Update app.py

app.py

@@ -1,44 +1,29 @@
 import gradio as gr
-import torch
-import os
-import requests
-import io
-from PIL import Image
-API_URL = "https://api-inference.huggingface.co/models/EvanZhouDev/open-genmoji"
-headers = {"Authorization": "Bearer " + os.getenv("HUGGINGFACE_API_TOKEN")}
-def infer(prompt):
-    def query(payload):
-    	response = requests.post(API_URL, headers=headers, json=payload)
-    	return response.content
-    image_bytes = query({
-    	"inputs": prompt,
-    })
+import numpy as np
+from huggingface_hub import InferenceClient
+client = InferenceClient("EvanZhouDev/open-genmoji", token=os.getenv("HUGGINGFACE_API_TOKEN"))
 
-with gr.Blocks() as demo:
-    with gr.Column(elem_id="col-container"):
-        gr.Markdown(" # Text-to-Image Gradio Template")
-
-        with gr.Row():
-            prompt = gr.Text(
-                label="Prompt",
-                show_label=False,
-                max_lines=1,
-                placeholder="Enter your prompt",
-                container=False,
-            )
-            run_button = gr.Button("Run", scale=0, variant="primary")
-            result = gr.Image(label="Result", show_label=False)
+# output is a PIL.Image object
 
+# Define the process function that takes a text prompt and returns an image
+def process(prompt):
+    # Placeholder for the actual image generation logic
+    # For demonstration, we generate a random image
+    image = client.text_to_image(prompt)
+    return image
 
+# Create a Gradio Blocks app
+with gr.Blocks() as demo:
+    # Create a Textbox for the input prompt
+    prompt_input = gr.Textbox(label="Enter a prompt")
+    # Create an Image component for the output image
+    image_output = gr.Image(label="Generated Image")
+    # Create a Button to trigger the image generation
+    generate_button = gr.Button("Generate Image")
+    
+    # Define the event listener for the button click
+    generate_button.click(fn=process, inputs=prompt_input, outputs=image_output)
 
-        # Run inference when run_button is clicked
-        run_button.click(
-            infer,
-            inputs=[
-                prompt
-            ],
-            outputs=[result],
-        )
-
+# Launch the interface
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()