src/streamlit_app.py

import random
import uuid
import logging
from datetime import datetime, timedelta
import streamlit as st
from openai import OpenAI

# ==================================================
# LOGGING
# ==================================================
logging.basicConfig(
    level=logging.INFO,
    format="%(asctime)s | %(levelname)s | %(message)s"
)
logger = logging.getLogger("AI-Agent")

# ==================================================
# RAW DATA (600+ ROWS WITH DATE)
# ==================================================
@st.cache_data
def generate_data(rows: int = 600):
    random.seed(42)
    today = datetime.today().date()
    data = []

    for i in range(1, rows + 1):
        data.append({
            "order_id": i,
            "order_date": today - timedelta(days=random.randint(0, 30)),
            "supplier": random.choice(
                ["Supplier A", "Supplier B", "Supplier C", "Supplier D"]
            ),
            "product": random.choice(
                ["Tomato", "Cheese", "Flour", "Oil", "Meat"]
            ),
            "quantity": random.randint(1, 100),
            "price": round(random.uniform(5, 50), 2),
            "delivery_days": random.randint(1, 14),
            "status": random.choice(
                ["Delivered", "Pending", "Delayed"]
            )
        })

    logger.info("Generated %d rows of data", len(data))
    return data

DATA = generate_data()

# ==================================================
# UTILS: FORMAT RESPONSE AS TEXT
# ==================================================
def format_rows_as_text(rows):
    lines = []
    for r in rows:
        lines.append(
            f"🧾 Order #{r['order_id']} | {r['order_date']}\n"
            f"   Product: {r['product']}\n"
            f"   Supplier: {r['supplier']}\n"
            f"   Qty: {r['quantity']} | Price: ${r['price']}\n"
            f"   Delivery: {r['delivery_days']} days | Status: {r['status']}\n"
        )
    return "\n".join(lines)

# ==================================================
# TOOLS
# ==================================================
def tool_get_stats():
    prices = [x["price"] for x in DATA]
    days = [x["delivery_days"] for x in DATA]

    logger.info("Tool → get_stats")
    return {
        "rows": len(DATA),
        "avg_price": round(sum(prices) / len(prices), 2),
        "avg_delivery_days": round(sum(days) / len(days), 2),
    }

def tool_query_product(product: str):
    logger.info("Tool → query_product(%s)", product)
    return [x for x in DATA if x["product"].lower() == product.lower()][:5]

def tool_query_last_days(days: int):
    logger.info("Tool → query_last_days(%d)", days)
    cutoff = datetime.today().date() - timedelta(days=days)
    return [x for x in DATA if x["order_date"] >= cutoff][:5]

def tool_create_support_ticket(text: str):
    ticket_id = str(uuid.uuid4())[:8]
    logger.info("Tool → create_support_ticket (%s)", ticket_id)
    return ticket_id

# ==================================================
# SAFETY
# ==================================================
def is_dangerous(text: str):
    blocked = ["delete", "drop", "truncate", "remove"]
    return any(b in text.lower() for b in blocked)

# ==================================================
# AGENT
# ==================================================
def agent(user_input: str, openai_client: OpenAI):
    logger.info("User input: %s", user_input)

    if is_dangerous(user_input):
        return "❌ Dangerous operations are not allowed."

    text = user_input.lower()

    # ---- STATS ----
    if "stats" in text or "summary" in text:
        s = tool_get_stats()
        return (
            "📊 Business Overview\n"
            f"- Total rows: {s['rows']}\n"
            f"- Average price: ${s['avg_price']}\n"
            f"- Average delivery days: {s['avg_delivery_days']}"
        )

    # ---- LAST N DAYS ----
    if "last" in text and "day" in text:
        try:
            days = int([x for x in text.split() if x.isdigit()][0])
        except:
            days = 3

        rows = tool_query_last_days(days)
        if not rows:
            return f"No data found for last {days} days."

        return f"📦 Orders from last {days} days:\n\n" + format_rows_as_text(rows)

    # ---- PRODUCT ----
    if text.startswith("show"):
        product = user_input.replace("show", "").strip()
        rows = tool_query_product(product)

        if not rows:
            return "No records found. Would you like me to create a support ticket?"

        return f"📦 Showing orders for **{product}**:\n\n" + format_rows_as_text(rows)

    # ---- SUPPORT ----
    if "support" in text or "ticket" in text:
        ticket_id = tool_create_support_ticket(user_input)
        return (
            "🎫 Support Ticket Created\n"
            f"- Ticket ID: {ticket_id}\n"
            "- System: GitHub Issues (mock)"
        )

    # ---- OPENAI FALLBACK ----
    logger.info("LLM fallback via OpenAI")

    response = openai_client.chat.completions.create(
        model="gpt-4o-mini",
        messages=[
            {
                "role": "system",
                "content": (
                    "You are an AI procurement assistant. "
                    "You do NOT have access to raw data."
                )
            },
            {"role": "user", "content": user_input}
        ],
        max_tokens=150,
        temperature=0.3
    )

    return response.choices[0].message.content

# ==================================================
# STREAMLIT UI
# ==================================================
st.set_page_config(page_title="AI Procurement Agent", layout="wide")
st.title("🤖 AI Procurement Agent (OpenAI)")

# ---- SIDEBAR ----
st.sidebar.header("🔑 OpenAI Configuration")
api_key = st.sidebar.text_input(
    "OpenAI API Key",
    type="password",
    help="Paste your OpenAI API key here"
)

stats = tool_get_stats()
st.sidebar.header("📊 Business Information")
st.sidebar.metric("Rows", stats["rows"])
st.sidebar.metric("Avg Price", f"${stats['avg_price']}")
st.sidebar.metric("Avg Delivery Days", stats["avg_delivery_days"])

st.sidebar.markdown("### Sample queries")
st.sidebar.code(
    "show tomato\n"
    "last 3 days\n"
    "database stats\n"
    "create support ticket"
)

if not api_key:
    st.warning("Please enter your OpenAI API key to continue.")
    st.stop()

openai_client = OpenAI(api_key=api_key)

# ---- CHAT ----
if "messages" not in st.session_state:
    st.session_state.messages = []

user_input = st.chat_input("Ask the procurement agent...")

if user_input:
    st.session_state.messages.append(("user", user_input))
    reply = agent(user_input, openai_client)
    st.session_state.messages.append(("assistant", reply))

for role, message in st.session_state.messages:
    st.chat_message(role).write(message)