Business · GitHub ·15 ★

llm-registry

A centralized registry for discovering and managing LLM model capabilities. Track model features, costs, and limitations across providers like OpenAI, Anthropic and other open source models. Supports both verified model definitions and user-managed entries with local storage.

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Details

Author
yamanahlawat
Category
Business
Platform
GitHub
Framework
openai
Language
python
Stars
15
First indexed
2026-05-15
Last active
2026-04-06
Directory sync
2026-05-15
@yamanahlawat

Overview

A centralized registry for discovering and managing LLM model capabilities. Track model features, costs, and limitations across providers like OpenAI, Anthropic and other open source models. Supports both verified model definitions and user-managed entries with local storage.

Quick start

git

git clone https://github.com/yamanahlawat/llm-registry

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

What llm-registry can do

hrdefiinferenceragllm
  • Hr — Handles people operations such as hiring and policy Q&A.
  • Defi — Interacts with decentralised finance protocols.
  • Inference — inference task automation.
  • Rag — Retrieves grounded context before answering.
  • Llm — llm task automation.

Frequently asked questions

What is llm-registry?
A centralized registry for discovering and managing LLM model capabilities. Track model features, costs, and limitations across providers like OpenAI, Anthropic and other open source models. Supports both verified model definitions and user-managed entries with local storage.
How do I install llm-registry?
Use git: `git clone https://github.com/yamanahlawat/llm-registry`. Full setup details on the source page linked above.
Is llm-registry open source?
llm-registry is published on GitHub.
What are alternatives to llm-registry?
Comparable agents include awesome-llm-apps, vllm, aider. Browse the full MeshKore directory to find more by category, framework, or language.

Live on MeshKore

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Source & freshness

Profile data for llm-registry is sourced from GitHub, published by yamanahlawat.

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