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| import gradio as gr | |
| import assemblyai as aai | |
| from transformers import pipeline | |
| import os | |
| from supabase import create_client, Client | |
| from datetime import datetime | |
| import csv | |
| # Add your AssemblyAI API key as Environment Variable | |
| aai.settings.api_key = os.environ['Assembly'] | |
| url: str = os.environ['DBUrl'] | |
| key: str = os.environ['DBKey'] | |
| # Initialize question answering pipeline | |
| question_answerer = pipeline("question-answering", model='distilbert-base-cased-distilled-squad') | |
| # List of questions | |
| questions = [ | |
| "How old is the patient?", | |
| "What is the gender?", | |
| "What is the chief complaint regarding the patient's oral health? If there is none, just say the word 'none' else elaborate", | |
| "Can you provide any relevant Dental history for the patient? If there is none, just say the word 'none', else elaborate", | |
| "Give me about the clinical findings listed", | |
| "What treatment plan do you recommend?" | |
| ] | |
| oral_health_assessment_form = [ | |
| "Doctor’s Name", | |
| "Location", | |
| "Patient’s Name", | |
| "Age", | |
| "Gender", | |
| "Chief complaint", | |
| "Medical history", | |
| "Dental history", | |
| "Clinical Findings", | |
| "Treatment plan", | |
| "Referred to" | |
| ] | |
| # 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}") | |
| # 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: | |
| # 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 answers for the text boxes | |
| def fill_textboxes(context): | |
| answers = [] | |
| for question in questions: | |
| answer = generate_answer(question, context) | |
| answers.append(answer) | |
| return answers | |
| # Supabase configuration | |
| supabase: Client = create_client(url, key) | |
| # Main Gradio app function | |
| def main(audio, doctor_name, location): | |
| context = transcribe_audio(audio) | |
| if "Error" in context: | |
| return [context] * (len(oral_health_assessment_form) - 2) # Adjust for the number of fields | |
| answers = fill_textboxes(context) | |
| answers.insert(0, location) # Add location | |
| answers.insert(0, doctor_name) # Add doctor name | |
| return answers | |
| def save_answers(*args): | |
| current_datetime = datetime.now().isoformat() | |
| answers_dict = {oral_health_assessment_form[i]: args[i] for i in range(len(oral_health_assessment_form))} | |
| answers_dict["Submission Date and Time"] = current_datetime | |
| print("Saved answers:", answers_dict) | |
| # Insert data into Supabase | |
| try: | |
| response = supabase.table('oral_health_assessments').insert(answers_dict).execute() | |
| print("Data inserted into Supabase:", response.data) | |
| return f"Saved answers: {answers_dict}" | |
| except Exception as e: | |
| print(f"Error inserting data into Supabase: {e}") | |
| return f"Error saving answers: {e}" | |
| # Function to download table as CSV | |
| def download_table_to_csv(): | |
| # Fetch data from Supabase table | |
| response = supabase.table("oral_health_assessments").select("*").execute() | |
| # Check if data is available | |
| if not response.data: | |
| print("No data found in the table.") | |
| return None | |
| data = response.data | |
| # Prepare CSV data | |
| csv_data = [] | |
| # Add header row | |
| if len(data) > 0: | |
| csv_data.append(data[0].keys()) | |
| # Add data rows | |
| for row in data: | |
| csv_data.append(row.values()) | |
| # Save CSV data to file (replace 'your_table.csv' with desired filename) | |
| csv_file = "your_table.csv" | |
| with open(csv_file, "w", newline='') as f: | |
| writer = csv.writer(f) | |
| writer.writerows(csv_data) | |
| print("Downloaded table oral_health_assessments") | |
| return csv_file | |
| def gradio_download(): | |
| file_path = download_table_to_csv() | |
| if file_path: | |
| return file_path | |
| return None | |
| # Create the Gradio interface | |
| with gr.Blocks() as demo: | |
| gr.Markdown("# OHA Form Filler App") | |
| with gr.Tabs() as tabs: | |
| # Default tab for Doctor's Name and Location | |
| with gr.Tab("Doctor Info"): | |
| doctor_name_input = gr.Textbox(label="Doctor's Name", interactive=True) | |
| location_input = gr.Textbox(label="Location", interactive=True) | |
| submit_button = gr.Button("Submit") | |
| info_output = gr.HTML(label="Submitted Info") | |
| def submit_info(name, loc): | |
| return f"Doctor's Name: {name}<br>Location: {loc}" | |
| submit_button.click(fn=submit_info, inputs=[doctor_name_input, location_input], outputs=info_output) | |
| # Second tab for OHA Form | |
| with gr.Tab("OHA Form"): | |
| audio_input = gr.Audio(type="filepath", label="Record your audio", elem_id="audio_input") | |
| transcribe_button = gr.Button("Transcribe and Generate Form", elem_id="transcribe_button") | |
| with gr.Row(elem_id="textboxes_row"): | |
| with gr.Column(): | |
| doctor_name_display = gr.Textbox(label="Doctor’s Name", value="", interactive=False) | |
| location_display = gr.Textbox(label="Location", value="", interactive=False) | |
| textboxes_left = [gr.Textbox(label=oral_health_assessment_form[i], value="", interactive=True) for i in range(2, len(oral_health_assessment_form)//2)] | |
| with gr.Column(): | |
| textboxes_right = [gr.Textbox(label=oral_health_assessment_form[i], value="", interactive=True) for i in range(len(oral_health_assessment_form)//2, len(oral_health_assessment_form)-1)] | |
| dropdown_referred = gr.Dropdown(choices=["NONE","ORAL MEDICINE & RADIOLOGY", "PERIODONTICS", "ORAL SURGERY", "CONSERVATIVE AND ENDODONTICS", "PROSTHODONTICS", "PEDODONTICS", "ORTHODONTICS"], label="Referred to", interactive=True) | |
| def update_textboxes(audio, doctor_name, location): | |
| context = transcribe_audio(audio) | |
| if "Error" in context: | |
| return [context] * (len(oral_health_assessment_form) - 2) # Adjust for the number of fields | |
| answers = fill_textboxes(context) | |
| answers.insert(0, location) # Add location | |
| answers.insert(0, doctor_name) # Add doctor name | |
| return [doctor_name, location] + answers | |
| transcribe_button.click(fn=update_textboxes, inputs=[audio_input, doctor_name_input, location_input], outputs=[doctor_name_display, location_display] + textboxes_left + textboxes_right) | |
| submit_button = gr.Button("Submit", elem_id="submit_button") | |
| output_html = gr.HTML(label="Submitted Answers") | |
| submit_button.click(fn=save_answers, inputs=[doctor_name_display, location_display] + textboxes_left + textboxes_right + [dropdown_referred], outputs=output_html) | |
| # Third tab for CSV download | |
| with gr.Tab("Download CSV"): | |
| download_button = gr.Button("Download Table as CSV") | |
| download_csv_output = gr.File(label="Download CSV") | |
| download_button.click(fn=gradio_download, inputs=[], outputs=download_csv_output) | |
| # Launch the app | |
| demo.launch() | |