import os, cv2, face_recognition
from pathlib import Path
from dotenv import load_dotenv
from mcp.server.fastmcp import FastMCP
load_dotenv();mcp=FastMCP("Alfred Face Recognition");DB=Path(os.getenv('FACE_DB','/home/hermes/faces'));T=float(os.getenv('FACE_TOLERANCE','0.48'))
def encodings():
    known=[]
    for person in DB.iterdir() if DB.exists() else []:
        if not person.is_dir():continue
        for f in person.glob('*'):
            try:
                im=face_recognition.load_image_file(str(f)); es=face_recognition.face_encodings(im)
                if es:known.append((person.name,es[0]))
            except Exception:pass
    return known
@mcp.tool()
def identify_people(camera_index:int=0):
    cap=cv2.VideoCapture(camera_index);ok,frame=cap.read();cap.release()
    if not ok:raise RuntimeError('Caméra indisponible')
    rgb=cv2.cvtColor(frame,cv2.COLOR_BGR2RGB); locs=face_recognition.face_locations(rgb); es=face_recognition.face_encodings(rgb,locs); known=encodings();out=[]
    for e in es:
        name='inconnu';best=T
        for n,k in known:
            d=face_recognition.face_distance([k],e)[0]
            if d<best:name,best=n,d
        out.append({'name':name,'distance':float(best)})
    return {'count':len(out),'people':out,'unknown_count':sum(x['name']=='inconnu' for x in out)}
if __name__=='__main__':mcp.run()