modified app.py

app.py

@@ -1,3 +1,38 @@
 import gradio as gr
+from transformers import pipeline
+import random
 
-gr.load("models/Shakker-Labs/FLUX.1-dev-LoRA-add-details").launch()
+# Load the model
+text_to_image_pipeline = pipeline("text-to-image", model="models/Shakker-Labs/FLUX.1-dev-LoRA-add-details")
+
+def generate_image(prompt, cfg_scale, steps, width, height, randomize_seed, seed_value, lora_scale):
+    # Randomize seed if checkbox is checked
+    if randomize_seed:
+        seed_value = random.randint(0, 10000)
+    
+    # Use the model to generate an image based on the input parameters
+    # Here we assume `text_to_image_pipeline` can accept these parameters
+    return text_to_image_pipeline(prompt, cfg_scale=cfg_scale, steps=steps, width=width, height=height, seed=seed_value, lora_scale=lora_scale)
+
+# Define the Gradio interface
+interface = gr.Interface(
+    fn=generate_image,
+    inputs=[
+        gr.Textbox(label="Enter your text prompt"),
+        gr.Slider(minimum=0, maximum=100, step=0.1, default=7.5, label="CFG Scale"),
+        gr.Slider(minimum=1, maximum=100, step=1, default=25, label="Steps"),
+        gr.Slider(minimum=64, maximum=1024, step=8, default=512, label="Width"),
+        gr.Slider(minimum=64, maximum=1024, step=8, default=512, label="Height"),
+        gr.Checkbox(label="Randomize Seed"),
+        gr.Slider(minimum=0, maximum=10000, step=1, default=1234, label="Seed"),
+        gr.Slider(minimum=0, maximum=10, step=0.1, default=1.0, label="Lora Scale")
+    ],
+    outputs=gr.Image(label="Generated Image"),
+    title="Advanced Text-to-Image Generation",
+    description="Enter a text prompt and adjust the settings to generate an image.",
+    theme="dark",
+    layout="vertical"
+)
+
+# Launch the interface
+interface.launch()

gradio_cached_examples/13/indices.csv

@@ -0,0 +1 @@
+0

gradio_cached_examples/13/log.csv

@@ -0,0 +1,2 @@
+Output,flag,username,timestamp
+"{""path"": ""gradio_cached_examples/13/Output/aad06509c379deca76f8/image.webp"", ""url"": ""/file=/tmp/gradio/336cd5ec636993be48dffa5802a9bce794bf05dfbd5490c71fefbd30be128e00/image.webp"", ""size"": null, ""orig_name"": ""image.webp"", ""mime_type"": null, ""is_stream"": false, ""meta"": {""_type"": ""gradio.FileData""}}",,,2024-09-09 16:54:07.196794

requirements.txt

@@ -3,4 +3,7 @@ diffusers
 invisible_watermark
 torch
 transformers
-xformers
+xformers
+gradio
+Pillow
+numpy