Update app.py

app.py

@@ -28,15 +28,13 @@ API_TOKEN = os.getenv("HF_READ_TOKEN")
 headers = {"Authorization": f"Bearer {API_TOKEN}"}
 timeout = 100
 
-NUM_IMAGES_PER_PROMPT = 2
-
 def flip_image(x):
     return np.fliplr(x)
 
 def clear():
   return None    
 
-def result(lora_id, prompt, is_negative=False, steps=28, cfg_scale=3.5, sampler="DPM++ 2M Karras", seed=-1, strength=100, width=896, height=1152):
+def query(lora_id, prompt, is_negative=False, steps=28, cfg_scale=3.5, sampler="DPM++ 2M Karras", seed=-1, strength=100, width=896, height=1152):
     if prompt == "" or prompt == None:
         return None
 
@@ -70,7 +68,6 @@ def result(lora_id, prompt, is_negative=False, steps=28, cfg_scale=3.5, sampler=
         "cfg_scale": cfg_scale,
         "seed": seed if seed != -1 else random.randint(1, 1000000000),
         "strength": strength,
-        "num_images_per_prompt": NUM_IMAGES_PER_PROMPT,
         "parameters": {
             "width": width,  # Pass the width to the API
             "height": height  # Pass the height to the API
@@ -115,80 +112,76 @@ with gr.Blocks(theme=theme, css=css, elem_id="app-container") as app:
         with gr.Column(elem_id="app-container"):
             with gr.Row():
                 with gr.Column(elem_id="prompt-container"):
-                    with gr.Group():
-                        with gr.Row():
-                            text_prompt = gr.Textbox(label="Image Prompt", placeholder="Enter a prompt here", lines=2, show_copy_button = True, elem_id="prompt-text-input")
-                        with gr.Row():
-                            with gr.Accordion("🎨 Lora trigger words", open=False):
-                            		gr.Markdown("""
-                                        - **sdxl-realistic**: szn style
-                                        - **Flux-Realism-FineDetailed**: Fine Detailed
-                                        - **Fashion-Hut-Modeling-LoRA**: Modeling
-                                        - **SD3.5-Large-Turbo-HyperRealistic-LoRA**: hyper realistic
-                                        - **Flux-Fine-Detail-LoRA**: Super Detail
-                                        - **SD3.5-Turbo-Realism-2.0-LoRA**: Turbo Realism
-                                        - **Canopus-LoRA-Flux-UltraRealism-2.0**: Ultra realistic 
-                                        - **extremely-detailed**: extremely detailed
-                                        - **SD3.5-Large-Photorealistic-LoRA**: photorealistic
-                                        - **Flux.1-Dev-LoRA-HDR-Realism**: HDR
-                                        - **prithivMLmods/Ton618-Epic-Realism-Flux-LoRA**: Epic Realism
-                                        - **john-singer-sargent-style**: John Singer Sargent Style
-                                        - **alphonse-mucha-style**: Alphonse Mucha Style
-                                        - **ultra-realistic-illustration**: ultra realistic illustration
-                                        - **eye-catching**: eye-catching
-                                        - **john-constable-style**: John Constable Style
-                                        - **film-noir**: in the style of FLMNR
-                                        - **flux-lora-pro-headshot**: PROHEADSHOT
-                            		""")                       
-                                
-                        with gr.Row():
-                            custom_lora = gr.Dropdown([" ", "jwu114/lora-sdxl-realistic", "prithivMLmods/Flux-Realism-FineDetailed", "prithivMLmods/Fashion-Hut-Modeling-LoRA", "prithivMLmods/SD3.5-Large-Turbo-HyperRealistic-LoRA", "prithivMLmods/Flux-Fine-Detail-LoRA", "prithivMLmods/SD3.5-Turbo-Realism-2.0-LoRA", "hugovntr/flux-schnell-realism", "fofr/sdxl-deep-down", "prithivMLmods/Canopus-LoRA-Flux-UltraRealism-2.0", "ntc-ai/SDXL-LoRA-slider.extremely-detailed", "prithivMLmods/Canopus-LoRA-Flux-FaceRealism", "prithivMLmods/SD3.5-Large-Photorealistic-LoRA", "prithivMLmods/Flux.1-Dev-LoRA-HDR-Realism", "prithivMLmods/Ton618-Epic-Realism-Flux-LoRA", "KappaNeuro/john-singer-sargent-style", "KappaNeuro/alphonse-mucha-style", "ntc-ai/SDXL-LoRA-slider.ultra-realistic-illustration", "ntc-ai/SDXL-LoRA-slider.eye-catching", "KappaNeuro/john-constable-style", "dvyio/flux-lora-film-noir", "dvyio/flux-lora-pro-headshot"], label="Custom LoRA",)
-                        with gr.Row():
-                            with gr.Accordion("⚙️ Advanced Settings", open=False, elem_id="settings-container"):
-                                negative_prompt = gr.Textbox(label="Negative Prompt", lines=5, placeholder="What should not be in the image", value=" (visible hand:1.3), (ugly:1.3), (duplicate:1.2), (morbid:1.1), (mutilated:1.1), out of frame, bad face, extra fingers, mutated hands, (poorly drawn hands:1.1), (poorly drawn face:1.3), (mutation:1.3), (deformed:1.3), blurry, (bad anatomy:1.1), (bad proportions:1.2), (extra limbs:1.1), cloned face, (disfigured:1.2), gross proportions, malformed limbs, (missing arms:1.1), (missing legs:1.1), (extra arms:1.2), (extra legs:1.2), fused fingers, too many fingers, (long neck:1.2), sketched by bad-artist, (bad-image-v2-39000:1.3) ")
-                                with gr.Row():
-                                    width = gr.Slider(label="Image Width", value=896, minimum=64, maximum=1216, step=32)
-                                    height = gr.Slider(label="Image Height", value=1152, minimum=64, maximum=1216, step=32)
-                                steps = gr.Slider(label="Sampling steps", value=50, minimum=1, maximum=100, step=1)
-                                cfg = gr.Slider(label="CFG Scale", value=3.5, minimum=1, maximum=20, step=0.5)
-                                method = gr.Radio(label="Sampling method", value="DPM++ 2M Karras", choices=["DPM++ 2M Karras", "DPM++ SDE Karras", "DEIS", "LMS", "DPM Adaptive", "DPM++ 2M", "DPM2 Ancestral", "DPM++ S", "DPM++ SDE", "DDPM", "DPM Fast", "dpmpp_2s_ancestral", "Euler", "Euler CFG PP", "Euler a", "Euler Ancestral", "Euler+beta", "Heun", "Heun PP2", "DDIM", "PLMS", "UniPC", "UniPC BH2"])
-                                strength = gr.Slider(label="Prompt Strength", value=100, minimum=0, maximum=100, step=1)
-                                num_images_per_prompt = gr.Slider(label="Images", minimum=1, maximum=5, step=1, value=2, interactive=True)
-                                seed = gr.Slider(label="Seed", value=-1, minimum=-1, maximum=1000000000, step=1)
-                    #with gr.Row():
-                        #with gr.Accordion("🫘Seed", open=False):
-                            #seed_output = gr.Textbox(label="Seed Used", show_copy_button = True, elem_id="seed-output")
-
-            with gr.Group():
-                with gr.Row():
-                    text_button = gr.Button("Run", variant='primary', elem_id="gen-button")
-                    #result = gr.Gallery(label="Result", columns=1, preview=True)
-                    clr_button =gr.Button("Clear Prompt",variant="primary", elem_id="clear_button")
-                    clr_button.click(lambda: gr.Textbox(value=""), None, text_prompt)
-                    
-                with gr.Row():
-                    image_output = gr.Image(type="pil", label="Image Output", format="png", show_share_button=False, elem_id="gallery")
-                with gr.Row():
-                    clear_btn = gr.Button(value="Clear Image", variant="primary", elem_id="clear_button")
-                    clear_btn.click(clear, inputs=[], outputs=[image_output])
-        
-                gr.Examples(
-                    examples = examples,
-                    inputs = [text_prompt],
-                    outputs=[result, seed],
-                )
-                
-        text_button.click(result, inputs=[custom_lora, text_prompt, negative_prompt, steps, cfg, method, seed, strength, width, height], outputs=[image_output, num_images_per_prompt, seed_output])
-    
-        with gr.Tab("Flip Image"):
+                    with gr.Row():
+                        text_prompt = gr.Textbox(label="Image Prompt", placeholder="Enter a prompt here", lines=2, show_copy_button = True, elem_id="prompt-text-input")
+                    with gr.Row():
+                        with gr.Accordion("🎨 Lora trigger words", open=False):
+                        		gr.Markdown("""
+                                    - **sdxl-realistic**: szn style
+                                    - **Flux-Realism-FineDetailed**: Fine Detailed
+                                    - **Fashion-Hut-Modeling-LoRA**: Modeling
+                                    - **SD3.5-Large-Turbo-HyperRealistic-LoRA**: hyper realistic
+                                    - **Flux-Fine-Detail-LoRA**: Super Detail
+                                    - **SD3.5-Turbo-Realism-2.0-LoRA**: Turbo Realism
+                                    - **Canopus-LoRA-Flux-UltraRealism-2.0**: Ultra realistic 
+                                    - **extremely-detailed**: extremely detailed
+                                    - **SD3.5-Large-Photorealistic-LoRA**: photorealistic
+                                    - **Flux.1-Dev-LoRA-HDR-Realism**: HDR
+                                    - **prithivMLmods/Ton618-Epic-Realism-Flux-LoRA**: Epic Realism
+                                    - **john-singer-sargent-style**: John Singer Sargent Style
+                                    - **alphonse-mucha-style**: Alphonse Mucha Style
+                                    - **ultra-realistic-illustration**: ultra realistic illustration
+                                    - **eye-catching**: eye-catching
+                                    - **john-constable-style**: John Constable Style
+                                    - **film-noir**: in the style of FLMNR
+                                    - **flux-lora-pro-headshot**: PROHEADSHOT
+                        		""")                       
+                            
+                    with gr.Row():
+                        custom_lora = gr.Dropdown([" ", "jwu114/lora-sdxl-realistic", "prithivMLmods/Flux-Realism-FineDetailed", "prithivMLmods/Fashion-Hut-Modeling-LoRA", "prithivMLmods/SD3.5-Large-Turbo-HyperRealistic-LoRA", "prithivMLmods/Flux-Fine-Detail-LoRA", "prithivMLmods/SD3.5-Turbo-Realism-2.0-LoRA", "hugovntr/flux-schnell-realism", "fofr/sdxl-deep-down", "prithivMLmods/Canopus-LoRA-Flux-UltraRealism-2.0", "ntc-ai/SDXL-LoRA-slider.extremely-detailed", "prithivMLmods/Canopus-LoRA-Flux-FaceRealism", "prithivMLmods/SD3.5-Large-Photorealistic-LoRA", "prithivMLmods/Flux.1-Dev-LoRA-HDR-Realism", "prithivMLmods/Ton618-Epic-Realism-Flux-LoRA", "KappaNeuro/john-singer-sargent-style", "KappaNeuro/alphonse-mucha-style", "ntc-ai/SDXL-LoRA-slider.ultra-realistic-illustration", "ntc-ai/SDXL-LoRA-slider.eye-catching", "KappaNeuro/john-constable-style", "dvyio/flux-lora-film-noir", "dvyio/flux-lora-pro-headshot"], label="Custom LoRA",)
+                    with gr.Row():
+                        with gr.Accordion("⚙️ Advanced Settings", open=False, elem_id="settings-container"):
+                            negative_prompt = gr.Textbox(label="Negative Prompt", lines=5, placeholder="What should not be in the image", value=" (visible hand:1.3), (ugly:1.3), (duplicate:1.2), (morbid:1.1), (mutilated:1.1), out of frame, bad face, extra fingers, mutated hands, (poorly drawn hands:1.1), (poorly drawn face:1.3), (mutation:1.3), (deformed:1.3), blurry, (bad anatomy:1.1), (bad proportions:1.2), (extra limbs:1.1), cloned face, (disfigured:1.2), gross proportions, malformed limbs, (missing arms:1.1), (missing legs:1.1), (extra arms:1.2), (extra legs:1.2), fused fingers, too many fingers, (long neck:1.2), sketched by bad-artist, (bad-image-v2-39000:1.3) ")
+                            with gr.Row():
+                                width = gr.Slider(label="Image Width", value=896, minimum=64, maximum=1216, step=32)
+                                height = gr.Slider(label="Image Height", value=1152, minimum=64, maximum=1216, step=32)
+                            strength = gr.Slider(label="Prompt Strength", value=100, minimum=0, maximum=100, step=1)    
+                            steps = gr.Slider(label="Sampling steps", value=50, minimum=1, maximum=100, step=1)
+                            cfg = gr.Slider(label="CFG Scale", value=3.5, minimum=1, maximum=20, step=0.5)
+                            seed = gr.Slider(label="Seed", value=-1, minimum=-1, maximum=1000000000, step=1)                            
+                            method = gr.Radio(label="Sampling method", value="DPM++ 2M Karras", choices=["DPM++ 2M Karras", "DPM++ SDE Karras", "DEIS", "LMS", "DPM Adaptive", "DPM++ 2M", "DPM2 Ancestral", "DPM++ S", "DPM++ SDE", "DDPM", "DPM Fast", "dpmpp_2s_ancestral", "Euler", "Euler CFG PP", "Euler a", "Euler Ancestral", "Euler+beta", "Heun", "Heun PP2", "DDIM", "PLMS", "UniPC", "UniPC BH2"])
+                    with gr.Row():
+                        with gr.Accordion("🫘Seed", open=False):
+                            seed_output = gr.Textbox(label="Seed Used", show_copy_button = True, elem_id="seed-output")
+                            
             with gr.Row():
-                image_input = gr.Image()
-                image_output = gr.Image(format="png")
-            with gr.Row():    
-                image_button = gr.Button("Run", variant='primary')
-                image_button.click(flip_image, inputs=image_input, outputs=image_output, concurrency_limit=2)
+                text_button = gr.Button("Run", variant='primary', elem_id="gen-button")
+                clr_button =gr.Button("Clear Prompt",variant="primary", elem_id="clear_button")
+                clr_button.click(lambda: gr.Textbox(value=""), None, text_prompt)
                 
-        app.queue(default_concurrency_limit=200, max_size=200)  # <-- Sets up a queue with default parameters
-        if __name__ == "__main__": 
-            app.launch(show_api=False, share=True)
+            with gr.Row():
+                image_output = gr.Image(type="pil", label="Image Output", format="png", show_share_button=False, elem_id="gallery")
+            with gr.Row():
+                clear_btn = gr.Button(value="Clear Image", variant="primary", elem_id="clear_button")
+                clear_btn.click(clear, inputs=[], outputs=[image_output])
+    
+            gr.Examples(
+                examples = examples,
+                inputs = [text_prompt],
+            )
+            
+    text_button.click(query, inputs=[custom_lora, text_prompt, negative_prompt, steps, cfg, method, seed, strength, width, height], outputs=[image_output, seed_output])
+
+    with gr.Tab("Flip Image"):
+        with gr.Row():
+            image_input = gr.Image()
+            image_output = gr.Image(format="png")
+        with gr.Row():    
+            image_button = gr.Button("Run", variant='primary')
+            image_button.click(flip_image, inputs=image_input, outputs=image_output, concurrency_limit=2)
+            
+    app.queue(default_concurrency_limit=200, max_size=200)  # <-- Sets up a queue with default parameters
+    if __name__ == "__main__": 
+        app.launch(show_api=False, share=False)
+