README.md

metadata

title: Mycelium
emoji: 🍄
colorFrom: red
colorTo: indigo
sdk: gradio
sdk_version: 6.16.0
python_version: '3.13'
app_file: app.py
pinned: true
license: mit
short_description: Stop losing ideas. Capture, connect, recall.
tags:
  - build-small-hackathon
  - backyard-ai
  - tiny-titan
  - nvidia-nemotron
  - off-brand
  - off-the-grid
  - field-notes
  - track:backyard
  - sponsor:nvidia
  - achievement:offgrid
  - achievement:offbrand
  - achievement:fieldnotes

Mycelium — Personal Knowledge Agent

Capture fast. Think later. Let the system surface what matters.

Mycelium is a local-first AI knowledge companion that closes the loop between saving something and actually learning from it. No more screenshot graveyards or forgotten browser tabs.

Demo

📹 Demo video

📝 LinkedIn post

📓 Field Notes — what I built, what broke, what I learned

The problem

Everyone has the same graveyard: saved links, screenshots, notes-to-self — all gone dark in a week. The capture habit exists. The recall loop doesn't.

Mycelium fixes the loop.

What it does

• Capture notes, URLs, and images — each processed into a structured summary with intent classification (learn / act / reference / ephemeral) and semantic tags
• ASK — semantic search across your knowledge base with LLM synthesis, follow-up questions, and Feynman self-testing
• BRIEF — daily digest of what you saved, with synthesis across captures and a weekly thread
• REVIEW — spaced repetition (SM-2) targeting specific claims from your own notes, not generic flashcards
• GRAPH — visual map of how your ideas connect via embedding similarity

How it works

1. You capture a note, URL, or image
2. NVIDIA Nemotron-Mini-4B extracts the core insight, classifies intent, generates tags and recall questions
3. Qwen2.5-VL-7B handles image captures — describe a whiteboard, diagram, or screenshot
4. BGE-base-en-v1.5 embeds summaries into a 768-dim vector space
5. Related captures link automatically via cosine similarity
6. The surface engine resurfaces what you should revisit, weighted by intent and time

Tech

• LLM: nvidia/Nemotron-Mini-4B-Instruct via HF Transformers + ZeroGPU
• Vision: Qwen/Qwen2.5-VL-7B-Instruct for image capture
• Embeddings: BAAI/bge-base-en-v1.5 (768-dim, top MTEB retrieval)
• Backend: FastAPI + SQLite (persistent at /data/mind.db)
• Frontend: React + TypeScript + Tailwind CSS

Prizes targeting

• Backyard AI track — practical tool solving a real daily problem
• Tiny Titan badge — Nemotron-Mini-4B drives all text intelligence (4B parameters)
• NVIDIA — built on nvidia/Nemotron-Mini-4B-Instruct

Built with

Built for the Build Small Hackathon · June 2026