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‎neural_network/chatbot/chatbot.py

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import datetime
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from typing import List, Dict, Any
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class Chatbot:
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"""
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A Chatbot class to manage chat conversations using an LLM service and a database to store chat data.
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Methods:
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- start_chat: Starts a new conversation, logs the start time.
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- handle_user_message: Processes user input and stores user message & bot response in DB.
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- end_chat: Ends the conversation and logs the end time.
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- continue_chat: Retains only the last few messages if the conversation exceeds 1000 messages.
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"""
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def __init__(self, db: Any, llm_service: Any) -> None:
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"""
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Initialize the Chatbot with a database and an LLM service.
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Parameters:
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- db: The database instance used for storing chat data.
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- llm_service: The language model service for generating responses.
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"""
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self.db = db
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self.llm_service = llm_service
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self.conversation_history: List[Dict[str, str]] = []
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self.chat_id_pk: int = None
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def start_chat(self) -> None:
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"""
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Start a new chat session and insert chat history to the database.
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"""
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start_time = datetime.datetime.now()
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is_stream = 1 # Start new conversation
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self.db.insert_chat_history(start_time, is_stream)
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self.chat_id_pk = self.db.get_latest_chat_id()
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def handle_user_message(self, user_input: str) -> str:
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"""
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Handle user input and generate a bot response.
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If the user sends '/stop', the conversation is terminated.
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Parameters:
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- user_input: The input provided by the user.
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Returns:
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- bot_response: The response generated by the bot.
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Raises:
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- ValueError: If user input is not a string or if no chat_id is available.
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Doctest:
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>>> class MockDatabase:
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... def __init__(self):
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... self.data = []
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... def insert_chat_data(self, *args, **kwargs):
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... pass
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... def insert_chat_history(self, *args, **kwargs):
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... pass
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... def get_latest_chat_id(self):
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... return 1
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...
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>>> class MockLLM:
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... def generate_response(self, conversation_history):
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... if conversation_history[-1]["content"] == "/stop":
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... return "conversation-terminated"
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... return "Mock response"
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>>> db_mock = MockDatabase()
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>>> llm_mock = MockLLM()
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>>> bot = Chatbot(db_mock, llm_mock)
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>>> bot.start_chat()
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>>> bot.handle_user_message("/stop")
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'conversation-terminated'
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>>> bot.handle_user_message("Hello!")
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'Mock response'
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"""
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if not isinstance(user_input, str):
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raise ValueError("User input must be a string.")
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if self.chat_id_pk is None:
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raise ValueError("Chat has not been started. Call start_chat() first.")
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self.conversation_history.append({"role": "user", "content": user_input})
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if user_input == "/stop":
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self.end_chat()
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return "conversation-terminated"
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else:
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bot_response = self.llm_service.generate_response(self.conversation_history)
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print(f"Bot : ",bot_response)
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self.conversation_history.append(
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{"role": "assistant", "content": bot_response}
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)
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self._store_message_in_db(user_input, bot_response)
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return bot_response
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def _store_message_in_db(self, user_input: str, bot_response: str) -> None:
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"""
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Store user input and bot response in the database.
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Parameters:
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- user_input: The message from the user.
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- bot_response: The response generated by the bot.
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Raises:
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- ValueError: If insertion into the database fails.
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"""
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try:
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self.db.insert_chat_data(self.chat_id_pk, user_input, bot_response)
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except Exception as e:
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raise ValueError(f"Failed to insert chat data: {e}")
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def end_chat(self) -> None:
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"""
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End the chat session and update the chat history in the database.
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"""
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current_time = datetime.datetime.now()
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is_stream = 2 # End of conversation
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try:
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user_input = "/stop"
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bot_response = "conversation-terminated"
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print(f"Bot : ",bot_response)
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self.db.insert_chat_data(self.chat_id_pk, user_input, bot_response)
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self.db.insert_chat_history(current_time, is_stream)
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except Exception as e:
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raise ValueError(f"Failed to update chat history: {e}")
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def continue_chat(self) -> None:
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"""
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Retain only the last few entries if the conversation exceeds 1000 messages.
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"""
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if len(self.conversation_history) > 1000:
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self.conversation_history = self.conversation_history[-3:]

‎neural_network/chatbot/db.py

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import os
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from dotenv import load_dotenv
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import mysql.connector
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from mysql.connector import MySQLConnection
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load_dotenv()
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class Database:
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"""
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A class to manage the connection to the MySQL database using configuration from environment variables.
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Attributes:
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-----------
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config : dict
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The database connection parameters like user, password, host, and database name.
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"""
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def __init__(self) -> None:
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self.config = {
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"user": os.environ.get("DB_USER"),
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"password": os.environ.get("DB_PASSWORD"),
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"host": os.environ.get("DB_HOST"),
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"database": os.environ.get("DB_NAME"),
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}
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def connect(self) -> MySQLConnection:
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"""
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Establish a connection to the MySQL database.
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Returns:
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--------
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MySQLConnection
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A connection object for interacting with the MySQL database.
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Raises:
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-------
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mysql.connector.Error
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If the connection to the database fails.
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"""
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return mysql.connector.connect(**self.config)
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class ChatDatabase:
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"""
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A class to manage chat-related database operations, such as creating tables,
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inserting chat history, and retrieving chat data.
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Attributes:
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-----------
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db : Database
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An instance of the `Database` class for establishing connections to the MySQL database.
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"""
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def __init__(self, db: Database) -> None:
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self.db = db
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def create_tables(self) -> None:
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"""
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Create the necessary tables for chat history and chat data in the database.
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If the tables already exist, they will not be created again.
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Raises:
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-------
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mysql.connector.Error
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If there is any error executing the SQL statements.
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"""
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conn = self.db.connect()
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cursor = conn.cursor()
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cursor.execute(
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"""
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CREATE TABLE IF NOT EXISTS ChatDB.Chat_history (
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chat_id INT AUTO_INCREMENT PRIMARY KEY,
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start_time DATETIME,
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is_stream INT
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)
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"""
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)
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cursor.execute(
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"""
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CREATE TABLE IF NOT EXISTS ChatDB.Chat_data (
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id INT AUTO_INCREMENT PRIMARY KEY,
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chat_id INT,
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user TEXT,
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assistant TEXT,
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FOREIGN KEY (chat_id) REFERENCES ChatDB.Chat_history(chat_id)
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)
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"""
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)
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cursor.execute("DROP TRIGGER IF EXISTS update_is_stream")
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cursor.execute(
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"""
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CREATE TRIGGER update_is_stream
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AFTER UPDATE ON ChatDB.Chat_history
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FOR EACH ROW
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BEGIN
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UPDATE ChatDB.Chat_data
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SET is_stream = NEW.is_stream
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WHERE chat_id = NEW.chat_id;
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END;
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"""
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)
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conn.commit()
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cursor.close()
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conn.close()
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def insert_chat_history(self, start_time: str, is_stream: int) -> None:
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"""
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Insert a new chat history record into the database.
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Parameters:
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-----------
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start_time : str
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The starting time of the chat session.
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is_stream : int
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An integer indicating whether the chat is in progress (1) or ended (2).
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Raises:
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-------
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mysql.connector.Error
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If there is any error executing the SQL statements.
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"""
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conn = self.db.connect()
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cursor = conn.cursor()
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cursor.execute(
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"""
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INSERT INTO ChatDB.Chat_history (start_time, is_stream)
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VALUES (%s, %s)
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""",
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(start_time, is_stream),
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)
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conn.commit()
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cursor.close()
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conn.close()
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def get_latest_chat_id(self) -> int:
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"""
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Retrieve the chat ID of the most recent chat session from the database.
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Returns:
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--------
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int
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The ID of the latest chat session.
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Raises:
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-------
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mysql.connector.Error
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If there is any error executing the SQL statements.
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"""
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conn = self.db.connect()
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cursor = conn.cursor()
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cursor.execute(
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"""
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SELECT chat_id FROM ChatDB.Chat_history WHERE
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chat_id=(SELECT MAX(chat_id) FROM ChatDB.Chat_history)
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"""
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)
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chat_id_pk = cursor.fetchone()[0]
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cursor.close()
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conn.close()
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return chat_id_pk
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def insert_chat_data(
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self, chat_id: int, user_message: str, assistant_message: str
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) -> None:
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"""
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Insert a new chat data record into the database.
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Parameters:
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-----------
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chat_id : int
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The ID of the chat session to which this data belongs.
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user_message : str
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The message provided by the user in the chat session.
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assistant_message : str
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The response from the assistant in the chat session.
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Raises:
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-------
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mysql.connector.Error
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If there is any error executing the SQL statements.
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"""
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conn = self.db.connect()
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cursor = conn.cursor()
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cursor.execute(
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"""
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INSERT INTO ChatDB.Chat_data (chat_id, user, assistant)
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VALUES (%s, %s, %s)
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""",
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(chat_id, user_message, assistant_message),
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)
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conn.commit()
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cursor.close()
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conn.close()

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