gpt4free/g4f/Provider/Blackbox.py
H Lohaus 76c3683403
Remove webview js api, Add unittest for provider has model, Use cooki… (#2470)
* Remove webview js api, Add unittest for provider has model, Use cookies dir for cache
2024-12-08 20:39:40 +01:00

288 lines
11 KiB
Python

from __future__ import annotations
from aiohttp import ClientSession
import random
import string
import json
import re
import aiohttp
import json
from pathlib import Path
from ..typing import AsyncResult, Messages, ImageType
from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
from ..image import ImageResponse, to_data_uri
from ..cookies import get_cookies_dir
from .helper import format_prompt
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'
image_models = ['ImageGeneration', 'repomap']
vision_models = [default_model, 'gpt-4o', 'gemini-pro', 'gemini-1.5-flash', 'llama-3.1-8b', 'llama-3.1-70b', 'llama-3.1-405b']
userSelectedModel = ['gpt-4o', 'gemini-pro', 'claude-sonnet-3.5', 'blackboxai-pro']
agentMode = {
'ImageGeneration': {'mode': True, 'id': "ImageGenerationLV45LJp", 'name': "Image Generation"}
}
trendingAgentMode = {
"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-3.1-405"},
#
'Python Agent': {'mode': True, 'id': "Python Agent"},
'Java Agent': {'mode': True, 'id': "Java Agent"},
'JavaScript Agent': {'mode': True, 'id': "JavaScript Agent"},
'HTML Agent': {'mode': True, 'id': "HTML Agent"},
'Google Cloud Agent': {'mode': True, 'id': "Google Cloud Agent"},
'Android Developer': {'mode': True, 'id': "Android Developer"},
'Swift Developer': {'mode': True, 'id': "Swift Developer"},
'Next.js Agent': {'mode': True, 'id': "Next.js Agent"},
'MongoDB Agent': {'mode': True, 'id': "MongoDB Agent"},
'PyTorch Agent': {'mode': True, 'id': "PyTorch Agent"},
'React Agent': {'mode': True, 'id': "React Agent"},
'Xcode Agent': {'mode': True, 'id': "Xcode Agent"},
'AngularJS Agent': {'mode': True, 'id': "AngularJS Agent"},
#
'blackboxai-pro': {'mode': True, 'id': "BLACKBOXAI-PRO"},
#
'repomap': {'mode': True, 'id': "repomap"},
#
'Heroku Agent': {'mode': True, 'id': "Heroku Agent"},
'Godot Agent': {'mode': True, 'id': "Godot Agent"},
'Go Agent': {'mode': True, 'id': "Go Agent"},
'Gitlab Agent': {'mode': True, 'id': "Gitlab Agent"},
'Git Agent': {'mode': True, 'id': "Git Agent"},
'Flask Agent': {'mode': True, 'id': "Flask Agent"},
'Firebase Agent': {'mode': True, 'id': "Firebase Agent"},
'FastAPI Agent': {'mode': True, 'id': "FastAPI Agent"},
'Erlang Agent': {'mode': True, 'id': "Erlang Agent"},
'Electron Agent': {'mode': True, 'id': "Electron Agent"},
'Docker Agent': {'mode': True, 'id': "Docker Agent"},
'DigitalOcean Agent': {'mode': True, 'id': "DigitalOcean Agent"},
'Bitbucket Agent': {'mode': True, 'id': "Bitbucket Agent"},
'Azure Agent': {'mode': True, 'id': "Azure Agent"},
'Flutter Agent': {'mode': True, 'id': "Flutter Agent"},
'Youtube Agent': {'mode': True, 'id': "Youtube Agent"},
'builder Agent': {'mode': True, 'id': "builder Agent"},
}
additional_prefixes = {
'gpt-4o': '@GPT-4o',
'gemini-pro': '@Gemini-PRO',
'claude-sonnet-3.5': '@Claude-Sonnet-3.5'
}
model_prefixes = {
**{
mode: f"@{value['id']}" for mode, value in trendingAgentMode.items()
if mode not in ["gemini-1.5-flash", "llama-3.1-8b", "llama-3.1-70b", "llama-3.1-405b", "repomap"]
},
**additional_prefixes
}
models = list(dict.fromkeys([default_model, *userSelectedModel, *list(agentMode.keys()), *list(trendingAgentMode.keys())]))
model_aliases = {
"gpt-4": "blackboxai",
"gpt-4": "gpt-4o",
"gpt-4o-mini": "gpt-4o",
"gpt-3.5-turbo": "blackboxai",
"gemini-flash": "gemini-1.5-flash",
"claude-3.5-sonnet": "claude-sonnet-3.5",
"flux": "ImageGeneration",
}
@classmethod
def _get_cache_file(cls) -> Path:
dir = Path(get_cookies_dir())
dir.mkdir(exist_ok=True)
return dir / 'blackbox.json'
@classmethod
def _load_cached_value(cls) -> str | None:
cache_file = cls._get_cache_file()
if cache_file.exists():
try:
with open(cache_file, 'r') as f:
data = json.load(f)
return data.get('validated_value')
except Exception as e:
print(f"Error reading cache file: {e}")
return None
@classmethod
def _save_cached_value(cls, value: str):
cache_file = cls._get_cache_file()
try:
with open(cache_file, 'w') as f:
json.dump({'validated_value': value}, f)
except Exception as e:
print(f"Error writing to cache file: {e}")
@classmethod
async def fetch_validated(cls):
# Let's try to load the value from the cache first
cached_value = cls._load_cached_value()
if cached_value:
return cached_value
async with aiohttp.ClientSession() as session:
try:
async with session.get(cls.url) as response:
if response.status != 200:
print("Failed to load the page.")
return cached_value
page_content = await response.text()
js_files = re.findall(r'static/chunks/\d{4}-[a-fA-F0-9]+\.js', page_content)
key_pattern = re.compile(r'w="([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})"')
for js_file in js_files:
js_url = f"{cls.url}/_next/{js_file}"
async with session.get(js_url) as js_response:
if js_response.status == 200:
js_content = await js_response.text()
match = key_pattern.search(js_content)
if match:
validated_value = match.group(1)
# Save the new value to the cache file
cls._save_cached_value(validated_value)
return validated_value
except Exception as e:
print(f"Error fetching validated value: {e}")
return cached_value
@staticmethod
def generate_id(length=7):
characters = string.ascii_letters + string.digits
return ''.join(random.choice(characters) for _ in range(length))
@classmethod
def add_prefix_to_messages(cls, messages: Messages, model: str) -> Messages:
prefix = cls.model_prefixes.get(model, "")
if not prefix:
return messages
new_messages = []
for message in messages:
new_message = message.copy()
if message['role'] == 'user':
new_message['content'] = (prefix + " " + message['content']).strip()
new_messages.append(new_message)
return new_messages
@classmethod
async def create_async_generator(
cls,
model: str,
messages: Messages,
prompt: str = None,
proxy: str = None,
web_search: bool = False,
image: ImageType = None,
image_name: str = None,
top_p: float = 0.9,
temperature: float = 0.5,
max_tokens: int = 1024,
**kwargs
) -> AsyncResult:
message_id = cls.generate_id()
messages = cls.add_prefix_to_messages(messages, model)
validated_value = await cls.fetch_validated()
formatted_message = format_prompt(messages)
model = cls.get_model(model)
messages = [{"id": message_id, "content": formatted_message, "role": "user"}]
if image is not None:
messages[-1]['data'] = {
"imagesData": [
{
"filePath": f"MultipleFiles/{image_name}",
"contents": to_data_uri(image)
}
],
"fileText": "",
"title": ""
}
headers = {
'accept': '*/*',
'content-type': 'application/json',
'origin': cls.url,
'referer': f'{cls.url}/',
'user-agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36'
}
data = {
"messages": messages,
"id": message_id,
"previewToken": None,
"userId": None,
"codeModelMode": True,
"agentMode": cls.agentMode.get(model, {}) if model in cls.agentMode else {},
"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": None,
"clickedAnswer2": False,
"clickedAnswer3": False,
"clickedForceWebSearch": False,
"visitFromDelta": False,
"mobileClient": False,
"userSelectedModel": model if model in cls.userSelectedModel else None,
"webSearchMode": web_search,
"validated": validated_value,
"imageGenerationMode": False,
"webSearchModePrompt": web_search
}
async with ClientSession(headers=headers) as session:
async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response:
response.raise_for_status()
response_text = await response.text()
if model in cls.image_models:
image_matches = re.findall(r'!\[.*?\]\((https?://[^\)]+)\)', response_text)
if image_matches:
image_url = image_matches[0]
yield ImageResponse(image_url, prompt)
return
response_text = re.sub(r'Generated by BLACKBOX.AI, try unlimited chat https://www.blackbox.ai', '', response_text, flags=re.DOTALL)
json_match = re.search(r'\$~~~\$(.*?)\$~~~\$', response_text, re.DOTALL)
if json_match:
search_results = json.loads(json_match.group(1))
answer = response_text.split('$~~~$')[-1].strip()
formatted_response = f"{answer}\n\n**Source:**"
for i, result in enumerate(search_results, 1):
formatted_response += f"\n{i}. {result['title']}: {result['link']}"
yield formatted_response
else:
yield response_text.strip()