Behavision/behavision/api.py

"""HTTP API + minimal live dashboard (FastAPI).

Every endpoint is guarded by engine readiness; the server can start before
models finish loading without a single unguarded None dereference.
"""
from __future__ import annotations

import asyncio
import time
import logging
import secrets
from pathlib import Path
from typing import Optional

from fastapi import Depends, FastAPI, HTTPException
from fastapi.responses import HTMLResponse, Response, StreamingResponse
from fastapi.security import HTTPBasic, HTTPBasicCredentials
from pydantic import BaseModel, ValidationError

from .config import ApiSection, CameraConfig, CameraTuning
from .commission import CommissionRun
from .events import Event
from .engine import Engine

log = logging.getLogger(__name__)

_STATIC = Path(__file__).parent / "static"


class RenamePayload(BaseModel):
    label: str


class CommissionPayload(BaseModel):
    seconds: float = 25.0


class MergePayload(BaseModel):
    """`into` is the identity that survives. `force` overrides the
    similarity guard and is never the default: a wrong merge cannot be
    undone, because nothing records which embedding came from whom."""
    into: int
    force: bool = False


class CameraPayload(BaseModel):
    """Camera as the UI submits it. Mirrors CameraConfig but every field is
    optional so PATCH can send a subset.

    Optional[...] rather than `X | None`: pydantic evaluates field annotations
    at runtime, and CameraConfig already uses this form.
    """
    id: Optional[str] = None
    url: Optional[str] = None
    host: Optional[str] = None
    port: Optional[int] = None
    path: Optional[str] = None
    username: Optional[str] = None
    password: Optional[str] = None
    webcam: Optional[int] = None
    max_width: Optional[int] = None
    # Per-camera gate overrides. Without this the store could hold them but
    # nothing could set them, so the commissioning advice ("loosen this
    # camera's quality gate") had no way to be acted on.
    tuning: Optional[CameraTuning] = None


def camera_public(cam: CameraConfig, worker=None) -> dict:
    """Camera as the API returns it.

    The password is NEVER included — not masked, not empty-string-if-set,
    absent. `safe_url()` already exists for exactly this and masks credentials
    inside the URL form too.
    """
    out = {
        "id": cam.id, "host": cam.host, "port": cam.port, "path": cam.path,
        "username": cam.username, "webcam": cam.webcam,
        "max_width": cam.max_width, "has_password": bool(cam.password),
        "url": cam.safe_url(),
        "tuning": cam.tuning.model_dump(),
    }
    if worker is not None:
        out.update(worker.stats())
        out["url"] = cam.safe_url()  # worker.stats() also carries a url key
    return out


def _auth_dependencies(api_cfg: ApiSection) -> list:
    """HTTP Basic over every route when credentials are configured.

    Applied at app level rather than per-route so a future endpoint cannot be
    added unprotected by omission. Basic (not a token) because the dashboard
    is a browser page: the browser prompts once and then attaches the header
    to the MJPEG <img> subresource too, which a bearer token cannot do.
    """
    if not api_cfg.auth_enabled:
        return []
    scheme = HTTPBasic()

    def check(credentials: HTTPBasicCredentials = Depends(scheme)) -> None:
        # compare_digest on both halves: no early exit, no timing signal.
        ok_user = secrets.compare_digest(
            credentials.username.encode("utf-8"),
            api_cfg.username.encode("utf-8"))
        ok_pass = secrets.compare_digest(
            credentials.password.encode("utf-8"),
            api_cfg.password.encode("utf-8"))
        if not (ok_user and ok_pass):
            raise HTTPException(401, "invalid credentials",
                                headers={"WWW-Authenticate": "Basic"})

    return [Depends(check)]


def _reencode(jpeg: bytes, width: int, quality: int) -> "bytes | None":
    """Decode, scale and re-encode one frame. None on any failure.

    None rather than an exception on purpose: the caller falls back to the
    original frame, so a re-encode that fails costs bandwidth rather than the
    picture. A live view that goes blank because a resize failed is a worse
    outcome than one that is briefly larger than asked for.
    """
    try:
        import cv2
        import numpy as np

        img = cv2.imdecode(np.frombuffer(jpeg, np.uint8), cv2.IMREAD_COLOR)
        if img is None:
            return None
        if 0 < width < img.shape[1]:
            # Only ever DOWN. Upscaling a frame to a requested width would send
            # more bytes than the original for no more detail.
            scale = width / img.shape[1]
            img = cv2.resize(img, (width, max(1, int(img.shape[0] * scale))),
                             interpolation=cv2.INTER_AREA)
        q = quality if 1 <= quality <= 100 else 75
        ok, buf = cv2.imencode(".jpg", img, [int(cv2.IMWRITE_JPEG_QUALITY), q])
        return buf.tobytes() if ok else None
    except Exception:
        log.debug("frame re-encode failed", exc_info=True)
        return None


def create_app(engine: Engine) -> FastAPI:
    app = FastAPI(title="Behavision", version="1.0.0",
                  dependencies=_auth_dependencies(engine.cfg.api))

    def worker_or_404(camera_id: str):
        worker = engine.workers.get(camera_id)
        if worker is None:
            raise HTTPException(404, f"unknown camera '{camera_id}'")
        return worker

    @app.get("/", response_class=HTMLResponse)
    def dashboard() -> str:
        return (_STATIC / "dashboard.html").read_text(encoding="utf-8")

    @app.get("/api/health")
    def health() -> dict:
        from .paths import describe
        return {"status": "ok" if engine.started_at else "starting",
                "recognition_model": engine.encoder.model_name,
                # "where is my database" must be answerable from the API: the
                # tray, the installer and support all need it, and installed
                # it is not next to the code.
                "paths": {**describe(), "data_dir": str(engine.cfg.app.data_dir),
                          "models_dir": str(engine.cfg.app.models_dir)},
                "cameras": {cid: w.source.connected
                            for cid, w in engine.workers.items()}}

    @app.get("/api/stats")
    def stats() -> dict:
        return engine.stats()

    @app.get("/api/events")
    def events(limit: int = 50) -> list:
        return list(engine.bus.recent)[:limit]

    @app.get("/api/identities")
    def identities(limit: int = 200) -> list:
        return engine.store.list_identities(limit)

    @app.get("/api/sightings")
    def sightings(limit: int = 100) -> list:
        return engine.store.recent_sightings(limit)

    @app.patch("/api/identities/{identity_id}")
    def rename_identity(identity_id: int, payload: RenamePayload) -> dict:
        if not engine.store.rename_identity(identity_id, payload.label.strip()):
            raise HTTPException(404, "identity not found")
        return engine.store.get_identity(identity_id)

    @app.get("/api/identities/{identity_id}/embedding")
    def identity_embedding(identity_id: int) -> dict:
        """One identity's best stored vector, for forwarding to the server.

        This returns biometric personal data. It is on the authenticated local
        API and bound to loopback in the product, and it exists because the
        event bus deliberately does not carry embeddings — putting a 512-float
        template on the bus would send it to the log sink and the email sink
        too.
        """
        best = engine.store.best_embedding(identity_id, engine.gallery.model_name)
        if best is None:
            raise HTTPException(404, "no embedding for this identity "
                                     "(or it was made by a different model)")
        vector, quality = best
        return {"identity_id": identity_id,
                "model": engine.gallery.model_name,
                "quality": round(quality, 3),
                "embedding": [round(float(x), 6) for x in vector]}

    @app.get("/api/identities/duplicates")
    def duplicate_identities(limit: int = 20) -> list:
        """Identity pairs that look like one person enrolled twice."""
        return engine.gallery.duplicate_candidates(limit)

    @app.post("/api/identities/{identity_id}/merge")
    def merge_identity(identity_id: int, payload: MergePayload) -> dict:
        result = engine.gallery.merge_identities(
            identity_id, payload.into, force=payload.force)
        if not result.get("ok"):
            reason = result.get("reason", "merge refused")
            # 409, not 400: the request is well formed, it conflicts with what
            # the gallery believes. The body carries the measured similarity so
            # the UI can show the operator what it is asking them to override.
            status = 404 if "not found" in reason else 409
            raise HTTPException(status, detail=result)
        engine.bus.publish(Event(
            type="identity.merged", camera_id="",
            data={k: result[k] for k in
                  ("source", "target", "label", "similarity", "forced",
                   "embeddings_moved", "sightings_moved")}))
        return result

    @app.delete("/api/identities/{identity_id}")
    def delete_identity(identity_id: int) -> dict:
        if not engine.gallery.delete_identity(identity_id):
            raise HTTPException(404, "identity not found")
        return {"deleted": identity_id}

    @app.get("/api/cameras")
    def cameras() -> list:
        out = []
        for cam in engine.camera_store.list():
            out.append(camera_public(cam, engine.workers.get(cam.id)))
        return out

    @app.post("/api/cameras", status_code=201)
    def add_camera(payload: CameraPayload) -> dict:
        data = payload.model_dump(exclude_none=True)
        if not data.get("id"):
            raise HTTPException(400, "id is required")
        try:
            cam = CameraConfig.model_validate(data)
            cam.source()  # reject "no url, no host, no webcam" before storing
            # Resolve the per-camera gates here too. Without this an inverted
            # enroll/match pair was only caught when the worker was built,
            # which surfaced as a 500 "stored but failed to start" instead of
            # telling the user what was wrong with what they typed.
            engine.cfg.recognition.merged(cam.tuning)
        except (ValidationError, ValueError) as exc:
            raise HTTPException(400, str(exc))
        try:
            engine.camera_store.add(cam)
        except ValueError as exc:
            raise HTTPException(409, str(exc))
        try:
            engine.add_camera(cam)
        except Exception as exc:
            # Never leave the store describing a camera the engine refused —
            # the two would disagree until the next restart.
            engine.camera_store.delete(cam.id)
            raise HTTPException(500, f"camera stored but failed to start: {exc}")
        return camera_public(cam, engine.workers.get(cam.id))

    @app.patch("/api/cameras/{camera_id}")
    def edit_camera(camera_id: str, payload: CameraPayload) -> dict:
        fields = payload.model_dump(exclude_none=True)
        fields.pop("id", None)
        try:
            if "tuning" in fields:
                engine.cfg.recognition.merged(
                    CameraTuning.model_validate(fields["tuning"]))
            cam = engine.camera_store.update(camera_id, fields)
        except (ValidationError, ValueError) as exc:
            raise HTTPException(400, str(exc))
        if cam is None:
            raise HTTPException(404, f"unknown camera '{camera_id}'")
        engine.restart_camera(cam)  # a changed URL needs a fresh connection
        return camera_public(cam, engine.workers.get(cam.id))

    @app.delete("/api/cameras/{camera_id}")
    def delete_camera(camera_id: str) -> dict:
        if not engine.camera_store.delete(camera_id):
            raise HTTPException(404, f"unknown camera '{camera_id}'")
        engine.remove_camera(camera_id)
        return {"deleted": camera_id}

    @app.post("/api/cameras/{camera_id}/commission")
    def start_commission(camera_id: str,
                         payload: CommissionPayload) -> dict:
        """Begin a placement check: watch this camera for N seconds and judge
        whether faces here are good enough to enrol."""
        worker = worker_or_404(camera_id)
        # The camera's own gate, not the global one - the whole point is to
        # judge this view against the threshold it will actually run under.
        worker.commission = CommissionRun(
            camera_id, worker.rcfg.min_enroll_quality, payload.seconds)
        return worker.commission.report()

    @app.get("/api/cameras/{camera_id}/commission")
    def commission_result(camera_id: str) -> dict:
        worker = worker_or_404(camera_id)
        if worker.commission is None:
            raise HTTPException(404, "no placement check has been run")
        return worker.commission.report()

    @app.delete("/api/cameras/{camera_id}/commission")
    def cancel_commission(camera_id: str) -> dict:
        worker = worker_or_404(camera_id)
        if worker.commission is not None:
            worker.commission.cancel()
        return {"cancelled": camera_id}

    @app.post("/api/cameras/test")
    def test_camera(payload: CameraPayload) -> dict:
        """Try a camera WITHOUT saving it - the UI's Test button.

        Deliberately a sync def so FastAPI runs it in the threadpool:
        cv2.VideoCapture blocks hard and a wrong host can hang for the full
        FFmpeg timeout, which would stall the whole event loop.
        """
        from .capture import probe_source

        data = payload.model_dump(exclude_none=True)
        data.setdefault("id", "__test__")
        try:
            cam = CameraConfig.model_validate(data)
            source = cam.source()
        except (ValidationError, ValueError) as exc:
            return {"ok": False, "error": str(exc)}
        return probe_source(source, cam.max_width)

    @app.get("/api/cameras/{camera_id}/frame.jpg")
    def frame(camera_id: str, width: int = 0, quality: int = 0) -> Response:
        """The latest frame, optionally re-encoded smaller.

        `width`/`quality` exist for the live relay, which sends several frames
        a second up a shop's uplink and cannot afford the full-size picture the
        dashboard uses. The re-encode happens here rather than in the agent
        because this process already has OpenCV open and the frame decoded;
        shipping a scaler into the agent would be the same work done twice.

        Done on demand, not on every frame: a camera nobody is watching must
        not pay for a second encode it will never use.
        """
        jpeg = worker_or_404(camera_id).latest_jpeg()
        if jpeg is None:
            raise HTTPException(503, "no frame yet")
        if width > 0 or quality > 0:
            jpeg = _reencode(jpeg, width, quality) or jpeg
        return Response(jpeg, media_type="image/jpeg")

    @app.get("/api/cameras/{camera_id}/stream.mjpeg")
    async def stream(camera_id: str) -> StreamingResponse:
        worker = worker_or_404(camera_id)

        async def generate():
            boundary = b"--frame\r\nContent-Type: image/jpeg\r\n\r\n"
            # Stop when the camera is deleted or its worker dies - otherwise a
            # removed camera leaves this generator running for the life of the
            # process, holding a reference to a worker nothing else can see.
            # Driven by the camera, not a timer: a frame goes out when the
            # capture thread has one newer than the last one sent, so nothing
            # is sent twice and nothing waits on the recognition pipeline.
            # Capped at 15 fps - the office cameras' own rate - so a viewer
            # never costs more encodes than the camera produces pictures.
            last_ts, min_gap, sent_at = 0.0, 1.0 / 15, 0.0
            while engine.workers.get(camera_id) is worker and worker.is_alive():
                now = time.time()
                if now - sent_at < min_gap:
                    await asyncio.sleep(min_gap - (now - sent_at))
                    continue
                jpeg, ts = worker.latest_jpeg_since(last_ts)
                if jpeg is None:
                    await asyncio.sleep(0.02)
                    continue
                last_ts, sent_at = ts, time.time()
                yield boundary + jpeg + b"\r\n"

        return StreamingResponse(
            generate(),
            media_type="multipart/x-mixed-replace; boundary=frame")

    return app