Practical overview
When it fits
Use the browser-native mode when you want document extraction, BM25 retrieval and storage handled in the browser. Choose the optional backend route when the documented FastAPI and FAISS semantic-search stack fits your setup.
Who it is for
- People who want to search or ask questions across a collection of PDF or DOCX documents.
- Developers exploring a document-grounded chatbot or semantic document-search interface.
Documented uses
- Retrieve relevant passages from a document collection in response to a question.
- Search across multiple documents or focus retrieval on a single document.
- Request summaries or comparisons drawing on multiple uploaded files.
Requirements & limits
The repository is public and MIT-licensed. Local setup requires Node.js 18 or later; Python 3.10 or later is only needed for backend mode.
- Standalone mode parses PDFs and extracts DOCX content in the browser, then uses BM25 and IndexedDB.
- Hybrid mode uses FastAPI, SentenceTransformers with all-MiniLM-L6-v2, and FAISS for dense semantic search.
- The README supports API-key entry through browser settings or configuration in a project .env file.
Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.
Set up the browser frontend
Install and launch the frontend in standalone or connected mode.
Before you start
- Node.js 18 or higher
- A local copy of the repository
Steps
Open a terminal in the repository's frontend directory.
Run the command below to install frontend dependencies.
npm installRun the command below and open
http://localhost:5173in a browser.npm run dev
Expected outcome
The React frontend is launched locally.
Guide limitations
- This procedure covers frontend setup only; backend FAISS mode requires the separately documented Python setup.
- The setup instructions do not establish that a particular model provider or API credential is available.
Set up the optional FAISS backend
Install and start the FastAPI backend for the documented hybrid mode.
Before you start
- Python 3.10 or higher
- A local copy of the repository
Steps
Open a terminal in the repository's backend directory.
Create a virtual environment with the command below and activate it using the instructions for your operating system.
python -m venv venvInstall backend dependencies with the command below.
pip install -r requirements.txtRun the command below; the README gives
http://localhost:8000as the server address.python app.py
Expected outcome
The FastAPI backend is started for the hybrid setup; its interactive Swagger documentation is listed at `http://localhost:8000/docs`.
Guide limitations
- Python backend setup is optional and is not required for the browser-native standalone mode.
- These steps describe setup, not a verification of a working deployment or a complete document-query workflow.
Compare options for Retrieval-augmented applications
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.
| Project | Documented purpose | Platform | Access and requirements |
|---|---|---|---|
| Neurolens Knowledge Retrieval Engine | Retrieve relevant passages from a document collection in response to a question. | Server, Web | The repository is public and MIT-licensed. Local setup requires Node.js 18 or later; Python 3.10 or later is only needed for backend mode. |
| Rag Powered AI Assistant Transforming Data Retrieval And Analysis Across The Web And Pdfs | Retrieve relevant passages from web and PDF content to answer a question. | Web | |
| LangChain in Supabase Edge Functions | Initialize and start a Supabase project locally. | Cloud, Server |
Sources & review
Source record details
- Source availability
- Active
- Sources checked
- 15 October 2026
- Original website title
- udityamerit/NeuroLens-Knowledge-Retrieval-Engine · Official homepage title · retained in its source language