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.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+wedding_docs/Cherry&Samuel[[:space:]]Wedding[[:space:]]plan[[:space:]]version[[:space:]]1.1.docx filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,344 @@
+import os, io, glob, time, hashlib
+import pandas as pd
+import numpy as np
+from typing import List, Tuple
+from dataclasses import dataclass
+from dotenv import load_dotenv
+
+# Telegram
+from telegram import Update
+from telegram.constants import ParseMode
+from telegram.ext import Application, CommandHandler, MessageHandler, ContextTypes, filters
+
+# OpenAI
+from openai import OpenAI
+
+# Files / parsing
+from docx import Document as DocxDocument
+from pypdf import PdfReader
+
+# Vector store
+import faiss
+
+load_dotenv()
+import httpx
+if not hasattr(httpx, "proxies"):
+    httpx.proxies = None
+    
+OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
+TELEGRAM_BOT_TOKEN = os.getenv("TELEGRAM_BOT_TOKEN")
+OPENAI_MODEL = os.getenv("OPENAI_MODEL", "gpt-4o-mini")
+EMBEDDING_MODEL = os.getenv("EMBEDDING_MODEL", "text-embedding-3-small")
+STRICT_DOC_MODE = (os.getenv("STRICT_DOC_MODE", "true").lower() == "true")
+
+DOCS_DIR = os.getenv("DOCS_DIR", "wedding_docs")
+INDEX_PATH = os.getenv("INDEX_PATH", "wedding.index")
+META_CSV = os.getenv("META_CSV", "wedding_chunks.csv")
+
+client = OpenAI(api_key=OPENAI_API_KEY)
+
+# -----------------------------
+# Utilities to read documents
+# -----------------------------
+
+def read_txt_md(path: str) -> str:
+    with open(path, "r", encoding="utf-8", errors="ignore") as f:
+        return f.read()
+
+def read_docx(path: str) -> str:
+    doc = DocxDocument(path)
+    return "\n".join(p.text for p in doc.paragraphs)
+
+def read_pdf(path: str) -> str:
+    reader = PdfReader(path)
+    texts = []
+    for page in reader.pages:
+        try:
+            texts.append(page.extract_text() or "")
+        except Exception:
+            pass
+    return "\n".join(texts)
+
+def read_csv_file(path: str, max_rows: int = 20000, max_chars: int = 400_000) -> str:
+    """
+    Read a CSV as text that’s friendly for RAG.
+    - Coerces everything to string
+    - Skips bad lines
+    - Truncates very large files by rows and total chars (to avoid blowing up memory)
+    """
+    try:
+        df = pd.read_csv(
+            path,
+            dtype=str,
+            on_bad_lines="skip",      # pandas>=1.4
+            nrows=max_rows,           # safeguard for very large CSVs
+            encoding="utf-8"
+        )
+    except UnicodeDecodeError:
+        # Fallback for odd encodings
+        df = pd.read_csv(
+            path,
+            dtype=str,
+            on_bad_lines="skip",
+            nrows=max_rows,
+            encoding="latin-1"
+        )
+
+    df = df.fillna("")
+
+    # Build a compact, readable text block:
+    # 1) schema
+    cols = list(df.columns)
+    schema_block = "COLUMNS: " + ", ".join(cols)
+
+    # 2) first N rows as pipe-separated lines (more RAG-friendly than raw CSV)
+    #    Example line: "col1=..., col2=..., col3=..."
+    lines = []
+    for _, row in df.iterrows():
+        kv = [f"{c}={row[c]}" for c in cols]
+        lines.append(" | ".join(kv))
+        # Hard cap to avoid giant strings
+        if sum(len(x) for x in lines) > max_chars:
+            lines.append("…(truncated)")
+            break
+
+    data_block = "\n".join(lines)
+    return f"{schema_block}\n{data_block}"
+
+def load_all_docs(folder: str) -> List[Tuple[str, str]]:
+    paths = []
+    # ADD "*.csv" here
+    for ext in ("*.md", "*.txt", "*.docx", "*.pdf", "*.csv"):
+        paths.extend(glob.glob(os.path.join(folder, ext)))
+
+    docs = []
+    for p in paths:
+        if p.endswith((".md", ".txt")):
+            text = read_txt_md(p)
+        elif p.endswith(".docx"):
+            text = read_docx(p)
+        elif p.endswith(".pdf"):
+            text = read_pdf(p)
+        elif p.endswith(".csv"):  # <--- NEW
+            text = read_csv_file(p)
+        else:
+            continue
+        docs.append((p, text))
+    return docs
+
+
+# -----------------------------
+# Chunk + Embed + Index
+# -----------------------------
+
+def chunk_text(text: str, source: str, chunk_size: int = 300, overlap: int = 80) -> List[dict]:
+    words = text.split()
+    chunks = []
+    i = 0
+    while i < len(words):
+        chunk_words = words[i:i+chunk_size]
+        chunk = " ".join(chunk_words)
+        chunks.append({
+            "source": source,
+            "chunk": chunk,
+            "hash": hashlib.md5((source + str(i) + chunk).encode("utf-8")).hexdigest()
+        })
+        i += (chunk_size - overlap)
+    return chunks
+
+def embed_texts(texts: List[str]) -> np.ndarray:
+    # Returns an array of shape (n, d)
+    # Uses OpenAI embeddings
+    resp = client.embeddings.create(model=EMBEDDING_MODEL, input=texts)
+    vecs = [item.embedding for item in resp.data]
+    return np.array(vecs).astype("float32")
+
+@dataclass
+class RAGIndex:
+    index: faiss.IndexFlatIP
+    df: pd.DataFrame  # columns: [source, chunk, hash, vector]
+    dim: int
+
+def build_or_load_index(force_rebuild: bool = False) -> RAGIndex:
+    docs = load_all_docs(DOCS_DIR)
+    if not docs:
+        raise RuntimeError(f"No docs found in {DOCS_DIR}/. Put your itinerary files there.")
+
+    # Simple staleness check: if any file is newer than index, rebuild
+    def newest_mtime():
+        paths = []
+        for ext in ("*.md", "*.txt", "*.docx", "*.pdf"):
+            paths.extend(glob.glob(os.path.join(DOCS_DIR, ext)))
+        return max(os.path.getmtime(p) for p in paths)
+
+    index_exists = os.path.exists(INDEX_PATH) and os.path.exists(META_CSV)
+    need_rebuild = force_rebuild
+    if index_exists:
+        idx_mtime = min(os.path.getmtime(INDEX_PATH), os.path.getmtime(META_CSV))
+        need_rebuild = need_rebuild or (newest_mtime() > idx_mtime)
+
+    if index_exists and not need_rebuild:
+        df = pd.read_csv(META_CSV)
+        vecs = np.load(INDEX_PATH)
+        dim = vecs.shape[1]
+        index = faiss.IndexFlatIP(dim)
+        faiss.normalize_L2(vecs)
+        index.add(vecs)
+        return RAGIndex(index=index, df=df, dim=dim)
+
+    # Rebuild
+    all_chunks = []
+    for path, text in docs:
+        if not text.strip():
+            continue
+        all_chunks.extend(chunk_text(text, source=path))
+
+    if not all_chunks:
+        raise RuntimeError("Docs were read but produced no chunks. Check formats.")
+
+    df = pd.DataFrame(all_chunks)
+    vecs = embed_texts(df["chunk"].tolist())
+    # Normalize for cosine similarity via inner product
+    faiss.normalize_L2(vecs)
+    np.save(INDEX_PATH, vecs)
+    df.to_csv(META_CSV, index=False)
+
+    dim = vecs.shape[1]
+    index = faiss.IndexFlatIP(dim)
+    index.add(vecs)
+    return RAGIndex(index=index, df=df, dim=dim)
+
+# -----------------------------
+# Retrieval + Answering
+# -----------------------------
+
+def retrieve(query: str, rag: RAGIndex, k: int = 7) -> List[dict]:
+    qvec = embed_texts([query])
+    faiss.normalize_L2(qvec)
+    D, I = rag.index.search(qvec, k)
+    results = []
+    for score, idx in zip(D[0], I[0]):
+        if idx == -1:
+            continue
+        row = rag.df.iloc[int(idx)]
+        results.append({
+            "score": float(score),
+            "source": row["source"],
+            "chunk": row["chunk"]
+        })
+    return results
+
+SYSTEM_PROMPT = (
+    "You are a helpful, concise wedding assistant for Samuel's wedding. "
+    "Answer ONLY using the provided context from the wedding documents. "
+    "If the answer isn’t in the docs, say you don’t have that info and suggest who to contact (e.g., Overall IC). "
+    "Keep answers under 6 bullets or 150 words when possible. Use SGT times."
+)
+
+async def answer_with_rag(question: str, rag: RAGIndex) -> str:
+    ctx = retrieve(question, rag, k=6)
+    context_blocks = []
+    for r in ctx:
+        # Keep brief context slices
+        text = r["chunk"]
+        if len(text) > 800:
+            text = text[:800] + "…"
+        context_blocks.append(f"[Source: {os.path.basename(r['source'])}]\n{text}")
+
+    context_text = "\n\n".join(context_blocks)
+
+    messages = [
+        {"role": "system", "content": SYSTEM_PROMPT},
+        {"role": "user", "content": f"Context from docs:\n\n{context_text}\n\nQuestion: {question}"}
+    ]
+
+    completion = client.chat.completions.create(
+        model=OPENAI_MODEL,
+        messages=messages,
+        temperature=0.2,
+    )
+    answer = completion.choices[0].message.content.strip()
+
+    if STRICT_DOC_MODE and (not context_blocks or "I don’t have that info" in answer):
+        # If no context matched strongly, enforce honesty
+        if len(context_blocks) == 0:
+            return (
+                "I couldn’t find this in the wedding docs. Please check the Family Playbook or ask the Overall IC. "
+                "You can also /refresh to make sure I have the latest files."
+            )
+    return answer
+
+# -----------------------------
+# Telegram Handlers
+# -----------------------------
+RAG = None  # lazy loaded
+
+async def ensure_rag(force: bool = False):
+    global RAG
+    if RAG is None or force:
+        RAG = build_or_load_index(force_rebuild=force)
+
+async def start(update: Update, context: ContextTypes.DEFAULT_TYPE):
+    await ensure_rag(False)
+    msg = (
+        "👋 Hello! I’m the Wedding Q&A Bot. Ask me anything about roles, timings, addresses, and logistics.\n\n"
+        "Examples:\n"
+        "• What time is the solemnisation?\n"
+        "• What’s Mum’s role during tea ceremony?\n"
+        "• Where to park at the hotel?\n"
+        "• Who holds the ang bao box?\n\n"
+        "Admins can /refresh after updating the docs."
+    )
+    await update.message.reply_text(msg)
+
+async def help_cmd(update: Update, context: ContextTypes.DEFAULT_TYPE):
+    await update.message.reply_text(
+        "Send a normal question, or use:\n"
+        "/role <name> — quick role lookup\n"
+        "/refresh — rebuild knowledge from latest docs (admin only, but not enforced)"
+    )
+
+async def role_cmd(update: Update, context: ContextTypes.DEFAULT_TYPE):
+    await ensure_rag(False)
+    name = " ".join(context.args).strip()
+    if not name:
+        await update.message.reply_text("Usage: /role <name>")
+        return
+    q = f"What is the role and responsibilities of {name}? Include timings and contact if available."
+    ans = await answer_with_rag(q, RAG)
+    await update.message.reply_text(ans, parse_mode=ParseMode.MARKDOWN)
+
+async def refresh_cmd(update: Update, context: ContextTypes.DEFAULT_TYPE):
+    await ensure_rag(True)
+    await update.message.reply_text("✅ Refreshed. I’m now using the latest documents in wedding_docs/.")
+
+async def on_message(update: Update, context: ContextTypes.DEFAULT_TYPE):
+    await ensure_rag(False)
+    text = (update.message.text or "").strip()
+    if not text:
+        return
+    ans = await answer_with_rag(text, RAG)
+    # Telegram has 4096 char limit per message; be safe
+    if len(ans) > 3500:
+        ans = ans[:3500] + "…"
+    await update.message.reply_text(ans, parse_mode=ParseMode.MARKDOWN)
+
+def main():
+    if not TELEGRAM_BOT_TOKEN:
+        raise RuntimeError("TELEGRAM_BOT_TOKEN missing")
+    if not OPENAI_API_KEY:
+        raise RuntimeError("OPENAI_API_KEY missing")
+
+    app = Application.builder().token(TELEGRAM_BOT_TOKEN).build()
+
+    app.add_handler(CommandHandler("start", start))
+    app.add_handler(CommandHandler("help", help_cmd))
+    app.add_handler(CommandHandler("role", role_cmd))
+    app.add_handler(CommandHandler("refresh", refresh_cmd))
+    app.add_handler(MessageHandler(filters.TEXT & ~filters.COMMAND, on_message))
+
+    print("Bot running… Press Ctrl+C to stop.")
+    app.run_polling(drop_pending_updates=True)
+
+if __name__ == "__main__":
+    main()

requirements.txt

@@ -0,0 +1,11 @@
+python-telegram-bot==20.7
+openai>=1.51.0
+faiss-cpu==1.8.0.post1
+python-dotenv==1.0.1
+pydantic==2.9.2
+pandas==2.2.3
+numpy==1.26.4
+python-docx==1.1.2
+pypdf==5.0.0
+unstructured==0.15.7
+unstructured[pdf]==0.15.7

wedding_docs/Cherry&Samuel Wedding plan version 1.1.docx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:438cecd73269200d9df2e16d29c094216886e72b349d4daa87298338ee3ca760
+size 4997938

wedding_docs/Samuel wedding locations.csv

@@ -0,0 +1,8 @@
+Property,Address,Google maps link,Details,Key Holders / Notes
+Groom’s Airbnb,67 Jalan Taman Jalong 2,https://maps.app.goo.gl/z8TwJpvgpNXZQGMm8,"Master: Samuel & CherryRoom 2: Andy, Kenneth, Zixian, EdwinRoom 3: Yuqi",Keys: Samuel & Yuqi
+Groom’s Family Airbnb,68 Jalan Taman Jalong 2,https://maps.app.goo.gl/fYvFjK6XDURJjw5UA,"Master: Mummy, LilianRoom 2: Auntie Wendy, Uncle BarryRoom 3–4: Samson & Wife or Sandra & Keyi",Keys: Samson & Sandra
+Bride’s House,17 Jalan Taman Jalong 4,https://maps.app.goo.gl/bNmqgDt3iuKPHV2C9,Cherry’s family,—
+Chloe (MUA) Hotel,MH Sentral,https://maps.app.goo.gl/JLvsg29VXKCmdbwo6,Chloe,5 mins from Groom’s Airbnb
+Relatives’ Airbnb 1,"No. 232 Jalan Kemiri 8, Taman Kemiri, 31100 Sungai Siput (U), Perak",https://maps.app.goo.gl/Z3KsK5dQTh97qXNWA,阿姨 family (7 pax),—
+Relatives’ Airbnb 2,"No. 250 Jalan Bistari 7, Taman Lintang Bistari, 31100 Sungai Siput (U), Perak",,Pei Wen + Husband + Serene (key holder)NabJesc + Winky + Cat + Ice (key holder)Photographer standby room,5 mins from Bride’s home
+Phongmun Restaurant Sdn Bhd,"Komersial Water pond, & 99-1, Persiaran Komersial 1, &, Persiaran Komersial 5, 31100 Sungai Siput, Perak, Malaysia",https://maps.app.goo.gl/bHuKnnUYpJKBjRzA6,Wedding dinner,

wedding_docs/Samuel wedding schedule.csv

@@ -0,0 +1,87 @@
+,Date / Time,Event / Task,Person(s) in Charge,Location,Notes / Items to Bring / Remarks
+23 Oct 2025 (Thu),23 Oct 2025 (Thu),,,,
+1,23 Oct 2025 (Thu),Arrive in Ipoh (Evening),Cherry & Samuel,—,Reach in evening
+2,23 Oct 2025 (Thu),"Prepare remaining red packets (Jie Mei, Xiong Di)",Samuel,Groom’s Airbnb,Exchange for balance $700 + $200; keep in sling bag (from mother)
+3,23 Oct 2025 (Thu),Collect 1st batch of red packets,Samuel,From DA GU,—
+4,23 Oct 2025 (Thu),Final decoration of Cherry’s home (4 flower beds),Cherry & family,Bride’s home,—
+5,23 Oct 2025 (Thu),Cycle count & remove door gifts from Toyogo bin (to use as cooler box for beers + drinks),Samuel & friends,Bride’s home,—
+6,23 Oct 2025 (Thu),Prepare Tupperware to freeze ice cubes,Samuel,Bride’s home & Airbnb,For 24th dinner buffet
+7,23 Oct 2025 (Thu),Restaurant lighting & LED screen test (bring thumbdrive),Samuel + LED Guy,Phongmun Restaurant,"Discuss walk-in aisle, remove table stands/cards"
+8,23 Oct 2025 (Thu),Pack to bring to Airbnb (for 24th),Samuel & Cherry,—,"Glass cup x2, 150 scratch cards, clear glass box w/ test tube sand, Groom’s Airbnb deco tools, clothing, red bedsheet set, red pajamas, drinks for buffet"
+9,23 Oct 2025 (Thu),Pack to bring to restaurant (for 24th),Samuel,—,"Poster stand, 150 door gifts, registration items, restaurant drinks, thumbdrive (Capcut video, opening video, PPS)"
+24 Oct (Fri) ,,,,,
+1,24 Oct (Fri) Morning,Meet deco team (Michelle) at restaurant,Cherry & Samuel,Phongmun Restaurant,Check deco setup
+2,24 Oct (Fri) 1:00 PM,Check-in at Groom’s Airbnb,Cherry & Samuel,67/68 Jalan Taman Jalong 2,Earliest time
+3,24 Oct (Fri) —,Check-in at Relatives’ Airbnb,Cherry & Samuel,Various (TBC),—
+4,24 Oct (Fri) Afternoon,Make bed w/ red bedsheet & pillow cases,Samuel,Airbnb,—
+5,24 Oct (Fri) Afternoon,Make ice cubes,Samuel,Airbnb,—
+6,24 Oct (Fri) 2:25 PM,Friends & relatives arrive (airport),All,Ipoh,Settle own lunch; travel to Airbnb/hotel
+7,24 Oct (Fri) 5:00 PM,Groom’s car deco (Lce’s car),Lce + Cherry,Groom’s Airbnb,Cherry to tag along; Samuel stay
+8,24 Oct (Fri) 6:30 PM,Buffet Dinner @ Bride’s home,All,Bride’s home,Album ready for viewing (Johor Auntie)
+9,24 Oct (Fri) During buffet,"Decorate 3 xiong di’s cars (Jake, Ah San, Cherry’s brother)",Samuel’s group,Bride’s home,After Cherry returns
+10,24 Oct (Fri) During buffet,Bring beers,Jake,Bride’s home,—
+11,24 Oct (Fri) During buffet,Retrieve/make ice cubes,Samuel,Bride’s home,Buy backup ice cubes from mart
+12,24 Oct (Fri) During buffet,Paste stickers on cups & scratch cards,"Kenneth, Yuqi, Andy, Zixian",Airbnb,—
+13,24 Oct (Fri) After buffet,Deco Groom’s Airbnb,"Kenneth, Yuqi, Andy, Zixian",Airbnb,—
+14,24 Oct (Fri) After buffet,"Restaurant test run (lighting, LED, march-in)","Samuel, Cherry, Samson, Sandra, Keyi, Pei Wen, Serene, Jessie",Phongmun Restaurant,"Bring thumbdrive, test Kahoot, check tables/cards"
+15,24 Oct (Fri) Night,Bring to restaurant,Samuel,—,"Poster stand, drinks, 150 door gifts"
+16,24 Oct (Fri) Night,Deco team setup,"Michelle (walkway, VIP) + Jessie (lighting)",Phongmun Restaurant,—
+25 Oct 2025 (Sat) ,,,,,
+1,25 Oct 2025 (Sat) 0800 HRS,Simple breakfast (dapao 20 pax),Cherry’s brother,Airbnb,—
+2,25 Oct 2025 (Sat) 0900 HRS,All brothers arrive,All Xiong Di,Groom’s Airbnb,"Ah Lung, Ah San, Chloe to note"
+3,25 Oct 2025 (Sat) 0930 HRS,Depart for Bride’s house,Samson (lead),From Groom’s Airbnb,"1-min drive
+a.        Car 1 (Lce’s car 8 Seater alphard) – Driver: Samson 
+ Samuel + Xiao Feng (PIC of Wedding customs)
+b.        Car 2 (Cherry’s brother car) – Driver: Ah long 
+Kenneth + Andy + Yuqi
+c.        Car 3 (Jake’s car) – Driver: Jake 
+Zixian + Wen Qing + Chloe 
+d.        Car 4 (ah bang’s car 7 Seater): Driver: Ah San
+Pei Wen + Serene + Sandra + Keyi + Samson’s wife + Ah San’s wife"
+4,25 Oct 2025 (Sat) —,Red packet distribution,Samson,—,Samson holds sling bag
+5,25 Oct 2025 (Sat) 0945 HRS,Arrival at Bride’s house,All,Bride’s home,Niece NiNi opens car
+6,25 Oct 2025 (Sat) 1030 HRS,Gate games,Jie Mei + Cherry,Bride’s home,—
+7,25 Oct 2025 (Sat) 1130 HRS,Tea ceremony & prayers,All,Bride’s home,Finish ~12 pm
+8,25 Oct 2025 (Sat) 1230 HRS,Return to Airbnb,All,Groom’s Airbnb,Lunch provided
+9,25 Oct 2025 (Sat) 1145 HRS,Brothers standby to travel back,Xiong Di,Bride’s home,Use same seating arrangement
+10,25 Oct 2025 (Sat) 1230 HRS,Tea ceremony (Groom’s side) + Photos,All,Groom’s Airbnb,Pei Wen/Serene to reserve 2 lunch portions for photographers
+25 Oct 2025 (Sat) Evening Wedding Dinner,,,,,
+1,25 Oct 2025 (Sat) 3:00 pm–6:00 pm,Makeup at restaurant,Chloe (MUA),Phongmun Restaurant,"Bride 3:15–5:30, Groom 5:30–6:00, Mothers 3:00–6:00"
+2,25 Oct 2025 (Sat) 4.20 pm-4:50 pm Pick up and reach restaurant ,"1. Samson to fetch setup team from both airbnbs with 8-seater Alphard.
+2. Bring items from airbnb to setup","Pei Wen + Husband, Serene, Sandra, Keyi, Samson + Wife, Jessie",To restaurant,"Items to bring from Airbnb for setup on 25th
+        Bride & Groom’s Cups (Wash and standby – Sandra & Keyi to fill up with Chinese tea and standby at entrance & handover to me & cherry during 2nd march in @ 8.30 pm)
+        Samson to place Test tubes containing colored sand + clear glass box at registration counter table. Plus scratch card (distribute those with Samuel logo).
+        Pei Wen & Serene to place 4 beds of flowers to place in front of TV Screen (Check if the flowers will block the screen content)"
+3,25 Oct 2025 (Sat) —,Table setup,"Pei Wen + Husband, Serene, Sandra, Keyi, Samson + Wife, Jessie",Restaurant,"Items already at restaurant (brought over on 24th) for setup
+        Samson to setup “Poster Stand” beside registration counter
+        All - Place door gift x 150 pcs at each seat in the restaurant (already at restaurant, limited gifts, do not need to place on Samuel's family table) 
+        Sandra & Keyi to Tag table no. cards at each table stand for each table using seat plan (Cherry & Samuel to clarify 1 day earlier with restaurant boss where are the stands/cards)"
+4,25 Oct 2025 (Sat) 1700 HRS,Live band & Emcee setup,"Alex (Band), James (Emcee)",Restaurant,Sound system setup
+5,25 Oct 2025 (Sat) 1800 HRS,Early dinner (crew),"6 pax (2 photographers, 1 MUA, 2 band, 1 emcee)",Restaurant,
+6,25 Oct 2025 (Sat) 1800 HRS,Guest registration opens,"Sandra, Samson, Cherry’s cousin (Matthew)",Entrance,"Samson & Sandra to standby at reception before 6 pm to register guests using the guest list (Cherry’s cousin – Matthew will be assisting as well)
+       Bring ballpoint pen. Register guest (Tick their name according) > Cherry bought registration book from shopee
+        Let them know their table no. 
+        Pass them 1 scratch card each (Ask them to Scratch after Emcee’s announcement)
+        Receive red packets & indicate in the template (Check with guest if they are providing any red packets politely / 想请问一下，您这边会准备红包吗?)  (Cherry & Samuel to confirm where to store these red packets) Check guest wrote name on angbao
+        After registration, direct Guests to fill up the clear glass box using the test tubes colored sand
+        Registration cut-off at 7 pm."
+7,25 Oct 2025 (Sat) 1900 HRS,Registration closes,—,—,Wedding dinner begins
+8,25 Oct 2025 (Sat) 1900 HRS,Guests seated / photo taking,Bride & Groom,Restaurant,Photographer at booth
+9,25 Oct 2025 (Sat) 1900 HRS,Pre-wedding shoot Taiwan video,Jessie,Restaurant,
+10,25 Oct 2025 (Sat) 1915 HRS,First march-in (parents + couple),All,Restaurant,"Songs: Joey “分分鐘需要你”, “not my business”"
+11,25 Oct 2025 (Sat) 1930 HRS,Food serving starts,Restaurant,—,Wedding slideshow
+12,25 Oct 2025 (Sat) 1935 HRS,Live band performance,Alex,—,45 mins
+13,25 Oct 2025 (Sat) 2000 HRS,Second march-in prep,Sandra & Keyi,Entrance,Hand sticker cups
+14,25 Oct 2025 (Sat) 2030 HRS,Second march-in,Bride & Groom,Restaurant,Spotify song link
+15,25 Oct 2025 (Sat) 2035 HRS,Cake-cutting & champagne toast,Couple + Family,Stage,Song: SEVENTEEN – Reasons of My Smiles
+16,25 Oct 2025 (Sat) 2100 HRS,CapCut highlight video,Photographer,Screen,Tea ceremony highlights
+17,25 Oct 2025 (Sat) 2120 HRS,Kahoot game,Emcee + VIP guests,Restaurant,"Game:  Kahoot (VIP scanned QR code to join the game ) 
+https://slempire.rhinopal.top?oid=2510059PQFQMUW
+https://create.kahoot.it/share/samuel-cherry-final-wedding-game/4d55c251-77e5-4269-8c70-4110c70148c4
+
+When play Kahoot game, background song: https://open.spotify.com/track/4ppXYFIKT0GM6bGnxYk7qm?si=u3JXZSEgRNanLX94_B0HjQ
+3 Winners (Red packets)"
+18,25 Oct 2025 (Sat) 2130 HRS,Scratch card game,Emcee,Restaurant,"10 winners (red packets), background music: ROSÉ & Bruno Mars “APT.”"
+19,25 Oct 2025 (Sat) 0.90625,Toast to guests,Couple,All tables,—
+20,25 Oct 2025 (Sat) 9:45 pm–10:15 pm,Final live band set,Alex,Restaurant,Until end of dinner
+21,25 Oct 2025 (Sat) 10:15–10:30 pm,Event ends,All,Restaurant,"Clean-up, end"