This is a submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass
In modern software engineering, developers spend prolonged hours tethered to terminal output and high-luminance displays.
VerdantAI is an edge-native, open-source agronomy and ecological companion engineered around a single design objective: minimize digital interface duration and transition computational workflows into physical horticultural stewardship.
gemma2:2b, gemma2:9b), OpenAI-compatible vLLM endpoints, or offline edge heuristics.
The complete source code is released under the MIT License and hosted on GitHub:
Decentralized botanical intelligence designed to minimize screen dependency and facilitate offline horticultural stewardship.
Developed for the Hacktoberfest 2026 Open-Source AI Challenge (Week 1: Touch Grass).
Modern software development often leads to prolonged screen exposure and disconnection from physical ecosystems. VerdantAI is an edge-native, open-source agronomy platform engineered with a strict design constraint: minimize interface latency and compute duration to direct the user back to hands-on agricultural and ecological engagement.
Powered by Google's Gemma 2 open-weight model family and client-side botanical heuristics, VerdantAI provides localized agronomic guidance, specimen diagnostics, and field protocols without requiring continuous cloud connectivity or proprietary API tokens.
Calculates frost probability intervals, vernalization thresholds, and optimal sowing calendars across multiple global agricultural zones (Zone 5-11, South Asian plain agro-climates). All computations execute deterministically in the client…
bash
git clone https://github.com/Kunal-CodeLab/verdant-ai.git
cd verdant-ai