Update app.py

app.py

@@ -3,11 +3,6 @@ import assemblyai as aai
 from transformers import pipeline
 import pandas as pd
 import os
-from firebase_admin import credentials, db, initialize_app
-
-# Initialize Firebase with your credentials
-cred = credentials.Certificate('credentials.json')
-initialize_app(cred, {'databaseURL': 'https://learning-5fd92-default-rtdb.asia-southeast1.firebasedatabase.app/'})
 
 # Replace with your AssemblyAI API key
 aai.settings.api_key = "62acec891bb04c339ec059b738bedac6"
@@ -39,7 +34,6 @@ questions = [
     "What treatment plan do you recommend? Choose only from Options: (Scaling, Filling, Pulp therapy/RCT, Extraction, Medication, Referral) and nothing else"
 ]
 
-# List for the oral health assessment form
 oral_health_assessment_form = [
     "Doctor’s Name",
     "Child’s Name",
@@ -71,15 +65,17 @@ def generate_answer(question, context):
     return result['answer']
 
 # Function to handle audio recording and transcription
-def transcribe_audio(audio_data):
+def transcribe_audio(audio_path):
+    print(f"Received audio file at: {audio_path}")
+    
+    # Check if the file exists and is not empty
+    if not os.path.exists(audio_path):
+        return "Error: Audio file does not exist."
+    
+    if os.path.getsize(audio_path) == 0:
+        return "Error: Audio file is empty."
+    
     try:
-        # Save audio data to a temporary file
-        audio_path = '/tmp/audio.wav'
-        with open(audio_path, 'wb') as f:
-            f.write(audio_data)
-        
-        print(f"Saved audio file at: {audio_path}")
-
         # Transcribe the audio file using AssemblyAI
         transcriber = aai.Transcriber()
         print("Starting transcription...")
@@ -108,18 +104,9 @@ def fill_dataframe(context):
         data.append({"Question": question, "Answer": answer})
     return pd.DataFrame(data)
 
-# Function to push data to Firebase
-def push_to_firebase(data):
-    try:
-        ref = db.reference("/")
-        ref.push(data)
-        print("Data pushed to Firebase successfully.")
-    except Exception as e:
-        print(f"Error pushing data to Firebase: {e}")
-
 # Main Gradio app function
-def main(audio_data):
-    context = transcribe_audio(audio_data)
+def main(audio):
+    context = transcribe_audio(audio)
     
     if "Error" in context:
         return context
@@ -131,27 +118,23 @@ def main(audio_data):
     
     # Add a title to the DataFrame
     df['Question'] = oral_health_assessment_form
-    
+
     # Convert DataFrame to HTML table with editable text boxes
     table_html = df.to_html(index=False, escape=False, formatters={"Answer": lambda x: f'<input type="text" value="{x}" />'})
     
-    # Create submit button and save data to Firebase
-    submit_button = gr.Button("Submit")
-    output_html = gr.HTML(label="Assessment Form")
-    
-    def submit_data():
-        data = df.set_index('Question').to_dict()['Answer']
-        push_to_firebase(data)
-    
-    submit_button.click(fn=submit_data)
-    
-    return gr.Interface(
-        [gr.Audio(type="bytes", label="Record your audio")],
-        [output_html, submit_button],
-        title="Audio Transcription and Question Answering App",
-        live=False
-    )
+    return table_html
+
+# Create the Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("# Audio Transcription and Question Answering App")
+    with gr.Row():
+        with gr.Column():
+            audio_input = gr.Audio(type="filepath", label="Record your audio")
+            output_html = gr.HTML(label="Assessment Form")
+        with gr.Column():
+            transcribe_button = gr.Button("Transcribe and Generate Form")
+
+    transcribe_button.click(fn=main, inputs=audio_input, outputs=output_html)
 
 # Launch the app
-main_app = main()
-main_app.launch()
+demo.launch()