Code Editor for app.py

import streamlit as st
import pandas as pd
import numpy as np
import plotly.graph_objects as go
from datetime import datetime, timedelta

# Sample data generation
def generate_sample_data():
    current_month = datetime.now()
    last_month = current_month - timedelta(days=30)
    
    data = {
        'total_published': 1250,
        'kba_viewed_last_month': 0.78,  # 78%
        'kba_ticket_attachments': 456,
        'article_quality_index': 0.85,  # 85%
        'contribution_index': 0.72,  # 72%
        'fcr_rate': 0.65,  # 65%
        'helpful_rate': 0.92,  # 92%
        'deflection_rate': 0.45,  # 45%
        'participation_rate_change': 0.15,  # +15%
        'articles_updated': 89,
        'articles_retired': 12,
        'articles_from_tickets': 34,
        'articles_reviewed': 0.88,  # 88%
    }
    return data

# Page layout
st.set_page_config(page_title="Knowledge Base Analytics", layout="wide")
st.title("Knowledge Base Analytics Dashboard")

# Generate sample data
data = generate_sample_data()

# Create three columns for metrics
col1, col2, col3 = st.columns(3)

# Column 1 metrics
with col1:
    st.metric(
        label="Total Published Articles",
        value=data['total_published'],
        delta=f"+{15} this month"
    )
    st.metric(
        label="KBAs Viewed Rate (Last Month)",
        value=f"{data['kba_viewed_last_month']:.0%}",
        delta=f"{5}%"
    )
    st.metric(
        label="Article Quality Index",
        value=f"{data['article_quality_index']:.0%}",
        delta=f"{3}%"
    )
    st.metric(
        label="Ticket Deflection Rate",
        value=f"{data['deflection_rate']:.0%}",
        delta=f"{7}%"
    )

# Column 2 metrics
with col2:
    st.metric(
        label="KBAs Attached to Tickets",
        value=data['kba_ticket_attachments'],
        delta=f"+{23} vs last month"
    )
    st.metric(
        label="FCR Rate",
        value=f"{data['fcr_rate']:.0%}",
        delta=f"{4}%"
    )
    st.metric(
        label="Articles Updated",
        value=data['articles_updated'],
        delta=f"+{12} this month"
    )
    st.metric(
        label="Articles from Tickets",
        value=data['articles_from_tickets'],
        delta=f"+{8} this month"
    )

# Column 3 metrics
with col3:
    st.metric(
        label="Contribution Index",
        value=f"{data['contribution_index']:.0%}",
        delta=f"{6}%"
    )
    st.metric(
        label="Articles Marked Helpful",
        value=f"{data['helpful_rate']:.0%}",
        delta=f"{2}%"
    )
    st.metric(
        label="Articles Retired",
        value=data['articles_retired'],
        delta=f"-{3} this month"
    )
    st.metric(
        label="Articles Reviewed",
        value=f"{data['articles_reviewed']:.0%}",
        delta=f"{5}%"
    )

# Create trend charts
st.subheader("Monthly Trends")

# Sample monthly data for trends
months = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun']
article_creation = [45, 52, 61, 58, 65, 72]
article_usage = [320, 350, 410, 380, 450, 480]

# Create two columns for charts
chart_col1, chart_col2 = st.columns(2)

with chart_col1:
    fig1 = go.Figure()
    fig1.add_trace(go.Scatter(x=months, y=article_creation, mode='lines+markers', name='New Articles'))
    fig1.update_layout(title='Article Creation Trend', xaxis_title='Month', yaxis_title='Count')
    st.plotly_chart(fig1, use_container_width=True)

with chart_col2:
    fig2 = go.Figure()
    fig2.add_trace(go.Bar(x=months, y=article_usage, name='Article Usage'))
    fig2.update_layout(title='Article Usage Trend', xaxis_title='Month', yaxis_title='Views')
    st.plotly_chart(fig2, use_container_width=True)

# Add filters
st.sidebar.header("Filters")
date_range = st.sidebar.selectbox(
    "Time Period",
    ["Last 30 Days", "Last Quarter", "Last 6 Months", "Last Year"]
)

article_type = st.sidebar.multiselect(
    "Article Type",
    ["How-to", "Troubleshooting", "Feature Documentation", "Release Notes"],
    ["How-to", "Troubleshooting"]
)

department = st.sidebar.multiselect(
    "Department",
    ["Sales", "Support", "Engineering", "Product"],
    ["Support", "Engineering"]
)