Project Title

llm-app — Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data synchronization

Overview

llm-app is an open-source project that provides ready-to-deploy Large Language Model (LLM) application templates for RAG (Retrieval-Augmented Generation) and AI enterprise search. It enables high-accuracy, real-time data synchronization with various data sources, including file systems, Google Drive, SharePoint, S3, Kafka, and PostgreSQL. The project stands out for its ease of deployment, scalability, and built-in data indexing capabilities.

Key Features

Scalable AI application templates for RAG and enterprise search
Real-time data synchronization with various data sources
Built-in data indexing for vector search, hybrid search, and full-text search
No infrastructure dependencies, easy deployment on-cloud or on-premises
Customizable pipeline steps for adding new data sources or changing indexing methods

Use Cases

Enterprise search: Companies can use llm-app to create scalable, high-accuracy search solutions for their internal documents and data.
RAG applications: Developers can leverage llm-app to build question-answering systems that provide answers based on live, connected data sources.
Data indexing: llm-app can be used to create real-time document indexing pipelines for RAG applications, acting as a vector store service.

Advantages

Easy deployment and scalability: Templates can be tested locally and deployed on various cloud platforms or on-premises.
Real-time data synchronization: Keeps the application up-to-date with the latest data from connected sources.
Customizable and flexible: Allows for easy changes in the pipeline, such as adding new data sources or modifying indexing methods.

Limitations / Considerations

Unknown licensing: The project's license is not specified, which may affect its use in commercial applications.
Limited documentation: The README provides an overview, but more detailed documentation on customization and deployment would be beneficial.

Langchain: A framework for building applications with LLMs, offering integration with llm-app for retriever backends.
Llamaindex: A tool for building personal knowledge bases, which can be integrated with llm-app for document indexing.
Haystack: An open-source search framework that can be used for building enterprise search solutions, offering an alternative to llm-app.

Basic Information

GitHub: https://github.com/pathwaycom/llm-app
Stars: 31,303
License: Unknown
Last Commit: 2025-09-04

📊 Project Information

Project Name: llm-app
GitHub URL: https://github.com/pathwaycom/llm-app
Programming Language: Jupyter Notebook
⭐ Stars: 31,303
🍴 Forks: 866
📅 Created: 2023-07-19
🔄 Last Updated: 2025-09-04

🏷️ Project Topics

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🎮 Online Demos

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llm-app

Project Description