Get ready-to-run cloud templates for AI pipelines and enterprise search. For startup founders in need of machine learning solutions.
59,438 stars1,430 forksJupyter NotebookQuality 8/10Updated 6/5/2026100% free · open source
What it does
Llm-app provides ready-to-deploy cloud templates for building real-time AI search and data integration across business systems, automating information workflows.
•When you need to integrate data from multiple sources like Sharepoint, Google Drive, or PostgreSQL into a unified search system
•When automating workflows that require real-time data updates from APIs or event streams like Kafka
•When building AI-powered search functionality into your application with live data synchronization
Quick start
1Navigate into the cloned repository with 'cd llm-app'
2Pull the Docker image with 'docker pull pathwaycom/llm-app'
3Run the Docker container with 'docker run -p 8000:8000 pathwaycom/llm-app'
4Access the application at 'http://localhost:8000' to start configuring your AI search and data integration
5Modify the configuration files, such as those in the 'config' directory, to connect to your specific data sources
Ready-to-paste prompt
docker run -p 8000:8000 -v $(pwd)/config:/app/config pathwaycom/llm-app --sync-sharepoint --sync-postgres
Heads up: Ensure you have Docker installed and running on your system, as llm-app is designed to be Docker-friendly and requires it to run the application
Saves to your device
Topics
chatbot
hugging-face
llm
llm-local
llm-prompting
llm-security
llmops
machine-learning
open-ai
pathway
rag
real-time
retrieval-augmented-generation
vector-database
vector-index
Quick Actions
Details
Creator
pathwaycom
Language
Jupyter Notebook
Category
support
Published
7/19/2023
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