GH Repository · pathwaycom
llm-app
Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, and more.
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Jupyter Notebookragchatbotpythonllmllm-localllm-securityllmopsmachine-learningllm-promptingopen-aipathwayreal-timehugging-facevector-indexvector-databaseretrieval-augmented-generation
A collection of ready-to-run templates for building RAG applications, AI pipelines, and enterprise search over live data sources. The templates are Docker-friendly and stay in sync with sources like SharePoint, Google Drive, S3, Kafka, and PostgreSQL.
Reach for it when you want prebuilt RAG or search pipelines that keep vector indexes up to date with changing data instead of one-off batch ingestion.
Use it to
- Deploy a RAG chatbot over company documents
- Build enterprise search across SharePoint, Drive, and S3
- Keep a vector index synced with Kafka or PostgreSQL streams
- Prototype AI pipelines locally with Docker
- Run LLM pipelines against real-time data APIs
For Developers building RAG and search apps on live data
- Role
- rag
- Language
- Jupyter Notebook
- Licence
- MIT
- Forks
- 1,498
- Open issues
- 5
- Last push
- 2026-07-05
topicsragreal-timevector-databasellmopsenterprise-searchpathway