app.py

import streamlit as st
import plotly.graph_objects as go
from transformers import pipeline
from pydub import AudioSegment
import os
import re
from docx import Document
from docx.shared import Pt
from docx.enum.text import WD_PARAGRAPH_ALIGNMENT
from datetime import datetime

# Page config
st.set_page_config(page_title="Atma.ai - Session Summarizer + Export", layout="wide")

st.title("🧠 Atma.ai – Advanced Mental Health Session Summarizer")
st.markdown("Upload a therapy session audio (Tamil-English mix) to view the transcript, summary, emotional analysis, and export everything to Word!")

# Upload audio
uploaded_file = st.file_uploader("🎙️ Upload audio file", type=["wav", "mp3", "m4a"])

if uploaded_file:
    st.audio(uploaded_file)

    # Convert audio to required format
    audio_path = "temp_audio.wav"
    audio = AudioSegment.from_file(uploaded_file)
    audio = audio.set_channels(1).set_frame_rate(16000)
    audio.export(audio_path, format="wav")

    try:
        pass  # Placeholder to avoid empty try
    except Exception as e:
        st.error(f"❌ Processing failed: {e}")
        tab1, tab2, tab3, tab4 = st.tabs(["📝 Transcript", "📋 Summary", "💬 Emotions", "📈 Trends"])
            tab1, tab2, tab3 = tab1, tab2, tab3, tab4 = st.tabs(["📝 Transcript", "📋 Summary", "💬 Emotions", "📈 Trends"])

            with tab1:
                st.subheader("📝 Speaker-Simulated Transcript")
                st.markdown(diarized_transcript, unsafe_allow_html=True)

            with tab2:
                st.subheader("📋 Contextual Summary")
                st.write(summary[0]["summary_text"])

            with tab3:
                st.subheader("💬 Emotional Insights (Overall)")
                if 'emotion_scores' in locals():
                    for emo in emotion_scores[0]:
                        st.write(f"{emo['label']}: {round(emo['score']*100, 2)}%")
                else:
                    st.write("No emotional data to display.")
                
            with tab4:
                st.subheader("📈 Emotional Trends Over Time")

                session_dates = ["2024-04-01", "2024-04-08", "2024-04-15", "2024-04-22"]
                anxiety_scores = [70, 65, 55, 40]
                sadness_scores = [30, 20, 25, 15]
            
                fig = go.Figure()
                fig.add_trace(go.Scatter(x=session_dates, y=anxiety_scores, mode='lines+markers', name='Anxiety'))
                fig.add_trace(go.Scatter(x=session_dates, y=sadness_scores, mode='lines+markers', name='Sadness'))
                fig.update_layout(title='Emotional Trends', xaxis_title='Date', yaxis_title='Score (%)')
                st.plotly_chart(fig)

            # Export Button
            st.subheader("📥 Export Session Report")

            def generate_docx(transcript, summary_text, emotions):
                doc = Document()

                # Title
                title = doc.add_heading('Session Summary - Atma.ai', 0)
                title.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER

                # Date
                date_paragraph = doc.add_paragraph(f"Date: {datetime.now().strftime('%Y-%m-%d')}")
                date_paragraph.runs[0].italic = True

                doc.add_paragraph("\n")

                # Transcript
                doc.add_heading('📝 Transcript', level=1)
                transcript_para = doc.add_paragraph(transcript)
                transcript_para.runs[0].font.size = Pt(12)

                doc.add_paragraph("\n")

                # Summary
                doc.add_heading('📋 Summary', level=1)
                summary_para = doc.add_paragraph(summary_text)
                summary_para.runs[0].font.size = Pt(12)

                doc.add_paragraph("\n")

                # Emotional Insights
                doc.add_heading('💬 Emotional Insights', level=1)
                for emo in emotions[0]:
                    emotion_para = doc.add_paragraph(f"{emo['label']}: {round(emo['score']*100, 2)}%")
                    emotion_para.runs[0].font.size = Pt(12)

                # Footer
                doc.add_paragraph("\n\n---\nGenerated by Atma.ai – Confidential", style="Intense Quote")

                output_path = "session_summary.docx"
                doc.save(output_path)
                return output_path

            if st.button("Generate and Download Report (.docx)"):
                output_file = generate_docx(diarized_transcript, summary[0]["summary_text"], emotion_scores)
                with open(output_file, "rb") as f:
                    st.download_button(label="📥 Download Report", data=f, file_name="session_summary.docx", mime="application/vnd.openxmlformats-officedocument.wordprocessingml.document")

    except Exception as err:
        st.error(f"❌ Processing failed: {err}")
    finally:
        if os.path.exists(audio_path):
            os.remove(audio_path)