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@@ -1,55 +1,511 @@ |
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import time |
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""" |
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A simple wrapper for the official ChatGPT API |
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""" |
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import argparse |
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import json |
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import os |
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import sys |
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from datetime import date |
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import openai |
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import tiktoken |
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from bot.bot import Bot |
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from revChatGPT.revChatGPT import Chatbot |
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from common.log import logger |
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from config import conf |
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user_session = dict() |
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last_session_refresh = time.time() |
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ENGINE = os.environ.get("GPT_ENGINE") or "text-chat-davinci-002-20221122" |
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ENCODER = tiktoken.get_encoding("gpt2") |
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# ChatGPT web接口 (暂时不可用) |
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class ChatGPTBot(Bot): |
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def __init__(self): |
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config = { |
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"Authorization": "<Your Bearer Token Here>", # This is optional |
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"session_token": conf().get("session_token") |
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def get_max_tokens(prompt: str) -> int: |
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""" |
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Get the max tokens for a prompt |
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""" |
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return 4000 - len(ENCODER.encode(prompt)) |
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# ['text-chat-davinci-002-20221122'] |
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class Chatbot: |
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""" |
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Official ChatGPT API |
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""" |
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def __init__(self, api_key: str, buffer: int = None) -> None: |
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""" |
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Initialize Chatbot with API key (from https://platform.openai.com/account/api-keys) |
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""" |
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openai.api_key = api_key or os.environ.get("OPENAI_API_KEY") |
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self.conversations = Conversation() |
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self.prompt = Prompt(buffer=buffer) |
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def _get_completion( |
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self, |
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prompt: str, |
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temperature: float = 0.5, |
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stream: bool = False, |
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): |
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""" |
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Get the completion function |
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""" |
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return openai.Completion.create( |
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engine=ENGINE, |
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prompt=prompt, |
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temperature=temperature, |
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max_tokens=get_max_tokens(prompt), |
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stop=["\n\n\n"], |
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stream=stream, |
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) |
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def _process_completion( |
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self, |
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user_request: str, |
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completion: dict, |
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conversation_id: str = None, |
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user: str = "User", |
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) -> dict: |
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if completion.get("choices") is None: |
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raise Exception("ChatGPT API returned no choices") |
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if len(completion["choices"]) == 0: |
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raise Exception("ChatGPT API returned no choices") |
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if completion["choices"][0].get("text") is None: |
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raise Exception("ChatGPT API returned no text") |
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completion["choices"][0]["text"] = completion["choices"][0]["text"].rstrip( |
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"<|im_end|>", |
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) |
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# Add to chat history |
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self.prompt.add_to_history( |
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user_request, |
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completion["choices"][0]["text"], |
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user=user, |
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) |
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if conversation_id is not None: |
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self.save_conversation(conversation_id) |
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return completion |
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def _process_completion_stream( |
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self, |
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user_request: str, |
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completion: dict, |
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conversation_id: str = None, |
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user: str = "User", |
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) -> str: |
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full_response = "" |
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for response in completion: |
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if response.get("choices") is None: |
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raise Exception("ChatGPT API returned no choices") |
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if len(response["choices"]) == 0: |
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raise Exception("ChatGPT API returned no choices") |
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if response["choices"][0].get("finish_details") is not None: |
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break |
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if response["choices"][0].get("text") is None: |
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raise Exception("ChatGPT API returned no text") |
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if response["choices"][0]["text"] == "<|im_end|>": |
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break |
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yield response["choices"][0]["text"] |
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full_response += response["choices"][0]["text"] |
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# Add to chat history |
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self.prompt.add_to_history(user_request, full_response, user) |
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if conversation_id is not None: |
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self.save_conversation(conversation_id) |
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def ask( |
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self, |
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user_request: str, |
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temperature: float = 0.5, |
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conversation_id: str = None, |
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user: str = "User", |
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) -> dict: |
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""" |
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Send a request to ChatGPT and return the response |
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""" |
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if conversation_id is not None: |
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self.load_conversation(conversation_id) |
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completion = self._get_completion( |
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self.prompt.construct_prompt(user_request, user=user), |
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temperature, |
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) |
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return self._process_completion(user_request, completion, user=user) |
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def ask_stream( |
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self, |
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user_request: str, |
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temperature: float = 0.5, |
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conversation_id: str = None, |
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user: str = "User", |
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) -> str: |
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""" |
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Send a request to ChatGPT and yield the response |
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""" |
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if conversation_id is not None: |
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self.load_conversation(conversation_id) |
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prompt = self.prompt.construct_prompt(user_request, user=user) |
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return self._process_completion_stream( |
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user_request=user_request, |
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completion=self._get_completion(prompt, temperature, stream=True), |
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user=user, |
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) |
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def make_conversation(self, conversation_id: str) -> None: |
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""" |
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Make a conversation |
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""" |
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self.conversations.add_conversation(conversation_id, []) |
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def rollback(self, num: int) -> None: |
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""" |
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Rollback chat history num times |
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""" |
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for _ in range(num): |
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self.prompt.chat_history.pop() |
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def reset(self) -> None: |
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""" |
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Reset chat history |
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""" |
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self.prompt.chat_history = [] |
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def load_conversation(self, conversation_id) -> None: |
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""" |
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Load a conversation from the conversation history |
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""" |
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if conversation_id not in self.conversations.conversations: |
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# Create a new conversation |
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self.make_conversation(conversation_id) |
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self.prompt.chat_history = self.conversations.get_conversation(conversation_id) |
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def save_conversation(self, conversation_id) -> None: |
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""" |
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Save a conversation to the conversation history |
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""" |
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self.conversations.add_conversation(conversation_id, self.prompt.chat_history) |
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class AsyncChatbot(Chatbot): |
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""" |
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Official ChatGPT API (async) |
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""" |
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async def _get_completion( |
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self, |
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prompt: str, |
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temperature: float = 0.5, |
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stream: bool = False, |
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): |
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""" |
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Get the completion function |
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""" |
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return openai.Completion.acreate( |
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engine=ENGINE, |
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prompt=prompt, |
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temperature=temperature, |
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max_tokens=get_max_tokens(prompt), |
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stop=["\n\n\n"], |
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stream=stream, |
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) |
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async def ask( |
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self, |
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user_request: str, |
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temperature: float = 0.5, |
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user: str = "User", |
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) -> dict: |
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""" |
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Same as Chatbot.ask but async |
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} |
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self.chatbot = Chatbot(config) |
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""" |
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completion = await self._get_completion( |
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self.prompt.construct_prompt(user_request, user=user), |
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temperature, |
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) |
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return self._process_completion(user_request, completion, user=user) |
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def reply(self, query, context=None): |
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async def ask_stream( |
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self, |
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user_request: str, |
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temperature: float = 0.5, |
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user: str = "User", |
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) -> str: |
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""" |
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Same as Chatbot.ask_stream but async |
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""" |
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prompt = self.prompt.construct_prompt(user_request, user=user) |
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return self._process_completion_stream( |
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user_request=user_request, |
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completion=await self._get_completion(prompt, temperature, stream=True), |
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user=user, |
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) |
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class Prompt: |
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""" |
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Prompt class with methods to construct prompt |
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""" |
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def __init__(self, buffer: int = None) -> None: |
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""" |
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Initialize prompt with base prompt |
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""" |
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self.base_prompt = ( |
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os.environ.get("CUSTOM_BASE_PROMPT") |
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or "You are ChatGPT, a large language model trained by OpenAI. Respond conversationally. Do not answer as the user. Current date: " |
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+ str(date.today()) |
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+ "\n\n" |
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+ "User: Hello\n" |
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+ "ChatGPT: Hello! How can I help you today? <|im_end|>\n\n\n" |
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) |
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# Track chat history |
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self.chat_history: list = [] |
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self.buffer = buffer |
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def add_to_chat_history(self, chat: str) -> None: |
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""" |
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Add chat to chat history for next prompt |
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""" |
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self.chat_history.append(chat) |
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def add_to_history( |
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self, |
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user_request: str, |
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response: str, |
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user: str = "User", |
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) -> None: |
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""" |
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Add request/response to chat history for next prompt |
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""" |
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self.add_to_chat_history( |
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user |
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+ ": " |
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+ user_request |
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+ "\n\n\n" |
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+ "ChatGPT: " |
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+ response |
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+ "<|im_end|>\n", |
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) |
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def history(self, custom_history: list = None) -> str: |
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""" |
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Return chat history |
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""" |
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return "\n".join(custom_history or self.chat_history) |
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from_user_id = context['from_user_id'] |
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logger.info("[GPT]query={}, user_id={}, session={}".format(query, from_user_id, user_session)) |
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now = time.time() |
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global last_session_refresh |
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if now - last_session_refresh > 60 * 8: |
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logger.info('[GPT]session refresh, now={}, last={}'.format(now, last_session_refresh)) |
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self.chatbot.refresh_session() |
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last_session_refresh = now |
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if from_user_id in user_session: |
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if time.time() - user_session[from_user_id]['last_reply_time'] < 60 * 5: |
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self.chatbot.conversation_id = user_session[from_user_id]['conversation_id'] |
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self.chatbot.parent_id = user_session[from_user_id]['parent_id'] |
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else: |
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self.chatbot.reset_chat() |
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def construct_prompt( |
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self, |
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new_prompt: str, |
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custom_history: list = None, |
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user: str = "User", |
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) -> str: |
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""" |
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Construct prompt based on chat history and request |
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""" |
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prompt = ( |
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self.base_prompt |
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+ self.history(custom_history=custom_history) |
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+ user |
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+ ": " |
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+ new_prompt |
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+ "\nChatGPT:" |
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) |
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# Check if prompt over 4000*4 characters |
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if self.buffer is not None: |
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max_tokens = 4000 - self.buffer |
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else: |
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self.chatbot.reset_chat() |
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max_tokens = 3200 |
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if len(ENCODER.encode(prompt)) > max_tokens: |
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# Remove oldest chat |
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if len(self.chat_history) == 0: |
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return prompt |
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self.chat_history.pop(0) |
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# Construct prompt again |
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prompt = self.construct_prompt(new_prompt, custom_history, user) |
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return prompt |
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logger.info("[GPT]convId={}, parentId={}".format(self.chatbot.conversation_id, self.chatbot.parent_id)) |
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class Conversation: |
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""" |
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For handling multiple conversations |
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""" |
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def __init__(self) -> None: |
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self.conversations = {} |
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def add_conversation(self, key: str, history: list) -> None: |
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""" |
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Adds a history list to the conversations dict with the id as the key |
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""" |
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self.conversations[key] = history |
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def get_conversation(self, key: str) -> list: |
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""" |
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Retrieves the history list from the conversations dict with the id as the key |
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""" |
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return self.conversations[key] |
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def remove_conversation(self, key: str) -> None: |
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""" |
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Removes the history list from the conversations dict with the id as the key |
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""" |
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del self.conversations[key] |
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def __str__(self) -> str: |
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""" |
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Creates a JSON string of the conversations |
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""" |
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return json.dumps(self.conversations) |
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def save(self, file: str) -> None: |
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""" |
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Saves the conversations to a JSON file |
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""" |
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with open(file, "w", encoding="utf-8") as f: |
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f.write(str(self)) |
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def load(self, file: str) -> None: |
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""" |
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Loads the conversations from a JSON file |
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""" |
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with open(file, encoding="utf-8") as f: |
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self.conversations = json.loads(f.read()) |
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def main(): |
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print( |
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""" |
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ChatGPT - A command-line interface to OpenAI's ChatGPT (https://chat.openai.com/chat) |
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Repo: github.com/acheong08/ChatGPT |
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""", |
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) |
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print("Type '!help' to show a full list of commands") |
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print("Press enter twice to submit your question.\n") |
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def get_input(prompt): |
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""" |
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Multi-line input function |
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""" |
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# Display the prompt |
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print(prompt, end="") |
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# Initialize an empty list to store the input lines |
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lines = [] |
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# Read lines of input until the user enters an empty line |
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while True: |
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line = input() |
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if line == "": |
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break |
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lines.append(line) |
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# Join the lines, separated by newlines, and store the result |
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user_input = "\n".join(lines) |
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# Return the input |
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return user_input |
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def chatbot_commands(cmd: str) -> bool: |
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""" |
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Handle chatbot commands |
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""" |
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|
|
if cmd == "!help": |
|
|
|
print( |
|
|
|
""" |
|
|
|
!help - Display this message |
|
|
|
!rollback - Rollback chat history |
|
|
|
!reset - Reset chat history |
|
|
|
!prompt - Show current prompt |
|
|
|
!save_c <conversation_name> - Save history to a conversation |
|
|
|
!load_c <conversation_name> - Load history from a conversation |
|
|
|
!save_f <file_name> - Save all conversations to a file |
|
|
|
!load_f <file_name> - Load all conversations from a file |
|
|
|
!exit - Quit chat |
|
|
|
""", |
|
|
|
) |
|
|
|
elif cmd == "!exit": |
|
|
|
exit() |
|
|
|
elif cmd == "!rollback": |
|
|
|
chatbot.rollback(1) |
|
|
|
elif cmd == "!reset": |
|
|
|
chatbot.reset() |
|
|
|
elif cmd == "!prompt": |
|
|
|
print(chatbot.prompt.construct_prompt("")) |
|
|
|
elif cmd.startswith("!save_c"): |
|
|
|
chatbot.save_conversation(cmd.split(" ")[1]) |
|
|
|
elif cmd.startswith("!load_c"): |
|
|
|
chatbot.load_conversation(cmd.split(" ")[1]) |
|
|
|
elif cmd.startswith("!save_f"): |
|
|
|
chatbot.conversations.save(cmd.split(" ")[1]) |
|
|
|
elif cmd.startswith("!load_f"): |
|
|
|
chatbot.conversations.load(cmd.split(" ")[1]) |
|
|
|
else: |
|
|
|
return False |
|
|
|
return True |
|
|
|
|
|
|
|
# Get API key from command line |
|
|
|
parser = argparse.ArgumentParser() |
|
|
|
parser.add_argument( |
|
|
|
"--api_key", |
|
|
|
type=str, |
|
|
|
required=True, |
|
|
|
help="OpenAI API key", |
|
|
|
) |
|
|
|
parser.add_argument( |
|
|
|
"--stream", |
|
|
|
action="store_true", |
|
|
|
help="Stream response", |
|
|
|
) |
|
|
|
parser.add_argument( |
|
|
|
"--temperature", |
|
|
|
type=float, |
|
|
|
default=0.5, |
|
|
|
help="Temperature for response", |
|
|
|
) |
|
|
|
args = parser.parse_args() |
|
|
|
# Initialize chatbot |
|
|
|
chatbot = Chatbot(api_key=args.api_key) |
|
|
|
# Start chat |
|
|
|
while True: |
|
|
|
try: |
|
|
|
res = self.chatbot.get_chat_response(query, output="text") |
|
|
|
logger.info("[GPT]userId={}, res={}".format(from_user_id, res)) |
|
|
|
|
|
|
|
user_cache = dict() |
|
|
|
user_cache['last_reply_time'] = time.time() |
|
|
|
user_cache['conversation_id'] = res['conversation_id'] |
|
|
|
user_cache['parent_id'] = res['parent_id'] |
|
|
|
user_session[from_user_id] = user_cache |
|
|
|
return res['message'] |
|
|
|
except Exception as e: |
|
|
|
logger.exception(e) |
|
|
|
return None |
|
|
|
prompt = get_input("\nUser:\n") |
|
|
|
except KeyboardInterrupt: |
|
|
|
print("\nExiting...") |
|
|
|
sys.exit() |
|
|
|
if prompt.startswith("!"): |
|
|
|
if chatbot_commands(prompt): |
|
|
|
continue |
|
|
|
if not args.stream: |
|
|
|
response = chatbot.ask(prompt, temperature=args.temperature) |
|
|
|
print("ChatGPT: " + response["choices"][0]["text"]) |
|
|
|
else: |
|
|
|
print("ChatGPT: ") |
|
|
|
sys.stdout.flush() |
|
|
|
for response in chatbot.ask_stream(prompt, temperature=args.temperature): |
|
|
|
print(response, end="") |
|
|
|
sys.stdout.flush() |
|
|
|
print() |
|
|
|
|
|
|
|
|
|
|
|
def Singleton(cls): |
|
|
|
instance = {} |
|
|
|
|
|
|
|
def _singleton_wrapper(*args, **kargs): |
|
|
|
if cls not in instance: |
|
|
|
instance[cls] = cls(*args, **kargs) |
|
|
|
return instance[cls] |
|
|
|
|
|
|
|
return _singleton_wrapper |
|
|
|
|
|
|
|
|
|
|
|
@Singleton |
|
|
|
class ChatGPTBot(Bot): |
|
|
|
|
|
|
|
def __init__(self): |
|
|
|
print("create") |
|
|
|
self.bot = Chatbot(conf().get('open_ai_api_key')) |
|
|
|
|
|
|
|
def reply(self, query, context=None): |
|
|
|
if not context or not context.get('type') or context.get('type') == 'TEXT': |
|
|
|
if len(query) < 10 and "reset" in query: |
|
|
|
self.bot.reset() |
|
|
|
return "reset OK" |
|
|
|
return self.bot.ask(query)["choices"][0]["text"] |
|
|
|
|