xyc0123456789
1 year ago
2 changed files with 500 additions and 44 deletions
+ 499
- 43
bot/chatgpt/chat_gpt_bot.py
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| @@ -1,55 +1,511 @@ | |||
| import time | |||
| """ | |||
| A simple wrapper for the official ChatGPT API | |||
| """ | |||
| import argparse | |||
| import json | |||
| import os | |||
| import sys | |||
| from datetime import date | |||
| import openai | |||
| import tiktoken | |||
| from bot.bot import Bot | |||
| from revChatGPT.revChatGPT import Chatbot | |||
| from common.log import logger | |||
| from config import conf | |||
| user_session = dict() | |||
| last_session_refresh = time.time() | |||
| ENGINE = os.environ.get("GPT_ENGINE") or "text-chat-davinci-002-20221122" | |||
| ENCODER = tiktoken.get_encoding("gpt2") | |||
| # ChatGPT web接口 (暂时不可用) | |||
| class ChatGPTBot(Bot): | |||
| def __init__(self): | |||
| config = { | |||
| "Authorization": "<Your Bearer Token Here>", # This is optional | |||
| "session_token": conf().get("session_token") | |||
| def get_max_tokens(prompt: str) -> int: | |||
| """ | |||
| Get the max tokens for a prompt | |||
| """ | |||
| return 4000 - len(ENCODER.encode(prompt)) | |||
| # ['text-chat-davinci-002-20221122'] | |||
| class Chatbot: | |||
| """ | |||
| Official ChatGPT API | |||
| """ | |||
| def __init__(self, api_key: str, buffer: int = None) -> None: | |||
| """ | |||
| Initialize Chatbot with API key (from https://platform.openai.com/account/api-keys) | |||
| """ | |||
| openai.api_key = api_key or os.environ.get("OPENAI_API_KEY") | |||
| self.conversations = Conversation() | |||
| self.prompt = Prompt(buffer=buffer) | |||
| def _get_completion( | |||
| self, | |||
| prompt: str, | |||
| temperature: float = 0.5, | |||
| stream: bool = False, | |||
| ): | |||
| """ | |||
| Get the completion function | |||
| """ | |||
| return openai.Completion.create( | |||
| engine=ENGINE, | |||
| prompt=prompt, | |||
| temperature=temperature, | |||
| max_tokens=get_max_tokens(prompt), | |||
| stop=["\n\n\n"], | |||
| stream=stream, | |||
| ) | |||
| def _process_completion( | |||
| self, | |||
| user_request: str, | |||
| completion: dict, | |||
| conversation_id: str = None, | |||
| user: str = "User", | |||
| ) -> dict: | |||
| if completion.get("choices") is None: | |||
| raise Exception("ChatGPT API returned no choices") | |||
| if len(completion["choices"]) == 0: | |||
| raise Exception("ChatGPT API returned no choices") | |||
| if completion["choices"][0].get("text") is None: | |||
| raise Exception("ChatGPT API returned no text") | |||
| completion["choices"][0]["text"] = completion["choices"][0]["text"].rstrip( | |||
| "<|im_end|>", | |||
| ) | |||
| # Add to chat history | |||
| self.prompt.add_to_history( | |||
| user_request, | |||
| completion["choices"][0]["text"], | |||
| user=user, | |||
| ) | |||
| if conversation_id is not None: | |||
| self.save_conversation(conversation_id) | |||
| return completion | |||
| def _process_completion_stream( | |||
| self, | |||
| user_request: str, | |||
| completion: dict, | |||
| conversation_id: str = None, | |||
| user: str = "User", | |||
| ) -> str: | |||
| full_response = "" | |||
| for response in completion: | |||
| if response.get("choices") is None: | |||
| raise Exception("ChatGPT API returned no choices") | |||
| if len(response["choices"]) == 0: | |||
| raise Exception("ChatGPT API returned no choices") | |||
| if response["choices"][0].get("finish_details") is not None: | |||
| break | |||
| if response["choices"][0].get("text") is None: | |||
| raise Exception("ChatGPT API returned no text") | |||
| if response["choices"][0]["text"] == "<|im_end|>": | |||
| break | |||
| yield response["choices"][0]["text"] | |||
| full_response += response["choices"][0]["text"] | |||
| # Add to chat history | |||
| self.prompt.add_to_history(user_request, full_response, user) | |||
| if conversation_id is not None: | |||
| self.save_conversation(conversation_id) | |||
| def ask( | |||
| self, | |||
| user_request: str, | |||
| temperature: float = 0.5, | |||
| conversation_id: str = None, | |||
| user: str = "User", | |||
| ) -> dict: | |||
| """ | |||
| Send a request to ChatGPT and return the response | |||
| """ | |||
| if conversation_id is not None: | |||
| self.load_conversation(conversation_id) | |||
| completion = self._get_completion( | |||
| self.prompt.construct_prompt(user_request, user=user), | |||
| temperature, | |||
| ) | |||
| return self._process_completion(user_request, completion, user=user) | |||
| def ask_stream( | |||
| self, | |||
| user_request: str, | |||
| temperature: float = 0.5, | |||
| conversation_id: str = None, | |||
| user: str = "User", | |||
| ) -> str: | |||
| """ | |||
| Send a request to ChatGPT and yield the response | |||
| """ | |||
| if conversation_id is not None: | |||
| self.load_conversation(conversation_id) | |||
| prompt = self.prompt.construct_prompt(user_request, user=user) | |||
| return self._process_completion_stream( | |||
| user_request=user_request, | |||
| completion=self._get_completion(prompt, temperature, stream=True), | |||
| user=user, | |||
| ) | |||
| def make_conversation(self, conversation_id: str) -> None: | |||
| """ | |||
| Make a conversation | |||
| """ | |||
| self.conversations.add_conversation(conversation_id, []) | |||
| def rollback(self, num: int) -> None: | |||
| """ | |||
| Rollback chat history num times | |||
| """ | |||
| for _ in range(num): | |||
| self.prompt.chat_history.pop() | |||
| def reset(self) -> None: | |||
| """ | |||
| Reset chat history | |||
| """ | |||
| self.prompt.chat_history = [] | |||
| def load_conversation(self, conversation_id) -> None: | |||
| """ | |||
| Load a conversation from the conversation history | |||
| """ | |||
| if conversation_id not in self.conversations.conversations: | |||
| # Create a new conversation | |||
| self.make_conversation(conversation_id) | |||
| self.prompt.chat_history = self.conversations.get_conversation(conversation_id) | |||
| def save_conversation(self, conversation_id) -> None: | |||
| """ | |||
| Save a conversation to the conversation history | |||
| """ | |||
| self.conversations.add_conversation(conversation_id, self.prompt.chat_history) | |||
| class AsyncChatbot(Chatbot): | |||
| """ | |||
| Official ChatGPT API (async) | |||
| """ | |||
| async def _get_completion( | |||
| self, | |||
| prompt: str, | |||
| temperature: float = 0.5, | |||
| stream: bool = False, | |||
| ): | |||
| """ | |||
| Get the completion function | |||
| """ | |||
| return openai.Completion.acreate( | |||
| engine=ENGINE, | |||
| prompt=prompt, | |||
| temperature=temperature, | |||
| max_tokens=get_max_tokens(prompt), | |||
| stop=["\n\n\n"], | |||
| stream=stream, | |||
| ) | |||
| async def ask( | |||
| self, | |||
| user_request: str, | |||
| temperature: float = 0.5, | |||
| user: str = "User", | |||
| ) -> dict: | |||
| """ | |||
| Same as Chatbot.ask but async | |||
| } | |||
| self.chatbot = Chatbot(config) | |||
| """ | |||
| completion = await self._get_completion( | |||
| self.prompt.construct_prompt(user_request, user=user), | |||
| temperature, | |||
| ) | |||
| return self._process_completion(user_request, completion, user=user) | |||
| def reply(self, query, context=None): | |||
| async def ask_stream( | |||
| self, | |||
| user_request: str, | |||
| temperature: float = 0.5, | |||
| user: str = "User", | |||
| ) -> str: | |||
| """ | |||
| Same as Chatbot.ask_stream but async | |||
| """ | |||
| prompt = self.prompt.construct_prompt(user_request, user=user) | |||
| return self._process_completion_stream( | |||
| user_request=user_request, | |||
| completion=await self._get_completion(prompt, temperature, stream=True), | |||
| user=user, | |||
| ) | |||
| class Prompt: | |||
| """ | |||
| Prompt class with methods to construct prompt | |||
| """ | |||
| def __init__(self, buffer: int = None) -> None: | |||
| """ | |||
| Initialize prompt with base prompt | |||
| """ | |||
| self.base_prompt = ( | |||
| os.environ.get("CUSTOM_BASE_PROMPT") | |||
| or "You are ChatGPT, a large language model trained by OpenAI. Respond conversationally. Do not answer as the user. Current date: " | |||
| + str(date.today()) | |||
| + "\n\n" | |||
| + "User: Hello\n" | |||
| + "ChatGPT: Hello! How can I help you today? <|im_end|>\n\n\n" | |||
| ) | |||
| # Track chat history | |||
| self.chat_history: list = [] | |||
| self.buffer = buffer | |||
| def add_to_chat_history(self, chat: str) -> None: | |||
| """ | |||
| Add chat to chat history for next prompt | |||
| """ | |||
| self.chat_history.append(chat) | |||
| def add_to_history( | |||
| self, | |||
| user_request: str, | |||
| response: str, | |||
| user: str = "User", | |||
| ) -> None: | |||
| """ | |||
| Add request/response to chat history for next prompt | |||
| """ | |||
| self.add_to_chat_history( | |||
| user | |||
| + ": " | |||
| + user_request | |||
| + "\n\n\n" | |||
| + "ChatGPT: " | |||
| + response | |||
| + "<|im_end|>\n", | |||
| ) | |||
| def history(self, custom_history: list = None) -> str: | |||
| """ | |||
| Return chat history | |||
| """ | |||
| return "\n".join(custom_history or self.chat_history) | |||
| from_user_id = context['from_user_id'] | |||
| logger.info("[GPT]query={}, user_id={}, session={}".format(query, from_user_id, user_session)) | |||
| now = time.time() | |||
| global last_session_refresh | |||
| if now - last_session_refresh > 60 * 8: | |||
| logger.info('[GPT]session refresh, now={}, last={}'.format(now, last_session_refresh)) | |||
| self.chatbot.refresh_session() | |||
| last_session_refresh = now | |||
| if from_user_id in user_session: | |||
| if time.time() - user_session[from_user_id]['last_reply_time'] < 60 * 5: | |||
| self.chatbot.conversation_id = user_session[from_user_id]['conversation_id'] | |||
| self.chatbot.parent_id = user_session[from_user_id]['parent_id'] | |||
| else: | |||
| self.chatbot.reset_chat() | |||
| def construct_prompt( | |||
| self, | |||
| new_prompt: str, | |||
| custom_history: list = None, | |||
| user: str = "User", | |||
| ) -> str: | |||
| """ | |||
| Construct prompt based on chat history and request | |||
| """ | |||
| prompt = ( | |||
| self.base_prompt | |||
| + self.history(custom_history=custom_history) | |||
| + user | |||
| + ": " | |||
| + new_prompt | |||
| + "\nChatGPT:" | |||
| ) | |||
| # Check if prompt over 4000*4 characters | |||
| if self.buffer is not None: | |||
| max_tokens = 4000 - self.buffer | |||
| else: | |||
| self.chatbot.reset_chat() | |||
| max_tokens = 3200 | |||
| if len(ENCODER.encode(prompt)) > max_tokens: | |||
| # Remove oldest chat | |||
| if len(self.chat_history) == 0: | |||
| return prompt | |||
| self.chat_history.pop(0) | |||
| # Construct prompt again | |||
| prompt = self.construct_prompt(new_prompt, custom_history, user) | |||
| return prompt | |||
| logger.info("[GPT]convId={}, parentId={}".format(self.chatbot.conversation_id, self.chatbot.parent_id)) | |||
| class Conversation: | |||
| """ | |||
| For handling multiple conversations | |||
| """ | |||
| def __init__(self) -> None: | |||
| self.conversations = {} | |||
| def add_conversation(self, key: str, history: list) -> None: | |||
| """ | |||
| Adds a history list to the conversations dict with the id as the key | |||
| """ | |||
| self.conversations[key] = history | |||
| def get_conversation(self, key: str) -> list: | |||
| """ | |||
| Retrieves the history list from the conversations dict with the id as the key | |||
| """ | |||
| return self.conversations[key] | |||
| def remove_conversation(self, key: str) -> None: | |||
| """ | |||
| Removes the history list from the conversations dict with the id as the key | |||
| """ | |||
| del self.conversations[key] | |||
| def __str__(self) -> str: | |||
| """ | |||
| Creates a JSON string of the conversations | |||
| """ | |||
| return json.dumps(self.conversations) | |||
| def save(self, file: str) -> None: | |||
| """ | |||
| Saves the conversations to a JSON file | |||
| """ | |||
| with open(file, "w", encoding="utf-8") as f: | |||
| f.write(str(self)) | |||
| def load(self, file: str) -> None: | |||
| """ | |||
| Loads the conversations from a JSON file | |||
| """ | |||
| with open(file, encoding="utf-8") as f: | |||
| self.conversations = json.loads(f.read()) | |||
| def main(): | |||
| print( | |||
| """ | |||
| ChatGPT - A command-line interface to OpenAI's ChatGPT (https://chat.openai.com/chat) | |||
| Repo: github.com/acheong08/ChatGPT | |||
| """, | |||
| ) | |||
| print("Type '!help' to show a full list of commands") | |||
| print("Press enter twice to submit your question.\n") | |||
| def get_input(prompt): | |||
| """ | |||
| Multi-line input function | |||
| """ | |||
| # Display the prompt | |||
| print(prompt, end="") | |||
| # Initialize an empty list to store the input lines | |||
| lines = [] | |||
| # Read lines of input until the user enters an empty line | |||
| while True: | |||
| line = input() | |||
| if line == "": | |||
| break | |||
| lines.append(line) | |||
| # Join the lines, separated by newlines, and store the result | |||
| user_input = "\n".join(lines) | |||
| # Return the input | |||
| return user_input | |||
| def chatbot_commands(cmd: str) -> bool: | |||
| """ | |||
| Handle chatbot commands | |||
| """ | |||
| 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"] | |||
+ 1
- 1
bridge/bridge.py
View File
| @@ -6,4 +6,4 @@ class Bridge(object): | |||
| pass | |||
| def fetch_reply_content(self, query, context): | |||
| return bot_factory.create_bot("openAI").reply(query, context) | |||
| return bot_factory.create_bot("chatGPT").reply(query, context) | |||
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