Update app.py

app.py

@@ -26,7 +26,8 @@ qwen_model = Qwen2VLForConditionalGeneration.from_pretrained(
 ).to(device).eval()
 qwen_processor = AutoProcessor.from_pretrained("prithivMLmods/JSONify-Flux", trust_remote_code=True)
 
-enhancer_long = pipeline("summarization", model="prithivMLmods/t5-Flan-Prompt-Enhance", device=device)
+# Prompt Enhancer
+enhancer_long = pipeline("summarization", model="gokaygokay/Lamini-Prompt-Enchance-Long", device=device)
 
 MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 2048
@@ -96,7 +97,6 @@ def process_workflow(image, text_prompt, use_enhancer, seed, randomize_seed, wid
     
     generator = torch.Generator(device=device).manual_seed(seed)
     
-    # Clear GPU cache before generating the image
     torch.cuda.empty_cache()
     
     try:
@@ -138,12 +138,34 @@ title = """<h1 align="center">FLUX.1-dev with Qwen2VL Captioner and Prompt Enhan
 <p><center>
 <a href="https://huggingface.co/black-forest-labs/FLUX.1-dev" target="_blank">[FLUX.1-dev Model]</a>
 <a href="https://huggingface.co/prithivMLmods/JSONify-Flux" target="_blank">[JSONify Flux Model]</a>
-<a href="https://huggingface.co/prithivMLmods/t5-Flan-Prompt-Enhance" target="_blank">[Prompt Enhancer t5]</a>
+<a href="https://huggingface.co/gokaygokay/Lamini-Prompt-Enchance-Long" target="_blank">[Prompt Enhancer Long]</a>
 <p align="center">Create long prompts from images or enhance your short prompts with prompt enhancer</p>
 </center></p>
 """
 
 with gr.Blocks(css=custom_css) as demo:
+    
+    # Sidebar with About details
+    with gr.Sidebar(label="Parameters", open=True):
+        gr.Markdown(
+            """
+            ### About
+            
+            #### FLUX.1-Dev
+            FLUX.1 [dev] is a 12 billion parameter rectified flow transformer capable of generating images from text descriptions.  
+            FLUX.1 [dev] is an open-weight, guidance-distilled model for non-commercial applications. Directly distilled from FLUX.1 [pro], FLUX.1 [dev] obtains similar quality and prompt adherence capabilities, while being more efficient than a standard model of the same size.  
+            [FLUX.1-dev on Hugging Face](https://huggingface.co/black-forest-labs/FLUX.1-dev)
+            
+            #### JSONify-Flux
+            JSONify-Flux is a multimodal image-text model based on the dataset of flux-generated images and architectures and built upon the Qwen2VL architecture. The JSON-base instruction has been manually removed to avoid JSON formatted captions.  
+            [JSONify-Flux on Hugging Face](https://huggingface.co/prithivMLmods/JSONify-Flux)
+            
+            #### t5-Flan-Prompt-Enhance
+            t5-Flan-Prompt-Enhance is a prompt summarization model based on flux synthetic prompts designed to enhance the richness of prompt details.  
+            [t5-Flan-Prompt-Enhance on Hugging Face](https://huggingface.co/prithivMLmods/t5-Flan-Prompt-Enhance)
+            """
+        )
+    
     gr.HTML(title)
     
     with gr.Row():
@@ -159,9 +181,9 @@ with gr.Blocks(css=custom_css) as demo:
                 width = gr.Slider(label="Width", minimum=256, maximum=MAX_IMAGE_SIZE, step=32, value=512)
                 height = gr.Slider(label="Height", minimum=256, maximum=MAX_IMAGE_SIZE, step=32, value=512)
                 guidance_scale = gr.Slider(label="Guidance Scale", minimum=1, maximum=15, step=0.1, value=3.5)
-                num_inference_steps = gr.Slider(label="Inference Steps", minimum=1, maximum=50, step=1, value=32)
+                num_inference_steps = gr.Slider(label="Inference Steps", minimum=1, maximum=50, step=1, value=20)
             
-            generate_btn = gr.Button("Generate Image Prompt", elem_classes="submit-btn")
+            generate_btn = gr.Button("Generate Image + Prompt Enhanced", elem_classes="submit-btn")
         
         with gr.Column(scale=1):
             with gr.Group(elem_classes="output-group"):
@@ -178,4 +200,4 @@ with gr.Blocks(css=custom_css) as demo:
         outputs=[output_image, final_prompt, used_seed]
     )
 
-demo.launch(debug=True)
+demo.launch(debug=True)