Gemma CogniVault

Mon, 25 May 2026 00:00:00 +0000

Overview

Gemma CogniVault is a 100% local, privacy-first AI study companion. Your documents stay on your hardware. Inference runs via Ollama on localhost. No telemetry, no embeddings sent to third parties, no exceptions. A live Privacy Vault Audit Panel confirms zero external connections at runtime.

It’s also genuinely capable — Gemma 4’s full surface (completion, vision, tools, reasoning) running on your laptop, wrapped in an app that turns your documents into quizzes, multi-lesson workshops, flashcard decks, and visual mindmaps, with a learning-progress dashboard and 25 achievement badges.

What’s inside

Layer	Technology
LLM & Embeddings	Ollama · `gemma4:e4b` · `embeddinggemma`
Agent Framework	Strands Agents SDK
Backend	FastAPI · Python 3.10+ · Pydantic
Vector Search	FAISS IndexFlatIP + BM25Okapi · Reciprocal Rank Fusion
Document Parsing	pypdf · python-docx · python-pptx · openpyxl · trafilatura
OCR	pytesseract · pymupdf · Pillow
Audio	faster-whisper
Workflow Engine	DBOS + PostgreSQL
Frontend	React 19 · TypeScript · Vite · Tailwind v4 · Framer Motion · TanStack Query

Four sections

Section	What it’s for
💬 Chat	Ask anything about your documents. Cited answers, scope filter, voice, attachments.
📚 Knowledge Base	Upload, categorise, and manage your documents. SHA-256 change detection on re-upload.
🎓 Study Hub	Four AI-powered study modes: Quiz · Workshop · Flashcards · Mindmaps.
📊 Dashboard	Total study time, current streak, 25 achievement badges, 90-day activity heatmap.

Highlights

🧠 Thinking Mode — collapsible reasoning panel streams Gemma 4’s chain of thought before the answer
🔍 Hybrid Retrieval — FAISS dense + BM25 keyword fused with Reciprocal Rank Fusion
🖼️ Multimodal — attach images, PDFs, and DOCX inline in chat
🛟 Durable workflows — DBOS-checkpointed ingestion; crash-safe and resumable
🏆 25 achievement badges — auto-tracked across chat, quizzes, workshops, flashcards, mindmaps
🔒 Vault Audit Panel — live “zero external connections” indicator

Writing about it

I’m publishing a series of posts unpacking the engineering decisions behind CogniVault — privacy framing, the retrieval stack, the agent loop, ingestion durability, getting JSON out of a local model, drawing mindmaps without a graph library, the gamification layer, and how the test suite avoids needing any infrastructure to run.

See the for the full series.

Try it

git clone https://github.com/ndimoforaretas/local-gemma-rag.git
cd local-gemma-rag
./scripts/setup.sh # one-time
./scripts/start.sh

Then open .