Next Generation Data
Interaction Solution with LLMs

Revolutionizing Database Interactions with Private LLM Technology

  • flan
  • Openai
  • vicuna
  • chatglm
  • llama.cpp
  • Llama
  • vLLM
  • falcon
  • gorilla
  • bard
  • claude
  • tongyi
  • zhipu
  • Baichuan
  • WizardLM
  • internlm
  • flan
  • Openai
  • vicuna
  • chatglm
  • llama.cpp
  • Llama
  • vLLM
  • falcon
  • gorilla
  • bard
  • claude
  • tongyi
  • zhipu
  • Baichuan
  • WizardLM
  • internlm
  • Six Major Features in DB-GPT

    DB-GPT revolutionizes Database Interaction with Private LLM Technology. In the coming era of Data 3.0, enterprises and developers can now harness the power of Large Language Models (LLMs) and Databases to create customized applications with minimal coding effort.

    1.Multi-Source Retriever-Augmented
    Generator (MS-RAG)

    MS-RAG (Multi-Source Retriever-Augmented Generator) is crafted to enhance the handling of intricate knowledge scenarios in the realm of Q&A.

    2.Generative Business intelligence

    Chat with your Excel, Databases, Datalakes and Lakehouses to empower data analysis and enhance business intelligence. Just as what you can do with ChatGPT.

    3.Service-oriented Multi-model
    Management Framework (SMMF)

    DB-GPT provides comprehensive model support, offering dozens of Large Language Models (LLMs) from both open-source and API agents. Our offerings include LLaMA/LLaMA2, Baichuan, ChatGLM, Wenxin, Tongyi, Zhipu, and many other models. SMMF (Service-oriented Multi-model Management Framework) is a versatile framework engineered for efficient deployment and management of various LLM in diverse computing environments. It's tailored for multi-model support, handling multiple inference frameworks, and adaptable to different deployment strategies including single-machine, cluster, and cloud-native deployments.

    SMMF

    4. Lightweight Automatic Fine-Tuning Framework for Text2SQL Task.

    DB-GPT offers an automated lightweight fine-tuning framework that enables several-lines code fine-tuning on a range of Large Language Models (LLMs) using diverse open-source Text2SQL datasets. It incorporates numerous fine-tuning techniques, including LoRA/QLoRA/Pturning. This framework simplifies Text2SQL fine-tuning, making it as straightforward as an assembly line process.

    fine-tune
    frame

    5.AWEL(Agentic Workflow Expression Language) & dbgpts (Data-Driven Agents)

    MS-RAG (Multi-Source Retriever-Augmented Generator) is crafted to enhance the handling of intricate knowledge scenarios in the realm of Q&A.

    6.Guarantee of Privacy and Security

    DB-GPT guarantees data privacy and security through the utilization of various technologies, such as privatized large models and proxy desensitization.

    frame