#99th of 65 in Learning and cookbooks
awesome-llm-apps
Collection of 100+ runnable LLM agent, RAG and voice app examples in Python
- Stars
- 143.6k
- License
- Apache-2.0
- Last commit
- Oct 2026
- Language
- Python
103,471 on 10 Apr 2026143,642 on 30 Oct 2026
From GitHub's daily star counts.
Checked on GitHub.
Overview
A repository of self-contained example apps, grouped into agent skills, starter agents, multi-agent teams, voice agents, MCP agents, RAG tutorials and generative UI demos. Most are Python and run with pip install and streamlit run, using Claude, Gemini, OpenAI, DeepSeek, Llama or Qwen. It is a set of templates to copy from, not one installable product.
Who it is for: Developers looking for working LLM agent and RAG example code to adapt
Strengths
- Broad coverage: starter agents, multi-agent teams, voice, MCP and about 20 RAG variants
- Each example is a separate folder, so one can be run without the rest
- Apache-2.0 license allows reuse in commercial projects
- Some examples run fully local, such as Llama 3.2 with Qdrant and no API keys
Weaknesses
- Not a library or product: no shared package, versioning or releases
- Many examples need paid API keys (OpenAI, Gemini, Firecrawl and others)
- Dependencies and quality vary per folder, with no single install
- A few entries link to external repos rather than containing the code
What it needs
- GPU optional
- Needs Python, Streamlit, LLM provider API keys (varies per app), Qdrant (some RAG apps)
- Models: Claude, Gemini, GPT, DeepSeek, Llama
Quick answers
Is awesome-llm-apps open source?
Yes. Its code is on GitHub under the Apache-2.0 license.
Does awesome-llm-apps need a GPU?
No. It runs on a CPU and can use a GPU when you have one.
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