Healthsearch Demo

Website type: Open‑source demo application / example project
Category: Open-source
Brand: weaviate
Source code: https://github.com/weaviate/healthsearch-demo

Overview

Healthsearch Demo is an open-source example application that demonstrates how to use Weaviate as a vector database to power semantic search over supplement products. It retrieves products based on user-written reviews and free-text queries, illustrating real-world semantic product search using vector embeddings.

Features

• Semantic product search

  • Retrieve supplement products based on natural-language queries.
  • Uses user-written reviews and health-related queries to match relevant products.
  • Demonstrates real-world semantic search behavior over vector embeddings.

• Vector database integration

  • Built around Weaviate as the vector database.
  • Stores and searches over vector embeddings of product information and reviews.

• End-to-end demo architecture

  • Backend folder implementing the server-side logic and integration with Weaviate.
  • Frontend folder providing a user interface for running semantic searches.
  • docker-compose.yml for bringing up the full stack with Docker.

• Health and supplement domain example

  • Focuses on supplement products and health effects as the example dataset.
  • Shows how health-related effects and outcomes can guide product retrieval.

• Open-source project assets

  • README.md with project usage and setup details.
  • CHANGELOG.md tracking changes.
  • CODE_OF_CONDUCT.md defining community guidelines.
  • LICENSE file specifying open-source licensing terms.

• Hosted demo (reference)

  • Linked live demo front-end for trying out semantic search behavior.

Technology Stack

• Weaviate (vector database)
• Docker / Docker Compose
• Separate backend and frontend applications (exact frameworks not specified in the provided content)

Use Cases

• Learning how to build semantic product search over user reviews.
• Example implementation of Weaviate in a health/supplement recommendation context.
• Reference architecture for vector-embedding-based search in other domains.

Pricing

• Open-source repository; no pricing information is provided in the available content.

License

• A LICENSE file is included in the repository; refer to it in the GitHub project for exact license terms.