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hyparProduction RAG you can read like a tutorial.

Open-source Nuxt 3 + pgvector reference for teams shipping RAG — and a learning track for devs starting from zero.

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What is hypar?

RAG (Retrieval-Augmented Generation) lets an AI answer questions from your own documents — but production RAG is hard: chunking strategy, hybrid retrieval, durable ingestion, citations, evals. hypar is a fully-working TypeScript reference app. Read the code like a tutorial, run it locally in minutes, adapt the patterns to your stack.

Devs learning RAGTeams shipping RAGResearchers benchmarking

Run locally

git clone https://github.com/albegosu/hypar.git
cd hypar
cp .env.example .env
# Edit .env — set GOOGLE_API_KEY at minimum
docker compose --profile full up -d --build
open http://localhost:3000
Full setup guide →

Architecture at a glance

Read the full architecture →

What's inside

Hybrid retrieval

pgvector cosine similarity combined with BM25, then MMR diversification.

Multi-provider embeddings

Gemini, OpenAI or Ollama. Switch at runtime without re-ingesting.

Durable ingestion

Workflow SDK with per-step retries; status polled, never lost on restart.

Vitest suite

Chunking, text helpers, agent commands, and search utilities covered in CI.

Source citations

Inline [1], [2] markers persisted on every assistant message and audited.

Rate limits and admin APIs

30/min chat, 10/min upload. /api/admin/* accepts a signed-in session or ADMIN_API_KEY.

Roadmap — 10 stages

View full roadmap →

01 · Now

Traceability

02 · Next

Measurable quality

03

SOTA retrieval

04

Robustness

05

Pluggable

06

Beyond text

07

Real memory

08

Knowledge graph

09

Self-hosted

10

Live product