import gradio as gr
from pydub import AudioSegment
from ailib import whisper_transcribe
import pandas as pd

def transcribe(audiofile):
    #audio = AudioSegment.from_file(audiofile)
    #open(filename, 'wb').write(audio)
    return whisper_transcribe(audiofile)

def display_text(option):
    resumen_historial = df[df.paciente==paciente]['Resumen'].iloc[0]
    historial = df[df.paciente==paciente]['EHR'].iloc[0]    
    
    return resumen_historial, historial

df = pd.read_csv('pacientes.csv')
pacientes = list(df['paciente'].unique())             # now contains PAC_ID
print('PAX:', pacientes, type(pacientes))
pid_dict = dict(zip(df.paciente, df.pac_id))
################################################
# gr.title("Demo CORFO")


with gr.Blocks() as demo:
    with gr.Row():     
        audemo = gr.Interface(
            transcribe,
            gr.Audio(sources=["microphone"], type="filepath"),
            "text",
        )
    with gr.Row():
        with gr.Column(scale=1):
            radio = gr.Radio(choices=pacientes, 
                             label="PACIENTE", value=pacientes[0], interactive=True)
        with gr.Column(scale=3):
            with gr.Row():
                left_text = gr.Markdown()
                right_text = gr.Markdown()
    
    radio.change(display_text, inputs=radio, outputs=[left_text, right_text])

demo.launch()