dataease/SQLBot🔥 active
🔥 基于大模型和 RAG 的智能问数系统,对话式数据分析神器。Text-to-SQL Generation via LLMs using RAG.
AI-native data platform: 60+ connectors, dlt-based ETL, DAG scheduling, per-source RAG knowledge bases, and sandboxed AI agents that query, chart, and analyze your data.
$ git clone https://github.com/xuwei95/ezdata.git🔥 基于大模型和 RAG 的智能问数系统,对话式数据分析神器。Text-to-SQL Generation via LLMs using RAG.
AI-powered virtual executive team — a single coherent executive persona backed by 8 specialist agents (FastAPI + Next.js).
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Hypergraph is more powerful. Transform unstructured text into structured knowledge with LLMs. Graphs, hypergraphs, and spatio-temporal extractions — with one command.
Everything you need to know to build your own RAG application
Jupyter Notebooks to help you get hands-on with Pinecone vector databases
This repository provides an advanced Retrieval-Augmented Generation (RAG) solution for complex question answering. It uses sophisticated graph based algorithm to handle the tasks.
Data from GitHub · snapshot Nov 13, 2026