RAG & Knowledge
SQLBot
SQLBot — DataEase's conversational analytics: ask in natural language, get SQL answers via LLMs plus RAG.
★ 6.9k starsGPL-3.0
View guide →An agentic AI data assistant - chat with your databases, run SQL and code, get reports
DB-GPT is an open-source rag & knowledge project by eosphoros-ai (eosphoros-ai/DB-GPT on GitHub). It has 20,090 GitHub stars and 2,957 forks, is released under the MIT license, and was last updated on GitHub on 4 October 2026.
Decide which database or files the assistant should analyze first.
Install the dbgpt-app package from PyPI with uv or pip - no source checkout required.
Start DB-GPT and let the first-run wizard choose your LLM provider and API key.
Open the web UI and ask a natural-language question about your data.
An agent explores your schema, plans an approach and iterates instead of answering in one shot.
Generates and runs SQL plus Python code to answer questions and build analyses.
Connects to multiple databases and data sources from one assistant.
Add skills and agents to extend what the assistant can do.
Code runs in a sandbox, keeping autonomous execution contained.
Turns analysis into reports through the built-in web interface.
Get the source code from GitHub and enter the project directory.
git clone https://github.com/eosphoros-ai/DB-GPT.git
cd DB-GPTThe recommended install uses uv; plain pip works too. Python 3.10+ is required.
uv pip install dbgpt-app
# or: pip install dbgpt-appFirst run launches an interactive wizard for your LLM provider, then starts the web server.
dbgpt start
# then open http://localhost:5670It is maintained by eosphoros-ai and contributors on GitHub.
Yes - DB-GPT is MIT licensed and free to use and modify.
The setup wizard asks for an LLM provider API key (profiles include OpenAI, Kimi/Moonshot and MiniMax in the install scripts); self-hosted models are an alternative for advanced setups.
Compared with text-to-SQL point tools, DB-GPT is a full agentic assistant - planning, code execution, skills and reporting - closer to an AI data analyst than a SQL generator.
Run uv pip install dbgpt-app, then dbgpt start, complete the wizard, and open the web UI at localhost:5670.
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