import gradio as gr 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" # 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" ] # List for the oral health assessment form 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_data): 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...") transcript = transcriber.transcribe(audio_path) print("Transcription process completed.") # Handle the transcription result if transcript.status == aai.TranscriptStatus.error: print(f"Error during transcription: {transcript.error}") return transcript.error else: 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) # 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) 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''}) # 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 ) # Launch the app main_app = main() main_app.launch()