import streamlit as st
import assemblyai as aai

from enum import Enum

class SentimentType(Enum):
    NEUTRAL = 'neutral'
    POSITIVE = 'POSITIVE'
    NEGATIVE = 'NEGATIVE'

class Entry:
    def __init__(self, text, start, end, confidence, speaker, sentiment):
        self.text = text
        self.start = start
        self.end = end
        self.confidence = confidence
        self.speaker = speaker
        self.sentiment = sentiment

if 'body' not in st.session_state:    
    st.session_state.body = []

st.session_state.summary = ""
st.session_state.senti = ""
def readFiles(file):
    audio_process(file)

def audio_process(file):
    aai.settings.api_key = "ea2cabb1f91545f28590043ea73fc63c"    
    config = aai.TranscriptionConfig(
        speech_model=aai.SpeechModel.best,
        iab_categories=True,
        # auto_chapters=True,
        #   content_safety=True,
        # auto_highlights=True,
        sentiment_analysis=True,
        entity_detection=True,
        speaker_labels=True,
        #   filter_profanity=True,
        language_detection=True,
        summarization=True,        
        # summary_type=aai.SummarizationType.bullets
    ).set_redact_pii(
    policies=[
        aai.PIIRedactionPolicy.medical_condition,
        # aai.PIIRedactionPolicy.email_address,
        # aai.PIIRedactionPolicy.phone_number,
        # aai.PIIRedactionPolicy.banking_information,
        # aai.PIIRedactionPolicy.credit_card_number,
        # aai.PIIRedactionPolicy.credit_card_cvv,
        # aai.PIIRedactionPolicy.date_of_birth,
        # aai.PIIRedactionPolicy.person_name
    ]
    )

    transcriber = aai.Transcriber(config=config)
    transcript = transcriber.transcribe(file)

    if transcript.status == aai.TranscriptStatus.error:
        print(transcript.error)
    else:        
        for utterance in transcript.utterances:
            result = {'speaker': utterance.speaker, 'answer': utterance.text}
            st.session_state.body.append(result)
        st.session_state.summary = transcript.summary
        negative = 0
        positive = 0
        neutral = 0
        for sentiment_result in transcript.sentiment_analysis:
            sents = sentiment_result.sentiment
           
            if sents.value=='NEGATIVE':
                negative = negative+1
            if sents.value=='NEUTRAL':
                neutral = neutral+1
            if sents.value=='POSITIVE':
                positive = positive+1
        
        st.session_state.senti = f"Neutral: {neutral}, Positive : {positive}, Negative : {negative}"       
        
            
col1, col2 = st.columns(2)  
def main():
    with st.sidebar:
        st.header("Upload Audio File Here", divider='rainbow')
        files = st.file_uploader('', accept_multiple_files=False)
        button = st.button("Process")
        if button:
            if files:
                with st.spinner("Processing"):
                    readFiles(files)
            else:
                st.error('No files selected')
    
    with col1:
        st.subheader('CONVERSATIONS', divider='rainbow')
        for chat in st.session_state.body:        
            with st.chat_message(chat["speaker"]):
                st.write(chat["answer"])
    with col2:
        st.subheader('SUMMARY', divider='rainbow')
        st.write(st.session_state.summary)
        st.subheader('SENTIMENT ANALYSIS', divider='rainbow')
        st.write(st.session_state.senti)
if __name__ == "__main__":
    main()