kjannette/citation_sentinel
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Revise README with enhanced project details

Browse Source 
Updated project description to include cosine similarity scoring and groundedness metric. Clarified user interaction with source documents and audio/video links.
This commit is contained in:
S Jannette
2026-05-08 03:50:29 -04:00
committed by GitHub
parent a6b0a95dfc
commit 8dbdc1dea4
1 changed files with 5 additions and 5 deletions
Download Patch File Download Diff File Expand all files Collapse all files

10
README.md
View File

@@ -1,11 +1,11 @@
# Citation Sentinel
A source-grounded research assistant inspired by Google's NotebookLM. MIT
license, by [@sjdev](https://sjdev.co). Users upload documents, links, youtube videos,
ask questions and receive answers (with inline citations) grounded in their sources.
A source-grounded research assistant that employs cosine similarity scoring for LLM generated query responses to provide a "groundedness" score. This is a metric in Retrieval-Augmented Generation (RAG) systems that quantifies how well an AI-generated answer is supported by retrieved context. It measures "faithfulness" to source documents, ensuring the answer is not hallucinated or pulled from the model's pre-training data.
MIT license, by [@sjdev](https://sjdev.co).
Built with a React/Vite frontend and a Node.js/Express backend, using Anthropic Claude for
generation, OpenAI Whisper for video audio track transcription, Voyage AI for embeddings and response cosine similarity scoring ("groundedness" score).
Users upload source documents, or provide links to online sources including audio/video (i.e. links to youtube videos). Users may then ask questions and receive answers (with inline citations) verifiably grounded in the provided information sources.
Built with a React/Vite frontend and a Node.js/Express backend, using Anthropic Claude for generation, OpenAI Whisper for video audio track transcription, Voyage AI for embeddings and response cosine similarity scoring (the "groundedness" score).
## Prerequisites