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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.

by read2 min views2 publishedOct 12, 2026

Submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass

Built in collaboration with @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, 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

Collaborator Submission Post: Check out Dhwanan's Post 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.

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