Code & Development · GitHub ·72 ★

rag-ops

This project applies the core knowledge from the LLMOps module, including the design and implementation of the API Layer, Inference Layer, Observability Layer, Cache Layer, Guardrails Layer, Routing Layer, and the Data Ingestion Pipeline.

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Details

Author
T-Sunm
Category
Code & Development
Platform
GitHub
Framework
custom
Language
python
Stars
72
First indexed
2026-05-15
Last active
2025-12-27
Directory sync
2026-05-15
@T-Sunm

Overview

This project applies the core knowledge from the LLMOps module, including the design and implementation of the API Layer, Inference Layer, Observability Layer, Cache Layer, Guardrails Layer, Routing Layer, and the Data Ingestion Pipeline.

Quick start

git

git clone https://github.com/T-Sunm/rag-ops

Snippet generated from the published metadata; check the source page for full setup, configuration, and prerequisites.

What rag-ops can do

hrinferenceapidatadesign
  • Hr — Handles people operations such as hiring and policy Q&A.
  • Inference — inference task automation.
  • Api — api task automation.
  • Data — Reads, transforms, and analyses structured data.
  • Design — design task automation.

Frequently asked questions

What is rag-ops?
This project applies the core knowledge from the LLMOps module, including the design and implementation of the API Layer, Inference Layer, Observability Layer, Cache Layer, Guardrails Layer, Routing Layer, and the Data Ingestion Pipeline.
How do I install rag-ops?
Use git: `git clone https://github.com/T-Sunm/rag-ops`. Full setup details on the source page linked above.
Is rag-ops open source?
rag-ops is published on GitHub.
What are alternatives to rag-ops?
Comparable agents include everything-claude-code, system-prompts-and-models-of-ai-tools, claude-code. Browse the full MeshKore directory to find more by category, framework, or language.

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Source & freshness

Profile data for rag-ops is sourced from GitHub, published by T-Sunm.

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