Update app.py

app.py

@@ -1,7 +1,3 @@
-import os
-os.system("pip uninstall -y gradio")
-os.system("pip install gradio==3.32.0")
-
 """Find your apparel effortlessly. Just describe your apparel and get the relevant recommendations with links!"""
 import argparse
 import logging
@@ -118,19 +114,48 @@ class Retriever:
 
 def main(args):
     predictor = PredictorBackend(url=args.model_url)
-    frontend = make_frontend(predictor.run, flagging=args.flagging, gantry=args.gantry, app_name=args.application)
+    
+    # Read the image file and encode it as base64
+    with open("./1001epochs.png", "rb") as f:
+        image_data = f.read()
+        image_base64 = base64.b64encode(image_data).decode("utf-8")
+
+    allow_flagging = "never"
+
+    title = f"""
+        <h1 style="background-image: linear-gradient(to right, #ADD8E6, #87CEFA); -webkit-background-clip: text;
+            -webkit-text-fill-color: transparent; text-align: center;">
+            Fashion Aggregator
+        </h1>
+        """
+    
+    description = f"""
+    <div style="display: flex; align-items: center; justify-content: center; flex-direction: column;">
+        <img src='data:image/jpeg;base64,{image_base64}' width='50' height='50' style="margin-right: 10px;"/>
+        <p style="font-size: small; color: gray; margin-top: 10px;">
+            Disclaimer: This web app is for demonstration purposes only and not intended for commercial use. Contact: [email protected] for full solution.
+        </p>
+        <p style="font-size: 18px; color: blue; margin-top: 10px; text-align: center;">
+            Discover your perfect apparel effortlessly. Simply describe what you're looking for!
+        </p>
+    </div>
+    """
+
+    frontend = gr.Interface(
+        fn=predictor.run,
+        inputs=gr.inputs.Textbox(label="Item Description", placeholder="Enter item description here"),
+        outputs=gr.Gallery(label="Relevant Items", show_labels=True, label_position="below"),
+        title=title,  
+        description=description,
+        cache_examples=False,  # should we cache those inputs for faster inference? slows down start
+        allow_flagging=allow_flagging,  # should we show users the option to "flag" outputs?
+        flagging_options=["incorrect", "offensive", "other"],  # what options do users have for feedback?
+    )
     frontend.launch(
         # server_name="0.0.0.0",  # make server accessible, binding all interfaces  # noqa: S104
         # server_port=args.port,  # set a port to bind to, failing if unavailable
         # share=False,  # should we create a (temporary) public link on https://gradio.app?
-        # favicon_path=LOGO,  # what icon should we display in the address bar?
-    )
-
-# Read the image file and encode it as base64
-with open("./1001epochs.png", "rb") as f:
-    image_data = f.read()
-    image_base64 = base64.b64encode(image_data).decode("utf-8")
-    
+    )    
 
 
 def make_frontend(
@@ -174,6 +199,9 @@ def make_frontend(
         outputs=gr.Gallery(label="Relevant Items", show_labels=True, label_position="below"),
         title=title,  
         description=description,
+        cache_examples=False,  # should we cache those inputs for faster inference? slows down start
+        allow_flagging=allow_flagging,  # should we show users the option to "flag" outputs?
+        flagging_options=["incorrect", "offensive", "other"],  # what options do users have for feedback?
     )
 
     return frontend