app.py

"""
IPL Score Predictor – Hugging Face Space
app.py  (entry point)
"""

import os, pickle, pathlib
import pandas as pd
import gradio as gr
from Mymodelfile import MyModel, ACTIVE_TEAMS, VENUE_NORM, SEASON_MAP

# ── paths ────────────────────────────────────────────────────────────────────
DATA_DIR   = pathlib.Path(".")
MODEL_PATH = DATA_DIR / "ipl_svr_model.pkl"

MATCHES_CSV    = DATA_DIR / "matches_updated_ipl_upto_2025.csv"
DELIVERIES_CSV = DATA_DIR / "deliveries_updated_ipl_upto_2025.csv"
PLAYERS_CSV    = DATA_DIR / "ipl_players_uniqueid.csv"

# ── venue list (canonical names from VENUE_NORM values) ──────────────────────
VENUES = sorted(set(VENUE_NORM.values()))

# ── team list ─────────────────────────────────────────────────────────────────
TEAMS = sorted(ACTIVE_TEAMS)

# ── toss options ──────────────────────────────────────────────────────────────
TOSS_DECISIONS = ["bat", "field"]

# ── innings options ───────────────────────────────────────────────────────────
INNINGS = ["1", "2"]

# ── season (current / upcoming) ───────────────────────────────────────────────
SEASONS = sorted(SEASON_MAP.keys(), key=lambda x: SEASON_MAP[x])


# ─────────────────────────────────────────────────────────────────────────────
# Model loading / training
# ─────────────────────────────────────────────────────────────────────────────

def _train_and_save() -> MyModel:
    print("Training model on provided CSVs …")
    deliveries = pd.read_csv(DELIVERIES_CSV)
    matches    = pd.read_csv(MATCHES_CSV)
    players    = pd.read_csv(PLAYERS_CSV) if PLAYERS_CSV.exists() else None

    mdl = MyModel()
    mdl.fit(deliveries, players_df=players, matches_df=matches)

    with open(MODEL_PATH, "wb") as f:
        pickle.dump(mdl, f)
    print("Model saved to", MODEL_PATH)
    return mdl


def _load_model() -> MyModel:
    if MODEL_PATH.exists():
        print("Loading cached model …")
        with open(MODEL_PATH, "rb") as f:
            return pickle.load(f)
    return _train_and_save()


# ─────────────────────────────────────────────────────────────────────────────
# Prediction helper
# ─────────────────────────────────────────────────────────────────────────────

def predict_score(
    batting_team: str,
    bowling_team: str,
    toss_winner:  str,
    toss_decision: str,
    venue:        str,
    wickets:      int,
    inning:       str,
    season:       str,
) -> str:

    if batting_team == bowling_team:
        return "⚠️  Batting and bowling teams must be different."

    test_df = pd.DataFrame([{
        "id":              1,
        "innings":         int(inning),
        "venue":           venue,
        "season":          season,
        "batting_team":    batting_team,
        "bowling_team":    bowling_team,
        "toss_winner":     toss_winner,
        "toss_decision":   toss_decision,
        # wickets encoded as comma-separated dummy player ids
        "Batsman's Player Id": ",".join(["P"] * (wickets + 2)),
    }])

    result_df = MODEL.predict(test_df)
    score     = int(result_df.iloc[0]["predicted_score"])
    return f"🏏  Predicted innings score:  **{score}**"


# ─────────────────────────────────────────────────────────────────────────────
# Build the Gradio UI
# ─────────────────────────────────────────────────────────────────────────────

CSS = """
/* ── root palette ─────────────────────────────────────────────────────────── */
:root {
    --ipl-blue:   #0a1628;
    --ipl-gold:   #d4a017;
    --ipl-cream:  #f5efe0;
    --ipl-red:    #c0392b;
    --card-bg:    rgba(255,255,255,0.04);
    --radius:     12px;
}

/* ── global ──────────────────────────────────────────────────────────────── */
body, .gradio-container {
    background: var(--ipl-blue) !important;
    font-family: 'Georgia', serif;
    color: var(--ipl-cream) !important;
}

/* ── header band ─────────────────────────────────────────────────────────── */
#header {
    text-align: center;
    padding: 28px 0 10px;
    border-bottom: 2px solid var(--ipl-gold);
    margin-bottom: 24px;
}
#header h1 {
    font-size: 2.4rem;
    color: var(--ipl-gold);
    letter-spacing: 0.08em;
    margin: 0 0 4px;
    text-shadow: 0 2px 12px rgba(212,160,23,.45);
}
#header p {
    font-size: 0.95rem;
    color: var(--ipl-cream);
    opacity: .7;
    margin: 0;
    letter-spacing: 0.05em;
}

/* ── section labels ──────────────────────────────────────────────────────── */
.gr-form label, .gr-block label span {
    color: var(--ipl-gold) !important;
    font-size: 0.82rem;
    letter-spacing: 0.06em;
    text-transform: uppercase;
}

/* ── dropdowns / inputs ──────────────────────────────────────────────────── */
select, input[type=number] {
    background: rgba(255,255,255,0.07) !important;
    border: 1px solid rgba(212,160,23,.4) !important;
    border-radius: var(--radius) !important;
    color: var(--ipl-cream) !important;
    padding: 8px 12px !important;
}
select:focus, input[type=number]:focus {
    border-color: var(--ipl-gold) !important;
    outline: none !important;
    box-shadow: 0 0 0 2px rgba(212,160,23,.25) !important;
}

/* ── predict button ──────────────────────────────────────────────────────── */
#predict-btn {
    background: linear-gradient(135deg, var(--ipl-gold) 0%, #b8860b 100%) !important;
    color: var(--ipl-blue) !important;
    font-weight: 700;
    font-size: 1rem;
    letter-spacing: 0.1em;
    text-transform: uppercase;
    border: none !important;
    border-radius: var(--radius) !important;
    padding: 14px 0 !important;
    margin-top: 12px;
    transition: transform .15s, box-shadow .15s;
}
#predict-btn:hover {
    transform: translateY(-2px);
    box-shadow: 0 6px 24px rgba(212,160,23,.45) !important;
}

/* ── result box ──────────────────────────────────────────────────────────── */
#result-box {
    background: var(--card-bg) !important;
    border: 1px solid var(--ipl-gold) !important;
    border-radius: var(--radius) !important;
    text-align: center;
    font-size: 1.5rem !important;
    color: var(--ipl-cream) !important;
    padding: 18px !important;
    min-height: 70px;
}

/* ── card wrappers ───────────────────────────────────────────────────────── */
.gr-group, .gr-box {
    background: var(--card-bg) !important;
    border: 1px solid rgba(212,160,23,.18) !important;
    border-radius: var(--radius) !important;
}

/* ── note block ──────────────────────────────────────────────────────────── */
#note {
    font-size: 0.78rem;
    color: rgba(245,239,224,.5);
    text-align: center;
    margin-top: 8px;
}
"""

def build_ui() -> gr.Blocks:
    with gr.Blocks(css=CSS, title="IPL Score Predictor") as demo:

        # ── header ────────────────────────────────────────────────────────
        gr.HTML("""
        <div id="header">
            <h1>🏏 IPL Score Predictor</h1>
            <p>SVR model · trained on IPL 2007 – 2025 data</p>
        </div>
        """)

        # ── inputs ────────────────────────────────────────────────────────
        with gr.Row():
            with gr.Column():
                batting_team = gr.Dropdown(
                    choices=TEAMS,
                    label="Batting Team",
                    value=TEAMS[0],
                )
                bowling_team = gr.Dropdown(
                    choices=TEAMS,
                    label="Bowling Team",
                    value=TEAMS[1],
                )

            with gr.Column():
                toss_winner = gr.Dropdown(
                    choices=TEAMS,
                    label="Toss Won By",
                    value=TEAMS[0],
                )
                toss_decision = gr.Dropdown(
                    choices=TOSS_DECISIONS,
                    label="Toss Decision",
                    value="bat",
                )

        with gr.Row():
            venue = gr.Dropdown(
                choices=VENUES,
                label="Venue",
                value=VENUES[0],
            )
            inning = gr.Dropdown(
                choices=INNINGS,
                label="Innings",
                value="1",
            )
            season = gr.Dropdown(
                choices=SEASONS,
                label="Season",
                value="2025",
            )
            wickets = gr.Number(
                label="Wickets Fallen (0–10)",
                value=0,
                minimum=0,
                maximum=10,
                precision=0,
            )

        # ── predict button ─────────────────────────────────────────────────
        predict_btn = gr.Button("Predict Score", elem_id="predict-btn")

        # ── output ────────────────────────────────────────────────────────
        result = gr.Markdown(
            value="*Fill in the inputs above and click Predict Score.*",
            elem_id="result-box",
        )

        gr.HTML("""
        <p id="note">
            Predictions are rounded up to the nearest 5. Model uses venue × wickets × h2h × form features.
        </p>
        """)

        # ── wiring ────────────────────────────────────────────────────────
        predict_btn.click(
            fn=predict_score,
            inputs=[
                batting_team, bowling_team,
                toss_winner, toss_decision,
                venue, wickets, inning, season,
            ],
            outputs=result,
        )

    return demo


# ─────────────────────────────────────────────────────────────────────────────
# Entry point
# ─────────────────────────────────────────────────────────────────────────────

if __name__ == "__main__":
    MODEL = _load_model()
    app   = build_ui()
    app.launch()
else:
    # When Hugging Face imports this module directly
    MODEL = _load_model()
    app   = build_ui()