mirror of
https://github.com/xtekky/gpt4free.git
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6a624acf55
Reuse cookies and access token in Copilot Send in the gui messages to multiple providers at once Add GUI documenation
602 lines
27 KiB
Python
602 lines
27 KiB
Python
from __future__ import annotations
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import re
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import asyncio
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import uuid
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import json
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import base64
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import time
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import requests
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import random
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from copy import copy
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try:
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import nodriver
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from nodriver.cdp.network import get_response_body
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has_nodriver = True
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except ImportError:
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has_nodriver = False
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from ..base_provider import AsyncGeneratorProvider, ProviderModelMixin
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from ...typing import AsyncResult, Messages, Cookies, ImageType, AsyncIterator
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from ...requests.raise_for_status import raise_for_status
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from ...requests import StreamSession
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from ...requests import get_nodriver
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from ...image import ImageResponse, ImageRequest, to_image, to_bytes, is_accepted_format
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from ...errors import MissingAuthError, NoValidHarFileError
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from ...providers.response import BaseConversation, FinishReason, SynthesizeData
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from ..helper import format_cookies
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from ..openai.har_file import get_request_config
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from ..openai.har_file import RequestConfig, arkReq, arkose_url, start_url, conversation_url, backend_url, backend_anon_url
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from ..openai.proofofwork import generate_proof_token
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from ..openai.new import get_requirements_token, get_config
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from ... import debug
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DEFAULT_HEADERS = {
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"accept": "*/*",
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"accept-encoding": "gzip, deflate, br, zstd",
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'accept-language': 'en-US,en;q=0.8',
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"referer": "https://chatgpt.com/",
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"sec-ch-ua": "\"Brave\";v=\"123\", \"Not:A-Brand\";v=\"8\", \"Chromium\";v=\"123\"",
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"sec-ch-ua-mobile": "?0",
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"sec-ch-ua-platform": "\"Windows\"",
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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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"sec-gpc": "1",
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"user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/123.0.0.0 Safari/537.36"
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}
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INIT_HEADERS = {
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'accept': '*/*',
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'accept-language': 'en-US,en;q=0.8',
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'cache-control': 'no-cache',
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'pragma': 'no-cache',
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'priority': 'u=0, i',
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'sec-ch-ua': '"Not)A;Brand";v="99", "Google Chrome";v="127", "Chromium";v="127"',
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'sec-ch-ua-arch': '"arm"',
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'sec-ch-ua-bitness': '"64"',
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'sec-ch-ua-mobile': '?0',
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'sec-ch-ua-model': '""',
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'sec-ch-ua-platform': '"macOS"',
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'sec-ch-ua-platform-version': '"14.4.0"',
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'sec-fetch-dest': 'document',
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'sec-fetch-mode': 'navigate',
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'sec-fetch-site': 'none',
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'sec-fetch-user': '?1',
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'upgrade-insecure-requests': '1',
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"user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/123.0.0.0 Safari/537.36"
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}
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class OpenaiChat(AsyncGeneratorProvider, ProviderModelMixin):
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"""A class for creating and managing conversations with OpenAI chat service"""
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label = "OpenAI ChatGPT"
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url = "https://chatgpt.com"
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working = True
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supports_gpt_4 = True
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supports_message_history = True
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supports_system_message = True
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default_model = "auto"
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fallback_models = [default_model, "gpt-4", "gpt-4o", "gpt-4o-mini", "gpt-4o-canmore", "o1-preview", "o1-mini"]
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vision_models = fallback_models
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synthesize_content_type = "audio/mpeg"
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_api_key: str = None
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_headers: dict = None
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_cookies: Cookies = None
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_expires: int = None
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@classmethod
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def get_models(cls):
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if not cls.models:
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try:
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response = requests.get(f"{cls.url}/backend-anon/models")
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response.raise_for_status()
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data = response.json()
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cls.models = [model.get("slug") for model in data.get("models")]
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except Exception:
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cls.models = cls.fallback_models
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return cls.models
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@classmethod
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async def upload_image(
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cls,
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session: StreamSession,
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headers: dict,
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image: ImageType,
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image_name: str = None
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) -> ImageRequest:
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"""
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Upload an image to the service and get the download URL
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Args:
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session: The StreamSession object to use for requests
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headers: The headers to include in the requests
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image: The image to upload, either a PIL Image object or a bytes object
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Returns:
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An ImageRequest object that contains the download URL, file name, and other data
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"""
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# Convert the image to a PIL Image object and get the extension
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data_bytes = to_bytes(image)
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image = to_image(data_bytes)
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extension = image.format.lower()
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data = {
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"file_name": "" if image_name is None else image_name,
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"file_size": len(data_bytes),
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"use_case": "multimodal"
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}
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# Post the image data to the service and get the image data
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async with session.post(f"{cls.url}/backend-api/files", json=data, headers=headers) as response:
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cls._update_request_args(session)
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await raise_for_status(response, "Create file failed")
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image_data = {
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**data,
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**await response.json(),
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"mime_type": is_accepted_format(data_bytes),
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"extension": extension,
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"height": image.height,
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"width": image.width
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}
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# Put the image bytes to the upload URL and check the status
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async with session.put(
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image_data["upload_url"],
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data=data_bytes,
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headers={
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**DEFAULT_HEADERS,
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"Content-Type": image_data["mime_type"],
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"x-ms-blob-type": "BlockBlob",
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"x-ms-version": "2020-04-08",
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"Origin": "https://chatgpt.com",
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}
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) as response:
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await raise_for_status(response)
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# Post the file ID to the service and get the download URL
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async with session.post(
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f"{cls.url}/backend-api/files/{image_data['file_id']}/uploaded",
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json={},
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headers=headers
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) as response:
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cls._update_request_args(session)
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await raise_for_status(response, "Get download url failed")
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image_data["download_url"] = (await response.json())["download_url"]
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return ImageRequest(image_data)
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@classmethod
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def create_messages(cls, messages: Messages, image_request: ImageRequest = None, system_hints: list = None):
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"""
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Create a list of messages for the user input
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Args:
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prompt: The user input as a string
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image_response: The image response object, if any
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Returns:
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A list of messages with the user input and the image, if any
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"""
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# Create a message object with the user role and the content
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messages = [{
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"author": {"role": message["role"]},
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"content": {"content_type": "text", "parts": [message["content"]]},
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"id": str(uuid.uuid4()),
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"create_time": int(time.time()),
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"metadata": {"serialization_metadata": {"custom_symbol_offsets": []}, "system_hints": system_hints},
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} for message in messages]
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# Check if there is an image response
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if image_request is not None:
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# Change content in last user message
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messages[-1]["content"] = {
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"content_type": "multimodal_text",
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"parts": [{
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"asset_pointer": f"file-service://{image_request.get('file_id')}",
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"height": image_request.get("height"),
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"size_bytes": image_request.get("file_size"),
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"width": image_request.get("width"),
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}, messages[-1]["content"]["parts"][0]]
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}
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# Add the metadata object with the attachments
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messages[-1]["metadata"] = {
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"attachments": [{
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"height": image_request.get("height"),
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"id": image_request.get("file_id"),
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"mimeType": image_request.get("mime_type"),
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"name": image_request.get("file_name"),
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"size": image_request.get("file_size"),
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"width": image_request.get("width"),
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}]
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}
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return messages
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@classmethod
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async def get_generated_image(cls, session: StreamSession, headers: dict, element: dict, prompt: str = None) -> ImageResponse:
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"""
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Retrieves the image response based on the message content.
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This method processes the message content to extract image information and retrieves the
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corresponding image from the backend API. It then returns an ImageResponse object containing
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the image URL and the prompt used to generate the image.
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Args:
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session (StreamSession): The StreamSession object used for making HTTP requests.
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headers (dict): HTTP headers to be used for the request.
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line (dict): A dictionary representing the line of response that contains image information.
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Returns:
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ImageResponse: An object containing the image URL and the prompt, or None if no image is found.
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Raises:
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RuntimeError: If there'san error in downloading the image, including issues with the HTTP request or response.
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"""
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try:
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prompt = element["metadata"]["dalle"]["prompt"]
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file_id = element["asset_pointer"].split("file-service://", 1)[1]
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except TypeError:
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return
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except Exception as e:
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raise RuntimeError(f"No Image: {e.__class__.__name__}: {e}")
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try:
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async with session.get(f"{cls.url}/backend-api/files/{file_id}/download", headers=headers) as response:
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cls._update_request_args(session)
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await raise_for_status(response)
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download_url = (await response.json())["download_url"]
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return ImageResponse(download_url, prompt)
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except Exception as e:
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raise RuntimeError(f"Error in downloading image: {e}")
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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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timeout: int = 180,
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cookies: Cookies = None,
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auto_continue: bool = False,
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history_disabled: bool = False,
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action: str = "next",
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conversation_id: str = None,
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conversation: Conversation = None,
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parent_id: str = None,
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image: ImageType = None,
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image_name: str = None,
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return_conversation: bool = False,
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max_retries: int = 3,
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web_search: bool = False,
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**kwargs
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) -> AsyncResult:
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"""
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Create an asynchronous generator for the conversation.
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Args:
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model (str): The model name.
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messages (Messages): The list of previous messages.
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proxy (str): Proxy to use for requests.
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timeout (int): Timeout for requests.
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api_key (str): Access token for authentication.
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cookies (dict): Cookies to use for authentication.
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auto_continue (bool): Flag to automatically continue the conversation.
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history_disabled (bool): Flag to disable history and training.
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action (str): Type of action ('next', 'continue', 'variant').
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conversation_id (str): ID of the conversation.
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parent_id (str): ID of the parent message.
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image (ImageType): Image to include in the conversation.
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return_conversation (bool): Flag to include response fields in the output.
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**kwargs: Additional keyword arguments.
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Yields:
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AsyncResult: Asynchronous results from the generator.
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Raises:
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RuntimeError: If an error occurs during processing.
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"""
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if cls.needs_auth:
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await cls.login(proxy)
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async with StreamSession(
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proxy=proxy,
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impersonate="chrome",
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timeout=timeout
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) as session:
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image_request = None
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if not cls.needs_auth:
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if cls._headers is None:
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cls._create_request_args(cookies)
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async with session.get(cls.url, headers=INIT_HEADERS) as response:
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cls._update_request_args(session)
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await raise_for_status(response)
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else:
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async with session.get(cls.url, headers=cls._headers) as response:
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cls._update_request_args(session)
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await raise_for_status(response)
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try:
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image_request = await cls.upload_image(session, cls._headers, image, image_name) if image else None
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except Exception as e:
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debug.log("OpenaiChat: Upload image failed")
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debug.log(f"{e.__class__.__name__}: {e}")
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model = cls.get_model(model)
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if conversation is None:
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conversation = Conversation(conversation_id, str(uuid.uuid4()) if parent_id is None else parent_id)
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else:
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conversation = copy(conversation)
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if cls._api_key is None:
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auto_continue = False
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conversation.finish_reason = None
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while conversation.finish_reason is None:
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async with session.post(
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f"{cls.url}/backend-anon/sentinel/chat-requirements"
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if cls._api_key is None else
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f"{cls.url}/backend-api/sentinel/chat-requirements",
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json={"p": get_requirements_token(RequestConfig.proof_token) if RequestConfig.proof_token else None},
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headers=cls._headers
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) as response:
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cls._update_request_args(session)
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await raise_for_status(response)
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chat_requirements = await response.json()
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need_turnstile = chat_requirements.get("turnstile", {}).get("required", False)
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need_arkose = chat_requirements.get("arkose", {}).get("required", False)
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chat_token = chat_requirements.get("token")
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if need_arkose and RequestConfig.arkose_token is None:
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await get_request_config(proxy)
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cls._create_request_args(RequestConfig,cookies, RequestConfig.headers)
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cls._set_api_key(RequestConfig.access_token)
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if RequestConfig.arkose_token is None:
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raise MissingAuthError("No arkose token found in .har file")
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if "proofofwork" in chat_requirements:
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if RequestConfig.proof_token is None:
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RequestConfig.proof_token = get_config(cls._headers.get("user-agent"))
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proofofwork = generate_proof_token(
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**chat_requirements["proofofwork"],
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user_agent=cls._headers.get("user-agent"),
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proof_token=RequestConfig.proof_token
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)
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[debug.log(text) for text in (
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f"Arkose: {'False' if not need_arkose else RequestConfig.arkose_token[:12]+'...'}",
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f"Proofofwork: {'False' if proofofwork is None else proofofwork[:12]+'...'}",
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f"AccessToken: {'False' if cls._api_key is None else cls._api_key[:12]+'...'}",
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)]
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data = {
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"action": action,
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"messages": None,
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"parent_message_id": conversation.message_id,
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"model": model,
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"timezone_offset_min":-60,
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"timezone":"Europe/Berlin",
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"history_and_training_disabled": history_disabled and not auto_continue and not return_conversation or not cls.needs_auth,
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"conversation_mode":{"kind":"primary_assistant","plugin_ids":None},
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"force_paragen":False,
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"force_paragen_model_slug":"",
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"force_rate_limit":False,
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"reset_rate_limits":False,
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"websocket_request_id": str(uuid.uuid4()),
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"system_hints": ["search"] if web_search else None,
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"supported_encodings":["v1"],
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"conversation_origin":None,
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"client_contextual_info":{"is_dark_mode":False,"time_since_loaded":random.randint(20, 500),"page_height":578,"page_width":1850,"pixel_ratio":1,"screen_height":1080,"screen_width":1920},
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"paragen_stream_type_override":None,
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"paragen_cot_summary_display_override":"allow",
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"supports_buffering":True
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}
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if conversation.conversation_id is not None:
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data["conversation_id"] = conversation.conversation_id
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debug.log(f"OpenaiChat: Use conversation: {conversation.conversation_id}")
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if action != "continue":
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messages = messages if conversation_id is None else [messages[-1]]
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data["messages"] = cls.create_messages(messages, image_request, ["search"] if web_search else None)
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headers = {
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**cls._headers,
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"accept": "text/event-stream",
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"content-type": "application/json",
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"openai-sentinel-chat-requirements-token": chat_token,
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}
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if RequestConfig.arkose_token:
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headers["openai-sentinel-arkose-token"] = RequestConfig.arkose_token
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if proofofwork is not None:
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headers["openai-sentinel-proof-token"] = proofofwork
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if need_turnstile and RequestConfig.turnstile_token is not None:
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headers['openai-sentinel-turnstile-token'] = RequestConfig.turnstile_token
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async with session.post(
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f"{cls.url}/backend-anon/conversation"
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if cls._api_key is None else
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f"{cls.url}/backend-api/conversation",
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json=data,
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headers=headers
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) as response:
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cls._update_request_args(session)
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if response.status == 403 and max_retries > 0:
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max_retries -= 1
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debug.log(f"Retry: Error {response.status}: {await response.text()}")
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await asyncio.sleep(5)
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continue
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await raise_for_status(response)
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if return_conversation:
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yield conversation
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async for line in response.iter_lines():
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async for chunk in cls.iter_messages_line(session, line, conversation):
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yield chunk
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if not history_disabled and RequestConfig.access_token is not None:
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yield SynthesizeData(cls.__name__, {
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"conversation_id": conversation.conversation_id,
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"message_id": conversation.message_id,
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"voice": "maple",
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})
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if auto_continue and conversation.finish_reason == "max_tokens":
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conversation.finish_reason = None
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action = "continue"
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await asyncio.sleep(5)
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else:
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break
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yield FinishReason(conversation.finish_reason)
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@classmethod
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async def iter_messages_line(cls, session: StreamSession, line: bytes, fields: Conversation) -> AsyncIterator:
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if not line.startswith(b"data: "):
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return
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elif line.startswith(b"data: [DONE]"):
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if fields.finish_reason is None:
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fields.finish_reason = "error"
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return
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try:
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line = json.loads(line[6:])
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except:
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return
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if isinstance(line, dict) and "v" in line:
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v = line.get("v")
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if isinstance(v, str) and fields.is_recipient:
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if "p" not in line or line.get("p") == "/message/content/parts/0":
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yield v
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elif isinstance(v, list) and fields.is_recipient:
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for m in v:
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if m.get("p") == "/message/content/parts/0":
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yield m.get("v")
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elif m.get("p") == "/message/metadata":
|
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fields.finish_reason = m.get("v", {}).get("finish_details", {}).get("type")
|
|
break
|
|
elif isinstance(v, dict):
|
|
if fields.conversation_id is None:
|
|
fields.conversation_id = v.get("conversation_id")
|
|
debug.log(f"OpenaiChat: New conversation: {fields.conversation_id}")
|
|
m = v.get("message", {})
|
|
fields.is_recipient = m.get("recipient", "all") == "all"
|
|
if fields.is_recipient:
|
|
c = m.get("content", {})
|
|
if c.get("content_type") == "multimodal_text":
|
|
generated_images = []
|
|
for element in c.get("parts"):
|
|
if isinstance(element, dict) and element.get("content_type") == "image_asset_pointer":
|
|
image = cls.get_generated_image(session, cls._headers, element)
|
|
generated_images.append(image)
|
|
for image_response in await asyncio.gather(*generated_images):
|
|
if image_response is not None:
|
|
yield image_response
|
|
if m.get("author", {}).get("role") == "assistant":
|
|
fields.message_id = v.get("message", {}).get("id")
|
|
return
|
|
if "error" in line and line.get("error"):
|
|
raise RuntimeError(line.get("error"))
|
|
|
|
@classmethod
|
|
async def synthesize(cls, params: dict) -> AsyncIterator[bytes]:
|
|
await cls.login()
|
|
async with StreamSession(
|
|
impersonate="chrome",
|
|
timeout=900
|
|
) as session:
|
|
async with session.get(
|
|
f"{cls.url}/backend-api/synthesize",
|
|
params=params,
|
|
headers=cls._headers
|
|
) as response:
|
|
await raise_for_status(response)
|
|
async for chunk in response.iter_content():
|
|
yield chunk
|
|
|
|
@classmethod
|
|
async def login(cls, proxy: str = None):
|
|
if cls._expires is not None and cls._expires < time.time():
|
|
cls._headers = cls._api_key = None
|
|
try:
|
|
await get_request_config(proxy)
|
|
cls._create_request_args(RequestConfig.cookies, RequestConfig.headers)
|
|
cls._set_api_key(RequestConfig.access_token)
|
|
except NoValidHarFileError:
|
|
if has_nodriver:
|
|
if RequestConfig.access_token is None:
|
|
await cls.nodriver_auth(proxy)
|
|
else:
|
|
raise
|
|
|
|
@classmethod
|
|
async def nodriver_auth(cls, proxy: str = None):
|
|
browser = await get_nodriver(proxy=proxy, user_data_dir="chatgpt")
|
|
page = browser.main_tab
|
|
def on_request(event: nodriver.cdp.network.RequestWillBeSent):
|
|
if event.request.url == start_url or event.request.url.startswith(conversation_url):
|
|
RequestConfig.headers = event.request.headers
|
|
elif event.request.url in (backend_url, backend_anon_url):
|
|
if "OpenAI-Sentinel-Proof-Token" in event.request.headers:
|
|
RequestConfig.proof_token = json.loads(base64.b64decode(
|
|
event.request.headers["OpenAI-Sentinel-Proof-Token"].split("gAAAAAB", 1)[-1].encode()
|
|
).decode())
|
|
if "OpenAI-Sentinel-Turnstile-Token" in event.request.headers:
|
|
RequestConfig.turnstile_token = event.request.headers["OpenAI-Sentinel-Turnstile-Token"]
|
|
if "Authorization" in event.request.headers:
|
|
RequestConfig.access_token = event.request.headers["Authorization"].split()[-1]
|
|
elif event.request.url == arkose_url:
|
|
RequestConfig.arkose_request = arkReq(
|
|
arkURL=event.request.url,
|
|
arkBx=None,
|
|
arkHeader=event.request.headers,
|
|
arkBody=event.request.post_data,
|
|
userAgent=event.request.headers.get("user-agent")
|
|
)
|
|
await page.send(nodriver.cdp.network.enable())
|
|
page.add_handler(nodriver.cdp.network.RequestWillBeSent, on_request)
|
|
page = await browser.get(cls.url)
|
|
user_agent = await page.evaluate("window.navigator.userAgent")
|
|
await page.select("#prompt-textarea", 240)
|
|
while True:
|
|
if RequestConfig.access_token:
|
|
break
|
|
body = await page.evaluate("JSON.stringify(window.__remixContext)")
|
|
if body:
|
|
match = re.search(r'"accessToken":"(.*?)"', body)
|
|
if match:
|
|
RequestConfig.access_token = match.group(1)
|
|
break
|
|
await asyncio.sleep(1)
|
|
while True:
|
|
if RequestConfig.proof_token:
|
|
break
|
|
await asyncio.sleep(1)
|
|
RequestConfig.data_build = await page.evaluate("document.documentElement.getAttribute('data-build')")
|
|
for c in await page.send(nodriver.cdp.network.get_cookies([cls.url])):
|
|
RequestConfig.cookies[c.name] = c.value
|
|
await page.close()
|
|
cls._create_request_args(RequestConfig.cookies, RequestConfig.headers, user_agent=user_agent)
|
|
cls._set_api_key(RequestConfig.access_token)
|
|
|
|
@staticmethod
|
|
def get_default_headers() -> dict:
|
|
return {
|
|
**DEFAULT_HEADERS,
|
|
"content-type": "application/json",
|
|
}
|
|
|
|
@classmethod
|
|
def _create_request_args(cls, cookies: Cookies = None, headers: dict = None, user_agent: str = None):
|
|
cls._headers = cls.get_default_headers() if headers is None else headers
|
|
if user_agent is not None:
|
|
cls._headers["user-agent"] = user_agent
|
|
cls._cookies = {} if cookies is None else cookies
|
|
cls._update_cookie_header()
|
|
|
|
@classmethod
|
|
def _update_request_args(cls, session: StreamSession):
|
|
for c in session.cookie_jar if hasattr(session, "cookie_jar") else session.cookies.jar:
|
|
cls._cookies[c.key if hasattr(c, "key") else c.name] = c.value
|
|
cls._update_cookie_header()
|
|
|
|
@classmethod
|
|
def _set_api_key(cls, api_key: str):
|
|
cls._api_key = api_key
|
|
cls._expires = int(time.time()) + 60 * 60 * 4
|
|
if api_key:
|
|
cls._headers["authorization"] = f"Bearer {api_key}"
|
|
|
|
@classmethod
|
|
def _update_cookie_header(cls):
|
|
if cls._cookies:
|
|
cls._headers["cookie"] = format_cookies(cls._cookies)
|
|
|
|
class Conversation(BaseConversation):
|
|
"""
|
|
Class to encapsulate response fields.
|
|
"""
|
|
def __init__(self, conversation_id: str = None, message_id: str = None, finish_reason: str = None):
|
|
self.conversation_id = conversation_id
|
|
self.message_id = message_id
|
|
self.finish_reason = finish_reason
|
|
self.is_recipient = False |