AI ChatBot

A simple AI ChatBot built with FastAPI as the backend and Streamlit as the frontend. This project uses Python 3.11 and integrates with Groq, OpenAI, and Tavily APIs. Sensitive API keys are stored securely in a .env file.

Overview

• Backend: FastAPI application deployed on Render.
• Frontend: Streamlit app hosted on Streamlit Community Cloud.
• API Keys: Managed using a .env file (not tracked in source control).

Features

• Chat Endpoint: FastAPI handles chat requests at the /chat endpoint.
• Interactive Frontend: Streamlit UI for chatting with the AI agent.
• API Integrations: Supports Groq, OpenAI, and Tavily APIs.
• Secure Configuration: All API keys and secrets are stored in a .env file.

Live Demo

Try out the AI ChatBot frontend hosted on Streamlit Community Cloud:

View Demo

Quick Start

Local Setup

1. Clone the Repository:

   git clone https://github.com/your-username/AI_ChatBot.git
   cd AI_ChatBot

2. Create and Activate a Virtual Environment:

   python -m venv venv
   source venv/bin/activate   # On Windows: venv\Scripts\activate

3. Install Dependencies:

   pip install -r requirements.txt

4. Configure Environment Variables:

   Create a .env file in the project root and add your API keys:

   GROQ_API_KEY="your_groq_api_key"
   OPENAI_API_KEY="your_openai_api_key"
   TAVILY_API_KEY="your_tavily_api_key"

5. Run the Backend Locally:

   Navigate to the folder containing backend.py (if needed, adjust your commands according to your project layout):

   uvicorn backend:app --host 127.0.0.1 --port 9999

6. Run the Frontend Locally:

   In the project root, run:

   streamlit run frontend.py

   Make sure the API_URL in your frontend.py points to your local backend (e.g., http://127.0.0.1:9999/chat).

Deployment

Deploying the Backend on Render

1. Repository Setup:

   • Push your project to GitHub.
   • In Render’s dashboard, create a new web service.
   • Set the Root Directory to the folder that contains your backend.py (if needed).

2. Configure Build & Start Commands:

   • Build Command:

     pip install -r requirements.txt

   • Start Command:

     uvicorn backend:app --host 0.0.0.0 --port $PORT

3. Environment Variables:

   • Add your API keys in the Render dashboard using the environment variable settings (or upload them via your .env file using Render's secret files feature).

4. Deploy:

   Once configured, trigger a deploy. Your backend will be available at a public URL (e.g., https://your-backend.onrender.com/chat).

Deploying the Frontend on Streamlit Community Cloud

1. Push Your Code to GitHub:
   Ensure that the repository (or a branch) containing frontend.py is available.

2. Create a New App on Streamlit Cloud:

   • Connect your GitHub repository.
   • Set up any necessary secrets using Streamlit's secrets management (if needed).

3. Update API URL:

   • In frontend.py, update API_URL to point to your deployed backend URL (e.g., https://your-backend.onrender.com/chat).

4. Deploy:

   Your Streamlit app will automatically build and deploy on the community cloud.