Llama Packs, introduced as part of the LlamaHub platform, serve as a community-driven repository of prepackaged modules designed to simplify the development of Language Model (LLM) applications by offering templates for various use cases, such as building a Streamlit app or implementing a retrieval system with Weaviate. These modules not only allow users to quickly initialize and run applications but also enable customization, providing access to the underlying code for further tailoring. The launch features over 16 templates developed in collaboration with partners, and these packs can be easily downloaded and integrated through the llama_index Python library or command-line interface. By offering both high-level templates and modular components, Llama Packs aim to streamline the process of building LLM applications, accommodating different abstraction levels and use case requirements, and are available alongside detailed documentation on LlamaHub.