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Semantra

Semantra is a Python command-line application that processes local text and PDF files and launches a local web interface for semantic search across them.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Semantra — OpenViST project profile in Search & Research AI.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use Semantra when you have local text or PDF files and want to explore them through a semantic query in a locally served web interface.

Who it is for

  • Journalists sifting through document collections
  • Researchers exploring papers
  • Students querying themes across reading material
  • Historians tracing connections across books

Documented uses

  • Find passages in text and PDF collections by meaning rather than exact wording.
  • Review the passages and documents most relevant to a query.
  • Refine search results with positive or negative result tags and query-term additions or subtractions.
Before you choose

Requirements & limits

Python 3.9 or later is required. The documented installation route uses pipx. The first run may download a local model; an OpenAI embedding option uses an external service and may involve payment or sharing data with that service.

  • The default workflow processes documents on the local computer using a downloaded model.
  • The first model download may take several minutes and several hundred megabytes of disk space.
  • Semantic results are ranked by relevance, but low-relevance results are still shown and exact wording is not guaranteed to match.
  • The web interface runs locally, by default at localhost:8080.

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

Install Semantra and search a local document collection

Set up the command-line tool and open a local semantic search interface for text or PDF files.

Before you start

  • Python 3.9 or later
  • pipx
  • Text or PDF files on the local computer

Steps

  1. Install pipx if needed, then run the command below and open a new terminal.

    Documented command
    python3 -m pipx ensurepath

  2. Install Semantra with the command below.

    Documented command
    python3 -m pipx install semantra

  3. Run semantra followed by one or more document filenames, such as semantra report.pdf book.txt.

  4. After processing, open the local web interface at its default address, localhost:8080, and enter a semantic query.

Expected outcome

A local web search page returns relevance-ranked results from the supplied documents, with highlighted passages and links to the relevant document sections.

Guide limitations

  • Initial document processing takes time; subsequent runs over the same collection are described as near instantaneous.
  • The first run may download a local model, taking several minutes and several hundred megabytes of disk space.
  • Semantic search may return low-relevance results and does not guarantee exact-text matches.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
14 October 2026
Original website title
freedmand/semantra-python · Official homepage title · retained in its source language
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