fix: save full conditioning (node 132) instead of text-only (nodes 6/7)

app.py

@@ -1003,33 +1003,38 @@ def generate_chunk_handler(
             api_wf[sampler_id]["inputs"]["add_noise"]  = "enable"
             api_wf[sampler_id]["inputs"]["noise_seed"] = final_seed
 
-            # Save cond from nodes 6 (pos) and 7 (neg)
+            # Save cond from node 132 (BerniniConditioning) to capture full visual context latents
+            # Find the actual original connections for the sampler
+            orig_pos = api_wf[sampler_id]["inputs"]["positive"]
+            orig_neg = api_wf[sampler_id]["inputs"]["negative"]
             api_wf["901"] = {"class_type": "BerniniChunkSaveCond", "inputs": {
-                "positive":   ["6", 0],
-                "negative":   ["7", 0],
+                "positive":   orig_pos,
+                "negative":   orig_neg,
                 "session_id": session_id,
             }}
 
             # Save output latent
-            pos_ref = ["901", 0]
-            neg_ref = ["901", 1]
-
             api_wf["902"] = {"class_type": "BerniniChunkSaveLatent", "inputs": {
                 "samples":    [sampler_id, 0],
                 "session_id": session_id,
             }}
+            # On step 0, sampler keeps its original positive/negative connections to node 132
+            
         else:
             # Step k>0: no noise, load saved cond + latent
             api_wf[sampler_id]["inputs"]["add_noise"]  = "disable"
 
-            # Load saved conditioning (fallback to fresh)
+            # Load saved conditioning (fallback to node 132 if file missing)
+            orig_pos = api_wf[sampler_id]["inputs"]["positive"]
+            orig_neg = api_wf[sampler_id]["inputs"]["negative"]
             api_wf["901"] = {"class_type": "BerniniChunkLoadCond", "inputs": {
-                "fallback_pos": ["6", 0],
-                "fallback_neg": ["7", 0],
+                "fallback_pos": orig_pos,
+                "fallback_neg": orig_neg,
                 "session_id":    session_id,
             }}
-            pos_ref = ["901", 0]
-            neg_ref = ["901", 1]
+            # Overwrite sampler inputs with the loaded conditioning
+            api_wf[sampler_id]["inputs"]["positive"] = ["901", 0]
+            api_wf[sampler_id]["inputs"]["negative"] = ["901", 1]
 
             # Load previous latent, feed into sampler
             api_wf["902"] = {"class_type": "BerniniChunkLoadLatent", "inputs": {
@@ -1044,10 +1049,6 @@ def generate_chunk_handler(
                 "session_id": session_id,
             }}
 
-        # Wire positive/negative from chunk nodes
-        api_wf[sampler_id]["inputs"]["positive"] = pos_ref
-        api_wf[sampler_id]["inputs"]["negative"] = neg_ref
-
         # Output node for this step — determines what the executor returns
         exec_node = NODE_OUTPUT if is_final else (902 if chunk_idx == 0 else 903)
         output_video = _execute_workflow(api_wf, exec_node)