Update app.py

app.py

@@ -31,6 +31,9 @@ from diffusers.utils import load_image
 
 import spaces
 
+# Import the prompt enhancer generator from enhance.py
+from enhance import generate as enhance_generate
+
 # Attempt to import loras from lora.py; otherwise use a default placeholder.
 try:
     from lora import loras
@@ -205,15 +208,16 @@ base_model = "black-forest-labs/FLUX.1-dev"
 taef1 = AutoencoderTiny.from_pretrained("madebyollin/taef1", torch_dtype=dtype).to(device)
 good_vae = AutoencoderKL.from_pretrained(base_model, subfolder="vae", torch_dtype=dtype).to(device)
 pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=dtype, vae=taef1).to(device)
-pipe_i2i = AutoPipelineForImage2Image.from_pretrained(base_model,
-                                                      vae=good_vae,
-                                                      transformer=pipe.transformer,
-                                                      text_encoder=pipe.text_encoder,
-                                                      tokenizer=pipe.tokenizer,
-                                                      text_encoder_2=pipe.text_encoder_2,
-                                                      tokenizer_2=pipe.tokenizer_2,
-                                                      torch_dtype=dtype
-                                                     )
+pipe_i2i = AutoPipelineForImage2Image.from_pretrained(
+    base_model,
+    vae=good_vae,
+    transformer=pipe.transformer,
+    text_encoder=pipe.text_encoder,
+    tokenizer=pipe.tokenizer,
+    text_encoder_2=pipe.text_encoder_2,
+    tokenizer_2=pipe.tokenizer_2,
+    torch_dtype=dtype,
+).to(device)
 MAX_SEED = 2**32-1
 
 pipe.flux_pipe_call_that_returns_an_iterable_of_images = flux_pipe_call_that_returns_an_iterable_of_images.__get__(pipe)
@@ -292,23 +296,32 @@ def generate_image_to_image(prompt_mash, image_input_path, image_strength, steps
     return final_image 
 
 @spaces.GPU(duration=100)
-def run_lora(prompt, image_input, image_strength, cfg_scale, steps, selected_index, randomize_seed, seed, width, height, lora_scale, progress=gr.Progress(track_tqdm=True)):
+def run_lora(prompt, image_input, image_strength, cfg_scale, steps, selected_index, randomize_seed, seed, width, height, lora_scale, use_enhancer, progress=gr.Progress(track_tqdm=True)):
+    # Check if a LoRA is selected.
     if selected_index is None:
         raise gr.Error("You must select a LoRA before proceeding.🧨")
     selected_lora = loras[selected_index]
     lora_path = selected_lora["repo"]
     trigger_word = selected_lora["trigger_word"]
-    if(trigger_word):
-        if "trigger_position" in selected_lora:
-            if selected_lora["trigger_position"] == "prepend":
-                prompt_mash = f"{trigger_word} {prompt}"
-            else:
-                prompt_mash = f"{prompt} {trigger_word}"
-        else:
+    # Prepare prompt by appending/prepending trigger word if available.
+    if trigger_word:
+        if "trigger_position" in selected_lora and selected_lora["trigger_position"] == "prepend":
             prompt_mash = f"{trigger_word} {prompt}"
+        else:
+            prompt_mash = f"{prompt} {trigger_word}"
     else:
         prompt_mash = prompt
 
+    # If prompt enhancer is enabled, stream the enhanced prompt.
+    enhanced_text = ""
+    if use_enhancer:
+        for enhanced_chunk in enhance_generate(prompt_mash):
+            enhanced_text = enhanced_chunk
+            # Yield intermediate output (no image yet, but update enhanced prompt textbox)
+            yield None, seed, gr.update(visible=False), enhanced_text
+        prompt_mash = enhanced_text  # Use final enhanced prompt for generation
+    # Else, leave prompt_mash as is.
+    
     with calculateDuration("Unloading LoRA"):
         pipe.unload_lora_weights()
         pipe_i2i.unload_lora_weights()
@@ -326,9 +339,9 @@ def run_lora(prompt, image_input, image_strength, cfg_scale, steps, selected_ind
         if randomize_seed:
             seed = random.randint(0, MAX_SEED)
             
-    if(image_input is not None):
+    if image_input is not None:
         final_image = generate_image_to_image(prompt_mash, image_input, image_strength, steps, cfg_scale, width, height, lora_scale, seed)
-        yield final_image, seed, gr.update(visible=False)
+        yield final_image, seed, gr.update(visible=False), enhanced_text
     else:
         image_generator = generate_image(prompt_mash, steps, seed, cfg_scale, width, height, lora_scale, progress)
         final_image = None
@@ -337,16 +350,16 @@ def run_lora(prompt, image_input, image_strength, cfg_scale, steps, selected_ind
             step_counter += 1
             final_image = image
             progress_bar = f'<div class="progress-container"><div class="progress-bar" style="--current: {step_counter}; --total: {steps};"></div></div>'
-            yield image, seed, gr.update(value=progress_bar, visible=True)
-        yield final_image, seed, gr.update(value=progress_bar, visible=False)
+            yield image, seed, gr.update(value=progress_bar, visible=True), enhanced_text
+        yield final_image, seed, gr.update(value=progress_bar, visible=False), enhanced_text
         
 def get_huggingface_safetensors(link):
     split_link = link.split("/")
-    if(len(split_link) == 2):
+    if len(split_link) == 2:
         model_card = ModelCard.load(link)
         base_model = model_card.data.get("base_model")
         print(base_model)
-        if((base_model != "black-forest-labs/FLUX.1-dev") and (base_model != "black-forest-labs/FLUX.1-schnell")):
+        if (base_model != "black-forest-labs/FLUX.1-dev") and (base_model != "black-forest-labs/FLUX.1-schnell"):
             raise Exception("Flux LoRA Not Found!")
         image_path = model_card.data.get("widget", [{}])[0].get("output", {}).get("url", None)
         trigger_word = model_card.data.get("instance_prompt", "")
@@ -355,30 +368,30 @@ def get_huggingface_safetensors(link):
         try:
             list_of_files = fs.ls(link, detail=False)
             for file in list_of_files:
-                if(file.endswith(".safetensors")):
+                if file.endswith(".safetensors"):
                     safetensors_name = file.split("/")[-1]
-                if (not image_url and file.lower().endswith((".jpg", ".jpeg", ".png", ".webp"))):
+                if not image_url and file.lower().endswith((".jpg", ".jpeg", ".png", ".webp")):
                     image_elements = file.split("/")
                     image_url = f"https://huggingface.co/{link}/resolve/main/{image_elements[-1]}"
         except Exception as e:
             print(e)
-            gr.Warning(f"You didn't include a link neither a valid Hugging Face repository with a *.safetensors LoRA")
-            raise Exception(f"You didn't include a link neither a valid Hugging Face repository with a *.safetensors LoRA")
+            gr.Warning("You didn't include a link nor a valid Hugging Face repository with a *.safetensors LoRA")
+            raise Exception("Invalid LoRA repository")
         return split_link[1], link, safetensors_name, trigger_word, image_url
     else:
         raise Exception("Invalid LoRA link format")
 
 def check_custom_model(link):
-    if(link.startswith("https://")):
-        if(link.startswith("https://huggingface.co") or link.startswith("https://www.huggingface.co")):
+    if link.startswith("https://"):
+        if link.startswith("https://huggingface.co") or link.startswith("https://www.huggingface.co"):
             link_split = link.split("huggingface.co/")
             return get_huggingface_safetensors(link_split[1])
-    else: 
+    else:
         return get_huggingface_safetensors(link)
 
 def add_custom_lora(custom_lora):
     global loras
-    if(custom_lora):
+    if custom_lora:
         try:
             title, repo, path, trigger_word, image = check_custom_model(custom_lora)
             print(f"Loaded custom LoRA: {repo}")
@@ -389,13 +402,13 @@ def add_custom_lora(custom_lora):
                 <img src="{image}" />
                 <div>
                     <h3>{title}</h3>
-                    <small>{"Using: <code><b>"+trigger_word+"</code></b> as the trigger word" if trigger_word else "No trigger word found. If there's a trigger word, include it in your prompt"}<br></small>
+                    <small>{"Using: <code><b>" + trigger_word + "</b></code> as the trigger word" if trigger_word else "No trigger word found. Include it in your prompt"}<br></small>
                 </div>
               </div>
             </div>
             '''
             existing_item_index = next((index for (index, item) in enumerate(loras) if item['repo'] == repo), None)
-            if(not existing_item_index):
+            if not existing_item_index:
                 new_item = {
                     "image": image,
                     "title": title,
@@ -409,8 +422,8 @@ def add_custom_lora(custom_lora):
         
             return gr.update(visible=True, value=card), gr.update(visible=True), gr.Gallery(selected_index=None), f"Custom: {path}", existing_item_index, trigger_word
         except Exception as e:
-            gr.Warning(f"Invalid LoRA: either you entered an invalid link, or a non-FLUX LoRA")
-            return gr.update(visible=True, value=f"Invalid LoRA: either you entered an invalid link, a non-FLUX LoRA"), gr.update(visible=False), gr.update(), "", None, ""
+            gr.Warning("Invalid LoRA: either you entered an invalid link or a non-FLUX LoRA")
+            return gr.update(visible=True, value="Invalid LoRA"), gr.update(visible=False), gr.update(), "", None, ""
     else:
         return gr.update(visible=False), gr.update(visible=False), gr.update(), "", None, ""
 
@@ -420,25 +433,25 @@ def remove_custom_lora():
 run_lora.zerogpu = True
 
 css = '''
-#gen_btn{height: 100%}
-#gen_column{align-self: stretch}
-#title{text-align: center}
-#title h1{font-size: 3em; display:inline-flex; align-items:center}
-#title img{width: 100px; margin-right: 0.5em}
-#gallery .grid-wrap{height: 10vh}
-#lora_list{background: var(--block-background-fill);padding: 0 1em .3em; font-size: 90%}
-.card_internal{display: flex;height: 100px;margin-top: .5em}
-.card_internal img{margin-right: 1em}
-.styler{--form-gap-width: 0px !important}
-#progress{height:30px}
-#progress .generating{display:none}
-.progress-container {width: 100%;height: 30px;background-color: #f0f0f0;border-radius: 15px;overflow: hidden;margin-bottom: 20px}
-.progress-bar {height: 100%;background-color: #4f46e5;width: calc(var(--current) / var(--total) * 100%);transition: width 0.5s ease-in-out}
+#gen_btn { height: 100%; }
+#gen_column { align-self: stretch; }
+#title { text-align: center; }
+#title h1 { font-size: 3em; display:inline-flex; align-items:center; }
+#title img { width: 100px; margin-right: 0.5em; }
+#gallery .grid-wrap { height: 10vh; }
+#lora_list { background: var(--block-background-fill); padding: 0 1em .3em; font-size: 90%; }
+.card_internal { display: flex; height: 100px; margin-top: .5em; }
+.card_internal img { margin-right: 1em; }
+.styler { --form-gap-width: 0px !important; }
+#progress { height:30px; }
+#progress .generating { display:none; }
+.progress-container { width: 100%; height: 30px; background-color: #f0f0f0; border-radius: 15px; overflow: hidden; margin-bottom: 20px; }
+.progress-bar { height: 100%; background-color: #4f46e5; width: calc(var(--current) / var(--total) * 100%); transition: width 0.5s ease-in-out; }
 '''
 
-with gr.Blocks(theme="YTheme/Minecraft", css=css, delete_cache=(60, 60)) as app:
+with gr.Blocks(theme=gr.themes.Base(), css=css, delete_cache=(60, 60)) as app:
     title = gr.HTML(
-        """<h1>FLUX LoRA DLC🥳</h1>""",
+        """<h1>Flux LoRA Generation</h1>""",
         elem_id="title",
     )
     selected_index = gr.State(None)
@@ -464,7 +477,7 @@ with gr.Blocks(theme="YTheme/Minecraft", css=css, delete_cache=(60, 60)) as app:
             custom_lora_info = gr.HTML(visible=False)
             custom_lora_button = gr.Button("Remove custom LoRA", visible=False)
         with gr.Column():
-            progress_bar = gr.Markdown(elem_id="progress",visible=False)
+            progress_bar = gr.Markdown(elem_id="progress", visible=False)
             result = gr.Image(label="Generated Image")
     with gr.Row():
         with gr.Accordion("Advanced Settings", open=False):
@@ -507,9 +520,11 @@ with gr.Blocks(theme="YTheme/Minecraft", css=css, delete_cache=(60, 60)) as app:
     gr.on(
         triggers=[generate_button.click, prompt.submit],
         fn=run_lora,
-        inputs=[prompt, input_image, image_strength, cfg_scale, steps, selected_index, randomize_seed, seed, width, height, lora_scale],
-        outputs=[result, seed, progress_bar]
+        inputs=[prompt, input_image, image_strength, cfg_scale, steps, selected_index, randomize_seed, seed, width, height, lora_scale, use_enhancer],
+        outputs=[result, seed, progress_bar, enhanced_prompt_box]
     )
-
+    with gr.Row():
+        gr.HTML("<div style='text-align:center; font-size:0.9em; margin-top:20px;'>Credits: <a href='https://ruslanmv.com' target='_blank'>ruslanmv.com</a></div>")
+    
 app.queue()
 app.launch(debug=True)