Experimenting with Javelit - The Streamlit for Java

1. streamlit

   1 323 42,767 9.9 Python

   Streamlit — A faster way to build and share data apps.

   

   Javelit brings the power of rapid prototyping and interactive web app development to the Java ecosystem, much like Streamlit does for Python. With its simple, loop-based programming model, developers can quickly build data-driven applications without needing extensive frontend knowledge, leveraging familiar Java syntax and the rich JVM ecosystem. The live-reload feature enables instant experimentation and iteration, making it ideal for prototyping AI agents, data visualizations, and interactive tools. By integrating seamlessly with libraries like LangGraph4j combined with both Spring AI and LangChain4j, Javelit empowers Java developers to create engaging user interfaces effortlessly, bridging the gap between backend logic and user-facing applications. Checkout project, try it and let me know your feedback and ... happy coding! 👋

2. InfluxDB

   www.influxdata.com featured

   InfluxDB – Built for High-Performance Time Series Workloads. InfluxDB 3 OSS is now GA. Transform, enrich, and act on time series data directly in the database. Automate critical tasks and eliminate the need to move data externally. Download now.

   

3. Spring Boot

   2 210 79,411 10.0 Java

   Spring Boot helps you to create Spring-powered, production-grade applications and services with absolute minimum fuss.

   

   When I started developing LangGraph4j, I tried to replicate my Python development ecosystem in Java. So I've experimented with the Java Notebooks through the rapaio-jupyter-kernel project, which allowed me to replicate the development experience I had with Jupyter Notebooks in Python quite well. For rapid prototyping, I relied almost entirely on Spring Boot framework, which is a fairly fast and enjoyable programming experience.

4. langgraph4j

   3 8 1,145 9.9 Java

   🚀 LangGraph for Java. A library for develop AI Agentic Architectures in the Java ecosystem. Designed to work seamlessly with both Langchain4j and Spring AI.

   

   Javelit brings the power of rapid prototyping and interactive web app development to the Java ecosystem, much like Streamlit does for Python. With its simple, loop-based programming model, developers can quickly build data-driven applications without needing extensive frontend knowledge, leveraging familiar Java syntax and the rich JVM ecosystem. The live-reload feature enables instant experimentation and iteration, making it ideal for prototyping AI agents, data visualizations, and interactive tools. By integrating seamlessly with libraries like LangGraph4j combined with both Spring AI and LangChain4j, Javelit empowers Java developers to create engaging user interfaces effortlessly, bridging the gap between backend logic and user-facing applications. Checkout project, try it and let me know your feedback and ... happy coding! 👋

5. rapaio-jupyter-kernel

   4 5 70 7.6 Jupyter Notebook

   Java jupyter kernel

   

   When I started developing LangGraph4j, I tried to replicate my Python development ecosystem in Java. So I've experimented with the Java Notebooks through the rapaio-jupyter-kernel project, which allowed me to replicate the development experience I had with Jupyter Notebooks in Python quite well. For rapid prototyping, I relied almost entirely on Spring Boot framework, which is a fairly fast and enjoyable programming experience.

6. langchain4j

   5 25 10,006 9.9 Java

   LangChain4j is an open-source Java library that simplifies the integration of LLMs into Java applications through a unified API, providing access to popular LLMs and vector databases. It makes implementing RAG, tool calling (including support for MCP), and agents easy. LangChain4j integrates seamlessly with various enterprise Java frameworks.

   

   Javelit brings the power of rapid prototyping and interactive web app development to the Java ecosystem, much like Streamlit does for Python. With its simple, loop-based programming model, developers can quickly build data-driven applications without needing extensive frontend knowledge, leveraging familiar Java syntax and the rich JVM ecosystem. The live-reload feature enables instant experimentation and iteration, making it ideal for prototyping AI agents, data visualizations, and interactive tools. By integrating seamlessly with libraries like LangGraph4j combined with both Spring AI and LangChain4j, Javelit empowers Java developers to create engaging user interfaces effortlessly, bridging the gap between backend logic and user-facing applications. Checkout project, try it and let me know your feedback and ... happy coding! 👋

7. Stream

   getstream.io featured

   Stream - Scalable APIs for Chat, Feeds, Moderation, & Video. Stream helps developers build engaging apps that scale to millions with performant and flexible Chat, Feeds, Moderation, and Video APIs and SDKs powered by a global edge network and enterprise-grade infrastructure.

   

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