A conversational search tool based on GraphRAG (Knowledge Graph) that built on top of TiDB Vector and LlamaIndex and DSPy.
Live Demo: TiDB.AI
Documentation: TiDB.AI Docs
- Perplexity-style Conversational Search page: Our platform features an advanced built-in website crawler, designed to elevate your browsing experience. This crawler effortlessly navigates official and documentation sites, ensuring comprehensive coverage and streamlined search processes through sitemap URL scraping.
You can even edit the Knowledge Graph to add more information or correct any inaccuracies. This feature is particularly useful for enhancing the search experience and ensuring that the information provided is accurate and up-to-date.
- Embeddable JavaScript Snippet: Integrate our conversational search window effortlessly into your website by copying and embedding a simple JavaScript code snippet. This widget, typically placed at the bottom right corner of your site, facilitates instant responses to product-related queries.
- Next.js – Framework
- TypeScript – Language
- Tailwind – CSS
- shadcn/ui - Design
- TiDB – Database to store chat history, vector, json, and analytic
- Kysely - SQL query builder
- NextAuth.js – Auth
- Vercel – Deployments
- LlamaIndex - RAG framework
- DSPy - The framework for programming—not prompting—foundation models
- TiDB Vector - Vector storage and search engine
TiDB.AI is open-source under the Apache License, Version 2.0. You can find it here.