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_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")