mirror of
https://github.com/xtekky/gpt4free.git
synced 2024-12-25 04:01:52 +03:00
240 lines
8.9 KiB
Python
240 lines
8.9 KiB
Python
from __future__ import annotations
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import re
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import random
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import string
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import json
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from aiohttp import ClientSession
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from ..typing import AsyncResult, Messages, ImageType
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from ..image import ImageResponse, to_data_uri
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from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
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class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):
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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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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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'gpt-4o',
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'gemini-pro',
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'gemini-1.5-flash',
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'claude-sonnet-3.5',
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'PythonAgent',
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'JavaAgent',
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'JavaScriptAgent',
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'HTMLAgent',
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'GoogleCloudAgent',
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'AndroidDeveloper',
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'SwiftDeveloper',
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'Next.jsAgent',
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'MongoDBAgent',
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'PyTorchAgent',
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'ReactAgent',
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'XcodeAgent',
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'AngularJSAgent',
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'ImageGeneration',
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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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"llama-3.1-8b": {'mode': True, 'id': "llama-3.1-8b"},
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'llama-3.1-70b': {'mode': True, 'id': "llama-3.1-70b"},
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'llama-3.1-405b': {'mode': True, 'id': "llama-3.1-405b"},
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'blackboxai-pro': {'mode': True, 'id': "BLACKBOXAI-PRO"},
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'PythonAgent': {'mode': True, 'id': "Python Agent"},
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'JavaAgent': {'mode': True, 'id': "Java Agent"},
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'JavaScriptAgent': {'mode': True, 'id': "JavaScript Agent"},
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'HTMLAgent': {'mode': True, 'id': "HTML Agent"},
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'GoogleCloudAgent': {'mode': True, 'id': "Google Cloud Agent"},
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'AndroidDeveloper': {'mode': True, 'id': "Android Developer"},
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'SwiftDeveloper': {'mode': True, 'id': "Swift Developer"},
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'Next.jsAgent': {'mode': True, 'id': "Next.js Agent"},
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'MongoDBAgent': {'mode': True, 'id': "MongoDB Agent"},
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'PyTorchAgent': {'mode': True, 'id': "PyTorch Agent"},
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'ReactAgent': {'mode': True, 'id': "React Agent"},
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'XcodeAgent': {'mode': True, 'id': "Xcode Agent"},
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'AngularJSAgent': {'mode': True, 'id': "AngularJS Agent"},
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}
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userSelectedModel = {
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"gpt-4o": "gpt-4o",
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"gemini-pro": "gemini-pro",
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'claude-sonnet-3.5': "claude-sonnet-3.5",
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'blackboxai-pro': "blackboxai-pro",
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}
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model_prefixes = {
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'gpt-4o': '@GPT-4o',
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'gemini-pro': '@Gemini-PRO',
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'claude-sonnet-3.5': '@Claude-Sonnet-3.5',
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'PythonAgent': '@Python Agent',
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'JavaAgent': '@Java Agent',
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'JavaScriptAgent': '@Java Agent',
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'HTMLAgent': '@HTML Agent',
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'GoogleCloudAgent': '@Google Cloud Agent',
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'AndroidDeveloper': '@Android Developer',
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'SwiftDeveloper': '@Swift Developer',
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'Next.jsAgent': '@Next.js Agent',
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'MongoDBAgent': '@MongoDB Agent',
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'PyTorchAgent': '@PyTorch Agent',
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'ReactAgent': '@React Agent',
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'XcodeAgent': '@Xcode Agent',
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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": f"{url}/?model=blackboxai",
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"blackboxai-pro": f"{url}/?model=blackboxai-pro",
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"gpt-4o": f"{url}/?model=gpt-4o",
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"gemini-pro": f"{url}/?model=gemini-pro",
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"claude-sonnet-3.5": f"{url}/?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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@classmethod
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def get_model(cls, model: str) -> str:
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if model in cls.models:
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return model
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elif model in cls.userSelectedModel:
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return model
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elif model in cls.model_aliases:
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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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cls,
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model: str,
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messages: Messages,
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proxy: str = None,
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image: ImageType = None,
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image_name: str = None,
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webSearchMode: bool = False,
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**kwargs
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) -> AsyncResult:
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model = cls.get_model(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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"referer": cls.model_referers.get(model, cls.url),
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"sec-ch-ua": '"Not;A=Brand";v="24", "Chromium";v="128"',
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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/128.0.0.0 Safari/537.36"
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}
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if model in cls.model_prefixes:
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prefix = cls.model_prefixes[model]
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if not messages[0]['content'].startswith(prefix):
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messages[0]['content'] = f"{prefix} {messages[0]['content']}"
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async with ClientSession(headers=headers) as session:
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if image is not None:
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messages[-1]["data"] = {
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"fileText": image_name,
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"imageBase64": to_data_uri(image)
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}
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random_id = ''.join(random.choices(string.ascii_letters + string.digits, k=7))
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data = {
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"messages": messages,
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"id": random_id,
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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": 1024,
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"playgroundTopP": 0.9,
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"playgroundTemperature": 0.5,
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"isChromeExt": False,
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"githubToken": None,
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"clickedAnswer2": False,
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"clickedAnswer3": False,
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"clickedForceWebSearch": False,
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"visitFromDelta": False,
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"mobileClient": False,
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"userSelectedModel": None,
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"webSearchMode": webSearchMode,
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}
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if model in cls.agentMode:
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data["agentMode"] = cls.agentMode[model]
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elif model in cls.trendingAgentMode:
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data["trendingAgentMode"] = cls.trendingAgentMode[model]
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elif model in cls.userSelectedModel:
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data["userSelectedModel"] = cls.userSelectedModel[model]
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async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response:
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response.raise_for_status()
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if model == 'ImageGeneration':
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response_text = await response.text()
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url_match = re.search(r'https://storage\.googleapis\.com/[^\s\)]+', response_text)
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if url_match:
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image_url = url_match.group(0)
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yield ImageResponse(image_url, alt=messages[-1]['content'])
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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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full_response = ""
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search_results_json = ""
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async for chunk in response.content.iter_any():
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if chunk:
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decoded_chunk = chunk.decode()
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decoded_chunk = re.sub(r'\$@\$v=[^$]+\$@\$', '', decoded_chunk)
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if decoded_chunk.strip():
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if '$~~~$' in decoded_chunk:
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search_results_json += decoded_chunk
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else:
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full_response += decoded_chunk
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yield decoded_chunk
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if data["webSearchMode"] and search_results_json:
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match = re.search(r'\$~~~\$(.*?)\$~~~\$', search_results_json, re.DOTALL)
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if match:
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search_results = json.loads(match.group(1))
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formatted_results = "\n\n**Sources:**\n"
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for i, result in enumerate(search_results[:5], 1):
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formatted_results += f"{i}. [{result['title']}]({result['link']})\n"
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yield formatted_results
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