Update app.py

app.py

@@ -1,10 +1,68 @@
 import gradio as gr
 import assemblyai as aai
-import os
+from transformers import pipeline
+import pandas as pd
 
 # Replace with your AssemblyAI API key
 aai.settings.api_key = "62acec891bb04c339ec059b738bedac6"
 
+# Initialize question answering pipeline
+question_answerer = pipeline("question-answering", model='distilbert-base-cased-distilled-squad')
+
+# List of questions
+questions = [
+    "Which grade is the child studying?",
+    "How old is the child?",
+    "What is the gender?",
+    "Can you provide the name and location of the child's school?",
+    "What are the names of the child's guardians or parents?",
+    "What is the chief complaint regarding the child's oral health? If there is none, just say the word 'none', else elaborate only on medication history",
+    "Can you provide any relevant medical history for the child? If there is none, just say the word 'none', else elaborate",
+    "Does the child take any medications regularly? If there is none, just say the word 'none'. If yes, please specify.",
+    "When was the child's previous dental visit? If no visits before, just say the word 'first' or mention the visit number and nothing else",
+    "Does the child have any habits such as thumb sucking, tongue thrusting, nail biting, or lip biting? If yes, just list them and don't provide any further details",
+    "Does the patient brush their teeth? Just use the words 'once daily', 'twice daily', or 'thrice daily' to answer, nothing else",
+    "Does the child experience bleeding gums? Just say 'yes' or 'no' for this and nothing else",
+    "Has the child experienced early childhood caries? Just say 'yes' or 'no' and nothing else",
+    "Please mention if tooth decay is present with tooth number(s), else just say the word 'none' and nothing else",
+    "Have any teeth been fractured? If yes, please mention the tooth number(s), else just say 'none' and nothing else",
+    "Is there any pre-shedding mobility of teeth? If yes, please specify, else just say 'none' and nothing else",
+    "Does the child have malocclusion? If yes, please provide details, else just say the word 'none' and nothing else",
+    "Does the child experience pain, swelling, or abscess? If yes, please provide details, else just say 'none' and nothing else",
+    "Are there any other findings you would like to note?",
+    "What treatment plan do you recommend? Choose only from Options: (Scaling, Filling, Pulp therapy/RCT, Extraction, Medication, Referral) and nothing else"
+]
+
+oral_health_assessment_form = [
+    "Doctor’s Name",
+    "Child’s Name",
+    "Grade",
+    "Age",
+    "Gender",
+    "School name and place",
+    "Guardian/Parents name",
+    "Chief complaint",
+    "Medical history",
+    "Medication history",
+    "Previous dental visit",
+    "Habits",
+    "Brushing habit",
+    "Bleeding gums",
+    "Early Childhood caries",
+    "Decayed",
+    "Fractured teeth",
+    "Preshedding mobility",
+    "Malocclusion",
+    "Does the child have pain, swelling or abscess? (Urgent care need)",
+    "Any other finding",
+    "Treatment plan",
+]
+
+# Function to generate answers for the questions
+def generate_answer(question, context):
+    result = question_answerer(question=question, context=context)
+    return result['answer']
+
 # Function to handle audio recording and transcription
 def transcribe_audio(audio_path):
     print(f"Received audio file at: {audio_path}")
@@ -29,24 +87,53 @@ def transcribe_audio(audio_path):
             print(f"Error during transcription: {transcript.error}")
             return transcript.error
         else:
-            print(f"Transcription text: {transcript.text}")
-            return transcript.text
+            context = transcript.text
+            print(f"Transcription text: {context}")
+            return context
     
     except Exception as e:
         print(f"Exception occurred: {e}")
         return str(e)
 
+# Function to fill in the DataFrame with answers
+def fill_dataframe(context):
+    data = []
+    for question in questions:
+        answer = generate_answer(question, context)
+        data.append({"Question": question, "Answer": answer})
+    return pd.DataFrame(data)
+
+# Main Gradio app function
+def main(audio):
+    context = transcribe_audio(audio)
+    
+    if "Error" in context:
+        return context
+    
+    df = fill_dataframe(context)
+    
+    # Add doctor's and patient's name to the beginning of the DataFrame
+    df = pd.concat([pd.DataFrame({"Question": ["Doctor’s Name", "Child’s Name"], "Answer": ["Dr. Charles Xavier", ""]}), df])
+    
+    # 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}" />'})
+    
+    return table_html
+
 # Create the Gradio interface
 with gr.Blocks() as demo:
-    gr.Markdown("# Audio Transcription App")
+    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_text = gr.Textbox(label="Transcription")
+            output_html = gr.HTML(label="Assessment Form")
         with gr.Column():
-            transcribe_button = gr.Button("Transcribe")
+            transcribe_button = gr.Button("Transcribe and Generate Form")
 
-    transcribe_button.click(fn=transcribe_audio, inputs=audio_input, outputs=output_text)
+    transcribe_button.click(fn=main, inputs=audio_input, outputs=output_html)
 
 # Launch the app
 demo.launch()