mirror of
https://github.com/zhayujie/chatgpt-on-wechat.git
synced 2026-03-02 16:29:20 +08:00
512 lines
15 KiB
Python
512 lines
15 KiB
Python
"""
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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 config import conf
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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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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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"""
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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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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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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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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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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":
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print(
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"""
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!help - Display this message
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!rollback - Rollback chat history
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!reset - Reset chat history
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!prompt - Show current prompt
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!save_c <conversation_name> - Save history to a conversation
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!load_c <conversation_name> - Load history from a conversation
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!save_f <file_name> - Save all conversations to a file
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!load_f <file_name> - Load all conversations from a file
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!exit - Quit chat
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""",
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)
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elif cmd == "!exit":
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exit()
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elif cmd == "!rollback":
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chatbot.rollback(1)
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elif cmd == "!reset":
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chatbot.reset()
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elif cmd == "!prompt":
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print(chatbot.prompt.construct_prompt(""))
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elif cmd.startswith("!save_c"):
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chatbot.save_conversation(cmd.split(" ")[1])
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elif cmd.startswith("!load_c"):
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chatbot.load_conversation(cmd.split(" ")[1])
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elif cmd.startswith("!save_f"):
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chatbot.conversations.save(cmd.split(" ")[1])
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elif cmd.startswith("!load_f"):
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chatbot.conversations.load(cmd.split(" ")[1])
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else:
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return False
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return True
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# Get API key from command line
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parser = argparse.ArgumentParser()
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parser.add_argument(
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"--api_key",
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type=str,
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required=True,
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help="OpenAI API key",
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)
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parser.add_argument(
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"--stream",
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action="store_true",
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help="Stream response",
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)
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parser.add_argument(
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"--temperature",
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type=float,
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default=0.5,
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help="Temperature for response",
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)
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args = parser.parse_args()
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# Initialize chatbot
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chatbot = Chatbot(api_key=args.api_key)
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# Start chat
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while True:
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try:
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prompt = get_input("\nUser:\n")
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except KeyboardInterrupt:
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print("\nExiting...")
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sys.exit()
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if prompt.startswith("!"):
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if chatbot_commands(prompt):
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continue
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if not args.stream:
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response = chatbot.ask(prompt, temperature=args.temperature)
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print("ChatGPT: " + response["choices"][0]["text"])
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else:
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print("ChatGPT: ")
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sys.stdout.flush()
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for response in chatbot.ask_stream(prompt, temperature=args.temperature):
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print(response, end="")
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sys.stdout.flush()
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print()
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def Singleton(cls):
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instance = {}
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def _singleton_wrapper(*args, **kargs):
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if cls not in instance:
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instance[cls] = cls(*args, **kargs)
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return instance[cls]
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return _singleton_wrapper
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@Singleton
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class ChatGPTBot(Bot):
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def __init__(self):
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print("create")
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self.bot = Chatbot(conf().get('open_ai_api_key'))
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def reply(self, query, context=None):
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if not context or not context.get('type') or context.get('type') == 'TEXT':
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if len(query) < 10 and "reset" in query:
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self.bot.reset()
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return "reset OK"
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return self.bot.ask(query)["choices"][0]["text"]
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