Plant Your Planet | geospatial & temporal analytical guide

A developer and collaborator @dkb73 built PlantMyPlanet, an open-source garden planning app that fetches real-time soil and climate data for a pinned location, matches it against 2,568 crops in the FAO EcoCrop dataset, and generates stage-by-stage care checklists. The FastAPI backend integrates Open-Meteo and NASA POWER weather APIs, while a contextual chat advisor powered by open-weight Google Gemma models via OpenRouter injects planting-specific context such as crop type, growth stage and pending tasks. If no API key is provided, the app falls back to a deterministic agronomic timeline.

Submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass Built in collaboration with @dkb73 https://dev.to/dkb73 PlantMyPlanet is an open-source, hyper-local garden planning application that starts with the ground under your feet instead of relying on a generic plant catalog. When a user drops a pin on the map, the application fetches real-time soil composition and climate parameters for those exact coordinates, matches them against $2,568$ crops in the FAO EcoCrop dataset, and generates a stage-by-stage outdoor care checklist accompanied by an AI chat advisor tied directly to that specific planting instance. Working alongside @dkb73 https://dev.to/dkb73 , my primary responsibilities centered around the FastAPI backend architecture, weather API integration, frontend user interface, and the LLM chat advisor system : FastAPI Backend Architecture: Designed and built the asynchronous FastAPI endpoints that coordinate requests, manage planting sessions, and handle data flow between the user interface, database, and external services. Weather API Integration: Built the integration with Open-Meteo and NASA POWER to pull live climate metrics, elevation, solar radiation, and $16$-day local weather forecasts dynamically based on user-selected coordinates. Frontend UI & Interactive Experience: Created the responsive user interface HTML/JS allowing users to drop a location pin, view suitabilities across crops, select planting scales, and track their garden progress stage-by-stage. Contextual LLM Chat Advisor: Developed the interactive chat system powered by open-weight models Google Gemma via OpenRouter . The prompt dynamically injects the specific planting context—crop type, days in the ground, current growth stage, pending tasks, and recent garden field notes—to deliver grounded, actionable advice. Backend: Python, FastAPI, Asyncio Frontend: HTML5, CSS3, JavaScript Weather & Climate APIs: Open-Meteo API, NASA POWER API AI Chat & Models: Google Gemma google/gemma-4-31b-it:free , google/gemma-4-26b-a4b-it:free , NVIDIA Nemotron, Liquid LFM via OpenRouter Database: PostgreSQL 16 FAO EcoCrop catalog GitHub Repository: github.com/dkb73/plantTheplanet https://github.com/dkb73/plantTheplanet Collaborator Submission Post: Check out Dhwanan's Post https://dev.to/dkb73 for full project architecture breakdown and additional screenshots. docker compose up -d python db/ingest ecocrop.py uvicorn app.main:app --host 0.0.0.0 --port 8000 --reload By combining transparent, public weather and environmental data with swappable open-weight models like Google Gemma , PlantMyPlanet provides grounded advice without hiding its reasoning inside a closed model. If an API key is omitted, the app gracefully falls back to a deterministic agronomic timeline—ensuring that real-world gardeners always have actionable guidance.