Educational Library Bot

This project provides a Python chatbot built with Langchain, Chainlit, AWS Bedrock (Amazon Titan Embeddings G1 - Text and Anthropic's Claude LLM) to interact with users about educational resources.

Prerequisites

• Python 3.12.1 (or a compatible version): This project requires a specific Python version to ensure compatibility with its dependencies. You can check your Python version by running python --version or python3 --version in your terminal. If you don't have the correct version, download it from https://www.python.org/downloads/.
• virtualenv tool: It helps isolate project dependencies. Install it using pip install virtualenv if you haven't already.

Getting Started

This section provides instructions on how to set up the project's environment to run smoothly.

1. Clone the Repository:

   Before setting up the environment, clone this repository from GitHub using the following command:

   git clone https://github.com/i-do-dev/educational-bot

   This will clone the repository into a local directory named educational-bot. You can change this name if you prefer.

2. Change Directory:

   Navigate into the project directory using the following command:

   cd educational-bot

Setting Up the Environment

1. Create a Virtual Environment:

   1. Open your terminal and navigate to your project directory (where you cloned the repository).

   2. Create a virtual environment named venv (you can choose any name) using the following command:

      virtualenv venv

   3. Activate the virtual environment:

      • Windows:

        venv\Scripts\activate.bat

      • macOS/Linux:

        source venv/bin/activate

      The terminal prompt should change to indicate that the virtual environment is active (usually prefixed with the environment name).

2. Install Dependencies

   (Optional) Environment Variables: The project might utilize environment variables stored in a .env file. If a file named .env-sample exists, copy it to .env and update the values according to the instructions within the .env-sample file. These variables might be essential for the project's functionality.

   Now that the virtual environment is activated, install the required packages listed in the requirements.txt file using the following command:

   pip install -r requirements.txt

   This will download and install all the necessary Python packages for your project within the isolated virtual environment.

3. Verify Installation

   (Optional) After installation, you can try running a simple script from your project to ensure everything is set up correctly.

Running the Chatbot

1. Indexing Data

   In order to index the data you will run following script:

   python index.py

2. Start the Bot:

   Once you've completed the setup steps, you can start the chatbot using the following command:

   chainlit run chat.py --port 80

   This command instructs Chainlit to run the specified Python script (chat.py) and exposes it on port 80 (you can change the port number if needed).

   This will launch your chatbot in a web interface accessible from any web browser on your machine by visiting http://localhost:80 (or the port you specified).

By following these steps, you'll have a properly configured environment to run this Python chatbot project using Python 3.12.1 (or a compatible version) and its dependencies isolated within the virtual environment. You can then launch the chatbot using the provided command.