Fixed what I broke maybe

app_storefront.py

@@ -3,50 +3,55 @@ import os
 import sys
 import gradio as gr
 
-# Make "core/" importable even on Spaces
+# Ensure "core/" is importable
 sys.path.append(os.path.join(os.path.dirname(__file__), "core"))
 
-# --- New modules ---
+# Import only functions; core.storefront doesn't export constants
 from core.model import model_generate, MODEL_NAME
 from core.memory import build_prompt_from_history
-from core.storefront import (
-    load_storefront,
-    storefront_qna,
-    extract_products,
-    get_rules,
-    DEFAULT_PRODUCTS as CORE_DEFAULT_PRODUCTS,
-    DEFAULT_PARKING as CORE_DEFAULT_PARKING,
-    DEFAULT_VENUE as CORE_DEFAULT_VENUE,
-    USE_HELPERS,
-    STORE_DATA,
-)
-
-# ---------------- Data for tabs (safe fallbacks) ----------------
-# Try to load JSON data; if not available, use module defaults.
-_loaded = load_storefront()  # may be None if JSON absent/empty
-if _loaded:
-    PRODUCTS = extract_products(_loaded) or CORE_DEFAULT_PRODUCTS
-    RULES = get_rules(_loaded) or {"venue": CORE_DEFAULT_VENUE, "parking": CORE_DEFAULT_PARKING}
+from core.storefront import load_storefront, storefront_qna, extract_products, get_rules
+
+# ---------------- Load data + safe fallbacks ----------------
+DATA = load_storefront()  # may be None if storefront_data.json missing/empty
+
+# Fallbacks used if JSON not present
+FALLBACK_PRODUCTS = [
+    {"sku": "CG-SET", "name": "Cap & Gown Set", "price": 59.00,
+     "notes": "Tassel included; ships until 10 days before the event"},
+    {"sku": "PK-1",   "name": "Parking Pass",   "price": 10.00,
+     "notes": "Multiple passes are allowed per student"}
+]
+FALLBACK_VENUE = [
+    "Formal attire recommended (not required).",
+    "No muscle shirts.",
+    "No sagging pants."
+]
+FALLBACK_PARKING = [
+    "No double parking.",
+    "Vehicles parked in handicap spaces will be towed."
+]
+
+# Normalize products/rules for the tabs
+if DATA:
+    PRODUCTS = extract_products(DATA) or FALLBACK_PRODUCTS
+    venue_rules, parking_rules = get_rules(DATA)
+    VENUE_RULES = venue_rules or FALLBACK_VENUE
+    PARKING_RULES = parking_rules or FALLBACK_PARKING
 else:
-    PRODUCTS = CORE_DEFAULT_PRODUCTS
-    RULES = {"venue": CORE_DEFAULT_VENUE, "parking": CORE_DEFAULT_PARKING}
+    PRODUCTS = FALLBACK_PRODUCTS
+    VENUE_RULES = FALLBACK_VENUE
+    PARKING_RULES = FALLBACK_PARKING
 
-DEFAULT_PRODUCTS = PRODUCTS
-DEFAULT_VENUE = RULES.get("venue", CORE_DEFAULT_VENUE)
-DEFAULT_PARKING = RULES.get("parking", CORE_DEFAULT_PARKING)
-
-# ---------------- Utilities ----------------
 def clean_generation(text: str) -> str:
-    """Tiny post-process to strip runaway prefixes or trailing artifacts."""
     return (text or "").strip()
 
 # ---------------- Chat logic ----------------
 def chat_pipeline(history, message, max_new_tokens=128, temperature=0.8, top_p=0.95):
-    # 1) Intercept storefront facts first (reduces hallucinations)
-    sf = storefront_qna(message)
+    # 1) Use storefront facts first (reduces hallucinations)
+    sf = storefront_qna(DATA, message)  # <-- pass DATA!
     if sf:
         return sf
-    # 2) Memory-aware prompt for the model
+    # 2) Memory-aware prompt to keep context grounded
     prompt = build_prompt_from_history(history, message, k=4)
     gen = model_generate(prompt, max_new_tokens, temperature, top_p)
     return clean_generation(gen)
@@ -62,24 +67,17 @@ CSS = """
 with gr.Blocks(title="Storefront Chat", css=CSS) as demo:
     gr.Markdown("## Storefront Chat")
 
-    # Single source of truth for conversation history
+    # Single history state (kept in sync with Chatbot)
     history_state = gr.State([])
 
     with gr.Tabs():
         # --- TAB: Chat ---
         with gr.TabItem("Chat"):
             with gr.Group(elem_classes=["panel"]):
-                chat = gr.Chatbot(
-                    height=360,
-                    bubble_full_width=False,
-                    label="Chat"
-                )
+                chat = gr.Chatbot(height=360, bubble_full_width=False, label="Chat")
 
                 with gr.Row():
-                    msg = gr.Textbox(
-                        placeholder="Ask about parking rules, attire, cap & gown, pickup times…",
-                        scale=5
-                    )
+                    msg  = gr.Textbox(placeholder="Ask about parking rules, attire, cap & gown, pickup times…", scale=5)
                     send = gr.Button("Send", scale=1)
 
                 # Quick chips
@@ -89,7 +87,7 @@ with gr.Blocks(title="Storefront Chat", css=CSS) as demo:
                     chip3 = gr.Button("Attire", variant="secondary")
                     chip4 = gr.Button("When do lots open?", variant="secondary")
 
-                # Advanced (sliders + health/capabilities) — kept off the main screen
+                # Advanced options (sliders + Health/Capabilities)
                 with gr.Accordion("Advanced chat options", open=False):
                     max_new = gr.Slider(32, 512, 128, 1, label="Max new tokens")
                     temp    = gr.Slider(0.1, 1.5, 0.8, 0.05, label="Temperature")
@@ -103,16 +101,16 @@ with gr.Blocks(title="Storefront Chat", css=CSS) as demo:
         # --- TAB: Products ---
         with gr.TabItem("Products"):
             gr.Markdown("### Available Items")
-            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]
-            gr.Dataframe(headers=cols, value=data, interactive=False, wrap=True, label="Products")
+            cols = ["sku", "name", "price", "notes"]
+            data = [[p.get(c, "") for c in cols] for p in PRODUCTS]
+            gr.Dataframe(headers=[c.upper() for c in cols], value=data, interactive=False, wrap=True, label="Products")
 
         # --- TAB: Rules ---
         with gr.TabItem("Rules"):
             gr.Markdown("### Venue rules")
-            gr.Markdown("- " + "\n- ".join(DEFAULT_VENUE))
+            gr.Markdown("- " + "\n- ".join(VENUE_RULES))
             gr.Markdown("### Parking rules")
-            gr.Markdown("- " + "\n- ".join(DEFAULT_PARKING))
+            gr.Markdown("- " + "\n- ".join(PARKING_RULES))
 
         # --- TAB: Logistics ---
         with gr.TabItem("Logistics"):
@@ -127,7 +125,6 @@ with gr.Blocks(title="Storefront Chat", css=CSS) as demo:
 
     # ---------- Helpers ----------
     def _append_bot_md(history, md_text):
-        """Append a bot-side markdown message while preserving the [[u,b],…] format."""
         history = history or []
         return history + [[None, md_text]]
 
@@ -135,49 +132,44 @@ with gr.Blocks(title="Storefront Chat", css=CSS) as demo:
     def on_send(history, message, max_new_tokens, temperature, top_p):
         t = (message or "").strip()
         if not t:
-            return history, history, ""  # no-op; keep shapes identical
-        # add user row
+            return history, history, ""  # no-op; shapes must match
         history = (history or []) + [[t, None]]
-        # generate reply using history prior to this turn
         reply = chat_pipeline(history[:-1], t, max_new_tokens, temperature, top_p)
         history[-1][1] = reply
-        # update both state and Chatbot, clear textbox
         return history, history, ""
 
     def _health_cb(history):
         md = (
             f"### Status: ✅ Healthy\n"
             f"- 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'}"
+            f"- Storefront JSON: {'loaded' if bool(DATA) else 'not found'}"
         )
         new_hist = _append_bot_md(history, md)
-        # Update chat AND status label
         return new_hist, new_hist, "Status: ✅ Healthy"
 
     def _caps_cb(history):
-        caps = [
-            "Chat (LLM text-generation, memory-aware prompt)",
-            "Storefront Q&A (parking, attire, products, logistics)",
-            "Adjustable: max_new_tokens, temperature, top-p",
-        ]
-        md = "### Capabilities\n- " + "\n- ".join(caps)
+        md = (
+            "### Capabilities\n"
+            "- Chat (LLM text-generation, memory-aware prompt)\n"
+            "- Storefront Q&A (parking, attire, products, logistics)\n"
+            "- Adjustable: max_new_tokens, temperature, top-p"
+        )
         new_hist = _append_bot_md(history, md)
         return new_hist, new_hist
 
-    # Wire up (update both the state and Chatbot widget)
+    # Wire up (state + chatbot)
     send.click(on_send, [history_state, msg, max_new, temp, topp], [history_state, chat, msg])
     msg.submit(on_send, [history_state, msg, max_new, temp, topp], [history_state, chat, msg])
 
-    # Chips → prefill textbox (don’t mutate history)
+    # Chips → prefill textbox
     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: "What time do the parking lots open?", outputs=msg)
 
-    # Health / Capabilities: now inside the Advanced accordion
+    # Health / Capabilities live inside Advanced
     health_btn.click(_health_cb, inputs=[history_state], outputs=[history_state, chat, status_md])
-    caps_btn.click(_caps_cb, inputs=[history_state], outputs=[history_state, chat])
+    caps_btn.click(_caps_cb,   inputs=[history_state], outputs=[history_state, chat])
 
 if __name__ == "__main__":
     demo.launch(server_name="0.0.0.0", server_port=int(os.getenv("PORT", "7860")))