A guide to building long-term compounding knowledge infrastructure. See details on GitHub .

Pathway LLM App

Production-ready templates for RAG and AI pipelines that support live data synchronization and large-scale document indexing.

Overview

Pathway LLM App provides ready-to-deploy templates for RAG, enterprise search, and AI pipelines. Templates handle live data syncing, large document indexing, and expose APIs or example frontends for rapid integration.

Key Features

  • App templates: question-answering, live document indexing, multimodal RAG, unstructured-to-SQL, and more.
  • Live data synchronization: automatically index and update from file systems, Google Drive, SharePoint, S3, Kafka, and databases.
  • Deployability: Docker-friendly with Streamlit and REST example frontends for demos and production integration.
  • Ecosystem integrations: built on Pathway Live Data framework and integrates with usearch, Tantivy, LangChain and other tools.

Use Cases

  • Enterprise knowledge search and RAG services with real-time data sync.
  • Multimodal document extraction and analysis for finance, legal, or research domains.
  • Fast RAG backend setup for connecting custom frontends or existing applications.

Technical Highlights

  • Built on Pathway Live Data (Python with a Rust engine) for high-performance streaming and indexing.
  • MIT licensed for easy adoption in enterprise and commercial projects.
  • Rich examples, CI templates, and deployment scripts to accelerate production readiness.

Comments

Pathway LLM App
Resource Info
🌱 Open Source 📚 RAG 🏗️ Framework