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AgriGuardAI

predicts danger for crops and give suggestions to farmers by using crop data and climate details in specific area

main functionlities

  • predicts danger for crops and give suggestions to farmers
  • expert farmer chat

Testing Account (incase you don't want to create a new account)

Email:

[email protected]

Password:

IBM_WATSON_AI

Video Demo

AgriGuardAI-demo.mp4

Full Presentation: https://youtu.be/L-3OkQVck6s

Tech Stack

Client: Next.js, TailwindCSS, Shadcn, StackAuth

Server: Next.js API, IBM Watson AI, Granite Model

Database: PostgreSQL (Neon), Drizzle ORM

Run on Local Machine

To deploy this project run:

  • change .env.example to .env.local in root
    NEXT_PUBLIC_STACK_PROJECT_ID=<your-project-id>
    NEXT_PUBLIC_STACK_PUBLISHABLE_CLIENT_KEY=<your-publishable-client-key>
    STACK_SECRET_SERVER_KEY=<your-secret-server-key>
    DRIZZLE_DATABASE_URL=<postgres-db-connection-url>
    NEXT_PUBLIC_IBM_PROJECT_ID=<project-id-from-ibm>
    NEXT_PUBLIC_IBM_MODEL_ID=<model-id-from-ibm>
    NEXT_PUBLIC_API_REQUEST_URL=<api-request-url-from-ibm>
    NEXT_PUBLIC_IBM_API_KEY=<api-key-from-ibm>

  • in drizzle.config.js change process.env.NEXT_PUBLIC_DRIZZLE_DATABASE_URL to your real database url, bcz env variables don't work in this file

  • after that run these commmands in row

  npm i
  npm run db:push
  npm run dev
  • to see and manage DB entries, run this
  npm run db:studio

Congradulations Your Local Setup is Ready