Merge a795eff4d5 into 65045730a6

comfy_extras/nodes_lt.py

@@ -338,8 +338,25 @@ class LTXVAddGuide(io.ComfyNode):
         noise_mask = get_noise_mask(latent)
 
         _, _, latent_length, latent_height, latent_width = latent_image.shape
+
+        # For mid-video multi-frame guides, prepend+strip a throwaway first frame so the VAE's "first latent = 1 pixel frame" asymmetry lands on the discarded slot
+        time_scale_factor = scale_factors[0]
+        num_frames_to_keep = ((image.shape[0] - 1) // time_scale_factor) * time_scale_factor + 1
+        resolved_frame_idx = frame_idx
+        if frame_idx < 0:
+            _, num_keyframes = get_keyframe_idxs(positive)
+            resolved_frame_idx = max((latent_length - num_keyframes - 1) * time_scale_factor + 1 + frame_idx, 0)
+        causal_fix = resolved_frame_idx == 0 or num_frames_to_keep == 1
+
+        if not causal_fix:
+            image = torch.cat([image[:1], image], dim=0)
+
         image, t = cls.encode(vae, latent_width, latent_height, image, scale_factors)
 
+        if not causal_fix:
+            t = t[:, :, 1:, :, :]
+            image = image[1:]
+
         frame_idx, latent_idx = cls.get_latent_index(positive, latent_length, len(image), frame_idx, scale_factors)
         assert latent_idx + t.shape[2] <= latent_length, "Conditioning frames exceed the length of the latent sequence."
 
@@ -352,6 +369,7 @@ class LTXVAddGuide(io.ComfyNode):
             t,
             strength,
             scale_factors,
+            causal_fix=causal_fix,
         )
 
         # Track this guide for per-reference attention control.