storefront_app.py

import os, json
import gradio as gr
from transformers import pipeline

# ---------------- Model (unchanged from your demo) ----------------
MODEL_NAME = os.getenv("HF_MODEL_GENERATION", "distilgpt2")
_pipe = None
def _get_pipe():
    global _pipe
    if _pipe is None:
        _pipe = pipeline("text-generation", model=MODEL_NAME)
    return _pipe

def model_generate(message, max_new_tokens=128, temperature=0.8, top_p=0.95):
    pipe = _get_pipe()
    out = pipe(
        message,
        max_new_tokens=int(max_new_tokens),
        do_sample=True,
        temperature=float(temperature),
        top_p=float(top_p),
        pad_token_id=50256,
    )
    return out[0]["generated_text"]

# ---------------- Storefront knowledge (prefers your helper module) ----------------
# First try to import your module (recommended location)
STORE_DATA = None
USE_HELPERS = False
try:
    from agenticcore.storefront_rules import (
        load_storefront, answer_faq, get_parking_rules, get_venue_rules, search_products
    )
    STORE_DATA = load_storefront()      # loads agenticcore/storefront_data.json by default
    USE_HELPERS = True
except Exception:
    # Fallback: try JSON next to this file or under agenticcore/
    CANDIDATE_JSON = [
        os.path.join(os.path.dirname(__file__), "storefront_data.json"),
        os.path.join(os.path.dirname(__file__), "agenticcore", "storefront_data.json"),
    ]
    for p in CANDIDATE_JSON:
        if os.path.exists(p):
            with open(p, "r", encoding="utf-8") as f:
                STORE_DATA = json.load(f)
            break

# Defaults (used when no JSON/module found)
DEFAULT_PRODUCTS = [
    {"SKU": "CG-SET", "Name": "Cap & Gown Set", "Price": 59.00, "Notes": "Tassel included; ship until 10 days before event"},
    {"SKU": "PK-1",   "Name": "Parking Pass",   "Price": 10.00, "Notes": "Multiple passes allowed per student"},
]
DEFAULT_PARKING = ["No double parking.", "Vehicles parked in handicap will be towed."]
DEFAULT_VENUE   = ["Formal attire recommended (not required).", "No muscle shirts.", "No sagging pants."]

if STORE_DATA:
    # Build right-panel tables from JSON schema
    try:
        DEFAULT_PRODUCTS = []
        for p in STORE_DATA.get("products", []):
            DEFAULT_PRODUCTS.append({
                "SKU": p.get("sku",""),
                "Name": p.get("name",""),
                "Price": p.get("price_usd", ""),
                "Notes": (p.get("description") or "")[:120],
            })
        pr = STORE_DATA.get("policies", {}).get("parking_rules", [])
        vr = STORE_DATA.get("policies", {}).get("venue_rules", [])
        DEFAULT_PARKING = pr or DEFAULT_PARKING
        DEFAULT_VENUE = vr or DEFAULT_VENUE
    except Exception:
        pass

def storefront_qna(text: str) -> str | None:
    """Try to answer with storefront data (FAQ, rules, products)."""
    t = (text or "").lower().strip()
    if not t:
        return None

    # Use your helper functions if available (preferred)
    if USE_HELPERS and STORE_DATA:
        a = answer_faq(STORE_DATA, t)
        if a:
            return a
        if "parking rule" in t or ("parking" in t and "rule" in t):
            rules = get_parking_rules(STORE_DATA)
            if rules:
                return "Parking rules:\n- " + "\n- ".join(rules)
        if "venue rule" in t or "dress code" in t or "attire" in t:
            rules = get_venue_rules(STORE_DATA)
            if rules:
                return "Venue rules:\n- " + "\n- ".join(rules)
        hits = search_products(STORE_DATA, t)
        if hits:
            lines = []
            for p in hits:
                price = p.get("price_usd")
                price_str = f"${price:.2f}" if isinstance(price, (int, float)) else str(price)
                lines.append(f"{p.get('name','Item')} — {price_str}: {p.get('description','')}")
            return "\n".join(lines)
        return None

    # Fallback logic (no helper module)
    if "parking" in t and ("more than one" in t or "multiple" in t or "extra" in t):
        return "Yes, multiple parking passes are allowed per student."
    if "parking rule" in t or ("parking" in t and "rule" in t):
        return "Parking rules:\n- " + "\n- ".join(DEFAULT_PARKING)
    if "venue rule" in t or "dress code" in t or "attire" in t:
        return "Venue rules:\n- " + "\n- ".join(DEFAULT_VENUE)
    if "cap" in t or "gown" in t:
        lines = []
        for p in DEFAULT_PRODUCTS:
            price = p.get("Price")
            price_str = f"${price:.2f}" if isinstance(price, (int, float)) else str(price)
            lines.append(f"{p.get('Name','Item')} — {price_str}: {p.get('Notes','')}")
        return "\n".join(lines)
    return None

def chat_pipeline(message, max_new_tokens=128, temperature=0.8, top_p=0.95):
    sf = storefront_qna(message)
    if sf:
        return sf
    return model_generate(message, max_new_tokens, temperature, top_p)

# ---------------- Gradio UI (storefront look) ----------------
CUSTOM_CSS = """
:root { --bg:#0b0d12; --panel:#0f172a; --panel-2:#111827; --border:#1f2940; --text:#e5e7eb; --muted:#9ca3af; }
.gradio-container { background: var(--bg) !important; color: var(--text) !important; }
#header, .panel { border:1px solid var(--border); border-radius:16px; background:var(--panel); }
.small { font-size:12px; color: var(--muted); }
.badge { font-size:12px; opacity:.9; padding:4px 8px; border:1px solid var(--border); border-radius:999px; background: rgba(255,255,255,.04); }
"""

with gr.Blocks(title="Storefront Chat • Cap & Gown + Parking", css=CUSTOM_CSS) as demo:
    with gr.Row(elem_id="header"):
        gr.Markdown("## Storefront Chat • Cap & Gown + Parking")
        gr.Markdown("<div class='badge'>Gradio • LLM • Storefront Q&A</div>", elem_classes=["small"])

    with gr.Row():
        with gr.Column(scale=3):
            with gr.Group(elem_classes=["panel"]):
                with gr.Row():
                    health_btn = gr.Button("Health", variant="secondary")
                    caps_btn = gr.Button("Capabilities", variant="secondary")
                    status_md = gr.Markdown("Status: not checked", elem_classes=["small"])

                chatbot = gr.Chatbot(value=[], height=360, bubble_full_width=False, avatar_images=(None, None), label="Chat")

                with gr.Row():
                    msg = gr.Textbox(placeholder="Ask about cap & gown sizes, parking rules, refunds, etc…", scale=5)
                    send = gr.Button("Send", scale=1)

                # Quick chips
                with gr.Row():
                    chip1 = gr.Button("Parking rules", variant="secondary")
                    chip2 = gr.Button("Multiple passes", variant="secondary")
                    chip3 = gr.Button("Attire", variant="secondary")
                    chip4 = gr.Button("Sizing", variant="secondary")
                    chip5 = gr.Button("Refunds", variant="secondary")
                    chip6 = gr.Button("Shipping cutoff", variant="secondary")

                with gr.Row():
                    max_new = gr.Slider(32, 512, 128, 1, label="Max new tokens")
                with gr.Row():
                    temp = gr.Slider(0.1, 1.5, 0.8, 0.05, label="Temperature")
                with gr.Row():
                    topp = gr.Slider(0.1, 1.0, 0.95, 0.05, label="Top-p")

        with gr.Column(scale=2):
            with gr.Group(elem_classes=["panel"]):
                gr.Markdown("### Products")
                cols = list(DEFAULT_PRODUCTS[0].keys()) if DEFAULT_PRODUCTS else ["SKU","Name","Price","Notes"]
                data = [[p.get(c,"") for c in cols] for p in DEFAULT_PRODUCTS]
                products_tbl = gr.Dataframe(headers=cols, value=data, interactive=False, wrap=True)

            with gr.Group(elem_classes=["panel"]):
                gr.Markdown("### Rules (Venue & Parking)")
                rules_md = gr.Markdown("- " + "\n- ".join(DEFAULT_VENUE + DEFAULT_PARKING))

            with gr.Group(elem_classes=["panel"]):
                gr.Markdown("### Logistics")
                gr.Markdown(
                    "- Shipping available until 10 days before event (typ. 3–5 business days)\n"
                    "- Pickup: Student Center Bookstore during week prior to event\n"
                    "- Graduates arrive 90 minutes early; guests 60 minutes early\n"
                    "- Lots A & B open 2 hours before; overflow as needed\n"
                    "\n*Try: “What time should I arrive?” or “Where do I pick up the gown?”*"
                )

    # ---- wiring ----
    def on_send(history, message, max_new_tokens, temperature, top_p):
        message = (message or "").strip()
        if not message:
            return history, ""
        history = history + [[message, None]]
        reply = chat_pipeline(message, max_new_tokens, temperature, top_p)
        history[-1][1] = reply
        return history, ""

    send.click(on_send, [chatbot, msg, max_new, temp, topp], [chatbot, msg])
    msg.submit(on_send, [chatbot, msg, max_new, temp, topp], [chatbot, msg])

    # Quick chips → prefill
    chip1.click(lambda: "What are the parking rules?", outputs=msg)
    chip2.click(lambda: "Can I buy multiple parking passes?", outputs=msg)
    chip3.click(lambda: "Is formal attire required?", outputs=msg)
    chip4.click(lambda: "How do I pick a cap & gown size?", outputs=msg)
    chip5.click(lambda: "What is the refund policy?", outputs=msg)
    chip6.click(lambda: "When is the shipping cutoff for cap & gown?", outputs=msg)

    # Health / capabilities
    def ui_health_check():
        return (f"### Status: ✅ Healthy\n- Model: `{MODEL_NAME}`\n"
                f"- Storefront module: {'yes' if USE_HELPERS else 'no'}\n"
                f"- Storefront JSON: {'loaded' if bool(STORE_DATA) else 'not found'}")
    def ui_capabilities():
        caps = [
            "Chat (LLM – text-generation)",
            "Quick storefront Q&A (parking rules, attire, products)",
            "Adjustable: max_new_tokens, temperature, top-p",
        ]
        return "### Capabilities\n- " + "\n- ".join(caps)

    def _health():
        return ui_health_check(), "Status: ✅ Healthy"

    health_btn.click(_health, outputs=[chatbot, status_md])
    caps_btn.click(ui_capabilities, outputs=chatbot)

if __name__ == "__main__":
    demo.launch(server_name="0.0.0.0", server_port=int(os.getenv("PORT", "7860")))