Offline, voice-first agricultural advisor in Kinyarwanda — built for the 8GB laptop, no GPU. ADTC 2026 submission.
# Twigire AI
**An offline, voice-first agricultural advisor in Kinyarwanda, grounded in Rwanda's own extension guidance — built to run on the laptop a farmer's cooperative actually owns.**
Submission for the Africa Deep Tech Challenge 2026 — Laptop LLM Challenge, Agriculture domain.
## Overview
Twigire AI runs a quantised small language model entirely on-device (8GB RAM, integrated graphics, no discrete GPU) and answers agricultural questions grounded in real Rwanda Agriculture Board (RAB) and MINAGRI extension materials — in Kinyarwanda, by voice.
- **No internet required** after setup
- **No cloud API costs**
- **Voice in, voice out** — removes the literacy barrier
- **Grounded, not hallucinated** — RAG over real extension documents, not open-ended generation
## Problem domain
Agriculture: crop advisory for smallholder farmers and extension officers, focused initially on coffee, potato, and maize.
## Architecture
User speech (Kinyarwanda)
→ Speech-to-text
→ Query embedding + retrieval over RAB/MINAGRI corpus
→ Small quantised LLM (Gemma edge variant, GGUF Q4, llama.cpp)
→ Grounded response generation
→ Text-to-speech (Kinyarwanda)
→ Spoken answer
## Repo structure
twigire-ai/
├── corpus/ # Source extension documents + processed chunks
├── src/ # Application code
│ ├── rag_pipeline.py
│ ├── voice_io.py
│ ├── model_config.py
│ └── main.py
├── eval/ # Evaluation question set + scoring scripts
├── report/ # ADTC 2026 report template submission
├── docs/ # Screenshots, architecture diagrams
├── requirements.txt
├── LICENSE
└── README.md
## Setup
```bash
git clone
github.com
cd twigire-ai
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
```
## Status
🚧 Active development for ADTC 2026 (deadline: Aug 25, 2026).
## Team
[Your name] — Kigali, Rwanda
## License
MIT — see LICENSE
## Setup
```bash
git clone
github.com
cd twigire-ai
python3 -m venv venv
sou …