This repository contains executable Python notebooks, sample apps, and resources for testing out the Elastic platform:
- Learn how to use Elasticsearch as a vector database to store embeddings, power hybrid and semantic search experiences, and more.
- Test Elastic's leading-edge, out-of-the-box capabilities like the Elastic Learned Sparse Encoder and reciprocal rank fusion (RRF), which produce best-in-class results without training or tuning.
- Integrate with projects like OpenAI, Hugging Face, and LangChain to use Elasticsearch as the backbone of your LLM-powered applications. For use cases like retrieval augmented generation (RAG), summarization, and question answering (QA).
The notebooks folder contains a range of executable Python notebooks, so you can test these features out for yourself. Colab provides an easy-to-use Python virtual environment in the browser.
The example-apps folder contains example apps that demonstrate Elasticsearch for a number of use cases, using different programming languages and frameworks.
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This software is licensed under the Apache License, version 2 ("ALv2").