fix(sampler): H3 scenes continue from the previous one, not just next to it

H3 has no latent conditioning, so a carried tail was noise it could overwrite:
the seam matched and the rest of the shot knew nothing about the scene before it.
The previous scene's last latent frame becomes this scene's frame-0 pin.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

samplers.py

@@ -4940,6 +4940,42 @@ class FunPackLTXAVSceneChainSampler:
                                           aug=None if aug >= 1.0 else aug)
         return positive, True
 
+    def _h3_has_first_frame_pin(self, conditioning):
+        pins = self._conditioning_value(conditioning, "minimax_keyframes") or []
+        return any(int(p.get("resolved_frame_index", -1)) == 0 for p in pins)
+
+    def _h3_continuation_pin(self, positive, carry_source):
+        """Continue an H3 scene from the previous one, the only way H3 can be told to.
+
+        LTX chains through the LATENT: the previous scene's tail is copied into the leading
+        frames and masked out of denoising, and the model treats those frames as context.
+        H3 has no latent conditioning at all — a pre-filled frame is, in its own terms, just
+        noise it is free to overwrite. The mask still holds those pixels in the output, so
+        the seam looked right while the rest of the shot was generated knowing nothing about
+        what came before: the chain produced a batch of unrelated clips.
+
+        The previous scene's last latent frame becomes this scene's frame-0 keyframe pin,
+        which is exactly the conditioning an i2v anchor uses. No VAE round trip: the frame is
+        already in latent space, and the pin path takes latents (the guide path already
+        relies on that). Skipped when something already pinned frame 0 — an explicit anchor
+        or a wired first_frame outranks a carried tail.
+
+        Returns (positive, applied).
+        """
+        if carry_source is None or self._h3_has_first_frame_pin(positive):
+            return positive, False
+        try:
+            video = self._latent_tensors(carry_source)[0]
+            if getattr(video, "ndim", 0) < 5 or int(video.shape[2]) < 1:
+                return positive, False
+            frame = video[:1, :, -1:].clone()
+        except Exception as error:  # noqa: BLE001
+            print(f"[FunPackSceneChain] H3: continuation pin skipped — {error}.")
+            return positive, False
+        positive = self._h3_add_keyframes(
+            positive, [{"resolved_frame_index": 0, "latent": frame}], self._h3_frame_count)
+        return positive, True
+
     def _h3_external_pins(self, conditioning):
         """Rescue the keyframe pins from a MiniMax H3 Image to Video node's conditioning.
 
@@ -6714,6 +6750,14 @@ class FunPackLTXAVSceneChainSampler:
                         run_mechanisms.append(f"h3_wired_keyframes({'+'.join(_pin_labels)})")
                     if "first" in _pin_labels:
                         _h3_opening_anchored = True
+                # Nothing claimed frame 0 and a previous scene exists: continue from its last
+                # frame. Without this the carried latent tail is not conditioning on H3 — the
+                # seam matched and the rest of the shot knew nothing about the scene before it.
+                if _carry_source is not None:
+                    scene_positive, _continued = self._h3_continuation_pin(
+                        scene_positive, _carry_source)
+                    if _continued:
+                        run_mechanisms.append("h3_continuation_pin")
 
             # ref2va reference blocks. Applied after the chunk is final because the blocks are
             # sized against this scene's canvas, and to every scene branch (fresh / anchored /

tests/test_minimax_h3_sampler.py

@@ -556,3 +556,52 @@ def test_a_wired_first_frame_overrides_the_timeline_anchor_on_frame_zero():
     out, _labels = node._apply_h3_external_pins(positive, pins, scene_index=0, scene_count=1)
     kfs = out[0][1]["minimax_keyframes"]
     assert len(kfs) == 1 and kfs[0]["latent"] is not anchor
+
+
+# ── continuing a scene from the one before it ────────────────────────────────
+
+def _pins(cond):
+    return (cond[0][1] or {}).get("minimax_keyframes") or []
+
+
+def test_a_continuation_scene_is_pinned_to_the_previous_scenes_last_frame():
+    """H3 has no latent conditioning: a carried tail is, in the model's terms, noise it may
+    overwrite. Without a pin the seam matched and the rest of the shot knew nothing about the
+    scene before it — the chain produced unrelated clips."""
+    node = h3_node()
+    previous = av_latent(video_t=37)
+    previous["samples"].unbind()[0][:, :, -1] = 7.0        # a mark only the last frame has
+    positive = [[torch.zeros(1, 8, 16), {}]]
+
+    out, applied = node._h3_continuation_pin(positive, previous)
+    assert applied is True
+    pins = _pins(out)
+    assert [p["resolved_frame_index"] for p in pins] == [0]
+    latent = pins[0]["latent"]
+    assert latent.shape == (1, 24, 1, 48, 84)              # exactly one latent frame
+    assert float(latent.max()) == 7.0                      # and it is the LAST one
+
+
+def test_an_explicit_anchor_outranks_the_carried_tail():
+    """An anchor image (or a wired first_frame) is the user saying where this scene starts;
+    the tail is inferred. Two pins cannot share frame 0."""
+    node = h3_node()
+    anchored = [[torch.zeros(1, 8, 16), {"minimax_keyframes": [
+        {"resolved_frame_index": 0, "latent": torch.full((1, 24, 1, 48, 84), 3.0)}]}]]
+    out, applied = node._h3_continuation_pin(anchored, av_latent())
+    assert applied is False
+    assert float(_pins(out)[0]["latent"].max()) == 3.0
+
+
+def test_the_opening_scene_has_nothing_to_continue_from():
+    node = h3_node()
+    positive = [[torch.zeros(1, 8, 16), {}]]
+    out, applied = node._h3_continuation_pin(positive, None)
+    assert applied is False and _pins(out) == []
+
+
+def test_an_unreadable_carry_source_skips_rather_than_failing_the_render():
+    node = h3_node()
+    positive = [[torch.zeros(1, 8, 16), {}]]
+    out, applied = node._h3_continuation_pin(positive, {"samples": torch.zeros(1, 24, 4)})
+    assert applied is False and _pins(out) == []