from __future__ import annotations import asyncio import aiohttp import random import string import json import uuid import re from typing import Optional, AsyncGenerator, Union from aiohttp import ClientSession, ClientResponseError from ..typing import AsyncResult, Messages, ImageType from .base_provider import AsyncGeneratorProvider, ProviderModelMixin from ..image import ImageResponse, to_data_uri 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' image_models = ['ImageGeneration'] models = [ default_model, 'blackboxai-pro', *image_models, "llama-3.1-8b", 'llama-3.1-70b', 'llama-3.1-405b', 'gpt-4o', 'gemini-pro', 'gemini-1.5-flash', 'claude-sonnet-3.5', 'PythonAgent', 'JavaAgent', 'JavaScriptAgent', 'HTMLAgent', 'GoogleCloudAgent', 'AndroidDeveloper', 'SwiftDeveloper', 'Next.jsAgent', 'MongoDBAgent', 'PyTorchAgent', 'ReactAgent', 'XcodeAgent', 'AngularJSAgent', ] agentMode = { 'ImageGeneration': {'mode': True, 'id': "ImageGenerationLV45LJp", 'name': "Image Generation"}, } trendingAgentMode = { "blackboxai": {}, "gemini-1.5-flash": {'mode': True, 'id': 'Gemini'}, "llama-3.1-8b": {'mode': True, 'id': "llama-3.1-8b"}, 'llama-3.1-70b': {'mode': True, 'id': "llama-3.1-70b"}, 'llama-3.1-405b': {'mode': True, 'id': "llama-3.1-405b"}, 'blackboxai-pro': {'mode': True, 'id': "BLACKBOXAI-PRO"}, 'PythonAgent': {'mode': True, 'id': "Python Agent"}, 'JavaAgent': {'mode': True, 'id': "Java Agent"}, 'JavaScriptAgent': {'mode': True, 'id': "JavaScript Agent"}, 'HTMLAgent': {'mode': True, 'id': "HTML Agent"}, 'GoogleCloudAgent': {'mode': True, 'id': "Google Cloud Agent"}, 'AndroidDeveloper': {'mode': True, 'id': "Android Developer"}, 'SwiftDeveloper': {'mode': True, 'id': "Swift Developer"}, 'Next.jsAgent': {'mode': True, 'id': "Next.js Agent"}, 'MongoDBAgent': {'mode': True, 'id': "MongoDB Agent"}, 'PyTorchAgent': {'mode': True, 'id': "PyTorch Agent"}, 'ReactAgent': {'mode': True, 'id': "React Agent"}, 'XcodeAgent': {'mode': True, 'id': "Xcode Agent"}, 'AngularJSAgent': {'mode': True, 'id': "AngularJS Agent"}, } userSelectedModel = { "gpt-4o": "gpt-4o", "gemini-pro": "gemini-pro", 'claude-sonnet-3.5': "claude-sonnet-3.5", } model_prefixes = { 'gpt-4o': '@GPT-4o', 'gemini-pro': '@Gemini-PRO', 'claude-sonnet-3.5': '@Claude-Sonnet-3.5', 'PythonAgent': '@Python Agent', 'JavaAgent': '@Java Agent', 'JavaScriptAgent': '@JavaScript Agent', 'HTMLAgent': '@HTML Agent', 'GoogleCloudAgent': '@Google Cloud Agent', 'AndroidDeveloper': '@Android Developer', 'SwiftDeveloper': '@Swift Developer', 'Next.jsAgent': '@Next.js Agent', 'MongoDBAgent': '@MongoDB Agent', 'PyTorchAgent': '@PyTorch Agent', 'ReactAgent': '@React Agent', 'XcodeAgent': '@Xcode Agent', 'AngularJSAgent': '@AngularJS Agent', 'blackboxai-pro': '@BLACKBOXAI-PRO', 'ImageGeneration': '@Image Generation', } model_referers = { "blackboxai": "/?model=blackboxai", "gpt-4o": "/?model=gpt-4o", "gemini-pro": "/?model=gemini-pro", "claude-sonnet-3.5": "/?model=claude-sonnet-3.5" } model_aliases = { "gemini-flash": "gemini-1.5-flash", "claude-3.5-sonnet": "claude-sonnet-3.5", "flux": "ImageGeneration", } @classmethod def get_model(cls, model: str) -> str: if model in cls.models: return model elif model in cls.model_aliases: return cls.model_aliases[model] else: return cls.default_model @staticmethod def generate_random_string(length: int = 7) -> str: characters = string.ascii_letters + string.digits return ''.join(random.choices(characters, k=length)) @staticmethod def generate_next_action() -> str: return uuid.uuid4().hex @staticmethod def generate_next_router_state_tree() -> str: router_state = [ "", { "children": [ "(chat)", { "children": [ "__PAGE__", {} ] } ] }, None, None, True ] return json.dumps(router_state) @staticmethod def clean_response(text: str) -> str: pattern = r'^\$\@\$v=undefined-rv1\$\@\$' cleaned_text = re.sub(pattern, '', text) return cleaned_text @classmethod async def create_async_generator( cls, model: str, messages: Messages, proxy: Optional[str] = None, image: ImageType = None, image_name: str = None, web_search: bool = False, **kwargs ) -> AsyncGenerator[Union[str, ImageResponse], None]: """ Creates an asynchronous generator for streaming responses from Blackbox AI. Parameters: model (str): Model to use for generating responses. messages (Messages): Message history. proxy (Optional[str]): Proxy URL, if needed. image (ImageType): Image data to be processed, if any. image_name (str): Name of the image file, if an image is provided. web_search (bool): Enables or disables web search mode. **kwargs: Additional keyword arguments. Yields: Union[str, ImageResponse]: Segments of the generated response or ImageResponse objects. """ if image is not None: messages[-1]['data'] = { 'fileText': '', 'imageBase64': to_data_uri(image), 'title': image_name } messages[-1]['content'] = 'FILE:BB\n$#$\n\n$#$\n' + messages[-1]['content'] model = cls.get_model(model) chat_id = cls.generate_random_string() next_action = cls.generate_next_action() next_router_state_tree = cls.generate_next_router_state_tree() agent_mode = cls.agentMode.get(model, {}) trending_agent_mode = cls.trendingAgentMode.get(model, {}) prefix = cls.model_prefixes.get(model, "") formatted_prompt = "" for message in messages: role = message.get('role', '').capitalize() content = message.get('content', '') if role and content: formatted_prompt += f"{role}: {content}\n" if prefix: formatted_prompt = f"{prefix} {formatted_prompt}".strip() referer_path = cls.model_referers.get(model, f"/?model={model}") referer_url = f"{cls.url}{referer_path}" common_headers = { 'accept': '*/*', 'accept-language': 'en-US,en;q=0.9', 'cache-control': 'no-cache', 'origin': cls.url, 'pragma': 'no-cache', 'priority': 'u=1, i', 'sec-ch-ua': '"Chromium";v="129", "Not=A?Brand";v="8"', 'sec-ch-ua-mobile': '?0', 'sec-ch-ua-platform': '"Linux"', 'sec-fetch-dest': 'empty', 'sec-fetch-mode': 'cors', 'sec-fetch-site': 'same-origin', 'user-agent': 'Mozilla/5.0 (X11; Linux x86_64) ' 'AppleWebKit/537.36 (KHTML, like Gecko) ' 'Chrome/129.0.0.0 Safari/537.36' } headers_api_chat = { 'Content-Type': 'application/json', 'Referer': referer_url } headers_api_chat_combined = {**common_headers, **headers_api_chat} payload_api_chat = { "messages": [ { "id": chat_id, "content": formatted_prompt, "role": "user", "data": messages[-1].get('data') } ], "id": chat_id, "previewToken": None, "userId": None, "codeModelMode": True, "agentMode": agent_mode, "trendingAgentMode": trending_agent_mode, "isMicMode": False, "userSystemPrompt": None, "maxTokens": 1024, "playgroundTopP": 0.9, "playgroundTemperature": 0.5, "isChromeExt": False, "githubToken": None, "clickedAnswer2": False, "clickedAnswer3": False, "clickedForceWebSearch": False, "visitFromDelta": False, "mobileClient": False, "webSearchMode": web_search, "userSelectedModel": cls.userSelectedModel.get(model, model) } headers_chat = { 'Accept': 'text/x-component', 'Content-Type': 'text/plain;charset=UTF-8', 'Referer': f'{cls.url}/chat/{chat_id}?model={model}', 'next-action': next_action, 'next-router-state-tree': next_router_state_tree, 'next-url': '/' } headers_chat_combined = {**common_headers, **headers_chat} data_chat = '[]' async with ClientSession(headers=common_headers) as session: try: async with session.post( cls.api_endpoint, headers=headers_api_chat_combined, json=payload_api_chat, proxy=proxy ) as response_api_chat: response_api_chat.raise_for_status() text = await response_api_chat.text() cleaned_response = cls.clean_response(text) if model in cls.image_models: match = re.search(r'!\[.*?\]\((https?://[^\)]+)\)', cleaned_response) if match: image_url = match.group(1) image_response = ImageResponse(images=image_url, alt="Generated Image") yield image_response else: yield cleaned_response else: if web_search: match = re.search(r'\$~~~\$(.*?)\$~~~\$', cleaned_response, re.DOTALL) if match: source_part = match.group(1).strip() answer_part = cleaned_response[match.end():].strip() try: sources = json.loads(source_part) source_formatted = "**Source:**\n" for item in sources: title = item.get('title', 'No Title') link = item.get('link', '#') position = item.get('position', '') source_formatted += f"{position}. [{title}]({link})\n" final_response = f"{answer_part}\n\n{source_formatted}" except json.JSONDecodeError: final_response = f"{answer_part}\n\nSource information is unavailable." else: final_response = cleaned_response else: if '$~~~$' in cleaned_response: final_response = cleaned_response.split('$~~~$')[0].strip() else: final_response = cleaned_response yield final_response except ClientResponseError as e: error_text = f"Error {e.status}: {e.message}" try: error_response = await e.response.text() cleaned_error = cls.clean_response(error_response) error_text += f" - {cleaned_error}" except Exception: pass yield error_text except Exception as e: yield f"Unexpected error during /api/chat request: {str(e)}" chat_url = f'{cls.url}/chat/{chat_id}?model={model}' try: async with session.post( chat_url, headers=headers_chat_combined, data=data_chat, proxy=proxy ) as response_chat: response_chat.raise_for_status() pass except ClientResponseError as e: error_text = f"Error {e.status}: {e.message}" try: error_response = await e.response.text() cleaned_error = cls.clean_response(error_response) error_text += f" - {cleaned_error}" except Exception: pass yield error_text except Exception as e: yield f"Unexpected error during /chat/{chat_id} request: {str(e)}"