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Redis Product Search

Redis Product Search is an open-source single-page demonstration app for visual and semantic product search with Redis Stack. It supports image- and text-based vector similarity, HNSW and flat indexing, and hybrid queries that pre-filter vector search with tags.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Redis Product Search — OpenViST project profile in RAG & Knowledge Systems.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use it to explore or adapt a product-search demonstration built around Redis Stack vector search, including image and text queries and tag-filtered hybrid search.

Who it is for

  • Developers exploring vector search in a product-catalog workflow.
  • Teams evaluating how image or text embeddings and tag filters can be combined in a Redis Stack demo.

Documented uses

  • Search a product catalog by visual similarity from an image.
  • Search by text using semantic vector similarity.
  • Compare HNSW and flat vector indexing approaches.
  • Combine vector similarity with tag pre-filters.
Before you choose

Requirements & limits

The repository is public and specifies a BSD-3-Clause license. Its README links to a hosted demo and documents Docker Compose and local development setup.

  • Redis Stack supplies vector search and JSON storage; the application uses RedisVL as its Python client.
  • The documented embedding components are PyTorch/Img2Vec for images and Hugging Face Sentence Transformers for text.
  • The README describes Docker Compose as the development setup and also provides separate local frontend and backend instructions.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Run the app with Docker Compose

Set up the documented development environment and start the application’s Docker containers.

Before you start

  • Docker Desktop
  • A local copy of the repository

Steps

  1. Copy .env.template to .env.

  2. Run the command below to run the Docker containers.

    Documented command
    make build

Expected outcome

The Docker containers are started for the application.

Guide limitations

  • The README notes that cached images may require adding --build and --force-recreate.
  • The guide covers the documented container-start steps, not verification of a successful search.
Documentation 1 ↗
Source-based practical guide

Start the frontend and backend locally

Set up and launch the frontend and FastAPI backend as separate local processes.

Before you start

  • Node.js and npm
  • Poetry
  • A local copy of the repository

Steps

  1. In frontend/, run the command below, then the command below.

    Documented command
    npm install
    Documented command
    npm run start

  2. Open http://localhost:3000 in a browser.

  3. In backend/, run poetry install.

  4. Run poetry run start to launch the FastAPI app.

Expected outcome

The README’s local-development steps start the frontend and backend separately.

Guide limitations

  • The guide describes local startup, not verification that the services connect or that searches succeed.
Documentation 1 ↗
COMPARE OPTIONS

Compare options for Vector search

These projects document a common task and share a project role. This is a source-based comparison, not an execution benchmark or a guarantee of interchangeability.

ProjectDocumented purposePlatformAccess and requirements
Redis Product SearchSearch a product catalog by visual similarity from an image.Docker, WebThe repository is public and specifies a BSD-3-Clause license. Its README links to a hosted demo and documents Docker Compose and local development setup.
Chatbot with PDF for Semantic SearchPrepare document content as embeddings and save it to a supported vector database.WebThe repository is identified as open source and publicly visible on GitHub.
AI LLM PlaygroundAsk questions about PDF documents through an assistant interface.Web
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
17 October 2026
Original website title
redis-developer/redis-product-search · Official homepage title · retained in its source language
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