Update app.py

app.py

@@ -4,17 +4,16 @@ from generate_prompts import generate_prompt
 from diffusers import AutoPipelineForText2Image
 from io import BytesIO
 import gradio as gr
-from concurrent.futures import ThreadPoolExecutor
 
 # Load the model once outside of the function
 print("Loading the model...")
 model = AutoPipelineForText2Image.from_pretrained("stabilityai/sdxl-turbo")
 print("Model loaded successfully.")
 
-def generate_image(prompt, prompt_name):
+async def generate_image(prompt, prompt_name):
     try:
         print(f"Generating response for {prompt_name} with prompt: {prompt}")
-        output = model(prompt=prompt, num_inference_steps=1, guidance_scale=0.0)
+        output = await asyncio.to_thread(model, prompt=prompt, num_inference_steps=1, guidance_scale=0.0)
         print(f"Output for {prompt_name}: {output}")
 
         # Check if the model returned images
@@ -35,7 +34,7 @@ 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, batch_size=5):
+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 = []
 
@@ -47,21 +46,13 @@ async def queue_api_calls(sentence_mapping, character_dict, selected_style, batc
         prompts.append((paragraph_number, prompt))
         print(f"Generated prompt for paragraph {paragraph_number}: {prompt}")
 
-    # 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)})
+    # Generate images for each prompt in parallel using asyncio
+    tasks = [generate_image(prompt, f"Prompt {paragraph_number}") for paragraph_number, prompt in prompts]
+    print("Tasks created for image generation.")
+    responses = await asyncio.gather(*tasks)
+    print("Responses received from image generation tasks.")
 
+    images = {paragraph_number: response for (paragraph_number, _), response in zip(prompts, responses)}
     print(f"Images generated: {images}")
     return images