Agentset
by
Provides an open‑source platform to build, evaluate, and ship production‑ready retrieval‑augmented generation (RAG) and agentic applications, offering end‑to‑end tooling from ingestion to hosting.
Agentset Overview
What is Agentset about?
Agentset is a comprehensive RAG platform that enables developers to create, benchmark, and deploy scalable retrieval‑augmented generation and autonomous agent solutions. It bundles ingestion pipelines, vector indexing, citation‑aware chat UI, multi‑tenant hosting, and a typed SDK.
How to use Agentset?
- Quick start (local)
cp .env.example .env # configure environment variables bun install # install dependencies bun db:deploy # run Prisma migrations bun dev:web # launch the web app locally - Agentset Cloud – sign up at
https://app.agentset.ai/loginfor a managed instance with a free tier (1,000 pages, 10,000 retrievals). - Self‑hosting – follow the guide
https://docs.agentset.ai/open-source/self-hostingto deploy on your own infrastructure. - Integration – consume the OpenAPI spec or TypeScript SDK (
npm i @agentset/sdk) to call ingestion, retrieval, and chat endpoints from any application.
Key features of Agentset
- Turnkey RAG pipeline: document ingestion, chunking, embeddings, and vector search.
- Model‑agnostic: plug any LLM, embedding model, or vector DB.
- Interactive chat playground with editable messages and inline citations.
- Production‑grade hosting with preview links, custom domains, and multi‑tenant isolation.
- Fully typed API + OpenAPI specification for seamless client generation.
- Built with TypeScript, Next.js, Prisma, Supabase, and Trigger.dev for robust scalability.
- Open‑source MIT license.
Use cases of Agentset
- Enterprise knowledge bases – turn internal docs, manuals, and tickets into searchable assistants.
- Customer support bots – provide citation‑backed answers drawn from product guides.
- Research assistants – ingest academic papers and retrieve exact passages with source links.
- Developer tools – power code‑assistants that reference SDK docs or code snippets.
- Learning platforms – create interactive tutors that quote textbook excerpts.
FAQ from the Agentset community
Q: Can I use my own vector database? A: Yes. The platform abstracts the store, so you can connect Milvus, Pinecone, Qdrant, etc., via configuration.
Q: Is there a free tier for self‑hosted deployments? A: The software itself is free under MIT; only cloud‑managed resources may incur costs.
Q: How do I add multi‑tenant isolation?
A: Enable the built‑in multi‑tenant mode in the .env file; the platform creates separate schema namespaces per tenant.
Q: What LLMs are supported? A: Any OpenAI‑compatible, Anthropic, Cohere, or locally hosted model that follows the standard chat completion API.
Q: Where can I report bugs or request features? A: Use the GitHub issue templates: https://github.com/agentset-ai/agentset/issues/new?template=bug_report.md and https://github.com/agentset-ai/agentset/issues/new?template=feature_request.md.
Agentset's README
Features
- Turnkey RAG: ingestion, chunking, embeddings, and retrieval
- Model agnostic: works with your choice of LLM, embeddings, and vector DB
- Chat playground with message editing and citations
- Production hosting with preview links and custom domains
- API + typed SDKs, OpenAPI spec
- Built-in multi-tenancy
- Built with TypeScript, Next.js, AI SDK, Prisma, Supabase, and Trigger.dev
Getting Started
Agentset Cloud
The fastest way to get started with Agentset. Generous free tier with 1,000 pages and 10,000 retrievals. No credit card required.
- Sign up: https://app.agentset.ai/login
Self-host Agentset
Follow our complete guide: https://docs.agentset.ai/open-source/self-hosting
Quick Start (Local Development)
# 1) Copy env and fill required values
cp .env.example .env
# 2) Install dependencies
bun install
# 3) Run database migrations (from the repo root)
bun db:deploy
# 4) Start the app
bun dev:web
Useful scripts:
bun db:studio– open Prisma Studiobun dev:web– run only the web app
Star Us
If you find Agentset useful, please give the repo a star — it helps a lot!
Contributing
We <3 contributions big and small. Feel free to:
- Open an issue for bugs and feature ideas
- Submit a PR with focused changes
- Improve docs or examples
Not sure where to start? Check existing issues: https://github.com/agentset-ai/agentset/issues
License
MIT :)
Star History
Made with ❤️ by the Agentset team.
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