ammirsm/llamaindex-omakase-rag
This project enhances the construction of RAG applications by addressing challenges, improving accessibility, scalability, and managing data and user access. It uses Django, Llamaindex, and Google Drive for effective database management.
Implements automated Google Drive synchronization with incremental change detection and deduplication during chunking, eliminating redundant file downloads and duplicate vector embeddings. Built on PostgreSQL and Celery for asynchronous task scheduling, it provides a complete production-ready stack with role-based access control, admin panels, and a REST API layer for LLM inference—transforming RAG from prototype scripts into scalable multi-tenant applications.
148 stars. No commits in the last 6 months.
Stars
148
Forks
16
Language
Python
License
MIT
Category
Last pushed
Apr 10, 2024
Commits (30d)
0
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