# TiDB AI Assistant Q&A focalizzato su TiDB con RAG e API - Findings24: - Sito web: - Prezzi: Freemium - Categorie: Assistente SQL AI, Strumenti Dev AI ## Cos'è TiDB AI Assistant? TiDB AI Assistant is a TiDB-focused question-answering product that presents itself as a knowledge-graph-based RAG system built with TiDB X Vector Storage and PyTiDB. The public homepage invites users to ask technical questions about TiDB and related workflows, and the product appears to be exposed through both a web interface and an API. The examples on the site center on practical TiDB topics such as storing and querying vectors with PyTiDB, using foreign keys, running vector search, full-text search, or hybrid search, and asking about TiDB Cloud pricing comparisons. The API documentation adds more detail by exposing objects for chat, knowledge bases, embeddings, reranking, evaluation, and knowledge-graph retrieval. ## Cosa può fare TiDB AI Assistant? ### Knowledge-graph-based RAG The homepage describes the product as a knowledge-graph-based RAG assistant, indicating that it combines retrieval over structured knowledge with generated answers. ### TiDB and PyTiDB foundation The product is built with TiDB X Vector Storage and PyTiDB, which ties the assistant to TiDB-oriented storage and Python access patterns. ### API for retrieval and chat workflows The Swagger UI exposes endpoints and object models for chat, knowledge bases, documents, chunks, entities, relationships, embeddings, reranking, and evaluation tasks. ### Multiple retrieval modes API schema names include vector search, full-text search, hybrid search, and knowledge-graph retrieval, showing multiple retrieval modes in the backend. ### Administrative and model management The docs include admin-oriented objects for API keys, data sources, models, and settings, suggesting the service is configurable through managed resources. ## Casi d'uso ### TiDB support and reference questions Ask operational or conceptual questions about TiDB, including topics such as foreign keys, cloud pricing, and feature behavior. ### Vector and hybrid search exploration Query vectors through PyTiDB and compare vector search with full-text or hybrid retrieval approaches. ### Retrieval app prototyping Build chat or knowledge-base workflows using the documented API objects for documents, chunks, embeddings, and retrieval. ### Knowledge-graph RAG workflows Work with knowledge-graph retrieval for question answering where relationships and entities matter alongside raw text. ### Assistant quality tuning Inspect evaluation, reranking, and model-management objects in the API when tuning retrieval quality or assistant behavior. ## Domande frequenti ### How do you access TiDB AI Assistant? The site shows TiDB AI Assistant as a web app with login access and an API documented through Swagger UI. The public pages do not provide setup steps beyond those entry points. ### What does TiDB AI Assistant do? The homepage presents it as a knowledge-graph-based RAG assistant built with TiDB X Vector Storage and PyTiDB, and the API docs expose knowledge-base, vector search, knowledge-graph retrieval, chat, embedding, reranking, and evaluation-related objects. ### Is pricing published? The rendered pages do not show pricing details. The pricing URL returns a 404, so there is no public pricing information in the collected sources. ### What kinds of questions is it aimed at? The homepage examples focus on TiDB-related questions such as vectors with PyTiDB, foreign keys, vector search, full-text search, hybrid search, and TiDB Cloud cost questions. ## Informazioni rapide - **Category**: AI Assistant - **Primary focus**: TiDB-related Q&A and retrieval - **Interface**: Web app plus Swagger-documented API - **Core stack**: TiDB X Vector Storage and PyTiDB - **Pricing**: Not published in the collected sources - **Source domain**: tidb.ai