Update app.py

app.py

@@ -1,38 +1,127 @@
-import gradio as gr
-import os, time, requests
+import os, time, requests, gradio as gr
+
+# ---------- Hot-patch to bypass Gradio 4.44.0 JSON-schema bug ----------
+import gradio.blocks as _blocks
+if not hasattr(_blocks.Blocks, "_api_info_patched"):
+    _blocks.Blocks._api_info_patched = True
+    _blocks.Blocks.get_api_info = lambda self: {}
+
+print("Gradio version:", gr.__version__)   # should be 4.44.0
 
 # ---------- Environment Variables ----------
 ASR_API_URL = os.getenv("ASR_API_URL")
 AUTH_TOKEN  = os.getenv("AUTH_TOKEN")
-
 if not ASR_API_URL or not AUTH_TOKEN:
     print("⚠️  ASR_API_URL or AUTH_TOKEN is not set; API calls will fail.")
 
-def transcribe_audio(audio_file):
+# ---------- Core Transcription Function ----------
+def transcribe_audio(file_path: str):
+    if not ASR_API_URL or not AUTH_TOKEN:
+        return "❌ Error: ASR_API_URL or AUTH_TOKEN is not set.", ""
+
     headers = {
+        "accept": "application/json",
         "Authorization": f"Bearer {AUTH_TOKEN}",
     }
-    files = {'file': open(audio_file, 'rb')}
-
-    response = requests.post(ASR_API_URL, headers=headers, files=files)
-    if response.status_code == 200:
-        return response.json().get('transcription', '')
-    else:
-        return f"Error: {response.text}"
-
-with gr.Blocks() as interface:
-    gr.Markdown("# Whisper Large V3 Speech Recognition")
-    gr.Markdown("Upload an audio file or use your microphone to transcribe speech to text.")
-    
-    # Create the input and output components
-    audio_input = gr.Audio(type="filepath", label="Input Audio")
-    output_text = gr.Textbox(label="Transcription")
-    
-    # Add a button to trigger the transcription
-    transcribe_button = gr.Button("Transcribe")
-    
-    # Bind the transcribe_audio function to the button click
-    transcribe_button.click(fn=transcribe_audio, inputs=audio_input, outputs=output_text)
-
-# Launch the Gradio app
-interface.queue().launch()
+
+    start = time.time()
+    try:
+        with open(file_path, "rb") as f:
+            files = {"file": (os.path.basename(file_path), f, "audio/mpeg")}
+            resp = requests.post(ASR_API_URL, headers=headers, files=files, timeout=120)
+    except Exception as e:
+        return f"❌ Error while calling ASR API: {e}", ""
+
+    elapsed = time.time() - start
+    if resp.status_code == 200:
+        data = resp.json()
+        text = data.get("transcription", "No transcription returned.")
+        return text, f"{data.get('time', elapsed):.2f} s"
+    return f"❌ Error: {resp.status_code}, {resp.text}", ""
+
+# ---------- Styling ----------
+VIOLET_MAIN = "#7F3FBF"   # primary violet
+VIOLET_LIGHT = "#C3A6FF"  # lighter violet for gradient/badge
+
+custom_css = f"""
+#gooya-title {{
+  color:#fff;
+  background:linear-gradient(90deg,{VIOLET_MAIN} 0%,{VIOLET_LIGHT} 100%);
+  border-radius:12px;padding:20px 10px;margin-bottom:12px;
+}}
+.gooya-badge {{
+  display:inline-block;background:{VIOLET_MAIN};color:#fff;
+  border-radius:16px;padding:6px 16px;font-size:.97rem;margin-top:4px;
+}}
+"""
+
+# ---------- UI ----------
+with gr.Blocks(css=custom_css, title="Gooya ASR v1.4") as demo:
+    gr.HTML(
+        f"""
+        <div id="gooya-title">
+          <h1 style='margin-bottom:10px;font-weight:800;font-size:2rem;'>
+              Gooya ASR <span style="font-size:1.1rem;font-weight:400;opacity:.8;">v1.4</span>
+          </h1>
+          <p style='font-size:1.12rem;margin-bottom:2px;'>
+              High-performance Persian Speech-to-Text
+          </p>
+          <p style='font-size:.98rem;color:#e9dbff'>
+              Upload or record a Persian audio file (max&nbsp;30&nbsp;s) and instantly get the transcription.
+          </p>
+        </div>
+        """
+    )
+
+    with gr.Row():
+        with gr.Column():
+            audio_input = gr.Audio(
+                label="Audio Input (upload or record, up to 30 s)",
+                type="filepath",
+                sources=["upload", "microphone"],
+            )
+        with gr.Column():
+            processing_time_tb = gr.Textbox(
+                label="⏱️ Processing Time",
+                interactive=False,
+                elem_classes="gooya-badge",
+            )
+            transcription_tb = gr.Textbox(
+                label="📝 Transcription",
+                lines=5,
+                show_copy_button=True,
+                placeholder="The transcription will appear here...",
+                elem_id="gooya-textbox",
+            )
+
+    with gr.Row():
+        btn_transcribe = gr.Button("Transcribe", variant="primary")
+        btn_clear      = gr.Button("Clear",      variant="secondary")
+
+    gr.Markdown(
+        """
+**Guidelines**  
+- Maximum audio length: **30 seconds**  
+- Audio content should be in Persian.  
+- Both transcription and processing time are displayed immediately.  
+
+See the [Persian ASR Leaderboard](https://huggingface.co/spaces/navidved/open_persian_asr_leaderboard) for benchmarks.
+"""
+    )
+
+    # ---------- Callbacks ----------
+    btn_transcribe.click(
+        transcribe_audio,
+        inputs=audio_input,
+        outputs=[transcription_tb, processing_time_tb],
+    )
+
+    btn_clear.click(
+        lambda: ("", "", None),
+        inputs=None,
+        outputs=[transcription_tb, processing_time_tb, audio_input],
+    )
+
+# ---------- Launch ----------
+if __name__ == "__main__":
+    demo.queue().launch()