edit-mind

RAG & Retrieval

A local AI-powered video knowledge base that indexes videos for transcription, frame analysis, and semantic search while running entirely on your own machine.

Track releases GitHub Website

TypeScript Latest v0.22.0 · 16d ago Security brief →

Features

Index videos with transcription, frame/object/face detection, and multi-model embeddings
Perform natural‑language semantic search across indexed video content using ChromaDB
Run fully locally for privacy‑preserving operation on any Docker‑enabled system

Security Response History

1 CVE

CVE	Severity	Disclosed	Patched (this tool)	vs Ecosystem Median
CVE-2023-4863 KEV	high CVSS 8.8	2023-09-13	2026-01-15	2y 4mo / median 2y 4mo

Recent releases

View all 14 releases →

Review required

v0.22.0 Security relevant 16d

Auth RBAC

REST API, MCP server, token management

patches CVE-2023-4863

Open

v0.21.0 New feature 1mo

Security fixes

Upgraded project dependencies with latest security patches

Notable features

Custom metadata for face recognition
Face attributes indexed in vector DB for rich searching

Full changelog

Overview

This release introduces custom face metadata enrichment to enable smarter video search, alongside security updates and updates to the README file, including a new Desktop App section and Edit Mind's featuring on Syntax.fm.

Features

Custom Metadata for Face Recognition

You can now attach rich, structured metadata to known faces and have it automatically indexed alongside face recognition results, a community-requested feature.

Place a metadata.json file inside each named face folder under your FACES_DIR, check the FACES_DIR environment variable in .env.system:

FACES_DIR/
└── Ilias/
    ├── photo.jpg
    └── metadata.json

Example FACES_DIR/Ilias/metadata.json:

{
  "name": "Ilias Haddad",
  "alternate_names": ["Ilias Hadd"],
  "nationalities": ["Netherlands", "Morocco"],
  "date_of_birth": "1989-03-01",
  "place_of_birth": "Dordrecht, Netherlands",
  "height_m": 1.87,
  "positions": ["Centre-back"],
  "current_club": "Union Touarga",
  "club_jersey_number": 20,
  "dual_nationality": true
}

When a video is indexed and the face of "Ilias" is recognized in a scene, all metadata properties are embedded into the vector DB document for that scene. This means you can now search scenes using any metadata attribute — for example, searching current_club: Union Touarga will return every scene featuring that person.

Other Improvements

Security updates: Upgraded project dependencies with the latest security patches.
README updates: Added a Desktop App section and highlighted the Edit Mind feature on Syntax.fm.