Meta-Llama-3.3-70B-Instruct-Turbo', 'Mistral-Small-24B-Instruct-2501', 'DeepSeek-LLM-Chat-(67B)', 'DBRX-Instruct', 'Qwen-QwQ-32B-Preview', 'Nous-Hermes-2-Mixtral-8x7B-DPO', 'Gemini-Flash-2.0']
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# Agent mode configurations
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agentMode = {
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'GPT-4o': {'mode': True, 'id': "GPT-4o", 'name': "GPT-4o"},
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'Gemini-PRO': {'mode': True, 'id': "Gemini-PRO", 'name': "Gemini-PRO"},
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'Claude-sonnet-3.7': {'mode': True, 'id': "Claude-sonnet-3.7", 'name': "Claude-sonnet-3.7"},
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'DeepSeek-V3': {'mode': True, 'id': "deepseek-chat", 'name': "DeepSeek-V3"},
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'DeepSeek-R1': {'mode': True, 'id': "deepseek-reasoner", 'name': "DeepSeek-R1"},
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'Meta-Llama-3.3-70B-Instruct-Turbo': {'mode': True, 'id': "meta-llama/Llama-3.3-70B-Instruct-Turbo", 'name': "Meta-Llama-3.3-70B-Instruct-Turbo"},
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'Gemini-Flash-2.0': {'mode': True, 'id': "Gemini/Gemini-Flash-2.0", 'name': "Gemini-Flash-2.0"},
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'Mistral-Small-24B-Instruct-2501': {'mode': True, 'id': "mistralai/Mistral-Small-24B-Instruct-2501", 'name': "Mistral-Small-24B-Instruct-2501"},
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'DeepSeek-LLM-Chat-(67B)': {'mode': True, 'id': "deepseek-ai/deepseek-llm-67b-chat", 'name': "DeepSeek-LLM-Chat-(67B)"},
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'DBRX-Instruct': {'mode': True, 'id': "databricks/dbrx-instruct", 'name': "DBRX-Instruct"},
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'Qwen-QwQ-32B-Preview': {'mode': True, 'id': "Qwen/QwQ-32B-Preview", 'name': "Qwen-QwQ-32B-Preview"},
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'Nous-Hermes-2-Mixtral-8x7B-DPO': {'mode': True, 'id': "NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO", 'name': "Nous-Hermes-2-Mixtral-8x7B-DPO"},
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}
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# Trending agent modes
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trendingAgentMode = {
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"Gemini Agent": {'mode': True, 'id': 'gemini'},
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"llama-3.1-405 Agent": {'mode': True, 'id': "llama-3.1-405"},
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'llama-3.1-70b Agent': {'mode': True, 'id': "llama-3.1-70b"},
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'llama-3.1-8b Agent': {'mode': True, 'id': "llama-3.1-8b"},
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'Python Agent': {'mode': True, 'id': "python"},
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'HTML Agent': {'mode': True, 'id': "html"},
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'Builder Agent': {'mode': True, 'id': "builder"},
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'Java Agent': {'mode': True, 'id': "java"},
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'JavaScript Agent': {'mode': True, 'id': "javascript"},
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'React Agent': {'mode': True, 'id': "react"},
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'Android Agent': {'mode': True, 'id': "android"},
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'Flutter Agent': {'mode': True, 'id': "flutter"},
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'Next.js Agent': {'mode': True, 'id': "next.js"},
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'AngularJS Agent': {'mode': True, 'id': "angularjs"},
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'Swift Agent': {'mode': True, 'id': "swift"},
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'MongoDB Agent': {'mode': True, 'id': "mongodb"},
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'PyTorch Agent': {'mode': True, 'id': "pytorch"},
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'Xcode Agent': {'mode': True, 'id': "xcode"},
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'Azure Agent': {'mode': True, 'id': "azure"},
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'Bitbucket Agent': {'mode': True, 'id': "bitbucket"},
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'DigitalOcean Agent': {'mode': True, 'id': "digitalocean"},
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'Docker Agent': {'mode': True, 'id': "docker"},
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'Electron Agent': {'mode': True, 'id': "electron"},
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'Erlang Agent': {'mode': True, 'id': "erlang"},
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'FastAPI Agent': {'mode': True, 'id': "fastapi"},
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'Firebase Agent': {'mode': True, 'id': "firebase"},
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'Flask Agent': {'mode': True, 'id': "flask"},
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'Git Agent': {'mode': True, 'id': "git"},
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'Gitlab Agent': {'mode': True, 'id': "gitlab"},
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'Go Agent': {'mode': True, 'id': "go"},
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'Godot Agent': {'mode': True, 'id': "godot"},
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'Google Cloud Agent': {'mode': True, 'id': "googlecloud"},
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'Heroku Agent': {'mode': True, 'id': "heroku"},
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}
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# Complete list of all models (for authorized users)
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_all_models = list(dict.fromkeys([
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default_model,
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*userSelectedModel,
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*image_models,
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*list(agentMode.keys()),
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*list(trendingAgentMode.keys())
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]))
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@classmethod
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def generate_session(cls, id_length: int = 21, days_ahead: int = 365) -> dict:
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"""
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Generate a dynamic session with proper ID and expiry format.
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Args:
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id_length: Length of the numeric ID (default: 21)
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days_ahead: Number of days ahead for expiry (default: 365)
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Returns:
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dict: A session dictionary with user information and expiry
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"""
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# Generate numeric ID
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numeric_id = ''.join(random.choice('0123456789') for _ in range(id_length))
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# Generate future expiry date
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future_date = datetime.now() + timedelta(days=days_ahead)
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expiry = future_date.strftime('%Y-%m-%dT%H:%M:%S.%f')[:-3] + 'Z'
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# Decode the encoded email
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encoded_email = "Z2lzZWxlQGJsYWNrYm94LmFp" # Base64 encoded email
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email = base64.b64decode(encoded_email).decode('utf-8')
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# Generate random image ID for the new URL format
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chars = string.ascii_letters + string.digits + "-"
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random_img_id = ''.join(random.choice(chars) for _ in range(48))
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image_url = f"https://lh3.googleusercontent.com/a/ACg8oc{random_img_id}=s96-c"
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return {
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"user": {
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"name": "BLACKBOX AI",
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"email": email,
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"image": image_url,
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"id": numeric_id
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},
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"expires": expiry
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}
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@classmethod
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async def fetch_validated(cls, url: str = "https://www.blackbox.ai", force_refresh: bool = False) -> Optional[str]:
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cache_file = Path(get_cookies_dir()) / 'blackbox.json'
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if not force_refresh and cache_file.exists():
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try:
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with open(cache_file, 'r') as f:
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data = json.load(f)
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if data.get('validated_value'):
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return data['validated_value']
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except Exception as e:
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debug.log(f"Blackbox: Error reading cache: {e}")
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js_file_pattern = r'static/chunks/\d{4}-[a-fA-F0-9]+\.js'
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uuid_pattern = r'["\']([0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{12})["\']'
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def is_valid_context(text: str) -> bool:
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return any(char + '=' in text for char in 'abcdefghijklmnopqrstuvwxyz')
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async with ClientSession() as session:
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try:
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async with session.get(url) as response:
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if response.status != 200:
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return None
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page_content = await response.text()
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js_files = re.findall(js_file_pattern, page_content)
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for js_file in js_files:
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js_url = f"{url}/_next/{js_file}"
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async with session.get(js_url) as js_response:
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if js_response.status == 200:
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js_content = await js_response.text()
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for match in re.finditer(uuid_pattern, js_content):
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start = max(0, match.start() - 10)
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end = min(len(js_content), match.end() + 10)
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context = js_content[start:end]
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if is_valid_context(context):
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validated_value = match.group(1)
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cache_file.parent.mkdir(exist_ok=True)
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try:
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with open(cache_file, 'w') as f:
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json.dump({'validated_value': validated_value}, f)
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except Exception as e:
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debug.log(f"Blackbox: Error writing cache: {e}")
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return validated_value
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except Exception as e:
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debug.log(f"Blackbox: Error retrieving validated_value: {e}")
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return None
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@classmethod
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def generate_id(cls, length: int = 7) -> str:
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chars = string.ascii_letters + string.digits
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return ''.join(random.choice(chars) for _ in range(length))
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@classmethod
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def get_models(cls) -> list:
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"""
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Returns a list of available models based on authorization status.
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Authorized users get the full list of models.
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Unauthorized users only get fallback_models.
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"""
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# Check if there are valid session data in HAR files
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has_premium_access = cls._check_premium_access()
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if has_premium_access:
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# For authorized users - all models
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debug.log(f"Blackbox: Returning full model list with {len(cls._all_models)} models")
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return cls._all_models
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else:
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# For demo accounts - only free models
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debug.log(f"Blackbox: Returning free model list with {len(cls.fallback_models)} models")
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return cls.fallback_models
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@classmethod
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def _check_premium_access(cls) -> bool:
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"""
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Checks for an authorized session in HAR files.
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Returns True if a valid session is found that differs from the demo.
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"""
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try:
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har_dir = get_cookies_dir()
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if not os.access(har_dir, os.R_OK):
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return False
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for root, _, files in os.walk(har_dir):
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for file in files:
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if file.endswith(".har"):
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try:
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with open(os.path.join(root, file), 'rb') as f:
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har_data = json.load(f)
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for entry in har_data['log']['entries']:
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# Only check requests to blackbox API
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if 'blackbox.ai/api' in entry['request']['url']:
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if 'response' in entry and 'content' in entry['response']:
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content = entry['response']['content']
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if ('text' in content and
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isinstance(content['text'], str) and
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'"user"' in content['text'] and
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'"email"' in content['text']):
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try:
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# Process request text
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text = content['text'].strip()
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if text.startswith('{') and text.endswith('}'):
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text = text.replace('\\"', '"')
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session_data = json.loads(text)
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# Check if this is a valid session
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if (isinstance(session_data, dict) and
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'user' in session_data and
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'email' in session_data['user']):
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# Check if this is not a demo session
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demo_session = cls.generate_session()
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if (session_data['user'].get('email') !=
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demo_session['user'].get('email')):
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# This is not a demo session, so user has premium access
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return True
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except:
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pass
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except:
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pass
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return False
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except Exception as e:
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debug.log(f"Blackbox: Error checking premium access: {e}")
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return False
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# Initialize models with fallback_models
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models = fallback_models
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model_aliases = {
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"gpt-4o": "GPT-4o",
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"claude-3.7-sonnet": "Claude-sonnet-3.7",
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"deepseek-v3": "DeepSeek-V3",
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"deepseek-r1": "DeepSeek-R1",
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"deepseek-chat": "DeepSeek-LLM-Chat-(67B)",
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}
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@classmethod
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def generate_session(cls, id_length: int = 21, days_ahead: int = 365) -> dict:
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"""
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Generate a dynamic session with proper ID and expiry format.
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Args:
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id_length: Length of the numeric ID (default: 21)
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days_ahead: Number of days ahead for expiry (default: 365)
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Returns:
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dict: A session dictionary with user information and expiry
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"""
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# Generate numeric ID
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numeric_id = ''.join(random.choice('0123456789') for _ in range(id_length))
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# Generate future expiry date
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future_date = datetime.now() + timedelta(days=days_ahead)
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expiry = future_date.strftime('%Y-%m-%dT%H:%M:%S.%f')[:-3] + 'Z'
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# Decode the encoded email
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encoded_email = "Z2lzZWxlQGJsYWNrYm94LmFp" # Base64 encoded email
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email = base64.b64decode(encoded_email).decode('utf-8')
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# Generate random image ID for the new URL format
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chars = string.ascii_letters + string.digits + "-"
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random_img_id = ''.join(random.choice(chars) for _ in range(48))
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image_url = f"https://lh3.googleusercontent.com/a/ACg8oc{random_img_id}=s96-c"
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return {
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"user": {
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"name": "BLACKBOX AI",
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"email": email,
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"image": image_url,
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"id": numeric_id
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},
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"expires": expiry
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}
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@classmethod
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async def fetch_validated(cls, url: str = "https://www.blackbox.ai", force_refresh: bool = False) -> Optional[str]:
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cache_file = Path(get_cookies_dir()) / 'blackbox.json'
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if not force_refresh and cache_file.exists():
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try:
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with open(cache_file, 'r') as f:
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data = json.load(f)
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if data.get('validated_value'):
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return data['validated_value']
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except Exception as e:
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debug.log(f"Blackbox: Error reading cache: {e}")
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js_file_pattern = r'static/chunks/\d{4}-[a-fA-F0-9]+\.js'
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uuid_pattern = r'["\']([0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{12})["\']'
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def is_valid_context(text: str) -> bool:
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return any(char + '=' in text for char in 'abcdefghijklmnopqrstuvwxyz')
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async with ClientSession() as session:
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try:
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async with session.get(url) as response:
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if response.status != 200:
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return None
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page_content = await response.text()
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js_files = re.findall(js_file_pattern, page_content)
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for js_file in js_files:
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js_url = f"{url}/_next/{js_file}"
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async with session.get(js_url) as js_response:
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if js_response.status == 200:
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js_content = await js_response.text()
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for match in re.finditer(uuid_pattern, js_content):
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start = max(0, match.start() - 10)
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end = min(len(js_content), match.end() + 10)
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context = js_content[start:end]
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if is_valid_context(context):
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validated_value = match.group(1)
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cache_file.parent.mkdir(exist_ok=True)
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try:
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with open(cache_file, 'w') as f:
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json.dump({'validated_value': validated_value}, f)
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except Exception as e:
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debug.log(f"Blackbox: Error writing cache: {e}")
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return validated_value
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except Exception as e:
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debug.log(f"Blackbox: Error retrieving validated_value: {e}")
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return None
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@classmethod
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def generate_id(cls, length: int = 7) -> str:
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chars = string.ascii_letters + string.digits
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return ''.join(random.choice(chars) for _ in range(length))
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@classmethod
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async def create_async_generator(
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cls,
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model: str,
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messages: Messages,
|
|
prompt: str = None,
|
|
proxy: str = None,
|
|
media: MediaListType = None,
|
|
top_p: float = None,
|
|
temperature: float = None,
|
|
max_tokens: int = None,
|
|
conversation: Conversation = None,
|
|
return_conversation: bool = False,
|
|
**kwargs
|
|
) -> AsyncResult:
|
|
model = cls.get_model(model)
|
|
headers = {
|
|
'accept': '*/*',
|
|
'accept-language': 'en-US,en;q=0.9',
|
|
'content-type': 'application/json',
|
|
'origin': 'https://www.blackbox.ai',
|
|
'referer': 'https://www.blackbox.ai/',
|
|
'user-agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36'
|
|
}
|
|
|
|
async with ClientSession(headers=headers) as session:
|
|
if conversation is None or not hasattr(conversation, "chat_id"):
|
|
conversation = Conversation(model)
|
|
conversation.validated_value = await cls.fetch_validated()
|
|
conversation.chat_id = cls.generate_id()
|
|
conversation.message_history = []
|
|
|
|
current_messages = []
|
|
for i, msg in enumerate(messages):
|
|
msg_id = conversation.chat_id if i == 0 and msg["role"] == "user" else cls.generate_id()
|
|
current_msg = {
|
|
"id": msg_id,
|
|
"content": msg["content"],
|
|
"role": msg["role"]
|
|
}
|
|
current_messages.append(current_msg)
|
|
|
|
if media is not None:
|
|
current_messages[-1]['data'] = {
|
|
"imagesData": [
|
|
{
|
|
"filePath": f"/{image_name}",
|
|
"contents": to_data_uri(image)
|
|
}
|
|
for image, image_name in media
|
|
],
|
|
"fileText": "",
|
|
"title": ""
|
|
}
|
|
|
|
# Try to get session data from HAR files
|
|
session_data = cls.generate_session() # Default fallback
|
|
session_found = False
|
|
|
|
# Look for HAR session data
|
|
har_dir = get_cookies_dir()
|
|
if os.access(har_dir, os.R_OK):
|
|
for root, _, files in os.walk(har_dir):
|
|
for file in files:
|
|
if file.endswith(".har"):
|
|
try:
|
|
with open(os.path.join(root, file), 'rb') as f:
|
|
har_data = json.load(f)
|
|
|
|
for entry in har_data['log']['entries']:
|
|
# Only look at blackbox API responses
|
|
if 'blackbox.ai/api' in entry['request']['url']:
|
|
# Look for a response that has the right structure
|
|
if 'response' in entry and 'content' in entry['response']:
|
|
content = entry['response']['content']
|
|
# Look for both regular and Google auth session formats
|
|
if ('text' in content and
|
|
isinstance(content['text'], str) and
|
|
'"user"' in content['text'] and
|
|
'"email"' in content['text'] and
|
|
'"expires"' in content['text']):
|
|
|
|
try:
|
|
# Remove any HTML or other non-JSON content
|
|
text = content['text'].strip()
|
|
if text.startswith('{') and text.endswith('}'):
|
|
# Replace escaped quotes
|
|
text = text.replace('\\"', '"')
|
|
har_session = json.loads(text)
|
|
|
|
# Check if this is a valid session object (supports both regular and Google auth)
|
|
if (isinstance(har_session, dict) and
|
|
'user' in har_session and
|
|
'email' in har_session['user'] and
|
|
'expires' in har_session):
|
|
|
|
file_path = os.path.join(root, file)
|
|
debug.log(f"Blackbox: Found session in HAR file")
|
|
|
|
session_data = har_session
|
|
session_found = True
|
|
break
|
|
except json.JSONDecodeError as e:
|
|
# Only print error for entries that truly look like session data
|
|
if ('"user"' in content['text'] and
|
|
'"email"' in content['text']):
|
|
debug.log(f"Blackbox: Error parsing likely session data: {e}")
|
|
|
|
if session_found:
|
|
break
|
|
|
|
except Exception as e:
|
|
debug.log(f"Blackbox: Error reading HAR file: {e}")
|
|
|
|
if session_found:
|
|
break
|
|
|
|
if session_found:
|
|
break
|
|
|
|
data = {
|
|
"messages": current_messages,
|
|
"agentMode": cls.agentMode.get(model, {}) if model in cls.agentMode else {},
|
|
"id": conversation.chat_id,
|
|
"previewToken": None,
|
|
"userId": None,
|
|
"codeModelMode": True,
|
|
"trendingAgentMode": cls.trendingAgentMode.get(model, {}) if model in cls.trendingAgentMode else {},
|
|
"isMicMode": False,
|
|
"userSystemPrompt": None,
|
|
"maxTokens": max_tokens,
|
|
"playgroundTopP": top_p,
|
|
"playgroundTemperature": temperature,
|
|
"isChromeExt": False,
|
|
"githubToken": "",
|
|
"clickedAnswer2": False,
|
|
"clickedAnswer3": False,
|
|
"clickedForceWebSearch": False,
|
|
"visitFromDelta": False,
|
|
"isMemoryEnabled": False,
|
|
"mobileClient": False,
|
|
"userSelectedModel": model if model in cls.userSelectedModel else None,
|
|
"validated": conversation.validated_value,
|
|
"imageGenerationMode": model == cls.default_image_model,
|
|
"webSearchModePrompt": False,
|
|
"deepSearchMode": False,
|
|
"domains": None,
|
|
"vscodeClient": False,
|
|
"codeInterpreterMode": False,
|
|
"customProfile": {
|
|
"name": "",
|
|
"occupation": "",
|
|
"traits": [],
|
|
"additionalInfo": "",
|
|
"enableNewChats": False
|
|
},
|
|
"session": session_data if session_data else cls.generate_session(),
|
|
"isPremium": True,
|
|
"subscriptionCache": None,
|
|
"beastMode": False,
|
|
"webSearchMode": False
|
|
}
|
|
|
|
# Add debugging before making the API call
|
|
if isinstance(session_data, dict) and 'user' in session_data:
|
|
# Генеруємо демо-сесію для порівняння
|
|
demo_session = cls.generate_session()
|
|
is_demo = False
|
|
|
|
if demo_session and isinstance(demo_session, dict) and 'user' in demo_session:
|
|
if session_data['user'].get('email') == demo_session['user'].get('email'):
|
|
is_demo = True
|
|
|
|
if is_demo:
|
|
debug.log(f"Blackbox: Making API request with built-in Developer Premium Account")
|
|
else:
|
|
user_email = session_data['user'].get('email', 'unknown')
|
|
debug.log(f"Blackbox: Making API request with HAR session email: {user_email}")
|
|
|
|
# Continue with the API request and async generator behavior
|
|
async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response:
|
|
await raise_for_status(response)
|
|
|
|
# Collect the full response
|
|
full_response = []
|
|
async for chunk in response.content.iter_any():
|
|
if chunk:
|
|
chunk_text = chunk.decode()
|
|
full_response.append(chunk_text)
|
|
# Only yield chunks for non-image models
|
|
if model != cls.default_image_model:
|
|
yield chunk_text
|
|
|
|
full_response_text = ''.join(full_response)
|
|
|
|
# For image models, check for image markdown
|
|
if model == cls.default_image_model:
|
|
image_url_match = re.search(r'!\[.*?\]\((.*?)\)', full_response_text)
|
|
if image_url_match:
|
|
image_url = image_url_match.group(1)
|
|
yield ImageResponse(images=[image_url], alt=format_image_prompt(messages, prompt))
|
|
return
|
|
|
|
# Handle conversation history once, in one place
|
|
if return_conversation:
|
|
conversation.message_history.append({"role": "assistant", "content": full_response_text})
|
|
yield conversation
|
|
# For image models that didn't produce an image, fall back to text response
|
|
elif model == cls.default_image_model:
|
|
yield full_response_text
|