services/charts.py

import plotly.graph_objects as go
import pandas as pd

def create_verdict_donut(df: pd.DataFrame) -> go.Figure:
    """
    Creates a High-Fidelity Donut Chart.
    """
    if df.empty:
        return _create_empty_figure("No Data")
    
    color_map = {
        'resolved': '#10B981',          # Emerald 500
        'possibly_resolved': '#34D399', # Emerald 400
        'duplicate': '#F59E0B',         # Amber 500
        'unresolved': '#64748B',        # Slate 500
        'error': '#EF4444',             # Red 500
        'unknown': '#CBD5E1'            # Slate 300
    }
    
    colors = [color_map.get(v, '#999') for v in df['verdict']]
    total = df['count'].sum()

    fig = go.Figure(data=[go.Pie(
        labels=df['verdict'],
        values=df['count'],
        hole=0.7,              
        marker=dict(colors=colors, line=dict(color='#1F2937', width=0)),         
        textinfo='value',
        hoverinfo='label+percent',
        textfont=dict(size=14, color='white')
    )])

    fig.update_layout(        
        title=dict(
            text="Analysis Distribution", 
            font=dict(size=14, color="#6B7280"),
            x=0.5,
            xanchor='center'
        ),
        
        showlegend=True,
        legend=dict(
            orientation="h", 
            yanchor="top", 
            y=-0.1,
            xanchor="center", 
            x=0.5,
            font=dict(color="#9CA3AF", size=11)
        ),
                
        margin=dict(t=40, b=60, l=20, r=20),
        height=250,
        paper_bgcolor='rgba(0,0,0,0)',
        plot_bgcolor='rgba(0,0,0,0)',
                
        annotations=[dict(text=str(total), x=0.5, y=0.5, font_size=32, showarrow=False, font_color="#E5E7EB")],
                
        modebar_remove=['zoom', 'pan', 'select', 'lasso2d', 'zoomIn2d', 'zoomOut2d', 'autoScale2d', 'resetScale2d', 'toImage']
    )

    return fig

def create_timeline_chart(full_df: pd.DataFrame) -> go.Figure:
    """
    Creates a Timeline showing activity over time.
    """
    if full_df.empty:
        return _create_empty_figure("No Timeline Data")

    df = full_df.copy()
    
    df['date'] = pd.to_datetime(df['updated_at'], errors='coerce').dt.date
    daily_counts = df.groupby('date').size().reset_index(name='count')
    
    fig = go.Figure()

    fig.add_trace(go.Scatter(
        x=daily_counts['date'],
        y=daily_counts['count'],
        mode='lines+markers',
        name='Activity',
        line=dict(color='#3B82F6', width=2, shape='spline'),
        marker=dict(size=4, color='#60A5FA', line=dict(width=0)),
        fill='tozeroy',
        fillcolor='rgba(59, 130, 246, 0.1)'
    ))

    fig.update_layout(    
        title=dict(
            text="Activity Timeline (Last Updates)", 
            font=dict(size=14, color="#6B7280"),
            x=0.5,
            xanchor='center'
        ),
        xaxis=dict(
            showgrid=False, 
            color="#9CA3AF",
            gridcolor="rgba(255,255,255,0.1)",
            tickformat="%b %d"
        ),
        yaxis=dict(
            showgrid=True, 
            gridcolor="rgba(255,255,255,0.05)", 
            color="#9CA3AF",
            zeroline=False
        ),
        margin=dict(t=40, b=20, l=30, r=10),
        height=250,
        paper_bgcolor='rgba(0,0,0,0)',
        plot_bgcolor='rgba(0,0,0,0)',
        showlegend=False,
                
        modebar_remove=['zoom', 'pan', 'select', 'lasso2d', 'zoomIn2d', 'zoomOut2d', 'autoScale2d', 'resetScale2d', 'toImage']
    )

    return fig

def _create_empty_figure(text):
    fig = go.Figure()
    fig.add_annotation(text=text, showarrow=False, font=dict(color="gray"))
    fig.update_layout(
        height=250,
        paper_bgcolor='rgba(0,0,0,0)', 
        plot_bgcolor='rgba(0,0,0,0)', 
        xaxis=dict(visible=False), 
        yaxis=dict(visible=False),
        modebar_remove=['zoom', 'pan', 'select', 'lasso2d', 'zoomIn2d', 'zoomOut2d', 'autoScale2d', 'resetScale2d', 'toImage']
    )
    return fig

def create_efficiency_funnel(stats_df: pd.DataFrame, total_open_issues: int) -> go.Figure:
    """
    Creates a Funnel Chart showing how the AI filters the noise.
    """
    if stats_df.empty:
        return _create_empty_figure("No Data")

    total_backlog = total_open_issues
    total_analyzed = stats_df['count'].sum()
    
    ai_solved = stats_df[stats_df['verdict'].isin(['resolved', 'duplicate', 'possibly_resolved'])]['count'].sum()
    
    
    values = [total_backlog, total_analyzed, ai_solved]
    stages = ["Total Backlog", "Analyzed by AI", "Actionable Findings"]
    
    fig = go.Figure(go.Funnel(
        y=stages,
        x=values,
        textinfo="value+percent initial",
                
        textfont=dict(color="#e5e5e5", size=12),         
        marker=dict(color=["#64748B", "#4486F0", "#10B981"]), 
        connector=dict(line=dict(color="rgba(128,128,128,0.5)", width=1))
    ))

    fig.update_layout(
        title=dict(
            text="AI Efficiency Funnel", 
            font=dict(size=14, color="#6B7280"),
            x=0.5, xanchor='center'
        ),
        xaxis=dict(
            showgrid=False, 
            color="#9CA3AF",
            gridcolor="rgba(255,255,255,0.1)",
            tickformat="%b %d"
        ),
        yaxis=dict(
            showgrid=True, 
            gridcolor="rgba(255,255,255,0.1)", 
            color="#9CA3AF",
            zeroline=False
        ),
        margin=dict(t=40, b=20, l=100, r=10),
        height=250,        
        paper_bgcolor='rgba(0,0,0,0)',
        plot_bgcolor='rgba(0,0,0,0)',
        showlegend=False,
        modebar_remove=['pan', 'select', 'lasso2d', 'autoScale2d', 'resetScale2d']
    )

    return fig