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Update app.py
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app.py
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@@ -4,13 +4,13 @@ from transformers import pipeline
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import os
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from supabase import create_client, Client
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from datetime import datetime
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# Add your AssemblyAI API key as Environment Variable
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aai.settings.api_key = os.environ['Assembly']
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url: str = os.environ['DBUrl']
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key: str = os.environ['DBKey']
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# Initialize question answering pipeline
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question_answerer = pipeline("question-answering", model='distilbert-base-cased-distilled-squad')
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@@ -62,6 +62,7 @@ oral_health_assessment_form = [
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"Any other finding",
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"Treatment plan",
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]
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# Function to generate answers for the questions
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def generate_answer(question, context):
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result = question_answerer(question=question, context=context)
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@@ -138,13 +139,24 @@ def save_answers(*args):
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print(f"Error inserting data into Supabase: {e}")
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return f"Error saving answers: {e}"
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# Create the Gradio interface
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with gr.Blocks() as demo:
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gr.Markdown("# OHA Form Filler App")
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# Add HTML box to show the status
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status_box = gr.HTML("<div id='status_box' style='width: 100px; height: 30px; background-color: red;'></div>")
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audio_input = gr.Audio(type="filepath", label="Record your audio", elem_id="audio_input")
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transcribe_button = gr.Button("Transcribe and Generate Form", elem_id="transcribe_button")
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@@ -157,16 +169,9 @@ with gr.Blocks() as demo:
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submit_button = gr.Button("Submit", elem_id="submit_button")
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output_html = gr.HTML(label="Submitted Answers")
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def update_status(audio):
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if audio:
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status_box_value = "<div id='status_box' style='width: 100px; height: 30px; background-color: green;'></div>"
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else:
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status_box_value = "<div id='status_box' style='width: 100px; height: 30px; background-color: red;'></div>"
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return status_box_value, main(audio)
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transcribe_button.click(fn=update_status, inputs=audio_input, outputs=[status_box, textboxes_left + textboxes_right])
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submit_button.click(fn=save_answers, inputs=textboxes_left + textboxes_right, outputs=output_html)
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# Launch the app
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demo.launch(share=True)
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import os
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from supabase import create_client, Client
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from datetime import datetime
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import pandas as pd
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# Add your AssemblyAI API key as Environment Variable
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aai.settings.api_key = os.environ['Assembly']
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url: str = os.environ['DBUrl']
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key: str = os.environ['DBKey']
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# Initialize question answering pipeline
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question_answerer = pipeline("question-answering", model='distilbert-base-cased-distilled-squad')
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"Any other finding",
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"Treatment plan",
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]
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# Function to generate answers for the questions
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def generate_answer(question, context):
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result = question_answerer(question=question, context=context)
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print(f"Error inserting data into Supabase: {e}")
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return f"Error saving answers: {e}"
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def download_csv():
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try:
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response = supabase.table('oral_health_assessments').select("*").execute()
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data = response.data
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if data:
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df = pd.DataFrame(data)
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csv_data = df.to_csv(index=False)
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return csv_data
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else:
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return "No data available"
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except Exception as e:
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print(f"Error fetching data from Supabase: {e}")
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return f"Error: {e}"
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# Create the Gradio interface
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with gr.Blocks() as demo:
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gr.Markdown("# OHA Form Filler App")
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download_button = gr.Button("Download CSV", elem_id="download_button")
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audio_input = gr.Audio(type="filepath", label="Record your audio", elem_id="audio_input")
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transcribe_button = gr.Button("Transcribe and Generate Form", elem_id="transcribe_button")
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submit_button = gr.Button("Submit", elem_id="submit_button")
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output_html = gr.HTML(label="Submitted Answers")
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transcribe_button.click(fn=main, inputs=audio_input, outputs=textboxes_left + textboxes_right)
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submit_button.click(fn=save_answers, inputs=textboxes_left + textboxes_right, outputs=output_html)
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download_button.click(fn=download_csv, inputs=None, outputs=gr.File(label="Download CSV"))
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# Launch the app
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demo.launch(share=True)
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