DB-GPT  by eosphoros-ai

AI-native data app development framework with agentic workflow

created 2 years ago
17,059 stars

Top 2.7% on sourcepulse

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Project Summary

DB-GPT is an open-source framework for building AI-native data applications, targeting developers and enterprises seeking to simplify LLM integration with data. It provides tools for multi-model management, RAG, Text2SQL optimization, and multi-agent collaboration, enabling less-code development of bespoke data-driven applications.

How It Works

DB-GPT integrates core capabilities like Retrieval Augmented Generation (RAG) for knowledge-based applications, Generative Business Intelligence (GBI) for data analysis and insights, a fine-tuning framework for domain-specific LLMs, and a data-driven multi-agents system for autonomous data execution. It emphasizes a "Data Factory" for data cleaning and processing, and seamless integration with various data sources.

Quick Start & Requirements

  • Install: Docker or from source code.
  • Prerequisites: Python, specific LLM dependencies (e.g., LLaMA, Qwen), potential GPU/CUDA for advanced features.
  • Resources: Detailed setup and usage guides are available in the Documents.

Highlighted Details

  • Supports private domain Q&A with unified vector storage and custom data extraction plugins.
  • Facilitates natural language interaction with diverse data sources (Excel, databases) and generates analytical reports.
  • Offers a fine-tuning framework for Text-to-SQL with reported 82.5% accuracy on the Spider dataset.
  • Manages dozens of open-source and API-based LLMs, including Llama, Baichuan, and Qwen.

Maintenance & Community

  • Active development with recent releases (V0.7.0).
  • Community channels include Discord and a Community repository.

Licensing & Compatibility

  • Licensed under the MIT License (MIT), permitting commercial use and closed-source linking.

Limitations & Caveats

The project is actively evolving, with features like GBI and multi-agent systems being core capabilities. Specific performance benchmarks beyond Text2SQL fine-tuning are not detailed in the README.

Health Check
Last commit

1 day ago

Responsiveness

1 day

Pull Requests (30d)
24
Issues (30d)
42
Star History
819 stars in the last 90 days

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