[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-10700":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":11,"languages":10,"totalLinesOfCode":10,"stars":12,"forks":13,"watchers":14,"openIssues":15,"contributorsCount":16,"subscribersCount":16,"size":16,"stars1d":16,"stars7d":16,"stars30d":17,"stars90d":16,"forks30d":16,"starsTrendScore":16,"compositeScore":18,"rankGlobal":10,"rankLanguage":10,"license":19,"archived":20,"fork":21,"defaultBranch":22,"hasWiki":21,"hasPages":21,"topics":23,"createdAt":10,"pushedAt":10,"updatedAt":41,"readmeContent":42,"aiSummary":43,"trendingCount":16,"starSnapshotCount":16,"syncStatus":44,"lastSyncTime":45,"discoverSource":46},10700,"LlamaIndexTS","run-llama\u002FLlamaIndexTS","run-llama","Data framework for your LLM applications. Focus on server side solution","https:\u002F\u002Fts.llamaindex.ai",null,"TypeScript",3075,521,20,109,0,1,30.15,"MIT License",true,false,"main",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40],"agent","chatbot","claude-ai","create-llama","embedding","groq-ai","javascript","llama","llama-index","llama3","llamaindex","llm","node","nodejs","openai","react","typescript","2026-06-12 02:02:25","> [!CAUTION]\n>\n> ## Deprecation Notice\n>\n> **This project is deprecated and no longer maintained.**\n> \n> For LlamaCloud\u002FLlamaParse usage, check out our docs: https:\u002F\u002Fdevelopers.llamaindex.ai\u002Fpython\u002Fcloud\u002F\n>\n> Thank you to everyone who contributed to and used LlamaIndex.TS.\n\n\u003Cp align=\"center\">\n  \u003Cimg height=\"100\" width=\"100\" alt=\"LlamaIndex logo\" src=\"https:\u002F\u002Fts.llamaindex.ai\u002Fsquare.svg\" \u002F>\n\u003C\u002Fp>\n\u003Ch1 align=\"center\">LlamaIndex.TS (Deprecated)\u003C\u002Fh1>\n\u003Ch3 align=\"center\">\n  Data framework for your LLM application.\n\u003C\u002Fh3>\n\n[![NPM Version](https:\u002F\u002Fimg.shields.io\u002Fnpm\u002Fv\u002Fllamaindex)](https:\u002F\u002Fwww.npmjs.com\u002Fpackage\u002Fllamaindex)\n[![NPM License](https:\u002F\u002Fimg.shields.io\u002Fnpm\u002Fl\u002Fllamaindex)](https:\u002F\u002Fgithub.com\u002Frun-llama\u002FLlamaIndexTS\u002Fblob\u002Fmain\u002FLICENSE)\n[![NPM Downloads](https:\u002F\u002Fimg.shields.io\u002Fnpm\u002Fdm\u002Fllamaindex)](https:\u002F\u002Fwww.npmjs.com\u002Fpackage\u002Fllamaindex)\n[![Discord](https:\u002F\u002Fimg.shields.io\u002Fdiscord\u002F1059199217496772688)](https:\u002F\u002Fdiscord.com\u002Finvite\u002FeN6D2HQ4aX)\n[![Twitter](https:\u002F\u002Fimg.shields.io\u002Ftwitter\u002Ffollow\u002Fllama_index)](https:\u002F\u002Fx.com\u002Fllama_index)\n\nUse your own data with large language models (LLMs, OpenAI ChatGPT and others) in JS runtime environments with TypeScript support.\n\nDocumentation: https:\u002F\u002Fts.llamaindex.ai\u002F\n\nTry examples online:\n\n[![Open in Stackblitz](https:\u002F\u002Fdeveloper.stackblitz.com\u002Fimg\u002Fopen_in_stackblitz.svg)](https:\u002F\u002Fstackblitz.com\u002Fgithub\u002Frun-llama\u002FLlamaIndexTS\u002Ftree\u002Fmain\u002Fexamples)\n\n## What is LlamaIndex.TS?\n\nLlamaIndex.TS aims to be a lightweight, easy to use set of libraries to help you integrate large language models into your applications with your own data.\n\n## Compatibility\n\n### Multiple JS Environment Support\n\nLlamaIndex.TS supports multiple JS environments, including:\n\n- Node.js >= 20 ✅\n- Deno ✅\n- Bun ✅\n- Nitro ✅\n- Vercel Edge Runtime ✅ (with some limitations)\n- Cloudflare Workers ✅ (with some limitations)\n\nFor now, browser support is limited due to the lack of support for [AsyncLocalStorage-like APIs](https:\u002F\u002Fgithub.com\u002Ftc39\u002Fproposal-async-context)\n\n### Supported LLMs:\n\n- OpenAI LLms\n- Anthropic LLms\n- Groq LLMs\n- Llama2, Llama3, Llama3.1 LLMs\n- MistralAI LLMs\n- Fireworks LLMs\n- DeepSeek LLMs\n- ReplicateAI LLMs\n- TogetherAI LLMs\n- HuggingFace LLms\n- DeepInfra LLMs\n- Gemini LLMs\n\n## Getting started\n\n```shell\nnpm install llamaindex\npnpm install llamaindex\nyarn add llamaindex\n```\n\n### Setup in Node.js, Deno, Bun, TypeScript...?\n\nSee our official document: https:\u002F\u002Fts.llamaindex.ai\u002Fdocs\u002Fllamaindex\u002Fgetting_started\n\n### Adding provider packages\n\nIn most cases, you'll also need to install provider packages to use LlamaIndexTS. These are for adding AI models, file readers for ingestion or storing documents, e.g. in vector databases.\n\nFor example, to use the OpenAI LLM, you would install the following package:\n\n```shell\nnpm install @llamaindex\u002Fopenai\npnpm install @llamaindex\u002Fopenai\nyarn add @llamaindex\u002Fopenai\n```\n\n## Playground\n\nCheck out our NextJS playground at https:\u002F\u002Fllama-playground.vercel.app\u002F. The source is available at https:\u002F\u002Fgithub.com\u002Frun-llama\u002Fts-playground\n\n## Core concepts for getting started:\n\nSee our documentation: https:\u002F\u002Fts.llamaindex.ai\u002Fdocs\u002Fllamaindex\u002Fgetting_started\u002Fconcepts\n\n## Contributing:\n\nPlease see our [contributing guide](CONTRIBUTING.md) for more information.\nYou are highly encouraged to contribute to LlamaIndex.TS!\n\n## Community\n\nPlease join our Discord! https:\u002F\u002Fdiscord.com\u002Finvite\u002FeN6D2HQ4aX\n","LlamaIndex.TS 是一个为大型语言模型（LLM）应用程序设计的数据框架，专注于服务器端解决方案。它支持多种JS运行环境如Node.js、Deno等，并兼容OpenAI、Anthropic等多种主流LLM。通过提供一系列轻量级且易于使用的库，该项目帮助开发者将自定义数据与LLM集成到应用中。尽管项目已不再维护并被弃用，但其设计理念和技术实现仍对需要在服务端快速搭建基于LLM的应用场景具有参考价值。",2,"2026-06-11 03:29:47","top_topic"]