This repository provides an interactive learning environment for Milvus, a vector database. It offers tutorials, demos, and use cases for developers and researchers working with unstructured data, enabling them to build AI applications like semantic search, RAG, and recommendation systems.

How It Works

The bootcamp utilizes Jupyter notebooks to guide users through various Milvus functionalities. It demonstrates integration with popular frameworks like LangChain and LlamaIndex, showcasing features such as vector search, full-text search, hybrid search, and multimodal retrieval using multi-vectors.

Quick Start & Requirements

• Install: Primarily through Jupyter notebooks, implying a Python environment.
• Prerequisites: Python, Jupyter Notebook. Specific Milvus installation details are likely within the notebooks.
• Resources: Requires a working Python environment and familiarity with Jupyter.

Highlighted Details

• Comprehensive tutorials covering RAG, semantic search, hybrid search, and recommendation systems.
• Demos for image search, RAG, and drug discovery.
• Examples of integrating Milvus with LangChain and LlamaIndex.
• Explores advanced topics like multimodal search and graph RAG.

Maintenance & Community

• Active community engagement via Discord.
• Presence on X, LinkedIn, YouTube, and Medium for news and updates.
• FAQ page and mailing lists for support and discussions.

Licensing & Compatibility

• The README does not explicitly state the license for this bootcamp repository. Milvus itself is typically Apache 2.0 licensed, but this specific project's license needs verification.

Limitations & Caveats

• The repository focuses on demonstrating Milvus use cases and does not appear to be a standalone application or library; it requires Milvus to be installed and configured separately.