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Piragi

Piragi is an open-source Python library for creating retrieval-augmented knowledge bases from local documents, remote storage and web sources. It provides embeddings, a vector store, retrieval and cited question answering, with optional integrations for alternate stores, local language models, crawling and knowledge graphs.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Piragi — 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 Piragi when building a Python application that needs retrieval over documents or supported remote sources, particularly when cited answers or a choice of vector-store backend are useful.

Who it is for

  • Python developers building document question-answering features
  • Teams assembling searchable knowledge collections from local files, cloud storage or documentation sites
  • Application developers who want retrieval results to pass to a separately chosen language model

Documented uses

  • Ingest documents and source locations into a knowledge base.
  • Ask questions and inspect answers with source citations.
  • Retrieve relevant text chunks and scores for use with a separate language model.
  • Connect a knowledge base to async application workflows.
  • Add optional crawling, alternate vector stores or knowledge-graph retrieval.
Before you choose

Requirements & limits

The repository identifies the project as open source under the MIT license. Installation is documented with pip. The README describes it as free and local by default.

  • The default vector store is LanceDB; PostgreSQL with pgvector, Pinecone, Supabase and custom stores are also documented.
  • Cloud-storage integrations use optional package extras for S3, Google Cloud Storage and Azure Blob Storage.
  • Recursive web crawling is optional and documented with same-domain, depth-three and 100-page default limits.
  • Ollama is optional; the library also documents configuring an LLM and retrieving chunks without using Piragi for generation.
  • Retrieval options include HyDE, hybrid search and cross-encoder reranking.

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 Piragi and prepare a local-model setup

Install the Python library and, if desired, install Ollama with the documented Llama 3.2 model.

Before you start

  • Python package installer capable of installing piragi
  • Ollama is optional for the local language-model setup

Steps

  1. Install the library with the command below.

    Documented command
    pip install piragi

  2. For the optional local-model route, install Ollama using its documented installation command.

  3. Pull the model with ollama pull llama3.2.

Expected outcome

Piragi is installed; the optional Ollama setup has the documented model pulled.

Guide limitations

  • These steps document installation only, not creation or use of a knowledge base.
  • No platform-specific installation details are provided.
Documentation 1 ↗
COMPARE OPTIONS

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.

ProjectDocumented purposePlatformAccess and requirements
PiragiIngest documents and source locations into a knowledge base.CLI, Self-hosted, ServerThe repository identifies the project as open source under the MIT license. Installation is documented with pip. The README describes it as free and local by default.
LangsearchCrawl website or local data for a knowledge base.CLI, Self-hosted, Server
Hybrid Search RagCombine document retrieval and language-model generation in a configurable workflow.
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
12 October 2026
Original website title
hemanth/piragi · Official homepage title · retained in its source language
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