LLM Agri Bot – Custom Chatbot with OpenAI & HuggingFace

A personalized chatbot for agriculture queries that integrates OpenAI GPT for text and HuggingFace for voice interactions.

Features

• Text chat – Ask any agriculture-related question.
• Voice input – Speak naturally and get responses.
• Smart responses – Powered by OpenAI’s language models.

Architecture

• Backend: Flask (Python)
• Text Model: OpenAI GPT-3.5/4 via API
• Voice Processing: HuggingFace Transformers (e.g., Wav2Vec2 for STT)
• Frontend: HTML/CSS/JS (see Sample_image/voicechat_web.png)

Prerequisites

• Python 3.8+
• OpenAI API key (get one)
• HuggingFace API token (get one)

Installation

1. Clone the repo:

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   git clone https://github.com/mohammed97ashraf/LLM_Agri_Bot.git
   cd LLM_Agri_Bot
   

2. Create a virtual environment (recommended):

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

3. Install dependencies:

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   pip install -r requirements.txt
   

4. Set up environment variables: Create a .env file in the root directory (never commit this file):

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   OPENAI_API_KEY=sk-your-openai-key
   HUGGINGFACE_API_KEY=hf_your_huggingface_token
   

Usage

1. Run the application:

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   python app.py
   

2. Open your browser and go to http://127.0.0.1:5000.

3. Type your question (e.g., "What crops grow best in loamy soil?") or click the microphone icon to speak.

Example Interactions

• User: What is the ideal pH for tomato plants? Bot: The ideal soil pH for tomatoes is between 6.0 and 6.8.
• User (voice): How to control aphids organically? Bot: Use neem oil spray or introduce ladybugs into your garden.

Troubleshooting

Project Structure

LLM_Agri_Bot/
├── app.py              # Main Flask application
├── requirements.txt    # Python dependencies
├── .env                # Environment variables (not committed)
├── Sample_image/       # Screenshots and design assets
├── README.md           # This file
├── CONTRIBUTING.md     # Contribution guidelines
└── CHANGELOG.md        # Version history

Contributing

Please read CONTRIBUTING.md for details on how to contribute.

License

This project is licensed under the MIT License – see the LICENSE file for details.

Acknowledgments

• OpenAI for language models
• HuggingFace for voice processing models
• Flask community

Future Improvements

• Complete voice input feature with real STT model integration
• Add WebSocket support for real-time streaming
• Implement user authentication
• Expand agriculture knowledge base with retrieval-augmented generation (RAG)
• Add support for multiple languages