Update app.py

app.py

@@ -1,8 +1,11 @@
 import gradio as gr
+from stablepy import Model_Diffusers
+
 from civitai_to_hf import (search_civitai, download_civitai, select_civitai_item, add_civitai_item, get_civitai_tag, select_civitai_all_item,
                            update_civitai_selection, update_civitai_checkbox, from_civitai_checkbox,
                            CIVITAI_TYPE, CIVITAI_BASEMODEL, CIVITAI_SORT, CIVITAI_PERIOD, CIVITAI_FILETYPE, download_file)
 
+
 css = """
 .title { font-size: 3em; align-items: center; text-align: center; }
 .info { align-items: center; text-align: center; }
@@ -10,9 +13,31 @@ css = """
 .desc [src$='#float'] { float: right; margin: 20px; }
 """
 
-with gr.Blocks(theme="NoCrypt/miku@>=1.2.2", fill_width=True, css=css, delete_cache=(60, 3600)) as demo:
+
+
+
+# Define the function to generate images
+def generate_image(model_id, prompt, lora_A, num_steps, guidance_scale, sampler, img_width, img_height):
+    model = Model_Diffusers(
+        base_model_id=model_id,
+        task_name='txt2img',
+    )
+
+    image, info_image = model(
+        prompt=prompt,
+        lora_A=lora_A,
+        num_steps=num_steps,
+        guidance_scale=guidance_scale,
+        sampler=sampler,
+        img_width=img_width,
+        img_height=img_height,
+    )
+    return image[0]
+
+
+with gr.Blocks(fill_width=True, css=css) as demo:
     with gr.Column():
-        gr.Markdown("# CivitAI to HF🤗 Downloader & Uploader", elem_classes="title")
+        gr.Markdown("# StableGR", elem_classes="title")
         state = gr.State(value={})
         with gr.Accordion("Search Civitai", open=True):
             with gr.Row():
@@ -51,18 +76,39 @@ with gr.Blocks(theme="NoCrypt/miku@>=1.2.2", fill_width=True, css=css, delete_ca
                 civitai_key = gr.Textbox(label="Your Civitai Key", value="", max_lines=1)
                 gr.Markdown("Your Civitai API key is available at [https://civitai.com/user/account](https://civitai.com/user/account).", elem_classes="info")
         
-        run_button = gr.Button(value="Download", variant="primary")
+        with gr.Row():
+            run_base = gr.Button(value="Download Base Model", variant="primary")
+            run_lora = gr.Button(value="Download Lora", variant="primary")
         output_but = gr.File(label="output")
         uploaded_urls = gr.CheckboxGroup(visible=False, choices=[], value=None) # hidden
         urls_md = gr.Markdown("<br><br>", elem_classes="result")
         urls_remain = gr.Textbox("Remaining URLs", value="", show_copy_button=True, visible=False)
+    with gr.Column():
+        base_model = gr.File(label="Base Models")
+        with gr.row():
+            prompt = gr.Textbox(label="Prompt", value="A highly detailed portrait of an underwater city, with towering spires and domes rising up from the ocean floor")
+        with gr.Row():
+            lora_A = gr.File(label="Lora")
+        num_steps = gr.Slider(label="Number of Steps", minimum=1, maximum=100, value=30, step=1)
+        guidance_scale = gr.Slider(label="Guidance Scale", minimum=0.1, maximum=20.0, value=7.5, step=0.1)
+        sampler = gr.Dropdown(label="Sampler", choices=["DPM++ 2M", "OtherSampler1", "OtherSampler2"], value="DPM++ 2M")
+        img_width = gr.Slider(label="Image Width", minimum=64, maximum=2048, value=512, step=64)
+        img_height = gr.Slider(label="Image Height", minimum=64, maximum=2048, value=1024, step=64)
+        generate_button = gr.Button("Generate Image")
         
 
     gr.on(
-        triggers=[run_button.click],
+        triggers=[run_base.click],
+        fn=download_file,
+        inputs=[dl_url, civitai_key],
+        outputs=[base_model],
+        queue=True,
+    )
+    gr.on(
+        triggers=[run_lora.click],
         fn=download_file,
         inputs=[dl_url, civitai_key],
-        outputs=[output_but],
+        outputs=[lora_A],
         queue=True,
     )
     gr.on(