mirror of
https://github.com/xtekky/gpt4free.git
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e8bd24a25b
* Improve slim docker image example, clean up OpenaiChat provider * Enhance event loop management for asynchronous generators * Fix attribute " shutdown_default_executor" not found in old python versions * asyncio file created with all async helpers * Add speech synthesize from Gemini. You can use it without a account
554 lines
24 KiB
Python
554 lines
24 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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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
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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, NoValidHarFileError
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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
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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=0.5",
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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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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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needs_auth = 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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default_vision_model = "gpt-4o"
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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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image_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)
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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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"Content-Type": image_data["mime_type"],
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"x-ms-blob-type": "BlockBlob"
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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)
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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):
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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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"id": str(uuid.uuid4()),
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"metadata": {"serialization_metadata": {"custom_symbol_offsets": []}}
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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) -> 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 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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**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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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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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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image_request = None
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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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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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"paragen_cot_summary_display_override": "allow",
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"history_and_training_disabled": history_disabled and not auto_continue and not return_conversation,
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"conversation_mode": {"kind":"primary_assistant"},
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"websocket_request_id": str(uuid.uuid4()),
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"supported_encodings": ["v1"],
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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)
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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:
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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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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")
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break
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elif isinstance(v, dict):
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if fields.conversation_id is None:
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fields.conversation_id = v.get("conversation_id")
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debug.log(f"OpenaiChat: New conversation: {fields.conversation_id}")
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m = v.get("message", {})
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fields.is_recipient = m.get("recipient") == "all"
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if fields.is_recipient:
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c = m.get("content", {})
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if c.get("content_type") == "multimodal_text":
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generated_images = []
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for element in c.get("parts"):
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if isinstance(element, dict) and element.get("content_type") == "image_asset_pointer":
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generated_images.append(
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cls.get_generated_image(session, cls._headers, element)
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)
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for image_response in await asyncio.gather(*generated_images):
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yield image_response
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if m.get("author", {}).get("role") == "assistant":
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fields.message_id = v.get("message", {}).get("id")
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return
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if "error" in line and line.get("error"):
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raise RuntimeError(line.get("error"))
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@classmethod
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async def synthesize(cls, params: dict) -> AsyncIterator[bytes]:
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await cls.login()
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async with StreamSession(
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impersonate="chrome",
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timeout=900
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) as session:
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async with session.get(
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f"{cls.url}/backend-api/synthesize",
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params=params,
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headers=cls._headers
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) as response:
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await raise_for_status(response)
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async for chunk in response.iter_content():
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yield chunk
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@classmethod
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async def login(cls, proxy: str = None):
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if cls._expires is not None and cls._expires < time.time():
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cls._headers = cls._api_key = None
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try:
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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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except NoValidHarFileError:
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if has_nodriver:
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await cls.nodriver_auth(proxy)
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else:
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raise
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@classmethod
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async def nodriver_auth(cls, proxy: str = None):
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browser = await get_nodriver(proxy=proxy)
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page = browser.main_tab
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def on_request(event: nodriver.cdp.network.RequestWillBeSent):
|
|
if event.request.url == start_url or event.request.url.startswith(conversation_url):
|
|
RequestConfig.access_request_id = event.request_id
|
|
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)
|
|
try:
|
|
if RequestConfig.access_request_id is not None:
|
|
body = await page.send(get_response_body(RequestConfig.access_request_id))
|
|
if isinstance(body, tuple) and body:
|
|
body = body[0]
|
|
if body:
|
|
match = re.search(r'"accessToken":"(.*?)"', body)
|
|
if match:
|
|
RequestConfig.access_token = match.group(1)
|
|
except KeyError:
|
|
pass
|
|
for c in await page.send(nodriver.cdp.network.get_cookies([cls.url])):
|
|
RequestConfig.cookies[c.name] = c.value
|
|
user_agent = await page.evaluate("window.navigator.userAgent")
|
|
await page.select("#prompt-textarea", 240)
|
|
while True:
|
|
if RequestConfig.proof_token:
|
|
break
|
|
await asyncio.sleep(1)
|
|
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):
|
|
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 |