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JavaScript-AI-Buildathon

  • 默认分支main
  • 大小85.1 MB
  • 更新1 周前
  • Issues7
在 GitHub 打开
avatarAzure-Samples

项目介绍

Azure-Samples/JavaScript-AI-Buildathon 是一个托管在 GitHub 上的开源项目,采用 MIT License 许可证,目前获得 124 个 Star、48 次 Fork。

仓库全名
Azure-Samples/JavaScript-AI-Buildathon

README 摘要

JavaScript AI Build-a-thon Learn AI with JavaScript and TypeScript through hands-on Quests. Self-paced. Open source. Up-to-date. Start with Quest 1 · Browse all Quests · Read the learning guide Start here This repository is for JavaScript and TypeScript developers who want to learn AI by building. You do not need to complete everything at once: choose the Quest that matches your goal, follow it at your own pace, and…

完整内容见 GitHub 原始 README 或本页 。

常见问题

JavaScript-AI-Buildathon 可以免费商用吗?

仓库采用 MIT License 许可证,可免费使用与修改,商业使用请遵守许可证条款(例如保留版权声明与许可声明)。

如何获取 JavaScript-AI-Buildathon 的源码?

可以直接克隆仓库:git clone https://github.com/Azure-Samples/JavaScript-AI-Buildathon.git,默认分支为 main;安装与运行步骤见仓库 README。

JavaScript-AI-Buildathon 最近还在维护吗?

仓库最近一次更新为 1 周前,当前有 7 个未关闭 Issue;Star 数为 124,可作为社区活跃度的参考。

本页面展示项目元数据与原始 README,GitRead 中文社区 编辑团队负责选题收录。

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关于

aiagentsaitoolkitfoundry-localmicrosoft-foundryrag
  • MIT License
  • 124 Stars
  • 48 Forks
  • 15 Watching

简要分析

热度分
235
价值分
89
活跃状态
活跃
GitHub

贡献者

juliamuiruri4juliamuiruri4BethanyJepBethanyJepCopilotCopilotsinediedsinedieddependabot[bot]dependabot[bot]danfiedler-msftdanfiedler-msftmicrosoft-github-operations[bot]microsoft-github-operations[bot]

JavaScript AI Build-a-thon: hands-on Quests, self-paced and always available

JavaScript AI Build-a-thon

Learn AI with JavaScript and TypeScript through hands-on Quests.

Self-paced. Open source. Up-to-date.

Start with Quest 1 · Browse all Quests · Read the learning guide


Start here

This repository is for JavaScript and TypeScript developers who want to learn AI by building. You do not need to complete everything at once: choose the Quest that matches your goal, follow it at your own pace, and return whenever you are ready for the next pattern.

New to AI development? Begin with local models in Quest 1, then move through the learning path in order. Already comfortable with models and retrieval? Start with the agent-focused Quests.

The learning path

Quest Build and explore Environment
1. Local AI Development Run models on-device and connect them to a JavaScript application Local
2. End-to-End Model Development Select, customize, evaluate, trace, and protect models with Microsoft Foundry Cloud
3. Serverless RAG Support System Build document ingestion, retrieval, grounded responses, streaming, and chat history Local & Cloud
4. Build Agents with AI Toolkit Compare models, build agents, connect MCP tools, evaluate responses, and export code Local & Cloud
5. Burger Ordering Agent System Explore a complete multi-service agent system with MCP integrations Local & Cloud

Foundations

Quests 1-3 cover three core AI application patterns: running models locally, working through an end-to-end model lifecycle, and grounding responses with retrieval-augmented generation.

Agents

Quests 4-5 move into agent design, MCP tool use, evaluation, orchestration, and the boundaries between an agent, its APIs, and external services.

How to use the Quests

  1. Open a Quest and review its prerequisites before starting.
  2. Follow the setup and hands-on steps in the Quest README.
  3. Use the optional recording at the top of a Quest when you want a guided walkthrough.
  4. Adapt the scenario or data to reinforce what you learned.
  5. Continue to the next Quest or choose another path from this page.

Cloud-based Quests can create costs. Review each Quest’s notes and remove cloud resources when you finish.

Community and support

  • Join the JavaScript AI community on Discord
  • Report a problem or suggest an improvement
  • Explore the documentation site

Appendix

March 2026 program archive

The March 2026 program introduced these five Quests through live sessions and a project-building program. Its winning projects, participant submissions, and reference links are preserved in the program archive.

June 2025 program archive

The June 2025 program brought together developers who turned real-world ideas into AI applications. Its project showcase is preserved in the program archive.


JavaScript at Microsoft · Code of Conduct · MIT License

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