rename to FaceVector Engine

Author: szeyu

CLAUDE.md

@@ -4,7 +4,7 @@ This file provides guidance to Claude Code (claude.ai/code) when working with co
 
 ## Project Overview
 
-AWS Rekognition Clone - An open-source alternative to AWS Rekognition. A Node.js/TypeScript face recognition system using ArcFace embeddings for face recognition, RetinaFace for face detection with landmarks, and PostgreSQL with pgvector extension for efficient vector similarity search.
+FaceVector Engine - A production-ready face recognition and vector similarity search engine. A Node.js/TypeScript system using ArcFace embeddings for face recognition, RetinaFace for face detection with landmarks, and PostgreSQL with pgvector extension for efficient vector similarity search.
 
 ## Development Commands
 

Makefile

@@ -47,7 +47,7 @@ db:
 	docker compose -f docker-compose.yml up -d db
 
 # Run the API locally
-run: install-dev db
+run: install-dev models db
 	npm run dev
 
 # Build and start the full stack (API + Postgres) with Docker Compose

README.md

@@ -1,6 +1,6 @@
-# AWS Rekognition Clone
+# FaceVector Engine
 
-An open-source AWS Rekognition alternative - A Node.js/TypeScript API for face recognition and analysis using ArcFace embeddings, RetinaFace face detection with landmarks, and PostgreSQL with pgvector for similarity search.
+A production-ready face recognition and vector similarity search engine. Built with Node.js/TypeScript, this API provides face detection, recognition, and matching using state-of-the-art ArcFace embeddings, RetinaFace detection, and PostgreSQL pgvector for efficient similarity search.
 
 ## Features
 
@@ -516,11 +516,11 @@ This confirms that the RetinaFace face detector correctly rejects images without
 
 ## Technology Stack
 
-- **Face Detection**: RetinaFace ResNet50 model for detecting faces with 5 facial landmarks (eyes, nose, mouth)
-- **Face Recognition**: ArcFace ResNet100 model for generating 512-dimensional face embeddings
+- **Face Detection**: RetinaFace ResNet50 - Detects faces with 5 facial landmarks (eyes, nose, mouth)
+- **Face Recognition**: ArcFace ResNet100 - Generates 512-dimensional face embeddings
 - **Vector Search**: PostgreSQL with pgvector extension for efficient similarity search
-- **Image Processing**: Jimp for image manipulation and ONNX Runtime for model inference
-- **API Framework**: Express.js with TypeScript
+- **Image Processing**: Jimp for image manipulation, ONNX Runtime for ML inference
+- **API Framework**: Express.js with TypeScript, Zod validation
 
 ## Notes
 

docker-compose.yml

@@ -1,7 +1,7 @@
 services:
   db:
     image: pgvector/pgvector:pg16
-    container_name: rekognition_clone_db
+    container_name: facevector_engine_db
     environment:
       POSTGRES_USER: ${POSTGRES_USER}
       POSTGRES_PASSWORD: ${POSTGRES_PASSWORD}
@@ -18,7 +18,7 @@ services:
       retries: 5
   api:
     build: .
-    container_name: rekognition_clone_api
+    container_name: facevector_engine_api
     environment:
       DATABASE_URL: postgres://${POSTGRES_USER}:${POSTGRES_PASSWORD}@db:5432/${POSTGRES_DB}
       PORT: ${PORT}

package-lock.json

@@ -1,7 +1,7 @@
 {
-  "name": "aws-rekognition-clone",
+  "name": "facevector-engine",
   "version": "1.0.0",
-  "description": "AWS Rekognition clone - Face recognition and analysis API using ONNX models (ArcFace, RetinaFace) with PostgreSQL pgvector",
+  "description": "FaceVector Engine - Face recognition and vector similarity search API using ArcFace embeddings, RetinaFace detection, and PostgreSQL pgvector",
   "main": "dist/server.js",
   "scripts": {
     "build": "tsc",