---
title: "llm-applications"
type: "tool"
slug: "ray-project-llm-applications"
canonical_url: "https://www.graphcanon.com/tools/ray-project-llm-applications"
github_url: "https://github.com/ray-project/llm-applications"
homepage_url: null
stars: 1857
forks: 255
primary_language: "Jupyter Notebook"
license: "CC-BY-4.0"
archived: false
categories: ["llm-frameworks", "inference-serving"]
tags: ["ray", "llms", "fine-tuning", "machine-learning", "serving", "openai", "anyscale", "llama2"]
updated_at: "2026-07-11T11:38:49.612923+00:00"
---

# llm-applications

> A comprehensive guide to building RAG-based LLM applications for production.

A comprehensive guide to building RAG-based LLM applications for production.

## Facts

- Repository: https://github.com/ray-project/llm-applications
- Stars: 1,857 · Forks: 255 · Open issues: 13 · Watchers: 16
- Primary language: Jupyter Notebook
- License: CC-BY-4.0
- Last pushed: 2024-08-02T00:27:10+00:00

## Trust & health

_Signals computed from public GitHub metadata. Not a security guarantee._

- Maintenance: Dormant (computed 2026-07-11T11:38:48.137Z)
- Security scan: No lockfile (0 critical, 0 high, 0 medium, 0 low) · last scan 2026-07-11T11:38:48.656Z
- Full report: [trust report](/tools/ray-project-llm-applications/trust.md) · [JSON](https://www.graphcanon.com/api/graphcanon/tools/ray-project-llm-applications/trust)

## Categories

- [LLM Frameworks](/categories/llm-frameworks.md)
- [Inference & Serving](/categories/inference-serving.md)

## Tags

ray, llms, fine-tuning, machine-learning, serving, openai, anyscale, llama2

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_+ 2 more not listed._

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/tools/ray-project-llm-applications`](/api/graphcanon/tools/ray-project-llm-applications)
- LLM index: [/llms.txt](/llms.txt)
- Full corpus: [/llms-full.txt](/llms-full.txt)

_GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_