AgroBot is an AI-powered chatbot designed to assist users with agriculture-related queries. Built using the RAG (Retrieval-Augmented Generation) technology, AgroBot combines advanced natural language processing with a rich database of agricultural knowledge to provide accurate, context-aware, and up-to-date information to farmers, researchers, and enthusiasts.
- Real-Time Answers: Get instant responses to agricultural questions.
- Context-Aware Responses: Powered by RAG technology, AgroBot retrieves relevant information from a pre-trained knowledge base and generates precise answers.
- Wide Coverage: Covers topics such as crop cultivation, pest management, soil health, irrigation, climate adaptation, agricultural technologies, and more.
- User-Friendly Interface: Simple and intuitive to use for individuals of all technical skill levels.
- User Input: Users ask a question related to agriculture.
- Retrieval: The RAG model searches a curated database of agricultural knowledge for the most relevant information.
- Generation: Using the retrieved data, AgroBot generates a detailed and user-friendly response.
- Response Delivery: The answer is delivered in real-time, ensuring users can act quickly.
- Farmers seeking guidance on crop management.
- Researchers exploring agricultural trends and data.
- Hobbyists and gardeners looking for tips on plant care.
- Organizations aiming to educate and support rural communities.
- Start the application.
- Interact with AgroBot by typing in your questions about agriculture.
- Receive detailed and actionable responses in real-time.
- Publish base version: only chatbot without RAG on streamline.
- Add RAG functionalities.
- Track performances with langfuse.
- Implement Hybrid RAG with Knowledge Graph Integration: • Develop a knowledge graph for structured agricultural data (crops, diseases, treatments). • Maintain vector embeddings for detailed agricultural documents. • Combine both approaches for enhanced query responses.
- Add more docs related to agricultural crops, with initial focus on grape cultivation: • Comprehensive information on grape varieties, growing conditions, and vineyard management. • Disease identification and treatment specific to viticulture. • Harvesting and post-harvest handling best practices.
- Track performances with beta testers.
- Publish online.
- Add support for voice input/output.
- Expand the knowledge base to include more regional and crop-specific data.
- Integrate with IoT devices for real-time field monitoring.
- Enable multi-language support for global accessibility.
- Add tools for drone integration: • Enable the chatbot to generate and optimize ArduPilot-compatible missions. • Leverage drones for specific tasks such as field surveys, monitoring crop health, or delivering targeted interventions based on user requests.
Contributions are welcome! Please follow these steps:
- Fork the repository.
- Create a new branch:
git checkout -b feature-name
- Make your changes and commit them:
git commit -m "Add feature name" - Push to your branch:
git push origin feature-name
- Create a pull request on the main repository.
This project is licensed under the Apache 2.0 License. See the LICENSE file for more details.
For questions or feedback, please contact:
- Email: support@agrobot.com
- GitHub: SaroAntonelloLovito