Update app.py

app.py

@@ -6,7 +6,6 @@ from diffusers import AutoPipelineForText2Image
 from io import BytesIO
 import gradio as gr
 import ray
-from ray.util import ActorPool
 
 ray.init()
 
@@ -44,21 +43,22 @@ class ModelActor:
             print(f"[{process_id}] Error generating image for {prompt_name}: {e}")
             return None
 
-def create_actor_pool(num_actors):
-    return ActorPool([ModelActor.remote() for _ in range(num_actors)])
-
-async def queue_api_calls(sentence_mapping, character_dict, selected_style, pool):
+async def queue_api_calls(sentence_mapping, character_dict, selected_style):
     print(f"queue_api_calls invoked with sentence_mapping: {sentence_mapping}, character_dict: {character_dict}, selected_style: {selected_style}")
     prompts = []
 
     for paragraph_number, sentences in sentence_mapping.items():
         combined_sentence = " ".join(sentences)
         print(f"combined_sentence for paragraph {paragraph_number}: {combined_sentence}")
-        prompt = generate_prompt(combined_sentence, sentence_mapping, character_dict, selected_style)
+        prompt = generate_prompt(combined_sentence, character_dict, selected_style)
         prompts.append((paragraph_number, prompt))
         print(f"Generated prompt for paragraph {paragraph_number}: {prompt}")
 
-    tasks = [pool.submit(lambda actor, p=prompt, pn=f"Prompt {paragraph_number}": actor.generate_image.remote(p, pn)) for paragraph_number, prompt in prompts]
+    num_prompts = len(prompts)
+    num_actors = min(num_prompts, 20)  # Limit to a maximum of 20 actors
+    model_actors = [ModelActor.remote() for _ in range(num_actors)]
+
+    tasks = [model_actors[i % num_actors].generate_image.remote(prompt, f"Prompt {paragraph_number}") for i, (paragraph_number, prompt) in enumerate(prompts)]
     print("Tasks created for image generation.")
 
     responses = await asyncio.gather(*[asyncio.to_thread(ray.get, task) for task in tasks])
@@ -77,8 +77,7 @@ def process_prompt(sentence_mapping, character_dict, selected_style):
         asyncio.set_event_loop(loop)
     print("Event loop created.")
 
-    pool = create_actor_pool(min(20, max(1, len(sentence_mapping))))  # Create pool with dynamic size
-    cmpt_return = loop.run_until_complete(queue_api_calls(sentence_mapping, character_dict, selected_style, pool))
+    cmpt_return = loop.run_until_complete(queue_api_calls(sentence_mapping, character_dict, selected_style))
     print(f"process_prompt completed with return value: {cmpt_return}")
     return cmpt_return