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DB-GPT

eosphoros-ai/DB-GPT

open-source agentic AI data assistant for the next generation of AI + Data products

GitHub Website

GraphCanon updated 2d · GitHub synced 2d · 47 views this month

20k stars2.9k forksLast push 3d Python MIT

Decision brief

DB-GPT is an open-source framework that integrates with various LLM services, streamlining tasks from reasoning to SQL execution and planning.

Good fit when

- You need a tool that can handle complex data processing and task automation using AI.
- Your project requires integration with multiple LLM service providers like OpenAI, Moonshot API (Kimi), or MiniMax.

Avoid when

- You are looking for a heavily community-customized or fine-tuned experience as,DB-GPT's flexibility might be limited compared to more customizable systems.
- Your use case strictly requires proprietary services and you seek a tool without dependency on third-party LLM services which DB-GPT inherently relies upon.

Observed Jul 11, 2026 · Source: enrich:decision_facts

DB-GPT alternatives Trust report

DB-GPT vs langflow DB-GPT vs AutoGPT DB-GPT vs WrenAI

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Maintenance and security

Full trust report

Maintenance: Very active (0d since push); As of 2d
Provenance: Not a fork · Organization account; As of 2d
Security (OSV): No lockfile; As of 1mo

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Install

pip install DB-GPT

PyPI

How it fits your stack(9)

Typed graph edges - alternatives, integrations, successors, and dependencies. Ranked by relationship type, not raw GitHub stars.

Relationship graph

Optional deeper exploration of typed edges and category neighbours.

awesome-llm-apps131k★

graphify108k★

AlternativeIntegratesDepends onRelated

awesome-llm-apps131k★

graphify108k★

AlternativeIntegratesDepends onRelated

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Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

DB-GPT is an open-source framework that leverages AI and LLMs to handle tasks involving reasoning, task planning, SQL writing/execution, and more. It integrates with various LLM services like OpenAI, Moonshot API (Kimi), and MiniMax.

Capability facts

Deploy: Self-host
Source: dockerfile:docker-compose.yml · Aug 18, 2026
Docker: Dockerfile present
Source: dockerfile:docker-compose.yml · Aug 18, 2026
Languages: python
Source: github.language+pyproject.toml · Aug 18, 2026

Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

Python runtimePython

Source: README excerpt (regex_v1, Aug 18, 2026)

> **Prerequisites:** Python **3.10+** and [uv](https://docs.astral.sh/uv/getting-started/installation/) (re

Source link

README

Plan and execute

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

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


---

### Advanced Installation






For Docker, local GPU models (vLLM, llama.cpp), or manual source-code setup, see the full docs:

- [**Install**](http://docs.dbgpt.cn/docs/installation)
  - [Docker](http://docs.dbgpt.cn/docs/installation/docker)
  - [Source Code](http://docs.dbgpt.cn/docs/installation/sourcecode)
- [**Quickstart**](http://docs.dbgpt.cn/docs/quickstart)
- [**Application**](http://docs.dbgpt.cn/docs/operation_manual)
  - [Development Guide](http://docs.dbgpt.cn/docs/cookbook/app/data_analysis_app_develop)
  - [App Usage](http://docs.dbgpt.cn/docs/application/app_usage)
  - [AWEL Flow Usage](http://docs.dbgpt.cn/docs/application/awel_flow_usage)
- [**Debugging**](http://docs.dbgpt.cn/docs/operation_manual/advanced_tutorial/debugging)
- [**Advanced Usage**](http://docs.dbgpt.cn/docs/application/advanced_tutorial/cli)
  - [SMMF](http://docs.dbgpt.cn/docs/application/advanced_tutorial/smmf)
  - [Finetune](http://docs.dbgpt.cn/docs/application/fine_tuning_manual/dbgpt_hub)
  - [AWEL](http://docs.dbgpt.cn/docs/awel/tutorial)

For agents

This page has a .md twin and JSON over the API.

/tools/eosphoros-ai-db-gpt.md GET /api/graphcanon/tools/eosphoros-ai-db-gpt GET /api/graphcanon/graph?tool=eosphoros-ai-db-gpt