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@ -1,6 +1,9 @@
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from __future__ import annotations
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import asyncio
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import uuid
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import json
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import os
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import uuid, json, asyncio, os
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from py_arkose_generator.arkose import get_values_for_request
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from async_property import async_cached_property
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from selenium.webdriver.common.by import By
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@ -14,7 +17,8 @@ from ...typing import AsyncResult, Messages
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from ...requests import StreamSession
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from ...image import to_image, to_bytes, ImageType, ImageResponse
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models = {
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# Aliases for model names
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MODELS = {
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"gpt-3.5": "text-davinci-002-render-sha",
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"gpt-3.5-turbo": "text-davinci-002-render-sha",
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"gpt-4": "gpt-4",
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@ -22,13 +26,15 @@ models = {
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}
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class OpenaiChat(AsyncGeneratorProvider):
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url = "https://chat.openai.com"
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working = True
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needs_auth = True
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"""A class for creating and managing conversations with OpenAI chat service"""
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url = "https://chat.openai.com"
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working = True
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needs_auth = True
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supports_gpt_35_turbo = True
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supports_gpt_4 = True
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_cookies: dict = {}
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_default_model: str = None
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supports_gpt_4 = True
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_cookies: dict = {}
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_default_model: str = None
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@classmethod
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async def create(
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@ -43,6 +49,23 @@ class OpenaiChat(AsyncGeneratorProvider):
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image: ImageType = None,
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**kwargs
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) -> Response:
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"""Create a new conversation or continue an existing one
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Args:
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prompt: The user input to start or continue the conversation
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model: The name of the model to use for generating responses
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messages: The list of previous messages in the conversation
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history_disabled: A flag indicating if the history and training should be disabled
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action: The type of action to perform, either "next", "continue", or "variant"
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conversation_id: The ID of the existing conversation, if any
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parent_id: The ID of the parent message, if any
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image: The image to include in the user input, if any
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**kwargs: Additional keyword arguments to pass to the generator
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Returns:
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A Response object that contains the generator, action, messages, and options
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"""
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# Add the user input to the messages list
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if prompt:
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messages.append({
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"role": "user",
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@ -67,20 +90,33 @@ class OpenaiChat(AsyncGeneratorProvider):
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)
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@classmethod
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async def upload_image(
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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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) -> ImageResponse:
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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 ImageResponse 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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image = to_image(image)
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extension = image.format.lower()
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# Convert the image to a bytes object and get the size
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data_bytes = to_bytes(image)
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data = {
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"file_name": f"{image.width}x{image.height}.{extension}",
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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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response.raise_for_status()
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image_data = {
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@ -91,6 +127,7 @@ class OpenaiChat(AsyncGeneratorProvider):
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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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@ -100,6 +137,7 @@ class OpenaiChat(AsyncGeneratorProvider):
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}
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) as response:
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response.raise_for_status()
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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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@ -110,24 +148,45 @@ class OpenaiChat(AsyncGeneratorProvider):
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return ImageResponse(download_url, image_data["file_name"], image_data)
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@classmethod
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async def get_default_model(cls, session: StreamSession, headers: dict):
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async def _get_default_model(cls, session: StreamSession, headers: dict):
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"""Get the default model name from the service
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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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Returns:
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The default model name as a string
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"""
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# Check the cache for the default model
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if cls._default_model:
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model = cls._default_model
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else:
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async with session.get(f"{cls.url}/backend-api/models", headers=headers) as response:
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data = await response.json()
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if "categories" in data:
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model = data["categories"][-1]["default_model"]
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else:
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RuntimeError(f"Response: {data}")
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cls._default_model = model
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return model
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return cls._default_model
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# Get the models data from the service
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async with session.get(f"{cls.url}/backend-api/models", headers=headers) as response:
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data = await response.json()
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if "categories" in data:
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cls._default_model = data["categories"][-1]["default_model"]
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else:
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raise RuntimeError(f"Response: {data}")
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return cls._default_model
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@classmethod
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def create_messages(cls, prompt: str, image_response: ImageResponse = None):
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def _create_messages(cls, prompt: str, image_response: ImageResponse = None):
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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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# Check if there is an image response
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if not image_response:
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# Create a content object with the text type and the prompt
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content = {"content_type": "text", "parts": [prompt]}
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else:
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# Create a content object with the multimodal text type and the image and the prompt
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content = {
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"content_type": "multimodal_text",
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"parts": [{
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@ -137,12 +196,15 @@ class OpenaiChat(AsyncGeneratorProvider):
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"width": image_response.get("width"),
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}, prompt]
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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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"id": str(uuid.uuid4()),
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"author": {"role": "user"},
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"content": content,
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}]
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# Check if there is an image response
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if image_response:
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# Add the metadata object with the attachments
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messages[0]["metadata"] = {
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"attachments": [{
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"height": image_response.get("height"),
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@ -156,19 +218,38 @@ class OpenaiChat(AsyncGeneratorProvider):
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return messages
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@classmethod
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async def get_image_response(cls, session: StreamSession, headers: dict, line: dict):
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if "parts" in line["message"]["content"]:
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part = line["message"]["content"]["parts"][0]
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if "asset_pointer" in part and part["metadata"]:
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file_id = part["asset_pointer"].split("file-service://", 1)[1]
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prompt = part["metadata"]["dalle"]["prompt"]
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async with session.get(
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f"{cls.url}/backend-api/files/{file_id}/download",
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headers=headers
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) as response:
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response.raise_for_status()
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download_url = (await response.json())["download_url"]
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return ImageResponse(download_url, prompt)
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async def _get_generated_image(cls, session: StreamSession, headers: dict, line: dict) -> ImageResponse:
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"""
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Retrieves the image response based on the message content.
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:param session: The StreamSession object.
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:param headers: HTTP headers for the request.
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:param line: The line of response containing image information.
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:return: An ImageResponse object with the image details.
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"""
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if "parts" not in line["message"]["content"]:
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return
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first_part = line["message"]["content"]["parts"][0]
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if "asset_pointer" not in first_part or "metadata" not in first_part:
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return
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file_id = first_part["asset_pointer"].split("file-service://", 1)[1]
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prompt = first_part["metadata"]["dalle"]["prompt"]
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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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response.raise_for_status()
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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 _delete_conversation(cls, session: StreamSession, headers: dict, conversation_id: str):
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async with session.patch(
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f"{cls.url}/backend-api/conversation/{conversation_id}",
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json={"is_visible": False},
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headers=headers
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) as response:
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response.raise_for_status()
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@classmethod
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async def create_async_generator(
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@ -188,26 +269,47 @@ class OpenaiChat(AsyncGeneratorProvider):
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response_fields: bool = False,
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**kwargs
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) -> AsyncResult:
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if model in models:
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model = models[model]
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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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access_token (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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response_fields (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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model = MODELS.get(model, model)
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if not parent_id:
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parent_id = str(uuid.uuid4())
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if not cookies:
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cookies = cls._cookies
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if not access_token:
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if not cookies:
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cls._cookies = cookies = get_cookies("chat.openai.com")
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if "access_token" in cookies:
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access_token = cookies["access_token"]
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cookies = cls._cookies or get_cookies("chat.openai.com")
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if not access_token and "access_token" in cookies:
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access_token = cookies["access_token"]
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if not access_token:
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login_url = os.environ.get("G4F_LOGIN_URL")
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if login_url:
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yield f"Please login: [ChatGPT]({login_url})\n\n"
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access_token, cookies = cls.browse_access_token(proxy)
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access_token, cookies = cls._browse_access_token(proxy)
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cls._cookies = cookies
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headers = {
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"Authorization": f"Bearer {access_token}",
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}
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headers = {"Authorization": f"Bearer {access_token}"}
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async with StreamSession(
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proxies={"https": proxy},
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impersonate="chrome110",
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@ -215,11 +317,11 @@ class OpenaiChat(AsyncGeneratorProvider):
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cookies=dict([(name, value) for name, value in cookies.items() if name == "_puid"])
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) as session:
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if not model:
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model = await cls.get_default_model(session, headers)
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model = await cls._get_default_model(session, headers)
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try:
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image_response = None
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if image:
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image_response = await cls.upload_image(session, headers, image)
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image_response = await cls._upload_image(session, headers, image)
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yield image_response
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except Exception as e:
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yield e
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@ -227,7 +329,7 @@ class OpenaiChat(AsyncGeneratorProvider):
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while not end_turn.is_end:
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data = {
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|
|
|
|
"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
|