Coffee Bot : Based on Gemini API

Overview

This repository contains a FastAPI-based application that integrates with Google's Generative AI (Gemini) model to create a conversational chatbot interface. Users can interact with the Gemini model by entering queries and receiving responses in real time.

Features

• Generative AI Integration: Uses the google.generativeai library to interact with the Gemini model.
• Customizable Parameters: Configure model parameters such as temperature, top_p, top_k, and max_output_tokens.
• Interactive Interface: Made with Vite based React, TypeScript and Tailwind.

Setup Instructions

Prerequisites for Backend

1. Python 3.X.
2. Install required Python libraries:

   pip install fastapi python-dotenv google-generativeai uvicorn

3. Obtain a Gemini API key from Google AI.

Environment Variables

Create a .env file in the root directory and add your Gemini API key:

GEMINI_API_KEY=your_api_key_here

Running the Application

1. Clone the repository:

   git clone https://github.com/your-username/gemini-chatbot.git
   cd coffeebot

2. Run the fastAPI backend:

   uvicorn main:app --host 127.0.0.1 --port 8000

3. Open the provided URL in your browser to interact with the chatbot.

4. Open another terminal and change directory for frontend:

cd frontend

npm install # to setup frontend

npm run dev # to start frontend in development mode

Configuration

The application allows customization of the model's generation configuration. Modify the following parameters in the code as needed:

• temperature: Controls the randomness of the output.
• top_p: Sets the nucleus sampling threshold.
• top_k: Limits the number of candidate tokens considered at each step.
• max_output_tokens: Maximum number of tokens in the output.

Usage

1. Start the application.
2. Enter your question in the input box and click "Enter".
3. View the AI response below the input box.

Code Structure

• app.py: The main application file containing the chatbot logic.
• .env: Environment file for storing Gemini API Key.

Error Handling

• Ensures the Gemini API key is provided. If missing, displays an error message and stops execution.
• Handles exceptions during model initialization or message processing, displaying user-friendly error messages.

Testing using Postman

Message

{
    "message": "Hello, dear Coffee Bot"
}

Response

{
    "reply": "Hello there!  How can I help you with your coffee needs today?\n"
}

Limitations

• There is no feature to save the chat history.
• Requires a valid Gemini API key to function.

Screenshots

Frontend Design

Message and Response between Coffee Bot and the user

License

This project is open-source and available under the MIT License.