Create app.py

app.py

@@ -0,0 +1,123 @@
+import gradio as gr
+import requests
+import time
+import os
+from dotenv import load_dotenv
+from huggingface_hub import list_models
+
+load_dotenv()
+API_URL = os.getenv("API_URL")
+class CreateProfile:
+    def __init__(self, _id=None):
+        self._id = _id
+        self.name = ""
+        self.username = ""
+        
+newprofile = CreateProfile()
+
+def check_active_users():
+    response = requests.get(f"{API_URL}/status")
+    if response.status_code == 200:
+        queue_length = response.json().get("queue_length", 0)
+        if queue_length > 2:
+            return False, "There's currently a high volume of requests. The server is busy processing these requests. Please try again later."
+    return True, ""
+
+def process_ui_image(image, user_task, progress=gr.Progress()):
+    progress(0)
+    
+    # Check the number of active users
+    can_proceed, message = check_active_users()
+    if not can_proceed:
+        return message
+    
+    # Upload image and user task to the API
+    files = {'image': open(image, 'rb')}
+    data = {'user_task': user_task, "name": newprofile.name, "username": newprofile.username}
+    response = requests.post(f"{API_URL}/process", files=files, data=data)
+    
+    if response.status_code != 200:
+        return f"Error: {response.text}"
+    
+    # Get the request ID from the response
+    request_id = response.json().get("request_id")
+    print("request_id",request_id)
+    
+    if not request_id:
+        return "Error: Failed to get request ID from the server."
+    
+    # Poll the status of the request
+    i = 0.01
+    while True:
+        status_response = requests.get(f"{API_URL}/status/{request_id}")
+        status = status_response.json()
+        
+        if status.get("status") == "completed":
+            progress(1)
+            break
+        elif status.get("status") == "failed":
+            return "Error: Processing failed."
+
+        progress(i)
+        i += 0.01
+        if i >= 0.9:
+            i = 0.9
+        time.sleep(1)
+    
+    # Download the final PDF
+    final_pdf_response = requests.get(f"{API_URL}/get_file")
+    
+    if final_pdf_response.status_code == 200:
+        with open("UXEva_report.pdf", "wb") as f:
+            f.write(final_pdf_response.content)
+        return "UXEva_report.pdf"
+    else:
+        return "Error: Failed to download the PDF."
+
+def update_submit_button(image, user_task):
+    if not image or not user_task:
+        return gr.update(interactive=False), gr.update(visible=True)
+    return gr.update(interactive=True), gr.update(visible=False)
+
+
+with gr.Blocks(css="""
+    .image-preview img {max-height: 400px; max-width: 400px;}
+    .disabled {cursor: not-allowed; color: red;}
+""") as demo:
+    gr.Markdown("""
+    <h1 style="text-align: center;">
+        <span style="color: green;">UXEva</span>: UI/UX Evaluation Tool Powered by LLM Agent
+    </h1>
+    """)
+    gr.LoginButton()
+    
+    with gr.Column(visible=False) as main_ui:
+        image_input = gr.Image(type="filepath", label="Upload UI Image", elem_classes="image-preview")
+        user_task_input = gr.Textbox(label="Enter User Task")
+        pdf_output = gr.File(label="Download PDF Report")
+        submit_btn = gr.Button("Submit", interactive=False)
+        warning = gr.Markdown("<span class='disabled'>Upload image and enter user task</span>", visible=False)
+    
+    image_input.change(update_submit_button, inputs=[image_input, user_task_input], outputs=[submit_btn, warning])
+    user_task_input.change(update_submit_button, inputs=[image_input, user_task_input], outputs=[submit_btn, warning])
+    
+    submit_btn.click(
+        process_ui_image, 
+        inputs=[image_input, user_task_input], 
+        outputs=[pdf_output]
+    )
+    def get_profile(profile: gr.OAuthProfile):
+        global newprofile
+        if profile is None:
+            print("unknow user.")
+        else:
+            newprofile.name = profile.name
+            newprofile.username = profile.username
+            print("profile name", profile.name)
+            print("profile username", profile.username)
+            return {main_ui: gr.Column(visible=True)}
+            
+    demo.load(get_profile, inputs=None, outputs=[main_ui])
+
+demo.queue(default_concurrency_limit=1, max_size=7)
+demo.launch()