Healthsearch Demo
Healthsearch is an open-source demo application that uses Weaviate as a vector database to retrieve supplement products based on user-written reviews and queries, illustrating real-world semantic product search over vector embeddings.
About this tool
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
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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.
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Vector database integration
- Built around Weaviate as the vector database.
- Stores and searches over vector embeddings of product information and reviews.
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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.ymlfor bringing up the full stack with Docker.
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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.
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Open-source project assets
README.mdwith project usage and setup details.CHANGELOG.mdtracking changes.CODE_OF_CONDUCT.mddefining community guidelines.LICENSEfile specifying open-source licensing terms.
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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
LICENSEfile is included in the repository; refer to it in the GitHub project for exact license terms.
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