Update app.py

app.py

@@ -112,99 +112,99 @@ class Retriever:
         return paths_and_scores
 
 
-def main(args):
-    predictor = PredictorBackend(url=args.model_url)
+# def main(args):
+#     predictor = PredictorBackend(url=args.model_url)
     
-    # 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>
-        """
+#     # 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?
-    )    
-
-
-def make_frontend(
-    fn: Callable[[Image], str], flagging: bool = False, gantry: bool = False, app_name: str = "fashion-aggregator"
-):
-    """Creates a gradio.Interface frontend for text to image search function."""
-
-    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?
+#     )    
+
+
+# def make_frontend(
+#     fn: Callable[[Image], str], flagging: bool = False, gantry: bool = False, app_name: str = "fashion-aggregator"
+# ):
+#     """Creates a gradio.Interface frontend for text to image search function."""
+
+#     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>
+#         """
     
-    disclaimer = f"""
-    <div style="display: flex; align-items: center; justify-content: center;">
-        <img src='data:image/jpeg;base64,{image_base64}' width='50' height='50' style="margin-right: 10px;"/>
-        <p style="font-size: small; color: gray;">
-            Disclaimer: This web app is for demonstration purposes only and not intended for commercial use. Contact: [email protected] for full solution.
-        </p>
-    </div>
-    """
+#     disclaimer = f"""
+#     <div style="display: flex; align-items: center; justify-content: center;">
+#         <img src='data:image/jpeg;base64,{image_base64}' width='50' height='50' style="margin-right: 10px;"/>
+#         <p style="font-size: small; color: gray;">
+#             Disclaimer: This web app is for demonstration purposes only and not intended for commercial use. Contact: [email protected] for full solution.
+#         </p>
+#     </div>
+#     """
     
-    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: The search results are based on embeddings and may not always be accurate.
-        </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=fn,
-        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?
-    )
-
-    return frontend
+#     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: The search results are based on embeddings and may not always be accurate.
+#         </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=fn,
+#         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?
+#     )
+
+#     return frontend
 
 
 class PredictorBackend:
@@ -240,40 +240,46 @@ class PredictorBackend:
         logging.info(f"PRED >begin\n{pred}\nPRED >end")
 
 
-def _make_parser():
-    parser = argparse.ArgumentParser(description=__doc__)
-    parser.add_argument(
-        "--model_url",
-        default=None,
-        type=str,
-        help="Identifies a URL to which to send image data. Data is base64-encoded, converted to a utf-8 string, and then set via a POST request as JSON with the key 'image'. Default is None, which instead sends the data to a model running locally.",
-    )
-    parser.add_argument(
-        "--port",
-        default=DEFAULT_PORT,
-        type=int,
-        help=f"Port on which to expose this server. Default is {DEFAULT_PORT}.",
-    )
-    parser.add_argument(
-        "--flagging",
-        action="store_true",
-        help="Pass this flag to allow users to 'flag' model behavior and provide feedback.",
-    )
-    parser.add_argument(
-        "--gantry",
-        action="store_true",
-        help="Pass --flagging and this flag to log user feedback to Gantry. Requires GANTRY_API_KEY to be defined as an environment variable.",
-    )
-    parser.add_argument(
-        "--application",
-        default=DEFAULT_APPLICATION_NAME,
-        type=str,
-        help=f"Name of the Gantry application to which feedback should be logged, if --gantry and --flagging are passed. Default is {DEFAULT_APPLICATION_NAME}.",
-    )
-    return parser
-
-
-if __name__ == "__main__":
-    parser = _make_parser()
-    args = parser.parse_args()
-    main(args)
+predictor = PredictorBackend()
+
+# 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?
+)