Update app.py

app.py

@@ -1,18 +1,75 @@
-import gradio as gr
 from transformers import pipeline
+import gradio as gr
+
+# Load the fine-tuned Whisper model
+pipe = pipeline(model="fawzanaramam/Whisper-Small-Finetuned-on-Surah-Fatiha")
 
-pipe = pipeline(model="fawzanaramam/Whisper-Small-Finetuned-on-Surah-Fatiha")  # change to "your-username/the-name-you-picked"
 
 def transcribe(audio):
-    text = pipe(audio)["text"]
-    return text
-
-iface = gr.Interface(
-    fn=transcribe, 
-    inputs=gr.Audio(sources=["microphone","upload"], type="filepath"), 
-    outputs="text",
-    title="Whisper Small Surah Fatiha",
-    description="Realtime demo for Surah Fatiha speech recognition using a fine-tuned Whisper small model.",
-)
-
-iface.launch()
+    """Transcribes the given audio using Whisper"""
+    return pipe(audio)["text"]
+
+
+def save_transcription(text):
+    """Creates a downloadable text file for the transcription"""
+    file_path = "transcription.txt"
+    with open(file_path, "w") as f:
+        f.write(text)
+    return file_path
+
+
+# UI Layout
+with gr.Blocks(
+    css="""
+    h1 { 
+        font-size: 32px; 
+        font-weight: bold;
+        text-align: center;
+    }
+    h2, h3 {
+        font-size: 26px; 
+        font-weight: bold;
+    }
+    .gr-button {
+        font-size: 18px;
+        font-weight: bold;
+    }
+    .gr-textbox {
+        font-size: 18px;
+    }
+"""
+) as demo:
+
+    gr.Markdown("# 📖 Whisper Small - Surah Fatiha Transcription")
+    gr.Markdown(
+        "Fine-tuned Whisper model for recognizing and transcribing Surah Fatiha."
+    )
+
+    with gr.Tab("🎤 Record Audio"):
+        mic_input = gr.Audio(
+            sources=["microphone"], type="filepath", label="Record Audio"
+        )
+        transcribe_btn_1 = gr.Button("Transcribe")
+        output_text_1 = gr.Textbox(label="Transcription", interactive=False)
+        download_btn_1 = gr.File(label="Download Transcription", visible=False)
+
+    with gr.Tab("📥 Upload Audio"):
+        file_input = gr.Audio(
+            sources=["upload"], type="filepath", label="Upload Audio File"
+        )
+        transcribe_btn_2 = gr.Button("Transcribe")
+        output_text_2 = gr.Textbox(label="Transcription", interactive=False)
+        download_btn_2 = gr.File(label="Download Transcription", visible=False)
+
+    # Function connections
+    transcribe_btn_1.click(fn=transcribe, inputs=mic_input, outputs=output_text_1)
+    transcribe_btn_2.click(fn=transcribe, inputs=file_input, outputs=output_text_2)
+
+    transcribe_btn_1.click(
+        fn=save_transcription, inputs=output_text_1, outputs=download_btn_1
+    )
+    transcribe_btn_2.click(
+        fn=save_transcription, inputs=output_text_2, outputs=download_btn_2
+    )
+
+demo.launch()