Busabase
Busabase 是一个开源(MIT)数据库与 AI 智能体工作空间——将数据、文档、技能和应用集成于一体。您可以本地运行、在网络内自托管或使用 Busabase Cloud,从而开启新时代。
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一分钟完成验证Open-source, self-hosted search and AI chat for your website, grounded in your own data
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Open-source, self-hosted search and AI chat for your website, grounded in your own data.
Interakt puts a search box and a chat window in front of your users without you assembling the pieces yourself. Point it at your data, decide how it should behave in the admin dashboard, and paste a snippet into your site.
Underneath is a curated stack: a search engine, an AI provider, a chat pipeline, a versioned prompt library and an analytics database. You see one dashboard, one API and two widgets.查看完整 README ↗Open-source, self-hosted search and AI chat for your website, grounded in your own data.
Website · Features · Documentation · API Reference · Integrations · Discussions
Interakt puts a search box and a chat window in front of your users without you assembling the pieces yourself. Point it at your data, decide how it should behave in the admin dashboard, and paste a snippet into your site.
Underneath is a curated stack: a search engine, an AI provider, a chat pipeline, a versioned prompt library and an analytics database. You see one dashboard, one API and two widgets.
flowchart LR
D["Your data<br/>catalog · docs · CMS · files"] --> IX["Search index"]
IX --> SE["Search experience"]
IX -- "tools" --> AE["AI chat experience"]
T["Custom HTTP tools · MCP servers"] --> AE
SE --> W["Widgets · REST API"]
AE --> W
W --> Y["Your website"]
IX -.-> ES[("Elasticsearch or<br/>Azure AI Search")]
AE -.-> LLM[("OpenAI · Ollama")]
You connect a data source, populate a search index, then build one or more experiences on top of it. The chat experience calls the search tools to answer from your data. The architecture overview has the full picture.
Needs Node.js 24 and Docker. Prefer to watch? The backend setup video walks through these steps.
git clone https://github.com/alphasolutionsrepo/interakt.git
cd interakt/backend
cp .env.example .env # fill in the three generated secrets at the top
cp setup/setup.config.example.yaml setup/setup.config.yaml # set your admin email and password
npm install
npm run infra:up # Postgres (pgvector) and Elasticsearch in Docker
npm run dev # migrates, seeds, creates the admin user → http://localhost:3000
Sign in and open Admin → Initial Setup. Connect an AI provider (Ollama is free and local), then load the Fashion Catalog demo: a populated index plus ready-made search and chat experiences with access tokens. Point the reference app in demo-site/ at it, or embed the widget below.
The full walkthrough, scripts and bring-your-own-database notes are in CONTRIBUTING.md. Hosting notes are in backend/docker/.
<div id="chat"></div>
<script src="https://your-interakt-host/embed/v1/widgets.js"></script>
<script>
window.ChatDropinUI.init({
containerId: 'chat',
accessToken: '<access token from the admin UI>',
});
</script>
Use SearchDropinUI for the search widget. The admin UI generates the exact snippet for each experience, and the widget docs cover launcher modes, placement and theming.
# Search through a search experience
curl -X POST https://your-interakt-host/api/v1/search/<experience-slug>/search \
-H "Authorization: Bearer <access token>" \
-H "Content-Type: application/json" \
-d '{ "query": "waterproof trail shoes" }'
# Chat through an AI experience (streams server-sent events)
curl -N -X POST https://your-interakt-host/api/v1/ai-experiences/<experience-slug>/chat \
-H "Authorization: Bearer <access token>" \
-H "Content-Type: application/json" \
-d '{ "message": "Which of these run true to size?" }'
Access tokens are issued per experience and are public and read-only by design. Writing documents into an index uses a server-side ingestion key instead. See the search, chat and ingestion guides, or the full API reference.
Step-by-step guides for Medusa, Storyblok and React / Next.js. The Interakt-Medusa repository is the demo storefront that guide is built on.
interakt/
├── backend/ Admin dashboard + REST APIs · Next.js 16, Drizzle, Postgres + pgvector
│ ├── widgets/ Embeddable search and chat widgets · Preact, built to public/embed/v1/widgets.js
│ ├── docker/ Production Dockerfile + local docker-compose (Postgres, pgAdmin, Elasticsearch)
│ └── src/content/docs/ The documentation, served in-app at /docs and published to docs.interakt.app
├── demo-site/ Reference consumer app on port 3001
└── docs-site/ Docusaurus + Redocusaurus shell for docs.interakt.app
Contributions are welcome. CONTRIBUTING.md covers local setup, conventions and how review works here. Found a bug or want a feature? Open an issue. Have a question? Start a discussion. For security issues, follow SECURITY.md and never open a public issue.
This project follows the Contributor Covenant code of conduct.