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author | Heiner Lohaus <hlohaus@users.noreply.github.com> | 2024-01-14 07:45:41 +0100 |
---|---|---|
committer | Heiner Lohaus <hlohaus@users.noreply.github.com> | 2024-01-14 07:45:41 +0100 |
commit | 5756586cde6ed6da147119113fb5a5fd640d5f83 (patch) | |
tree | 64a9612c8c32e3c7eb4cdeb6f4ad63a08e5706b0 /g4f/Provider/needs_auth/OpenaiChat.py | |
parent | Fix process_image in Bing (diff) | |
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Diffstat (limited to 'g4f/Provider/needs_auth/OpenaiChat.py')
-rw-r--r-- | g4f/Provider/needs_auth/OpenaiChat.py | 339 |
1 files changed, 229 insertions, 110 deletions
diff --git a/g4f/Provider/needs_auth/OpenaiChat.py b/g4f/Provider/needs_auth/OpenaiChat.py index a790f0de..7d352a46 100644 --- a/g4f/Provider/needs_auth/OpenaiChat.py +++ b/g4f/Provider/needs_auth/OpenaiChat.py @@ -1,6 +1,9 @@ from __future__ import annotations +import asyncio +import uuid +import json +import os -import uuid, json, asyncio, os from py_arkose_generator.arkose import get_values_for_request from async_property import async_cached_property from selenium.webdriver.common.by import By @@ -14,7 +17,8 @@ from ...typing import AsyncResult, Messages from ...requests import StreamSession from ...image import to_image, to_bytes, ImageType, ImageResponse -models = { +# Aliases for model names +MODELS = { "gpt-3.5": "text-davinci-002-render-sha", "gpt-3.5-turbo": "text-davinci-002-render-sha", "gpt-4": "gpt-4", @@ -22,13 +26,15 @@ models = { } class OpenaiChat(AsyncGeneratorProvider): - url = "https://chat.openai.com" - working = True - needs_auth = True + """A class for creating and managing conversations with OpenAI chat service""" + + url = "https://chat.openai.com" + working = True + needs_auth = True supports_gpt_35_turbo = True - supports_gpt_4 = True - _cookies: dict = {} - _default_model: str = None + supports_gpt_4 = True + _cookies: dict = {} + _default_model: str = None @classmethod async def create( @@ -43,6 +49,23 @@ class OpenaiChat(AsyncGeneratorProvider): image: ImageType = None, **kwargs ) -> Response: + """Create a new conversation or continue an existing one + + Args: + prompt: The user input to start or continue the conversation + model: The name of the model to use for generating responses + messages: The list of previous messages in the conversation + history_disabled: A flag indicating if the history and training should be disabled + action: The type of action to perform, either "next", "continue", or "variant" + conversation_id: The ID of the existing conversation, if any + parent_id: The ID of the parent message, if any + image: The image to include in the user input, if any + **kwargs: Additional keyword arguments to pass to the generator + + Returns: + A Response object that contains the generator, action, messages, and options + """ + # Add the user input to the messages list if prompt: messages.append({ "role": "user", @@ -67,20 +90,33 @@ class OpenaiChat(AsyncGeneratorProvider): ) @classmethod - async def upload_image( + async def _upload_image( cls, session: StreamSession, headers: dict, image: ImageType ) -> ImageResponse: + """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 + image: The image to upload, either a PIL Image object or a bytes object + + Returns: + An ImageResponse object that contains the download URL, file name, and other data + """ + # Convert the image to a PIL Image object and get the extension image = to_image(image) extension = image.format.lower() + # Convert the image to a bytes object and get the size data_bytes = to_bytes(image) data = { "file_name": f"{image.width}x{image.height}.{extension}", "file_size": len(data_bytes), "use_case": "multimodal" } + # Post the image data to the service and get the image data async with session.post(f"{cls.url}/backend-api/files", json=data, headers=headers) as response: response.raise_for_status() image_data = { @@ -91,6 +127,7 @@ class OpenaiChat(AsyncGeneratorProvider): "height": image.height, "width": image.width } + # Put the image bytes to the upload URL and check the status async with session.put( image_data["upload_url"], data=data_bytes, @@ -100,6 +137,7 @@ class OpenaiChat(AsyncGeneratorProvider): } ) as response: response.raise_for_status() + # 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={}, @@ -110,24 +148,45 @@ class OpenaiChat(AsyncGeneratorProvider): return ImageResponse(download_url, image_data["file_name"], image_data) @classmethod - async def get_default_model(cls, session: StreamSession, headers: dict): + async def _get_default_model(cls, session: StreamSession, headers: dict): + """Get the default model name from the service + + Args: + session: The StreamSession object to use for requests + headers: The headers to include in the requests + + Returns: + The default model name as a string + """ + # Check the cache for the default model if cls._default_model: - model = cls._default_model - else: - async with session.get(f"{cls.url}/backend-api/models", headers=headers) as response: - data = await response.json() - if "categories" in data: - model = data["categories"][-1]["default_model"] - else: - RuntimeError(f"Response: {data}") - cls._default_model = model - return model + return cls._default_model + # Get the models data from the service + async with session.get(f"{cls.url}/backend-api/models", headers=headers) as response: + data = await response.json() + if "categories" in data: + cls._default_model = data["categories"][-1]["default_model"] + else: + raise RuntimeError(f"Response: {data}") + return cls._default_model @classmethod - def create_messages(cls, prompt: str, image_response: ImageResponse = None): + def _create_messages(cls, prompt: str, image_response: ImageResponse = 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 + """ + # Check if there is an image response if not image_response: + # Create a content object with the text type and the prompt content = {"content_type": "text", "parts": [prompt]} else: + # Create a content object with the multimodal text type and the image and the prompt content = { "content_type": "multimodal_text", "parts": [{ @@ -137,12 +196,15 @@ class OpenaiChat(AsyncGeneratorProvider): "width": image_response.get("width"), }, prompt] } + # Create a message object with the user role and the content messages = [{ "id": str(uuid.uuid4()), "author": {"role": "user"}, "content": content, }] + # Check if there is an image response if image_response: + # Add the metadata object with the attachments messages[0]["metadata"] = { "attachments": [{ "height": image_response.get("height"), @@ -156,19 +218,38 @@ class OpenaiChat(AsyncGeneratorProvider): return messages @classmethod - async def get_image_response(cls, session: StreamSession, headers: dict, line: dict): - if "parts" in line["message"]["content"]: - part = line["message"]["content"]["parts"][0] - if "asset_pointer" in part and part["metadata"]: - file_id = part["asset_pointer"].split("file-service://", 1)[1] - prompt = part["metadata"]["dalle"]["prompt"] - async with session.get( - f"{cls.url}/backend-api/files/{file_id}/download", - headers=headers - ) as response: - response.raise_for_status() - download_url = (await response.json())["download_url"] - return ImageResponse(download_url, prompt) + async def _get_generated_image(cls, session: StreamSession, headers: dict, line: dict) -> ImageResponse: + """ + Retrieves the image response based on the message content. + + :param session: The StreamSession object. + :param headers: HTTP headers for the request. + :param line: The line of response containing image information. + :return: An ImageResponse object with the image details. + """ + if "parts" not in line["message"]["content"]: + return + first_part = line["message"]["content"]["parts"][0] + if "asset_pointer" not in first_part or "metadata" not in first_part: + return + file_id = first_part["asset_pointer"].split("file-service://", 1)[1] + prompt = first_part["metadata"]["dalle"]["prompt"] + try: + async with session.get(f"{cls.url}/backend-api/files/{file_id}/download", headers=headers) as response: + response.raise_for_status() + download_url = (await response.json())["download_url"] + return ImageResponse(download_url, prompt) + except Exception as e: + raise RuntimeError(f"Error in downloading image: {e}") + + @classmethod + async def _delete_conversation(cls, session: StreamSession, headers: dict, conversation_id: str): + async with session.patch( + f"{cls.url}/backend-api/conversation/{conversation_id}", + json={"is_visible": False}, + headers=headers + ) as response: + response.raise_for_status() @classmethod async def create_async_generator( @@ -188,26 +269,47 @@ class OpenaiChat(AsyncGeneratorProvider): response_fields: bool = False, **kwargs ) -> AsyncResult: - if model in models: - model = models[model] + """ + 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. + access_token (str): Access token for authentication. + cookies (dict): Cookies to use for authentication. + auto_continue (bool): Flag to automatically continue the conversation. + history_disabled (bool): Flag to disable history and training. + action (str): Type of action ('next', 'continue', 'variant'). + conversation_id (str): ID of the conversation. + parent_id (str): ID of the parent message. + image (ImageType): Image to include in the conversation. + response_fields (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. + """ + model = MODELS.get(model, model) if not parent_id: parent_id = str(uuid.uuid4()) if not cookies: - cookies = cls._cookies - if not access_token: - if not cookies: - cls._cookies = cookies = get_cookies("chat.openai.com") - if "access_token" in cookies: - access_token = cookies["access_token"] + cookies = cls._cookies or get_cookies("chat.openai.com") + if not access_token and "access_token" in cookies: + access_token = cookies["access_token"] if not access_token: login_url = os.environ.get("G4F_LOGIN_URL") if login_url: yield f"Please login: [ChatGPT]({login_url})\n\n" - access_token, cookies = cls.browse_access_token(proxy) + access_token, cookies = cls._browse_access_token(proxy) cls._cookies = cookies - headers = { - "Authorization": f"Bearer {access_token}", - } + + headers = {"Authorization": f"Bearer {access_token}"} + async with StreamSession( proxies={"https": proxy}, impersonate="chrome110", @@ -215,11 +317,11 @@ class OpenaiChat(AsyncGeneratorProvider): cookies=dict([(name, value) for name, value in cookies.items() if name == "_puid"]) ) as session: if not model: - model = await cls.get_default_model(session, headers) + model = await cls._get_default_model(session, headers) try: image_response = None if image: - image_response = await cls.upload_image(session, headers, image) + image_response = await cls._upload_image(session, headers, image) yield image_response except Exception as e: yield e @@ -227,7 +329,7 @@ class OpenaiChat(AsyncGeneratorProvider): while not end_turn.is_end: data = { "action": action, - "arkose_token": await cls.get_arkose_token(session), + "arkose_token": await cls._get_arkose_token(session), "conversation_id": conversation_id, "parent_message_id": parent_id, "model": model, @@ -235,7 +337,7 @@ class OpenaiChat(AsyncGeneratorProvider): } if action != "continue": prompt = format_prompt(messages) if not conversation_id else messages[-1]["content"] - data["messages"] = cls.create_messages(prompt, image_response) + data["messages"] = cls._create_messages(prompt, image_response) async with session.post( f"{cls.url}/backend-api/conversation", json=data, @@ -261,62 +363,80 @@ class OpenaiChat(AsyncGeneratorProvider): if "message_type" not in line["message"]["metadata"]: continue try: - image_response = await cls.get_image_response(session, headers, line) + image_response = await cls._get_generated_image(session, headers, line) if image_response: yield image_response except Exception as e: yield e if line["message"]["author"]["role"] != "assistant": continue - if line["message"]["metadata"]["message_type"] in ("next", "continue", "variant"): - conversation_id = line["conversation_id"] - parent_id = line["message"]["id"] - if response_fields: - response_fields = False - yield ResponseFields(conversation_id, parent_id, end_turn) - if "parts" in line["message"]["content"]: - new_message = line["message"]["content"]["parts"][0] - if len(new_message) > last_message: - yield new_message[last_message:] - last_message = len(new_message) + if line["message"]["content"]["content_type"] != "text": + continue + if line["message"]["metadata"]["message_type"] not in ("next", "continue", "variant"): + continue + conversation_id = line["conversation_id"] + parent_id = line["message"]["id"] + if response_fields: + response_fields = False + yield ResponseFields(conversation_id, parent_id, end_turn) + if "parts" in line["message"]["content"]: + new_message = line["message"]["content"]["parts"][0] + if len(new_message) > last_message: + yield new_message[last_message:] + last_message = len(new_message) if "finish_details" in line["message"]["metadata"]: if line["message"]["metadata"]["finish_details"]["type"] == "stop": end_turn.end() - break except Exception as e: - yield e + raise e if not auto_continue: break action = "continue" await asyncio.sleep(5) - if history_disabled: - async with session.patch( - f"{cls.url}/backend-api/conversation/{conversation_id}", - json={"is_visible": False}, - headers=headers - ) as response: - response.raise_for_status() + if history_disabled and auto_continue: + await cls._delete_conversation(session, headers, conversation_id) @classmethod - def browse_access_token(cls, proxy: str = None) -> tuple[str, dict]: + def _browse_access_token(cls, proxy: str = None) -> tuple[str, dict]: + """ + Browse to obtain an access token. + + Args: + proxy (str): Proxy to use for browsing. + + Returns: + tuple[str, dict]: A tuple containing the access token and cookies. + """ driver = get_browser(proxy=proxy) try: driver.get(f"{cls.url}/") - WebDriverWait(driver, 1200).until( - EC.presence_of_element_located((By.ID, "prompt-textarea")) + WebDriverWait(driver, 1200).until(EC.presence_of_element_located((By.ID, "prompt-textarea"))) + access_token = driver.execute_script( + "let session = await fetch('/api/auth/session');" + "let data = await session.json();" + "let accessToken = data['accessToken'];" + "let expires = new Date(); expires.setTime(expires.getTime() + 60 * 60 * 24 * 7);" + "document.cookie = 'access_token=' + accessToken + ';expires=' + expires.toUTCString() + ';path=/';" + "return accessToken;" ) - javascript = """ -access_token = (await (await fetch('/api/auth/session')).json())['accessToken']; -expires = new Date(); expires.setTime(expires.getTime() + 60 * 60 * 24 * 7); // One week -document.cookie = 'access_token=' + access_token + ';expires=' + expires.toUTCString() + ';path=/'; -return access_token; -""" - return driver.execute_script(javascript), get_driver_cookies(driver) + return access_token, get_driver_cookies(driver) finally: driver.quit() - @classmethod - async def get_arkose_token(cls, session: StreamSession) -> str: + @classmethod + async def _get_arkose_token(cls, session: StreamSession) -> str: + """ + Obtain an Arkose token for the session. + + Args: + session (StreamSession): The session object. + + Returns: + str: The Arkose token. + + Raises: + RuntimeError: If unable to retrieve the token. + """ config = { "pkey": "3D86FBBA-9D22-402A-B512-3420086BA6CC", "surl": "https://tcr9i.chat.openai.com", @@ -332,26 +452,30 @@ return access_token; if "token" in decoded_json: return decoded_json["token"] raise RuntimeError(f"Response: {decoded_json}") - -class EndTurn(): + +class EndTurn: + """ + Class to represent the end of a conversation turn. + """ def __init__(self): self.is_end = False def end(self): self.is_end = True -class ResponseFields(): - def __init__( - self, - conversation_id: str, - message_id: str, - end_turn: EndTurn - ): +class ResponseFields: + """ + Class to encapsulate response fields. + """ + def __init__(self, conversation_id: str, message_id: str, end_turn: EndTurn): self.conversation_id = conversation_id self.message_id = message_id self._end_turn = end_turn class Response(): + """ + Class to encapsulate a response from the chat service. + """ def __init__( self, generator: AsyncResult, @@ -360,13 +484,13 @@ class Response(): options: dict ): self._generator = generator - self.action: str = action - self.is_end: bool = False + self.action = action + self.is_end = False self._message = None self._messages = messages self._options = options self._fields = None - + async def generator(self): if self._generator: self._generator = None @@ -384,19 +508,16 @@ class Response(): def __aiter__(self): return self.generator() - + @async_cached_property async def message(self) -> str: - [_ async for _ in self.generator()] + await self.generator() return self._message - + async def get_fields(self): - [_ async for _ in self.generator()] - return { - "conversation_id": self._fields.conversation_id, - "parent_id": self._fields.message_id, - } - + await self.generator() + return {"conversation_id": self._fields.conversation_id, "parent_id": self._fields.message_id} + async def next(self, prompt: str, **kwargs) -> Response: return await OpenaiChat.create( **self._options, @@ -406,7 +527,7 @@ class Response(): **await self.get_fields(), **kwargs ) - + async def do_continue(self, **kwargs) -> Response: fields = await self.get_fields() if self.is_end: @@ -418,7 +539,7 @@ class Response(): **fields, **kwargs ) - + async def variant(self, **kwargs) -> Response: if self.action != "next": raise RuntimeError("Can't create variant from continue or variant request.") @@ -429,11 +550,9 @@ class Response(): **await self.get_fields(), **kwargs ) - + @async_cached_property async def messages(self): messages = self._messages - messages.append({ - "role": "assistant", "content": await self.message - }) + messages.append({"role": "assistant", "content": await self.message}) return messages
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