AI Chatbot - ReadMe

Overview

This is a simple AI chatbot using Streamlit and Groq's LLM (Llama3-70b-8192). It maintains a chat history and generates responses to user queries using AI.

Prerequisites

Ensure you have the following installed:

• Python (>=3.8)
• Required Python libraries: os, dotenv, langchain_groq, streamlit

Installation & Setup

1. Clone the repository (if applicable)

   git clone https://github.com/BLUERAY94/yt_AI_ChatBot.git
   cd yt_AI_ChatBot

2. Install dependencies

   pip install -r requirements.txt

3. Set up environment variables

   • Create a .env file in the project root.
   • Add the following line and replace your_groq_api_key with your actual key:

     GROQ_API_KEY=your_groq_api_key

Running the Application

1. Open a terminal and navigate to the project directory.
2. Run the Streamlit app:

   streamlit run chatbot.py.py

Key Features

• Loads Groq API Key from .env file.
• Uses Llama3-70b-8192 model with temperature 0.
• Displays user input and chatbot responses in a chat interface.
• Maintains chat history throughout the session.

Basic Flow

1. Load API Key: The .env file is read to set the Groq API key.
2. Initialize LLM: Creates a chatbot object using ChatGroq.
3. Display UI: Uses Streamlit to create an interactive chat interface.
4. Chat Processing:
   • Stores user input in session history.
   • Prepares a prompt with a system instruction.
   • Sends the query to the AI model.
   • Displays and stores the AI response.

Notes

• Ensure a valid API key is provided.
• This chatbot is a basic implementation and can be further enhanced.