pages/2_Sentiment_Analysis.py

import streamlit as st

st.set_page_config(
    page_title="Sentiment Analysis",
    page_icon="💬",
    layout="wide"
)

st.title("Sentiment Analysis Service")
st.markdown("### Status: Coming Week 2")

st.info("This service will be available after Week 2 development")

col1, col2 = st.columns([2, 1])

with col1:
    st.markdown("""
    ## What This Service Will Do
    
    Analyze sentiment of text using fine-tuned BERT model.
    
    **Capabilities:**
    - Positive, Negative, Neutral classification
    - Confidence scores
    - Batch processing support
    - Multi-language support
    
    ## Technical Implementation
    
    **Model**: DistilBERT (Fine-tuned)
    - Base: distilbert-base-uncased
    - Fine-tuned on IMDB dataset
    - 6 transformer layers
    
    **Features**:
    - Real-time inference
    - API endpoints
    - Batch processing
    - Caching for speed
    """)

with col2:
    st.markdown("### Demo UI Preview")
    
    text_input = st.text_area(
        "Enter text to analyze",
        placeholder="Type or paste text here...",
        disabled=True,
        height=150
    )
    
    if st.button("Analyze Sentiment", disabled=True):
        st.warning("Service will be available in Week 2")
    
    st.markdown("---")
    st.info("Results will appear here")

st.markdown("---")
st.caption("Coming in Week 2")