Update app.py

app.py

@@ -248,22 +248,27 @@ def inference(
         if invert_init_image and init_image is not None:
             init_image = invert_image(init_image)
 
-        out = pipe(
-            prompt=prompt,
-            negative_prompt=negative_prompt,
-            image=init_image,
-            control_image=control_image,
-            width=1024,
-            height=1024,
-            guidance_scale=float(guidance_scale),
-            controlnet_conditioning_scale=float(controlnet_conditioning_scale),
-            generator=generator,
-            strength=float(strength),
-            num_inference_steps=100,
-        )
-        
-        final_image = out.images[0]
-        
+        # Split the prompt into chunks to avoid truncation
+        prompt_chunks = split_prompt(prompt)
+        negative_prompt_chunks = split_prompt(negative_prompt)
+
+        final_image = None
+        for prompt_chunk, negative_prompt_chunk in zip(prompt_chunks, negative_prompt_chunks):
+            out = pipe(
+                prompt=prompt_chunk,
+                negative_prompt=negative_prompt_chunk,
+                image=init_image,
+                control_image=control_image,
+                width=1024,
+                height=1024,
+                guidance_scale=float(guidance_scale),
+                controlnet_conditioning_scale=float(controlnet_conditioning_scale),
+                generator=generator,
+                strength=float(strength),
+                num_inference_steps=100,
+            )
+            final_image = out.images[0] if final_image is None else final_image
+
         if invert_final_image:
             final_image = invert_image(final_image)
         
@@ -275,6 +280,27 @@ def inference(
         print(f"Unexpected error in inference: {str(e)}")
         return Image.new('RGB', (1024, 1024), color='white'), -1
 
+def split_prompt(prompt, max_length=77):
+    """Split the prompt into chunks that do not exceed the max_length."""
+    words = prompt.split()
+    chunks = []
+    current_chunk = []
+    current_length = 0
+
+    for word in words:
+        if current_length + len(word) + 1 > max_length:
+            chunks.append(" ".join(current_chunk))
+            current_chunk = [word]
+            current_length = len(word) + 1
+        else:
+            current_chunk.append(word)
+            current_length += len(word) + 1
+
+    if current_chunk:
+        chunks.append(" ".join(current_chunk))
+
+    return chunks
+
 def invert_init_image_display(image):
     if image is None:
         return None