from __future__ import annotations import os import re import asyncio import uuid import json import base64 import time import random from typing import AsyncIterator, Iterator, Optional, Generator, Dict from copy import copy try: import nodriver has_nodriver = True except ImportError: has_nodriver = False from ..base_provider import AsyncAuthedProvider, ProviderModelMixin from ...typing import AsyncResult, Messages, Cookies, MediaListType from ...requests.raise_for_status import raise_for_status from ...requests import StreamSession from ...requests import get_nodriver from ...image import ImageRequest, to_image, to_bytes, is_accepted_format from ...errors import MissingAuthError, NoValidHarFileError from ...providers.response import JsonConversation, FinishReason, SynthesizeData, AuthResult, ImageResponse, ImagePreview from ...providers.response import Sources, TitleGeneration, RequestLogin, Reasoning from ...tools.media import merge_media from ..helper import format_cookies, format_image_prompt from ..openai.models import default_model, default_image_model, models, image_models, text_models from ..openai.har_file import get_request_config from ..openai.har_file import RequestConfig, arkReq, arkose_url, start_url, conversation_url, backend_url, backend_anon_url from ..openai.proofofwork import generate_proof_token from ..openai.new import get_requirements_token, get_config from ... import debug DEFAULT_HEADERS = { "accept": "*/*", "accept-encoding": "gzip, deflate, br, zstd", 'accept-language': 'en-US,en;q=0.8', "referer": "https://chatgpt.com/", "sec-ch-ua": "\"Google Chrome\";v=\"131\", \"Chromium\";v=\"131\", \"Not_A Brand\";v=\"24\"", "sec-ch-ua-mobile": "?0", "sec-ch-ua-platform": "\"Windows\"", "sec-fetch-dest": "empty", "sec-fetch-mode": "cors", "sec-fetch-site": "same-origin", "sec-gpc": "1", "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36" } INIT_HEADERS = { 'accept': '*/*', 'accept-language': 'en-US,en;q=0.8', 'cache-control': 'no-cache', 'pragma': 'no-cache', 'priority': 'u=0, i', "sec-ch-ua": "\"Google Chrome\";v=\"131\", \"Chromium\";v=\"131\", \"Not_A Brand\";v=\"24\"", 'sec-ch-ua-arch': '"arm"', 'sec-ch-ua-bitness': '"64"', 'sec-ch-ua-mobile': '?0', 'sec-ch-ua-model': '""', "sec-ch-ua-platform": "\"Windows\"", 'sec-ch-ua-platform-version': '"14.4.0"', 'sec-fetch-dest': 'document', 'sec-fetch-mode': 'navigate', 'sec-fetch-site': 'none', 'sec-fetch-user': '?1', 'upgrade-insecure-requests': '1', "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36" } UPLOAD_HEADERS = { "accept": "application/json, text/plain, */*", 'accept-language': 'en-US,en;q=0.8', "referer": "https://chatgpt.com/", "priority": "u=1, i", "sec-ch-ua": "\"Google Chrome\";v=\"131\", \"Chromium\";v=\"131\", \"Not_A Brand\";v=\"24\"", "sec-ch-ua-mobile": "?0", 'sec-ch-ua-platform': '"macOS"', "sec-fetch-dest": "empty", "sec-fetch-mode": "cors", "sec-fetch-site": "cross-site", "x-ms-blob-type": "BlockBlob", "x-ms-version": "2020-04-08", "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36" } class OpenaiChat(AsyncAuthedProvider, ProviderModelMixin): """A class for creating and managing conversations with OpenAI chat service""" label = "OpenAI ChatGPT" url = "https://chatgpt.com" working = True use_nodriver = True supports_gpt_4 = True supports_message_history = True supports_system_message = True default_model = default_model default_image_model = default_image_model image_models = image_models vision_models = text_models models = models synthesize_content_type = "audio/aac" request_config = RequestConfig() _api_key: str = None _headers: dict = None _cookies: Cookies = None _expires: int = None @classmethod async def on_auth_async(cls, proxy: str = None, **kwargs) -> AsyncIterator: async for chunk in cls.login(proxy=proxy): yield chunk yield AuthResult( api_key=cls._api_key, cookies=cls._cookies or cls.request_config.cookies or {}, headers=cls._headers or cls.request_config.headers or cls.get_default_headers(), expires=cls._expires, proof_token=cls.request_config.proof_token, turnstile_token=cls.request_config.turnstile_token ) @classmethod async def upload_images( cls, session: StreamSession, auth_result: AuthResult, media: MediaListType, ) -> ImageRequest: """ Upload an image to the service and get the download URL Args: session: The StreamSession object to use for requests headers: The headers to include in the requests media: The images to upload, either a PIL Image object or a bytes object Returns: An ImageRequest object that contains the download URL, file name, and other data """ async def upload_image(image, image_name): debug.log(f"Uploading image: {image_name}") # Convert the image to a PIL Image object and get the extension data_bytes = to_bytes(image) image = to_image(data_bytes) extension = image.format.lower() data = { "file_name": "" if image_name is None else image_name, "file_size": len(data_bytes), "use_case": "multimodal" } # Post the image data to the service and get the image data headers = auth_result.headers if hasattr(auth_result, "headers") else None async with session.post(f"{cls.url}/backend-api/files", json=data, headers=headers) as response: cls._update_request_args(auth_result, session) await raise_for_status(response, "Create file failed") image_data = { **data, **await response.json(), "mime_type": is_accepted_format(data_bytes), "extension": extension, "height": image.height, "width": image.width } # Put the image bytes to the upload URL and check the status await asyncio.sleep(1) async with session.put( image_data["upload_url"], data=data_bytes, headers={ **UPLOAD_HEADERS, "Content-Type": image_data["mime_type"], "x-ms-blob-type": "BlockBlob", "x-ms-version": "2020-04-08", "Origin": "https://chatgpt.com", } ) as response: await raise_for_status(response) # Post the file ID to the service and get the download URL async with session.post( f"{cls.url}/backend-api/files/{image_data['file_id']}/uploaded", json={}, headers=auth_result.headers ) as response: cls._update_request_args(auth_result, session) await raise_for_status(response, "Get download url failed") image_data["download_url"] = (await response.json())["download_url"] return ImageRequest(image_data) return [await upload_image(image, image_name) for image, image_name in media] @classmethod def create_messages(cls, messages: Messages, image_requests: ImageRequest = None, system_hints: list = None): """ Create a list of messages for the user input Args: prompt: The user input as a string image_response: The image response object, if any Returns: A list of messages with the user input and the image, if any """ # merged_messages = [] # last_message = None # for message in messages: # current_message = last_message # if current_message is not None: # if current_message["role"] == message["role"]: # current_message["content"] += "\n" + message["content"] # else: # merged_messages.append(current_message) # last_message = message.copy() # else: # last_message = message.copy() # if last_message is not None: # merged_messages.append(last_message) messages = [{ "id": str(uuid.uuid4()), "author": {"role": message["role"]}, "content": {"content_type": "text", "parts": [message["content"]]}, "metadata": {"serialization_metadata": {"custom_symbol_offsets": []}, **({"system_hints": system_hints} if system_hints else {})}, "create_time": time.time(), } for message in messages] # Check if there is an image response if image_requests: # Change content in last user message messages[-1]["content"] = { "content_type": "multimodal_text", "parts": [*[{ "asset_pointer": f"file-service://{image_request.get('file_id')}", "height": image_request.get("height"), "size_bytes": image_request.get("file_size"), "width": image_request.get("width"), } for image_request in image_requests], messages[-1]["content"]["parts"][0]] } # Add the metadata object with the attachments messages[-1]["metadata"] = { "attachments": [{ "height": image_request.get("height"), "id": image_request.get("file_id"), "mimeType": image_request.get("mime_type"), "name": image_request.get("file_name"), "size": image_request.get("file_size"), "width": image_request.get("width"), } for image_request in image_requests] } return messages @classmethod async def get_generated_images(cls, session: StreamSession, auth_result: AuthResult, parts: list, prompt: str, conversation_id: str) -> AsyncIterator: download_urls = [] element = element.split("sediment://")[-1] url = f"{cls.url}/backend-api/conversation/{conversation_id}/attachment/{element}/download" debug.log(f"OpenaiChat: Downloading image: {url}") try: async with session.get(url, headers=auth_result.headers) as response: cls._update_request_args(auth_result, session) await raise_for_status(response) data = await response.json() download_url = data.get("download_url") download_urls.append(download_url) except Exception as e: debug.error("OpenaiChat: Download image failed") debug.error(e) return ImagePreview(download_urls, prompt) @classmethod async def create_authed( cls, model: str, messages: Messages, auth_result: AuthResult, proxy: str = None, timeout: int = 360, auto_continue: bool = False, action: str = "next", conversation: Conversation = None, media: MediaListType = None, return_conversation: bool = False, web_search: bool = False, prompt: str = None, **kwargs ) -> AsyncResult: """ Create an asynchronous generator for the conversation. Args: model (str): The model name. messages (Messages): The list of previous messages. proxy (str): Proxy to use for requests. timeout (int): Timeout for requests. api_key (str): Access token for authentication. auto_continue (bool): Flag to automatically continue the conversation. action (str): Type of action ('next', 'continue', 'variant'). conversation_id (str): ID of the conversation. media (MediaListType): Images to include in the conversation. return_conversation (bool): Flag to include response fields in the output. **kwargs: Additional keyword arguments. Yields: AsyncResult: Asynchronous results from the generator. Raises: RuntimeError: If an error occurs during processing. """ async with StreamSession( proxy=proxy, impersonate="chrome", timeout=timeout ) as session: image_requests = None if not cls.needs_auth: if cls._headers is None: cls._create_request_args(cls._cookies) async with session.get(cls.url, headers=INIT_HEADERS) as response: cls._update_request_args(auth_result, session) await raise_for_status(response) else: if cls._headers is None and getattr(auth_result, "cookies", None): cls._create_request_args(auth_result.cookies, auth_result.headers) if not cls._set_api_key(getattr(auth_result, "api_key", None)): raise MissingAuthError("Access token is not valid") async with session.get(cls.url, headers=cls._headers) as response: cls._update_request_args(auth_result, session) await raise_for_status(response) try: image_requests = await cls.upload_images(session, auth_result, merge_media(media, messages)) except Exception as e: debug.error("OpenaiChat: Upload image failed") debug.error(e) model = cls.get_model(model) if conversation is None: conversation = Conversation(None, str(uuid.uuid4()), getattr(auth_result, "cookies", {}).get("oai-did")) else: conversation = copy(conversation) if getattr(auth_result, "cookies", {}).get("oai-did") != getattr(conversation, "user_id", None): conversation = Conversation(None, str(uuid.uuid4())) if cls._api_key is None: auto_continue = False conversation.finish_reason = None sources = Sources([]) while conversation.finish_reason is None: async with session.post( f"{cls.url}/backend-anon/sentinel/chat-requirements" if cls._api_key is None else f"{cls.url}/backend-api/sentinel/chat-requirements", json={"p": None if not getattr(auth_result, "proof_token", None) else get_requirements_token(getattr(auth_result, "proof_token", None))}, headers=cls._headers ) as response: if response.status in (401, 403): raise MissingAuthError(f"Response status: {response.status}") else: cls._update_request_args(auth_result, session) await raise_for_status(response) chat_requirements = await response.json() need_turnstile = chat_requirements.get("turnstile", {}).get("required", False) need_arkose = chat_requirements.get("arkose", {}).get("required", False) chat_token = chat_requirements.get("token") # if need_arkose and cls.request_config.arkose_token is None: # await get_request_config(proxy) # cls._create_request_args(auth_result.cookies, auth_result.headers) # cls._set_api_key(auth_result.access_token) # if auth_result.arkose_token is None: # raise MissingAuthError("No arkose token found in .har file") if "proofofwork" in chat_requirements: user_agent = getattr(auth_result, "headers", {}).get("user-agent") proof_token = getattr(auth_result, "proof_token", None) if proof_token is None: auth_result.proof_token = get_config(user_agent) proofofwork = generate_proof_token( **chat_requirements["proofofwork"], user_agent=user_agent, proof_token=proof_token ) [debug.log(text) for text in ( #f"Arkose: {'False' if not need_arkose else auth_result.arkose_token[:12]+'...'}", #f"Proofofwork: {'False' if proofofwork is None else proofofwork[:12]+'...'}", #f"AccessToken: {'False' if cls._api_key is None else cls._api_key[:12]+'...'}", )] data = { "action": "next", "parent_message_id": conversation.message_id, "model": model, "timezone_offset_min":-60, "timezone":"Europe/Berlin", "conversation_mode":{"kind":"primary_assistant"}, "enable_message_followups":True, "system_hints": ["search"] if web_search else None, "supports_buffering":True, "supported_encodings":["v1"], "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}, "paragen_cot_summary_display_override":"allow" } if conversation.conversation_id is not None: data["conversation_id"] = conversation.conversation_id debug.log(f"OpenaiChat: Use conversation: {conversation.conversation_id}") conversation.prompt = format_image_prompt(messages, prompt) if action != "continue": data["parent_message_id"] = getattr(conversation, "parent_message_id", conversation.message_id) conversation.parent_message_id = None messages = messages if conversation.conversation_id is None else [{"role": "user", "content": prompt}] data["messages"] = cls.create_messages(messages, image_requests, ["search"] if web_search else None) headers = { **cls._headers, "accept": "text/event-stream", "content-type": "application/json", "openai-sentinel-chat-requirements-token": chat_token, } #if cls.request_config.arkose_token: # headers["openai-sentinel-arkose-token"] = cls.request_config.arkose_token if proofofwork is not None: headers["openai-sentinel-proof-token"] = proofofwork if need_turnstile and getattr(auth_result, "turnstile_token", None) is not None: headers['openai-sentinel-turnstile-token'] = auth_result.turnstile_token async with session.post( f"{cls.url}/backend-anon/conversation" if cls._api_key is None else f"{cls.url}/backend-api/conversation", json=data, headers=headers ) as response: cls._update_request_args(auth_result, session) if response.status in (401, 403, 429): raise MissingAuthError("Access token is not valid") await raise_for_status(response) buffer = u"" async for line in response.iter_lines(): async for chunk in cls.iter_messages_line(session, auth_result, line, conversation, sources): if isinstance(chunk, str): chunk = chunk.replace("\ue203", "").replace("\ue204", "").replace("\ue206", "") buffer += chunk if buffer.find(u"\ue200") != -1: if buffer.find(u"\ue201") != -1: buffer = buffer.replace("\ue200", "").replace("\ue202", "\n").replace("\ue201", "") buffer = buffer.replace("navlist\n", "#### ") def replacer(match): link = None if len(sources.list) > int(match.group(1)): link = sources.list[int(match.group(1))]["url"] return f"[[{int(match.group(1))+1}]]({link})" return f" [{int(match.group(1))+1}]" buffer = re.sub(r'(?:cite\nturn[0-9]+|turn[0-9]+)(?:search|news|view)(\d+)', replacer, buffer) else: continue yield buffer buffer = "" else: yield chunk if conversation.finish_reason is not None: break if sources.list: yield sources if conversation.generated_images: yield ImageResponse(conversation.generated_images.urls, conversation.prompt) conversation.generated_images = None conversation.prompt = None if return_conversation: yield conversation if auth_result.api_key is not None: yield SynthesizeData(cls.__name__, { "conversation_id": conversation.conversation_id, "message_id": conversation.message_id, "voice": "maple", }) if auto_continue and conversation.finish_reason == "max_tokens": conversation.finish_reason = None action = "continue" await asyncio.sleep(5) else: break yield FinishReason(conversation.finish_reason) @classmethod async def iter_messages_line(cls, session: StreamSession, auth_result: AuthResult, line: bytes, fields: Conversation, sources: Sources) -> AsyncIterator: if not line.startswith(b"data: "): return elif line.startswith(b"data: [DONE]"): return try: line = json.loads(line[6:]) except: return if not isinstance(line, dict): return if "type" in line: if line["type"] == "title_generation": yield TitleGeneration(line["title"]) fields.p = line.get("p", fields.p) if fields.p is not None and fields.p.startswith("/message/content/thoughts"): if fields.p.endswith("/content"): if fields.thoughts_summary: yield Reasoning(token="", status=fields.thoughts_summary) fields.thoughts_summary = "" yield Reasoning(token=line.get("v")) elif fields.p.endswith("/summary"): fields.thoughts_summary += line.get("v") return if "v" in line: v = line.get("v") if isinstance(v, str) and fields.recipient == "all": if "p" not in line or line.get("p") == "/message/content/parts/0": yield Reasoning(token=v) if fields.is_thinking else v elif isinstance(v, list): for m in v: if m.get("p") == "/message/content/parts/0" and fields.recipient == "all": yield m.get("v") elif m.get("p") == "/message/metadata/image_gen_title": fields.prompt = m.get("v") elif m.get("p") == "/message/content/parts/0/asset_pointer": fields.generated_images = await cls.get_generated_images(session, auth_result, m.get("v"), fields.prompt, fields.conversation_id) elif m.get("p") == "/message/metadata/search_result_groups": for entry in [p.get("entries") for p in m.get("v")]: for link in entry: sources.add_source(link) elif m.get("p") == "/message/metadata/content_references": for entry in m.get("v"): for link in entry.get("sources", []): sources.add_source(link) elif m.get("p") and re.match(r"^/message/metadata/content_references/\d+$", m.get("p")): sources.add_source(m.get("v")) elif m.get("p") == "/message/metadata/finished_text": fields.is_thinking = False yield Reasoning(status=m.get("v")) elif m.get("p") == "/message/metadata" and fields.recipient == "all": 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.recipient = m.get("recipient", fields.recipient) if fields.recipient == "all": c = m.get("content", {}) if c.get("content_type") == "text" and m.get("author", {}).get("role") == "tool" and "initial_text" in m.get("metadata", {}): fields.is_thinking = True yield Reasoning(status=m.get("metadata", {}).get("initial_text")) if c.get("content_type") == "multimodal_text": yield await cls.get_generated_images(session, auth_result, c.get("parts"), fields.prompt, fields.conversation_id) if m.get("author", {}).get("role") == "assistant": if fields.parent_message_id is None: fields.parent_message_id = v.get("message", {}).get("id") 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]: async for _ in cls.login(): pass async with StreamSession( impersonate="chrome", timeout=0 ) 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, api_key: str = None, proof_token: str = None, cookies: Cookies = None, headers: dict = None, **kwargs ) -> AsyncIterator: if cls._expires is not None and (cls._expires - 60*10) < time.time(): cls._headers = cls._api_key = None if cls._headers is None or headers is not None: cls._headers = {} if headers is None else headers if proof_token is not None: cls.request_config.proof_token = proof_token if cookies is not None: cls.request_config.cookies = cookies if api_key is not None: cls._create_request_args(cls.request_config.cookies, cls.request_config.headers) cls._set_api_key(api_key) else: try: cls.request_config = await get_request_config(cls.request_config, proxy) if cls.request_config is None: cls.request_config = RequestConfig() cls._create_request_args(cls.request_config.cookies, cls.request_config.headers) if cls.needs_auth and cls.request_config.access_token is None: raise NoValidHarFileError(f"Missing access token") if not cls._set_api_key(cls.request_config.access_token): raise NoValidHarFileError(f"Access token is not valid: {cls.request_config.access_token}") except NoValidHarFileError: if has_nodriver: if cls.request_config.access_token is None: yield RequestLogin(cls.label, os.environ.get("G4F_LOGIN_URL", "")) await cls.nodriver_auth(proxy) else: raise @classmethod async def nodriver_auth(cls, proxy: str = None): browser, stop_browser = await get_nodriver(proxy=proxy) try: page = browser.main_tab def on_request(event: nodriver.cdp.network.RequestWillBeSent, page=None): if event.request.url == start_url or event.request.url.startswith(conversation_url): if cls.request_config.headers is None: cls.request_config.headers = {} for key, value in event.request.headers.items(): cls.request_config.headers[key.lower()] = value elif event.request.url in (backend_url, backend_anon_url): if "OpenAI-Sentinel-Proof-Token" in event.request.headers: cls.request_config.proof_token = json.loads(base64.b64decode( event.request.headers["OpenAI-Sentinel-Proof-Token"].split("gAAAAAB", 1)[-1].split("~")[0].encode() ).decode()) if "OpenAI-Sentinel-Turnstile-Token" in event.request.headers: cls.request_config.turnstile_token = event.request.headers["OpenAI-Sentinel-Turnstile-Token"] if "Authorization" in event.request.headers: cls._api_key = event.request.headers["Authorization"].split()[-1] elif event.request.url == arkose_url: cls.request_config.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", return_by_value=True) while not await page.evaluate("document.getElementById('prompt-textarea').id"): await asyncio.sleep(1) while not await page.evaluate("document.querySelector('[data-testid=\"send-button\"]').type"): await asyncio.sleep(1) await page.evaluate("document.querySelector('[data-testid=\"send-button\"]').click()") while True: body = await page.evaluate("JSON.stringify(window.__remixContext)", return_by_value=True) if hasattr(body, "value"): body = body.value if body: match = re.search(r'"accessToken":"(.+?)"', body) if match: cls._api_key = match.group(1) break if cls._api_key is not None or not cls.needs_auth: break await asyncio.sleep(1) while True: if cls.request_config.proof_token: break await asyncio.sleep(1) cls.request_config.data_build = await page.evaluate("document.documentElement.getAttribute('data-build')") cls.request_config.cookies = await page.send(get_cookies([cls.url])) await page.close() cls._create_request_args(cls.request_config.cookies, cls.request_config.headers, user_agent=user_agent) cls._set_api_key(cls._api_key) finally: stop_browser() @staticmethod def get_default_headers() -> Dict[str, str]: 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, auth_result: AuthResult, session: StreamSession): if hasattr(auth_result, "cookies"): for c in session.cookie_jar if hasattr(session, "cookie_jar") else session.cookies.jar: auth_result.cookies[getattr(c, "key", getattr(c, "name", ""))] = c.value cls._cookies = auth_result.cookies cls._update_cookie_header() @classmethod def _set_api_key(cls, api_key: str): cls._api_key = api_key if api_key: exp = api_key.split(".")[1] exp = (exp + "=" * (4 - len(exp) % 4)).encode() cls._expires = json.loads(base64.b64decode(exp)).get("exp") debug.log(f"OpenaiChat: API key expires at\n {cls._expires} we have:\n {time.time()}") if time.time() > cls._expires: debug.log(f"OpenaiChat: API key is expired") return False else: cls._headers["authorization"] = f"Bearer {api_key}" return True return True @classmethod def _update_cookie_header(cls): if cls._cookies: cls._headers["cookie"] = format_cookies(cls._cookies) class Conversation(JsonConversation): """ Class to encapsulate response fields. """ def __init__(self, conversation_id: str = None, message_id: str = None, user_id: str = None, finish_reason: str = None, parent_message_id: str = None, is_thinking: bool = False): self.conversation_id = conversation_id self.message_id = message_id self.finish_reason = finish_reason self.recipient = "all" self.parent_message_id = message_id if parent_message_id is None else parent_message_id self.user_id = user_id self.is_thinking = is_thinking self.p = None self.thoughts_summary = "" self.prompt = None self.generated_images: ImagePreview = None def get_cookies( urls: Optional[Iterator[str]] = None ) -> Generator[Dict, Dict, Dict[str, str]]: params = {} if urls is not None: params['urls'] = [i for i in urls] cmd_dict = { 'method': 'Network.getCookies', 'params': params, } json = yield cmd_dict return {c["name"]: c["value"] for c in json['cookies']} if 'cookies' in json else {}