Update app.py

app.py

@@ -4,7 +4,7 @@ from generate_prompts import generate_prompt
 from diffusers import AutoPipelineForText2Image
 from io import BytesIO
 import gradio as gr
-from multiprocessing import Pool, cpu_count
+from concurrent.futures import ThreadPoolExecutor
 
 # Load the model once outside of the function
 print("Loading the model...")
@@ -35,7 +35,7 @@ def generate_image(prompt, prompt_name):
         print(f"Error generating image for {prompt_name}: {e}")
         return None
 
-async def queue_api_calls(sentence_mapping, character_dict, selected_style):
+async def queue_api_calls(sentence_mapping, character_dict, selected_style, batch_size=5):
     print(f"queue_api_calls invoked with sentence_mapping: {sentence_mapping}, character_dict: {character_dict}, selected_style: {selected_style}")
     prompts = []
 
@@ -47,13 +47,21 @@ async def queue_api_calls(sentence_mapping, character_dict, selected_style):
         prompts.append((paragraph_number, prompt))
         print(f"Generated prompt for paragraph {paragraph_number}: {prompt}")
 
-    # Use multiprocessing Pool to generate images in parallel
-    with Pool(cpu_count()) as pool:
-        tasks = [(prompt, f"Prompt {paragraph_number}") for paragraph_number, prompt in prompts]
-        responses = pool.starmap(generate_image, tasks)
-        print("Responses received from image generation tasks.")
+    # Set max_workers to the total number of prompts
+    max_workers = min(batch_size, len(prompts))
+
+    # Generate images for each prompt in parallel using threading
+    images = {}
+    with ThreadPoolExecutor(max_workers=max_workers) as executor:
+        loop = asyncio.get_running_loop()
+        for i in range(0, len(prompts), batch_size):
+            batch_prompts = prompts[i:i+batch_size]
+            tasks = [loop.run_in_executor(executor, generate_image, prompt, f"Prompt {paragraph_number}") for paragraph_number, prompt in batch_prompts]
+            print("Tasks created for image generation.")
+            responses = await asyncio.gather(*tasks)
+            print("Responses received from image generation tasks.")
+            images.update({paragraph_number: response for (paragraph_number, _), response in zip(batch_prompts, responses)})
 
-    images = {paragraph_number: response for (paragraph_number, _), response in zip(prompts, responses)}
     print(f"Images generated: {images}")
     return images