support recognition from an URL

app.py

@@ -22,12 +22,15 @@
 import base64
 import logging
 import os
+import tempfile
 import time
 from datetime import datetime
 
 import gradio as gr
 import torch
 import torchaudio
+import urllib.request
+
 
 from examples import examples
 from model import decode, get_pretrained_model, language_to_models, sample_rate
@@ -61,6 +64,28 @@ def build_html_output(s: str, style: str = "result_item_success"):
     </div>
     """
 
+def process_url(
+    language: str,
+    repo_id: str,
+    decoding_method: str,
+    num_active_paths: int,
+    url: str,
+):
+    logging.info(f"Processing URL: {url}")
+    with tempfile.NamedTemporaryFile() as f:
+        try:
+            urllib.request.urlretrieve(url, f.name)
+
+            return process(
+                in_filename=f.name,
+                language=language,
+                repo_id=repo_id,
+                decoding_method=decoding_method,
+                num_active_paths=num_active_paths,
+            )
+        except Exception as e:
+            logging.info(str(e))
+            return "", build_html_output(str(e), "result_item_error")
 
 def process_uploaded_file(
     language: str,
@@ -301,6 +326,18 @@ with demo:
                 fn=process_microphone,
             )
 
+        with gr.TabItem("From URL"):
+            url_textbox = gr.Textbox(
+                    max_lines=1,
+                    placeholder="URL to an audio file",
+                    label="URL",
+                    interactive=True,
+            )
+
+            url_button = gr.Button("Submit for recognition")
+            url_output = gr.Textbox(label="Recognized speech from URL")
+            url_html_info = gr.HTML(label="Info")
+
         upload_button.click(
             process_uploaded_file,
             inputs=[
@@ -324,6 +361,19 @@ with demo:
             ],
             outputs=[recorded_output, recorded_html_info],
         )
+
+        url_button.click(
+            process_url,
+            inputs=[
+                language_radio,
+                model_dropdown,
+                decoding_method_radio,
+                num_active_paths_slider,
+                url_textbox,
+            ],
+            outputs=[url_output, url_html_info],
+        )
+
     gr.Markdown(description)
 
 torch.set_num_threads(1)