DB-GPT: Open-Source Agentic AI Data Assistant

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An open-source AI data assistant that connects to your data, writes SQL and code, runs skills in sandboxed environments, and turns analysis into reports, insights, and action.

What is DB-GPT?

DB-GPT is an open-source agentic AI data assistant for the next generation of AI + Data products.

It helps users and teams:

• connect to databases, CSV / Excel files, warehouses, and knowledge bases
• ask questions in natural language and let AI write SQL autonomously
• run Python- and code-driven analysis workflows
• load and execute reusable skills for domain-specific tasks
• generate charts, dashboards, HTML reports, and analysis summaries
• execute tasks safely in sandboxed environments

DB-GPT is also a platform for building AI-native data agents, workflows, and applications with agents, AWEL, RAG, and multi-model support.

Why DB-GPT?

1. Agentic data analysis

Plan tasks, break work into steps, call tools, and complete analysis workflows end to end.

2. Autonomous SQL + code execution

Generate SQL and code to query data, clean datasets, compute metrics, and produce outputs.

3. Multi-source data access

Work across structured and unstructured sources, including databases, spreadsheets, documents, and knowledge bases.

4. Skills-driven extensibility

Package domain knowledge, analysis methods, and execution workflows into reusable skills.

5. Sandboxed execution

Run code and tools in isolated environments for safer, more reliable analysis.

What you can do with DB-GPT

• Analyze CSV / Excel files and generate visual reports
• Connect to databases and produce profiling reports
• Ask business questions in natural language and let AI write SQL automatically
• Perform financial report analysis with code, charts, and narrative summaries
• Create and reuse SQL analysis skills and domain workflows
• Combine code, SQL, retrieval, and tools in a single agentic workflow
• Build next-generation AI + Data assistants for your team or product

Product Workflow

Explore data

Connect files, databases, and knowledge bases in one workspace.

Plan and execute

Let AI reason through the task, write SQL and code, and execute step by step.

Use skills

Load reusable skills for repeatable business analysis workflows.

Generate reports

Produce charts, dashboards, HTML reports, and decision-ready outputs.

Quick Start

Get DB-GPT running in minutes with the one-line installer (macOS & Linux):

curl -fsSL https://raw.githubusercontent.com/eosphoros-ai/DB-GPT/main/scripts/install/install.sh | bash

Or specify a profile and API key directly:

curl -fsSL https://raw.githubusercontent.com/eosphoros-ai/DB-GPT/main/scripts/install/install.sh \
  | OPENAI_API_KEY=sk-xxx bash -s -- --profile openai

For Kimi 2.5 via Moonshot API:

curl -fsSL https://raw.githubusercontent.com/eosphoros-ai/DB-GPT/main/scripts/install/install.sh \
  | MOONSHOT_API_KEY=sk-xxx bash -s -- --profile kimi

For MiniMax via the OpenAI-compatible API:

curl -fsSL https://raw.githubusercontent.com/eosphoros-ai/DB-GPT/main/scripts/install/install.sh \
  | MINIMAX_API_KEY=sk-xxx bash -s -- --profile minimax

Already have a local DB-GPT checkout? Reuse it instead of cloning ~/.dbgpt/DB-GPT:

OPENAI_API_KEY=sk-xxx \
  bash scripts/install/install.sh --profile openai --repo-dir "$(pwd)" --yes

Or reuse your local repo with Kimi 2.5:

MOONSHOT_API_KEY=sk-xxx \
  bash scripts/install/install.sh --profile kimi --repo-dir "$(pwd)" --yes

Or reuse your local repo with MiniMax:

MINIMAX_API_KEY=sk-xxx \
  bash scripts/install/install.sh --profile minimax --repo-dir "$(pwd)" --yes

After installation, start the server with the generated profile config:

cd ~/.dbgpt/DB-GPT && uv run dbgpt start webserver --profile <profile>

Then open http://localhost:5670.

Prefer to review the script first?

curl -fsSL https://raw.githubusercontent.com/eosphoros-ai/DB-GPT/main/scripts/install/install.sh -o install.sh
less install.sh
bash install.sh --profile openai

Install via PyPI

Install DB-GPT from PyPI and start it with a single command — no source checkout required.

Prerequisites: Python 3.10+ and uv (recommended) or pip.

1. Install

# Recommended: use uv
uv pip install dbgpt-app

# Or with pip
pip install dbgpt-app

The default installation includes the core framework (CLI, FastAPI, Agent), OpenAI-compatible LLM support, DashScope / Tongyi support, RAG document parsing, and ChromaDB vector store.

2. Start

This is the beginning of the README. Read the rest at the original. Read the full README ↗