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supavec

supavec

The open-source alternative to Carbon.ai. Build powerful RAG applications with any data source, at any scale.

AI EngineeringGive agent knowledgeTypeScript
Open on GitHub
Momentum
+0stars in 24 hours0.0%
1.24k
Stars
115
Forks
+0
This week
4
Contributors
Created 2024-12-24 · Updated 2026-10-09 · #11013 today
Top developers
taishikatoManishKarki1997AnujKshatriya

supavec/supavec is ranked 11,013 with 1,239 stars.

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supavec/supavec is ranked 11,013 among these 8 peers; cookjohn/zotero-mcp is ranked 11,010.

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Key parameters and specifications
Key parameters and specifications
ParameterValue
LanguageTypeScript
CategoryAI Engineering
SubcategoryGive agent knowledge
KeywordsRAG
Stars1,239
Forks115
Contributors4
Created date2024-12-24
Updated date2026-10-09
Stars in 1 day0
Stars in 7 days0
Rank11,013
Previous rank10,974
Rank change-39
7-day stars rank12,850
Previous 7-day stars rank17,224
7-day stars rank change4,374
Total stars rank9,448
Previous total stars rank9,441
Total stars rank change-7
Frequently asked questions

How many stars and forks are recorded?

supavec/supavec has 1,239 stars and 115 forks.

What is the repository rank?

supavec/supavec is ranked 11,013.

What language and category are recorded?

supavec/supavec has 1,239 stars, uses TypeScript and belongs to AI Engineering.

Which repository is closest in rank?

supavec/supavec is compared with cookjohn/zotero-mcp, ranked 11,010 with 1,239 stars.

README

Supavec - The open-source alternative to Carbon.ai. Build powerful RAG applications with any data source, at any scale.

⚡ OSS RAG-as-a-Service — spin up vector search + chat API in <5 min
📈 630▲ on Product Hunt · 620⭐ on GitHub

Cloud version

https://www.supavec.com

Our simple API endpoints ✨

docs.supavec.com.

Related repositories

Built with

API docs

https://github.com/taishikato/supavec/blob/main/packages/api/README.md


Architecture & Design Philosophy

Scalable Multi-Tenant Design

  • Row-Level Security (RLS) for team-level data isolation
  • Usage‑based billing: Free 100 → Basic 750 → Ent 5000 req/mo
  • Batch embeddings: OpenAI cost -65 %

Vector Search Optimisation

  • Configurable chunk & overlap (+12 pts recall)
  • Hybrid filter (file_id + cosine) P95 210 ms

Performance & Observability

Real‑time Analytics

  • PostHog integration product & API events tracked (11 schema)
  • Request‑level tracing with unique IDs for rapid debugging
  • Async usage logging non‑blocking main flow

API Performance

  • Streaming or standard responses selectable per request
  • 100‑doc batch embedding reduces latency + cost
  • Background processing keeps critical path lean
// Example: choose streaming or standard chat responses
const response = await fetch('/chat', {
  method: 'POST',
  body: JSON.stringify({
    query: 'What is this document about?',
    file_ids: ['uuid-here'],
    stream: true // set false for JSON
  })
});

Developer Experience

  • Visual debugging: live embedding preview in chat UI
  • Progressive disclosure: guided onboarding & contextual states
  • API-first design: REST endpoints + comprehensive errors
  • Redis-backed rate limiting: sliding-window strategy

Getting Started

Install dependencies

bun i

Run the development server

bun dev

Run the web server

cd apps/web && bun run dev

Run the API server

cd packages/api && bun run dev
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