ametnes/nesis

Your AI Powered Enterprise Knowledge Partner. Designed to be used at scale from ingesting large amounts of documents formats such as pdfs, docx, xlsx, png, jpgs, tiff, mp3, mp4, jpeg. Integrates with s3, Windows Shares, Google Drive and more.

43
/ 100
Emerging

Implements a RAG (Retrieval-Augmented Generation) architecture that converts documents into vector embeddings using HuggingFace models, then queries them via pluggable LLMs like OpenAI for context-aware responses. Features role-based access control, multi-tenant user session management, and deployment flexibility across Docker, Kubernetes, and hybrid cloud/on-premises environments using connectors for S3, MinIO, Sharepoint, and Windows file shares.

No commits in the last 6 months.

Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 8 / 25
Maturity 16 / 25
Community 19 / 25

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Stars

55

Forks

20

Language

Python

License

Apache-2.0

Last pushed

Apr 03, 2025

Commits (30d)

0

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