Accelcorp is a comprehensive web application designed to assist farmers and veterinarians with crop management and animal health. The application consists of two main components: a crop analysis tool and the Vaidya AI for animal disease information.
ACCELCORP.mp4
- Users can input market trends for various crops
- Farmers can provide location, soil type, and desired crop
- The system analyzes the data and provides:
- Probability of success
- Detailed crop-specific information
- Environmental impact assessment
- Economic projections
- Focused on animal health and diseases
- Users can input a disease name
- The AI utilizes Large Language Models (LLM) to provide:
- Detailed information about the disease
- Source references, including book titles and page numbers
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Clone the repository:
git clone https://github.com/yourusername/accelcorp.git cd accelcorp -
Start the frontend:
cd frontend yarn yarn dev -
Start the backend:
cd backend yarn npx prisma migrate dev npx prisma generate tsc -b node dist/index.js -
Run Docker (ensure Docker is installed on your system):
make sure you run postgres image in the docker container and add a connection url in .env -
Update .env
add VITE_GEMINI_API_KEY -
Set up and run Vaidya AI:
cd Vaidya python ingest.py python app.py
We welcome contributions to Accelcorp! Please read our CONTRIBUTING.md file for details on our code of conduct and the process for submitting pull requests.
This project is licensed under the MIT License - see the LICENSE.md file for details.