fix(v1): wire model confidence, explicit source mode, unique event ids

A: PoseAdapter.set_confidence_threshold is applied on start, so the
   settings model-confidence field actually affects inference.
B: config source.mode ('stream'|'replay') is explicit; app no longer
   guesses the source type from the URL prefix.
C: FallStateMachine takes a session_id and from_config generates a
   unique one per run, so event ids never collide across restarts
   (no screenshot overwrite or duplicate JSONL identity in a day).

51 tests pass.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

v1/tests/test_config.py

@@ -56,6 +56,40 @@ def test_load_config_rejects_embedded_source_address(tmp_path):
         load_config(config_file)
 
 
+def test_source_mode_defaults_to_stream(tmp_path, monkeypatch):
+    config_file = tmp_path / "config.json"
+    _write_config(
+        config_file,
+        {"id": "lobby-camera-01", "rtsp_url_env": "SILVER_POSE_RTSP_URL"},
+    )
+    monkeypatch.setenv("SILVER_POSE_RTSP_URL", "rtsp://demo.invalid/live")
+
+    assert load_config(config_file).source_mode == "stream"
+
+
+def test_source_mode_replay_is_parsed(tmp_path, monkeypatch):
+    config_file = tmp_path / "config.json"
+    _write_config(
+        config_file,
+        {"id": "lobby-camera-01", "rtsp_url_env": "SILVER_POSE_RTSP_URL", "mode": "replay"},
+    )
+    monkeypatch.setenv("SILVER_POSE_RTSP_URL", "rtsp://demo.invalid/live")
+
+    assert load_config(config_file).source_mode == "replay"
+
+
+def test_invalid_source_mode_is_rejected(tmp_path, monkeypatch):
+    config_file = tmp_path / "config.json"
+    _write_config(
+        config_file,
+        {"id": "lobby-camera-01", "rtsp_url_env": "SILVER_POSE_RTSP_URL", "mode": "loop"},
+    )
+    monkeypatch.setenv("SILVER_POSE_RTSP_URL", "rtsp://demo.invalid/live")
+
+    with pytest.raises(ConfigError, match="mode"):
+        load_config(config_file)
+
+
 def test_runtime_config_version_is_stable_and_excludes_rtsp_address(tmp_path, monkeypatch):
     config_file = tmp_path / "config.json"
     _write_config(

v1/tests/test_fall_state.py

@@ -82,6 +82,25 @@ def test_confirmation_window_must_remain_within_customer_target():
         )
 
 
+def test_session_id_makes_event_ids_unique_across_runs():
+    run_a = FallStateMachine(
+        confirm_window_seconds=1.0, recovery_window_seconds=2.0,
+        config_version="cfg", session_id="run-a",
+    )
+    run_b = FallStateMachine(
+        confirm_window_seconds=1.0, recovery_window_seconds=2.0,
+        config_version="cfg", session_id="run-b",
+    )
+    run_a.update("P-0001", Evidence(True, True), now=0.0)
+    event_a = run_a.update("P-0001", Evidence(True, True), now=1.0)
+    run_b.update("P-0001", Evidence(True, True), now=0.0)
+    event_b = run_b.update("P-0001", Evidence(True, True), now=1.0)
+
+    assert event_a[0].event_id != event_b[0].event_id
+    assert "run-a" in event_a[0].event_id
+    assert "run-b" in event_b[0].event_id
+
+
 def test_each_track_has_an_independent_confirmation_window():
     machine = FallStateMachine(
         confirm_window_seconds=1.0,

v1/tests/test_pipeline.py

@@ -119,3 +119,18 @@ def test_pipeline_from_config_uses_runtime_version_for_confirmed_event():
     result = pipeline.process(_packet(1.1))
 
     assert result.events[0].config_version == config.runtime_config_version
+
+
+def test_from_config_gives_each_run_a_unique_event_id():
+    config = _config()
+
+    def confirm(pipeline):
+        pipeline.process(_packet(0.0))
+        pipeline.process(_packet(0.1))
+        return pipeline.process(_packet(1.1)).events[0].event_id
+
+    frames = [(_pose(),), (_pose(horizontal=True),), (_pose(horizontal=True),)]
+    first = confirm(FallPipeline.from_config(config, _SequencePoseAdapter(list(frames))))
+    second = confirm(FallPipeline.from_config(config, _SequencePoseAdapter(list(frames))))
+
+    assert first != second

v1/tests/test_pose.py

@@ -46,6 +46,61 @@ def test_from_results_extracts_person_box_confidence_and_seventeen_keypoints():
     assert poses[0].keypoints[5].confidence == 0.9
 
 
+class _RecordingPoseModel:
+    task = "pose"
+    names = {0: "person"}
+
+    class model:
+        kpt_shape = (17, 3)
+
+    def __init__(self):
+        self.calls = []
+
+    def __call__(self, image, conf, verbose):
+        self.calls.append(conf)
+
+        class _Empty:
+            names = {0: "person"}
+
+            class boxes:
+                xyxy = []
+                conf = []
+                cls = []
+
+            class keypoints:
+                data = []
+
+        return _Empty()
+
+
+def test_set_confidence_threshold_is_forwarded_to_inference(tmp_path):
+    weights = tmp_path / "pose.pt"
+    weights.write_bytes(b"fake-weights")
+    expected_sha256 = hashlib.sha256(weights.read_bytes()).hexdigest()
+    model = _RecordingPoseModel()
+    adapter = PoseAdapter(
+        weights, expected_sha256, confidence_threshold=0.25, model_factory=lambda _p: model
+    )
+
+    adapter.set_confidence_threshold(0.6)
+    adapter.infer(np.zeros((10, 10, 3), dtype=np.uint8))
+
+    assert adapter.confidence_threshold == 0.6
+    assert model.calls == [0.6]
+
+
+def test_set_confidence_threshold_rejects_out_of_range(tmp_path):
+    weights = tmp_path / "pose.pt"
+    weights.write_bytes(b"fake-weights")
+    expected_sha256 = hashlib.sha256(weights.read_bytes()).hexdigest()
+    adapter = PoseAdapter(
+        weights, expected_sha256, model_factory=lambda _p: _RecordingPoseModel()
+    )
+
+    with pytest.raises(ModelValidationError):
+        adapter.set_confidence_threshold(1.5)
+
+
 def test_pose_adapter_rejects_non_pose_model_after_hash_validation(tmp_path):
     model_path = tmp_path / "model.pt"
     model_path.write_bytes(b"model bytes")