dashboard.py

from __future__ import annotations
import pandas as pd
import gradio as gr
import plotly.express as px
from data import read_events, aggregate
from bandit import EmpiricalBayesHierarchicalThompson
from causal import fit_uplift_binary

BANDIT = EmpiricalBayesHierarchicalThompson(min_explore=0.05, margin=0.0, n_draws=10000)

def ui_refresh_tables():
    df = read_events()
    agg = aggregate()
    return df, agg

def ui_recommend():
    agg = aggregate()
    if agg.empty:
        return {"message": "No data yet. Upload or POST /api/ingest first."}
    rec = BANDIT.recommend(agg)
    return rec

def ui_plot_posteriors(medium: str):
    agg = aggregate()
    if agg.empty:
        return gr.update(visible=False), "No data"
    g = agg[agg["medium"].astype(str) == str(medium)].copy()
    if g.empty:
        return gr.update(visible=False), f"No data for medium={medium}"

    # 事後平均の棒グラフ（Laplace 平滑 CTR）
    g["ctr"] = (g["clicks"] + 1) / (g["impressions"] + 2)
    fig = px.bar(g, x="creative", y="ctr", color="is_control", barmode="group", title=f"CTR (Laplace) by creative @ {medium}")
    return gr.Plot(fig), ""

def ui_fit_uplift():
    agg = aggregate()
    if agg.empty:
        return {"message": "No data"}
    res = fit_uplift_binary(agg)
    return res

def build_ui():
    with gr.Blocks(title="AdCopy MAB Optimizer Pro") as demo:
        gr.Markdown("# AdCopy MAB Optimizer Pro — Hierarchical TS + Uplift")
        with gr.Tab("Data"):
            btn = gr.Button("Refresh")
            grid = gr.Dataframe(headers=["ts","date","medium","creative","is_control","impressions","clicks","conversions","cost","features_json"], wrap=True)
            grid_agg = gr.Dataframe()
            btn.click(ui_refresh_tables, outputs=[grid, grid_agg])
        with gr.Tab("Bandit"):
            bbtn = gr.Button("Suggest Allocation (TS)")
            jout = gr.JSON()
            bbtn.click(ui_recommend, outputs=jout)
            with gr.Row():
                medium = gr.Textbox(label="Medium for Plot", value="FB")
                plot = gr.Plot(visible=False)
                msg = gr.Markdown()
            plot_btn = gr.Button("Plot CTR by Creative")
            plot_btn.click(ui_plot_posteriors, inputs=[medium], outputs=[plot, msg])
        with gr.Tab("Uplift (Causal)"):
            cbtn = gr.Button("Fit Uplift Model")
            cout = gr.JSON()
            cbtn.click(ui_fit_uplift, outputs=cout)
    return demo