LangBoot: An Overview
LangBoot is an innovative project designed to integrate the capabilities of large language models (LLMs) into SpringBoot applications following the principles of Langchain. It provides a framework for developers to build AI-powered applications without delving into the complexities of training or fine-tuning AI models themselves. Instead, LangBoot focuses on leveraging existing powerful LLMs as foundational components to bring advanced capabilities to SpringBoot applications.
Technology Stack
LangBoot utilizes an impressive array of technologies and frameworks, making it robust and versatile. Below is a summary of the key components and their versions:
- Java: Version 17+, ensuring modern language features and performance.
- SpringBoot: Version 3.1.0 for building robust and scalable applications.
- Swagger-ui: Utilized through 'knife4j-openapi3-jakarta-spring-boot-starter' for API documentation.
- Hutool: A comprehensive toolkit offering a variety of utility modules.
- Redis: For caching purposes, enhancing performance and data access speed.
- Fastjson2: Used for JSON parsing, known for its speed and ease of use.
- MySQL Connector: For database connectivity, integrating seamlessly with MySQL databases.
- MyBatis-Plus: As the ORM framework, simplifying database operations.
- OpenAI Java Library: To interface with OpenAI models.
- Frontend Technologies: Including FreeMarker, Bootstrap, jQuery, and Recorder.js.
- Streaming Chat: Implemented using Server-Sent Events (SSE).
- Language Models and Embedding Libraries: Integration with models like OpenAI, Chatglm2, etc., and embedding services like Weaviate and Milvus.
LangChain RAG Principle
The project employs the LangChain Retrieval-Augmented Generation (RAG) principle, which enhances the capabilities of AI models by supplementing them with additional relevant data. This principle helps in improving the accuracy and relevance of the AI-generated responses by utilizing external knowledge sources.
Model Capability Matrix
LangBoot supports multiple AI models, each with varying capabilities:
- OpenAI: Excels in text generation, streaming output, voice interaction, function calls, and more.
- Baidu (Wenxin): Offers comprehensive support for text generation and other AI functions.
- Zhishu (GLM-4), Kimi, and Chatglm2: These models offer varying degrees of support for text generation and AI functions, enabling flexibility in choosing the right model for specific tasks.
Feature Roadmap
The feature roadmap provides a glimpse into current capabilities and future enhancements:
- Local Knowledge Base: Upload and integrate non-structured documents and connect various LLMs.
- System Features: Includes user login, stream chat, voice in/out, and more.
- Prompts Features: Such as summarization, translation, keyword extraction, and content safety analysis.
- Frontend: Mobile adaptation and optimized streaming output.
Quick Start Guide
LangBoot offers straightforward setup instructions to get started:
- Execute Database Scripts: Initialize with
init-script/db.sql. - Install Local Vector Database: Use
docker-compose up -dfor setup. - Configure Language Models: Add OpenAI API token in the configuration or start the local Chatglm2 model with
python .\openai_api.py.
Additional Resources and Configuration
For further details, users can refer to the project's Wiki and a guide on How to Build a High-Quality Knowledge Base.
Functional Demonstrations and Chat Demo
Various aspects of LangBoot's functionalities are showcased through images demonstrating UI components like login pages, homepages, and specific functional screens, including a Chat Demo that highlights the chat interface and local knowledge base integration.
Community and Support
LangBoot has a vibrant community with discussions facilitated via WeChat groups. Interested individuals are invited to join these groups to engage, learn, and contribute to the project.
LangBoot embodies the spirit of innovation by harnessing the potential of large language models within a well-structured SpringBoot application, providing developers with the tools to create sophisticated AI-driven solutions effortlessly.