gpt4free/g4f/Provider/Blackbox.py

from __future__ import annotations

from aiohttp import ClientSession
import os
import re
import json
import random
import string
import base64
from pathlib import Path
from typing import Optional
from datetime import datetime, timedelta

from ..typing import AsyncResult, Messages, MediaListType
from ..requests.raise_for_status import raise_for_status
from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
from ..image import to_data_uri
from ..cookies import get_cookies_dir
from .helper import format_prompt, format_image_prompt
from ..providers.response import JsonConversation, ImageResponse
from ..errors import ModelNotSupportedError
from .. import debug

class Conversation(JsonConversation):
    validated_value: str = None
    chat_id: str = None
    message_history: Messages = []

    def __init__(self, model: str):
        self.model = model

class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):
    label = "Blackbox AI"
    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 = "blackboxai"
    default_vision_model = default_model
    default_image_model = 'flux'
    
    # Completely free models
    fallback_models = [
        "blackboxai", 
        "blackboxai-pro",
        "gpt-4o-mini", 
        "GPT-4o", 
        "o1", 
        "o3-mini", 
        "Claude-sonnet-3.7", 
        "DeepSeek-V3", 
        "DeepSeek-R1", 
        "DeepSeek-LLM-Chat-(67B)",
        # Image models
        "flux",
        # Trending agent modes
        'Python Agent',
        'HTML Agent',
        'Builder Agent',
        'Java Agent',
        'JavaScript Agent',
        'React Agent',
        'Android Agent',
        'Flutter Agent',
        'Next.js Agent',
        'AngularJS Agent',
        'Swift Agent',
        'MongoDB Agent',
        'PyTorch Agent',
        'Xcode Agent',
        'Azure Agent',
        'Bitbucket Agent',
        'DigitalOcean Agent',
        'Docker Agent',
        'Electron Agent',
        'Erlang Agent',
        'FastAPI Agent',
        'Firebase Agent',
        'Flask Agent',
        'Git Agent',
        'Gitlab Agent',
        'Go Agent',
        'Godot Agent',
        'Google Cloud Agent',
        'Heroku Agent'
    ]
    
    image_models = [default_image_model]   
    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']

    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']

    # Agent mode configurations
    agentMode = {
        'GPT-4o': {'mode': True, 'id': "GPT-4o", 'name': "GPT-4o"},
        'Gemini-PRO': {'mode': True, 'id': "Gemini-PRO", 'name': "Gemini-PRO"},
        'Claude-sonnet-3.7': {'mode': True, 'id': "Claude-sonnet-3.7", 'name': "Claude-sonnet-3.7"},
        'DeepSeek-V3': {'mode': True, 'id': "deepseek-chat", 'name': "DeepSeek-V3"},
        'DeepSeek-R1': {'mode': True, 'id': "deepseek-reasoner", 'name': "DeepSeek-R1"},
        '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"},
        'Gemini-Flash-2.0': {'mode': True, 'id': "Gemini/Gemini-Flash-2.0", 'name': "Gemini-Flash-2.0"},
        'Mistral-Small-24B-Instruct-2501': {'mode': True, 'id': "mistralai/Mistral-Small-24B-Instruct-2501", 'name': "Mistral-Small-24B-Instruct-2501"},
        'DeepSeek-LLM-Chat-(67B)': {'mode': True, 'id': "deepseek-ai/deepseek-llm-67b-chat", 'name': "DeepSeek-LLM-Chat-(67B)"},
        'DBRX-Instruct': {'mode': True, 'id': "databricks/dbrx-instruct", 'name': "DBRX-Instruct"},
        'Qwen-QwQ-32B-Preview': {'mode': True, 'id': "Qwen/QwQ-32B-Preview", 'name': "Qwen-QwQ-32B-Preview"},
        'Nous-Hermes-2-Mixtral-8x7B-DPO': {'mode': True, 'id': "NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO", 'name': "Nous-Hermes-2-Mixtral-8x7B-DPO"},
    }

    # Trending agent modes
    trendingAgentMode = {
        'blackboxai-pro': {'mode': True, 'id': "BLACKBOXAI-PRO"},
        "Gemini Agent": {'mode': True, 'id': 'gemini'},
        "llama-3.1-405 Agent": {'mode': True, 'id': "llama-3.1-405"},
        'llama-3.1-70b Agent': {'mode': True, 'id': "llama-3.1-70b"},
        'llama-3.1-8b Agent': {'mode': True, 'id': "llama-3.1-8b"},
        'Python Agent': {'mode': True, 'id': "python"},
        'HTML Agent': {'mode': True, 'id': "html"},
        'Builder Agent': {'mode': True, 'id': "builder"},
        'Java Agent': {'mode': True, 'id': "java"},
        'JavaScript Agent': {'mode': True, 'id': "javascript"},
        'React Agent': {'mode': True, 'id': "react"},
        'Android Agent': {'mode': True, 'id': "android"},
        'Flutter Agent': {'mode': True, 'id': "flutter"},
        'Next.js Agent': {'mode': True, 'id': "next.js"},
        'AngularJS Agent': {'mode': True, 'id': "angularjs"},
        'Swift Agent': {'mode': True, 'id': "swift"},
        'MongoDB Agent': {'mode': True, 'id': "mongodb"},
        'PyTorch Agent': {'mode': True, 'id': "pytorch"},
        'Xcode Agent': {'mode': True, 'id': "xcode"},
        'Azure Agent': {'mode': True, 'id': "azure"},
        'Bitbucket Agent': {'mode': True, 'id': "bitbucket"},
        'DigitalOcean Agent': {'mode': True, 'id': "digitalocean"},
        'Docker Agent': {'mode': True, 'id': "docker"},
        'Electron Agent': {'mode': True, 'id': "electron"},
        'Erlang Agent': {'mode': True, 'id': "erlang"},
        'FastAPI Agent': {'mode': True, 'id': "fastapi"},
        'Firebase Agent': {'mode': True, 'id': "firebase"},
        'Flask Agent': {'mode': True, 'id': "flask"},
        'Git Agent': {'mode': True, 'id': "git"},
        'Gitlab Agent': {'mode': True, 'id': "gitlab"},
        'Go Agent': {'mode': True, 'id': "go"},
        'Godot Agent': {'mode': True, 'id': "godot"},
        'Google Cloud Agent': {'mode': True, 'id': "googlecloud"},
        'Heroku Agent': {'mode': True, 'id': "heroku"},
    }
    
    # Complete list of all models (for authorized users)
    _all_models = list(dict.fromkeys([
        default_model,
        *userSelectedModel,
        *image_models,
        *list(agentMode.keys()),
        *list(trendingAgentMode.keys())
    ]))
    
    @classmethod
    def generate_session(cls, id_length: int = 21, days_ahead: int = 365) -> dict:
        """
        Generate a dynamic session with proper ID and expiry format.
        
        Args:
            id_length: Length of the numeric ID (default: 21)
            days_ahead: Number of days ahead for expiry (default: 365)
        
        Returns:
            dict: A session dictionary with user information and expiry
        """
        # Generate numeric ID
        numeric_id = ''.join(random.choice('0123456789') for _ in range(id_length))
        
        # Generate future expiry date
        future_date = datetime.now() + timedelta(days=days_ahead)
        expiry = future_date.strftime('%Y-%m-%dT%H:%M:%S.%f')[:-3] + 'Z'
        
        # Decode the encoded email
        encoded_email = "Z2lzZWxlQGJsYWNrYm94LmFp"  # Base64 encoded email
        email = base64.b64decode(encoded_email).decode('utf-8')
        
        # Generate random image ID for the new URL format
        chars = string.ascii_letters + string.digits + "-"
        random_img_id = ''.join(random.choice(chars) for _ in range(48))
        image_url = f"https://lh3.googleusercontent.com/a/ACg8oc{random_img_id}=s96-c"
        
        return {
            "user": {
                "name": "BLACKBOX AI", 
                "email": email, 
                "image": image_url, 
                "id": numeric_id
            }, 
            "expires": expiry
        }

    @classmethod
    async def fetch_validated(cls, url: str = "https://www.blackbox.ai", force_refresh: bool = False) -> Optional[str]:
        cache_file = Path(get_cookies_dir()) / 'blackbox.json'
        
        if not force_refresh and cache_file.exists():
            try:
                with open(cache_file, 'r') as f:
                    data = json.load(f)
                    if data.get('validated_value'):
                        return data['validated_value']
            except Exception as e:
                debug.log(f"Blackbox: Error reading cache: {e}")
        
        js_file_pattern = r'static/chunks/\d{4}-[a-fA-F0-9]+\.js'
        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})["\']'

        def is_valid_context(text: str) -> bool:
            return any(char + '=' in text for char in 'abcdefghijklmnopqrstuvwxyz')

        async with ClientSession() as session:
            try:
                async with session.get(url) as response:
                    if response.status != 200:
                        return None

                    page_content = await response.text()
                    js_files = re.findall(js_file_pattern, page_content)

                for js_file in js_files:
                    js_url = f"{url}/_next/{js_file}"
                    async with session.get(js_url) as js_response:
                        if js_response.status == 200:
                            js_content = await js_response.text()
                            for match in re.finditer(uuid_pattern, js_content):
                                start = max(0, match.start() - 10)
                                end = min(len(js_content), match.end() + 10)
                                context = js_content[start:end]

                                if is_valid_context(context):
                                    validated_value = match.group(1)
                                    
                                    cache_file.parent.mkdir(exist_ok=True)
                                    try:
                                        with open(cache_file, 'w') as f:
                                            json.dump({'validated_value': validated_value}, f)
                                    except Exception as e:
                                        debug.log(f"Blackbox: Error writing cache: {e}")
                                        
                                    return validated_value

            except Exception as e:
                debug.log(f"Blackbox: Error retrieving validated_value: {e}")

        return None

    @classmethod
    def generate_id(cls, length: int = 7) -> str:
        chars = string.ascii_letters + string.digits
        return ''.join(random.choice(chars) for _ in range(length))
    
    @classmethod
    def get_models(cls) -> list:
        """
        Returns a list of available models based on authorization status.
        Authorized users get the full list of models.
        Unauthorized users only get fallback_models.
        """
        # Check if there are valid session data in HAR files
        has_premium_access = cls._check_premium_access()
        
        if has_premium_access:
            # For authorized users - all models
            debug.log(f"Blackbox: Returning full model list with {len(cls._all_models)} models")
            return cls._all_models
        else:
            # For demo accounts - only free models
            debug.log(f"Blackbox: Returning free model list with {len(cls.fallback_models)} models")
            return cls.fallback_models
    
    @classmethod
    def _check_premium_access(cls) -> bool:
        """
        Checks for an authorized session in HAR files.
        Returns True if a valid session is found that differs from the demo.
        """
        try:
            har_dir = get_cookies_dir()
            if not os.access(har_dir, os.R_OK):
                return False
                
            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 check requests to blackbox API
                                if 'blackbox.ai/api' in entry['request']['url']:
                                    if 'response' in entry and 'content' in entry['response']:
                                        content = entry['response']['content']
                                        if ('text' in content and 
                                            isinstance(content['text'], str) and 
                                            '"user"' in content['text'] and 
                                            '"email"' in content['text']):
                                            
                                            try:
                                                # Process request text
                                                text = content['text'].strip()
                                                if text.startswith('{') and text.endswith('}'):
                                                    text = text.replace('\\"', '"')
                                                    session_data = json.loads(text)
                                                    
                                                    # Check if this is a valid session
                                                    if (isinstance(session_data, dict) and 
                                                        'user' in session_data and 
                                                        'email' in session_data['user']):
                                                        
                                                        # Check if this is not a demo session
                                                        demo_session = cls.generate_session()
                                                        if (session_data['user'].get('email') != 
                                                            demo_session['user'].get('email')):
                                                            # This is not a demo session, so user has premium access
                                                            return True
                                            except:
                                                pass
                        except:
                            pass
            return False
        except Exception as e:
            debug.log(f"Blackbox: Error checking premium access: {e}")
            return False
    
    # Initialize models with fallback_models
    models = fallback_models
    
    model_aliases = {
        "gpt-4o": "GPT-4o",
        "claude-3.7-sonnet": "Claude-sonnet-3.7",
        "deepseek-v3": "DeepSeek-V3",
        "deepseek-r1": "DeepSeek-R1",
        "deepseek-chat": "DeepSeek-LLM-Chat-(67B)",
    }

    @classmethod
    def generate_session(cls, id_length: int = 21, days_ahead: int = 365) -> dict:
        """
        Generate a dynamic session with proper ID and expiry format.
        
        Args:
            id_length: Length of the numeric ID (default: 21)
            days_ahead: Number of days ahead for expiry (default: 365)
        
        Returns:
            dict: A session dictionary with user information and expiry
        """
        # Generate numeric ID
        numeric_id = ''.join(random.choice('0123456789') for _ in range(id_length))
        
        # Generate future expiry date
        future_date = datetime.now() + timedelta(days=days_ahead)
        expiry = future_date.strftime('%Y-%m-%dT%H:%M:%S.%f')[:-3] + 'Z'
        
        # Decode the encoded email
        encoded_email = "Z2lzZWxlQGJsYWNrYm94LmFp"  # Base64 encoded email
        email = base64.b64decode(encoded_email).decode('utf-8')
        
        # Generate random image ID for the new URL format
        chars = string.ascii_letters + string.digits + "-"
        random_img_id = ''.join(random.choice(chars) for _ in range(48))
        image_url = f"https://lh3.googleusercontent.com/a/ACg8oc{random_img_id}=s96-c"
        
        return {
            "user": {
                "name": "BLACKBOX AI", 
                "email": email, 
                "image": image_url, 
                "id": numeric_id
            }, 
            "expires": expiry
        }


    @classmethod
    async def fetch_validated(cls, url: str = "https://www.blackbox.ai", force_refresh: bool = False) -> Optional[str]:
        cache_file = Path(get_cookies_dir()) / 'blackbox.json'
        
        if not force_refresh and cache_file.exists():
            try:
                with open(cache_file, 'r') as f:
                    data = json.load(f)
                    if data.get('validated_value'):
                        return data['validated_value']
            except Exception as e:
                debug.log(f"Blackbox: Error reading cache: {e}")
        
        js_file_pattern = r'static/chunks/\d{4}-[a-fA-F0-9]+\.js'
        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})["\']'

        def is_valid_context(text: str) -> bool:
            return any(char + '=' in text for char in 'abcdefghijklmnopqrstuvwxyz')

        async with ClientSession() as session:
            try:
                async with session.get(url) as response:
                    if response.status != 200:
                        return None

                    page_content = await response.text()
                    js_files = re.findall(js_file_pattern, page_content)

                for js_file in js_files:
                    js_url = f"{url}/_next/{js_file}"
                    async with session.get(js_url) as js_response:
                        if js_response.status == 200:
                            js_content = await js_response.text()
                            for match in re.finditer(uuid_pattern, js_content):
                                start = max(0, match.start() - 10)
                                end = min(len(js_content), match.end() + 10)
                                context = js_content[start:end]

                                if is_valid_context(context):
                                    validated_value = match.group(1)
                                    
                                    cache_file.parent.mkdir(exist_ok=True)
                                    try:
                                        with open(cache_file, 'w') as f:
                                            json.dump({'validated_value': validated_value}, f)
                                    except Exception as e:
                                        debug.log(f"Blackbox: Error writing cache: {e}")
                                        
                                    return validated_value

            except Exception as e:
                debug.log(f"Blackbox: Error retrieving validated_value: {e}")

        return None

    @classmethod
    def generate_id(cls, length: int = 7) -> str:
        chars = string.ascii_letters + string.digits
        return ''.join(random.choice(chars) for _ in range(length))
    
    @classmethod
    async def create_async_generator(
        cls,
        model: str,
        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