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# Chatbot with Chat history stored in Database
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This project is a simple chatbot application built using Python, integrating a database for chat history storage and a language model service to generate responses. The chatbot can handle user messages, manage chat history, and terminate conversations upon receiving a `/stop` command.
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## Features
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- **Conversation Handling**: The bot processes user inputs and generates responses using a language model service.
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- **Database Integration**: Stores chat data (user messages and bot responses) and maintains chat history.
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- **Session Management**: Supports starting and terminating chat sessions, including proper logging of start and end times.
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- **Message Truncation**: Limits conversation history to the last few messages if the conversation exceeds a large number of entries.
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## Components
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- **`Chatbot` Class**: Core logic for handling user messages and managing the chat lifecycle.
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- **`Database` (Mocked in tests)**: Handles chat data storage (methods for inserting and retrieving data).
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- **`LLM Service` (Mocked in tests)**: Generates responses to user input based on conversation history.
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## Installation
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1. Clone the repository:
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2. Install the necessary dependencies
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```bash
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pip3 install requirements.txt
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```
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4. Run the bot or test it using `doctest`:
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```bash
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python3 -m doctest -v chatbot.py
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```
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## Usage
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1. **Create Database**: Create a databse named `ChatDB` in Mysql
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2. **Create .env**:
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```
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# Together API key
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TOGETHER_API_KEY="YOUR_API_KEY"
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# Groq API key
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GROQ_API_KEY = "YOUR_API_KEY"
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# MySQL connectionDB (if you're running locally)
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DB_USER = "<DB_USER_NAME>"
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DB_PASSWORD = "<DB_USER_NAME>"
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DB_HOST = "127.0.0.1"
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DB_NAME = "ChatDB"
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PORT = "3306"
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```
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7. **Handling Messages**: run below command to start the chat in console, you can login to your Database to check the chat history
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```python
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python3 main.py
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```
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10. **Ending the Chat**: When the user sends `/stop`, the chat will terminate and log the end of the conversation with the message 'conversation-terminated'
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## Testing
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The code includes basic `doctests` to verify the chatbot's functionality using mock services for the database and language model:
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- Run the tests:
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```bash
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python3 -m doctest -v chatbot.py
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```
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