#!/usr/bin/env python3
# -*- coding: utf-8 -*-

"""
analysisAI.py — pobiera dane z MySQL, liczy preagregaty, renderuje HTML i dokłada analizę AI.

ZMIENNE ŚRODOWISKOWE (mają domyślne wartości):
  OPENAI_API_KEY      - klucz do OpenAI (gdy pusty -> skrypt pokaże wersję bez AI)
  OPENAI_MODEL        - np. gpt-4.1 (domyślnie)
  MYSQL_HOST          - host MySQL (domyślnie: localhost)
  MYSQL_USER          - użytkownik MySQL (domyślnie: root)
  MYSQL_PASSWORD      - hasło MySQL (domyślnie: rootpassword)
  MYSQL_DATABASE      - nazwa bazy (domyślnie: preDb_0dcc87940d3655fa574b253df04ca1c3)
  MYSQL_PORT          - port MySQL (domyślnie: 3306)
  PERIOD_FROM         - data od (YYYY-MM-DD); gdy brak -> poprzedni pełny miesiąc
  PERIOD_TO           - data do (YYYY-MM-DD, exclusive); gdy brak -> pierwszy dzień bieżącego miesiąca
  INVOICE_TYPE        - typ dokumentu (domyślnie: normal)
"""

import os, sys, json, math, time, warnings
from datetime import date, timedelta

API_KEY = "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"


# Wycisz ostrzeżenie urllib3 (LibreSSL na macOS itp.)
try:
    from urllib3.exceptions import NotOpenSSLWarning
    warnings.filterwarnings("ignore", category=NotOpenSSLWarning)
except Exception:
    pass

import requests
import mysql.connector
from preaggregates import compute_preaggregates, serialize_for_ai

# --------- utils ---------

def getenv(k, d=None):
    return os.environ.get(k, d)

def last_full_month_bounds():
    """Zwraca (from_iso, to_iso) dla poprzedniego pełnego miesiąca."""
    today_first = date.today().replace(day=1)
    to_dt = today_first
    prev_last = today_first - timedelta(days=1)
    from_dt = prev_last.replace(day=1)
    return from_dt.isoformat(), to_dt.isoformat()

def compact_table(table, limit=30):
    """Przytnij listę rekordów i znormalizuj liczby (NaN/Inf -> None)."""
    out = []
    if not table:
        return out
    for i, row in enumerate(table):
        if i >= int(limit): break
        new = {}
        for k, v in row.items():
            if isinstance(v, float):
                new[k] = round(v, 6) if math.isfinite(v) else None
            else:
                new[k] = v
        out.append(new)
    return out

def build_ai_payload(serialized, period_label):
    """Kompaktowy JSON do AI (ograniczone rozmiary)."""
    return {
        "kpis_hint": {"period_label": period_label},
        "daily_sales": compact_table(serialized.get("daily_sales"), 30),
        "product_summary": compact_table(serialized.get("product_summary"), 50),
        "customer_summary": compact_table(serialized.get("customer_summary"), 50),
        "top10_products_by_sales": compact_table(serialized.get("top10_products_by_sales"), 10),
        "top10_customers_by_sales": compact_table(serialized.get("top10_customers_by_sales"), 10),
        "product_daily_sample": compact_table(serialized.get("product_daily"), 40),
    }

def call_openai_chat(api_key, model, system_prompt, user_payload_json,
                     temperature=0.3, connect_timeout=10, read_timeout=90, max_retries=3):
    """Wywołanie Chat Completions (retry + backoff). Zwraca HTML (sekcję) od AI."""
    url = "https://api.openai.com/v1/chat/completions"
    headers = {"Authorization": "Bearer " + api_key, "Content-Type": "application/json"}
    body = {
        "model": model,
        "messages": [
            {"role": "system", "content": system_prompt},
            {"role": "user", "content": "Dane (JSON):\n\n" + user_payload_json},
        ],
        "temperature": temperature,
        # "max_tokens": 1200,  # możesz odkomentować, aby ograniczyć długość odpowiedzi
    }
    last_err = None
    for attempt in range(1, int(max_retries) + 1):
        try:
            r = requests.post(url, headers=headers, json=body, timeout=(connect_timeout, read_timeout))
            if 200 <= r.status_code < 300:
                data = r.json()
                return data.get("choices", [{}])[0].get("message", {}).get("content", "")
            last_err = RuntimeError("OpenAI HTTP {}: {}".format(r.status_code, r.text))
        except requests.exceptions.RequestException as e:
            last_err = e
        time.sleep(min(2 ** attempt, 10))
    raise RuntimeError("OpenAI request failed: {}".format(last_err))

def fmt_money(v):
    try:
        return "{:,.2f}".format(float(v)).replace(",", " ").replace(".", ",")
    except Exception:
        return str(v)

def html_table(records, title=None, max_rows=20):
    """Proste generowanie tabeli HTML z listy dict-ów."""
    if not records:
        return '<div class="empty">Brak danych</div>'
    cols = list(records[0].keys())
    body_rows = records[:max_rows]
    thead = "".join("<th>{}</th>".format(c) for c in cols)
    trs = []
    for r in body_rows:
        tds = []
        for c in cols:
            val = r.get(c, "")
            if isinstance(val, (int, float)):
                # format dla kolumn „sales”, „qty”, „asp”, itp. – lekko ładniej
                if "sales" in c or "total" in c or "netto" in c:
                    tds.append('<td class="num">{}</td>'.format(fmt_money(val)))
                else:
                    tds.append('<td class="num">{}</td>'.format(val))
            else:
                tds.append('<td>{}</td>'.format(val))
        trs.append("<tr>{}</tr>".format("".join(tds)))
    cap = '<div class="tbl-title">{}</div>'.format(title) if title else ""
    return (
        cap +
        '<div class="tbl-wrap"><table class="tbl">'
        '<thead><tr>{}</tr></thead><tbody>{}</tbody></table></div>'.format(thead, "".join(trs))
    )

def render_report_html(period_label, kpis, parts, ai_section):
    """Składa finalny jeden <div> z lekkim CSS inline."""
    css = (
        "font-family:system-ui,-apple-system,Segoe UI,Roboto,Arial,sans-serif;"
        "max-width:1200px;margin:24px auto;padding:16px 20px;border:1px solid #e5e7eb;"
        "border-radius:12px;background:#fff;color:#111827"
    )
    kpi_item = (
        '<div class="kpi"><div class="kpi-label">{label}</div>'
        '<div class="kpi-value">{value}</div></div>'
    )
    kpi_html = "".join(
        kpi_item.format(label=lbl, value=val) for (lbl, val) in kpis
    )
    sections_html = "".join(parts)
    # jeśli AI nie zwróciło <div>, owiń
    if ai_section and not ai_section.lstrip().startswith("<div"):
        ai_section = '<div class="ai-section">{}</div>'.format(ai_section)

    return f"""
<div style="{css}">
  <h2 style="margin:0 0 12px;font-size:22px;">Raport sprzedaży — {period_label}</h2>
  <div style="display:grid;grid-template-columns:repeat(4,minmax(0,1fr));gap:12px;margin:12px 0 20px;">
    {kpi_html}
  </div>
  {sections_html}
  <div style="margin-top:20px;border-top:1px solid #e5e7eb;padding-top:16px;">
    <h3 style="margin:0 0 8px;font-size:18px;">Analiza i rekomendacje (AI)</h3>
    {ai_section if ai_section else '<div style="color:#6b7280">Brak odpowiedzi AI (brak OPENAI_API_KEY)</div>'}
  </div>
</div>
<style>
  .kpi {{background:#f8fafc;border:1px solid #e5e7eb;border-radius:10px;padding:12px;}}
  .kpi-label {{font-size:12px;color:#6b7280;margin-bottom:4px;}}
  .kpi-value {{font-size:18px;font-weight:700;}}
  .tbl-title {{font-weight:600;margin:16px 0 8px;font-size:15px;}}
  .tbl-wrap {{overflow-x:auto;border:1px solid #e5e7eb;border-radius:8px;}}
  .tbl {{border-collapse:collapse;width:100%;font-size:14px;}}
  .tbl thead th {{text-align:left;background:#f3f4f6;padding:8px;border-bottom:1px solid #e5e7eb;white-space:nowrap;}}
  .tbl tbody td {{padding:8px;border-bottom:1px solid #f3f4f6;vertical-align:top;}}
  .tbl td.num {{text-align:right;white-space:nowrap;}}
  .empty {{color:#6b7280;font-style:italic;margin:8px 0;}}
  .ai-section {{background:#f8fafc;border:1px solid #e5e7eb;border-radius:10px;padding:12px;}}
</style>
"""

# --------- main ---------

def main():
    # Konfiguracja DB
    cfg = {
        "host": getenv("MYSQL_HOST", "twinpol-mysql56"),
        # "host": getenv("MYSQL_HOST", "localhost"),
        "user": getenv("MYSQL_USER", "root"),
        "password": getenv("MYSQL_PASSWORD", "rootpassword"),
        "database": getenv("MYSQL_DATABASE", "preDb_0dcc87940d3655fa574b253df04ca1c3"),
        "port": int(getenv("MYSQL_PORT", "3306")),
    }

    # Zakres dat
    period_from = getenv("PERIOD_FROM")
    period_to = getenv("PERIOD_TO")
    if not period_from or not period_to:
        period_from, period_to = last_full_month_bounds()
    period_label = "{} .. {}".format(period_from, period_to)
    invoice_type = getenv("INVOICE_TYPE", "normal")

    # Konfiguracja AI
    #api_key = getenv("OPENAI_API_KEY", "")
    api_key = API_KEY
    model = getenv("OPENAI_MODEL", "gpt-4.1")
    system_prompt = (
        "Jesteś analitykiem sprzedaży. Zwróć TYLKO jedną sekcję HTML (bez <html>/<head>/<body>), "
        "może być pojedynczy <div> z nagłówkami i listami. Podsumuj trendy, wskaż kluczowe produkty/klientów, "
        "anomalia/odchylenia oraz daj 3–6 praktycznych rekomendacji. Krótko, konkretnie, po polsku."
    )

    # SQL -> rows
    try:
        cnx = mysql.connector.connect(**cfg)
        cur = cnx.cursor()
        cur.execute(
            """
            SELECT i.document_no,
                   i.parent_name,
                   DATE(i.register_date) AS register_date,
                   ii.code,
                   ii.name,
                   ii.quantity,
                   ii.total_netto
            FROM ecminvoiceoutitems AS ii
            JOIN ecminvoiceouts      AS i ON i.id = ii.ecminvoiceout_id
            WHERE i.register_date >= %s
              AND i.register_date <  %s
              AND i.type = %s
            """,
            (period_from, period_to, invoice_type),
        )
        rows = cur.fetchall()
        cur.close()
        cnx.close()
    except Exception as e:
        sys.stdout.write(
            '<div style="font-family:system-ui,-apple-system,Segoe UI,Roboto,Arial,sans-serif;'
            'max-width:900px;margin:24px auto;padding:16px 20px;border:1px solid #fecaca;'
            'border-radius:12px;background:#fff5f5;color:#991b1b;">'
            '<h3 style="margin:0 0 8px;font-size:18px;">Błąd połączenia/zapytania MySQL</h3>'
            '<p style="margin:0;">{}</p></div>'.format(str(e))
        )
        sys.exit(1)

    # Preagregaty
    try:
        results = compute_preaggregates(rows)
        serialized = serialize_for_ai(results)
    except Exception as e:
        sys.stdout.write(
            '<div style="font-family:system-ui,-apple-system,Segoe UI,Roboto,Arial,sans-serif;'
            'max-width:900px;margin:24px auto;padding:16px 20px;border:1px solid #fecaca;'
            'border-radius:12px;background:#fff5f5;color:#991b1b;">'
            '<h3 style="margin:0 0 8px;font-size:18px;">Błąd preagregacji</h3>'
            '<p style="margin:0;">{}</p></div>'.format(str(e))
        )
        sys.exit(1)

    # KPI (na podstawie daily_sales)
    daily = serialized.get("daily_sales") or []
    total_sales = sum((r.get("sales") or 0) for r in daily)
    total_qty = sum((r.get("qty") or 0) for r in daily)
    total_docs = sum((r.get("docs") or 0) for r in daily)
    asp = (total_sales / total_qty) if total_qty else None
    kpis = [
        ("Sprzedaż (PLN)", fmt_money(total_sales)),
        ("Ilość (szt.)", "{:,.0f}".format(total_qty).replace(",", " ")),
        ("Dokumenty", "{:,.0f}".format(total_docs).replace(",", " ")),
        ("ASP (PLN/szt.)", fmt_money(asp) if asp is not None else "—"),
    ]

    # Sekcje HTML z Twoich preagregatów
    top_prod = serialized.get("top10_products_by_sales") or []
    top_cli = serialized.get("top10_customers_by_sales") or []
    prod_tbl = html_table(top_prod, title="Top 10 produktów (po sprzedaży)", max_rows=10)
    cust_tbl = html_table(top_cli, title="Top 10 klientów (po sprzedaży)", max_rows=10)

    # Dane do AI
    ai_data = build_ai_payload(serialized, period_label)
    ai_json = json.dumps(ai_data, ensure_ascii=False, separators=(",", ":"), default=str)

    # Wołanie AI (opcjonalne)
    ai_section = ""
    if api_key:
        try:
            ai_section = call_openai_chat(
                api_key=api_key,
                model=model,
                system_prompt=system_prompt,
                user_payload_json=ai_json,
                temperature=0.3,
                connect_timeout=10,
                read_timeout=90,
                max_retries=3,
            )
        except Exception as e:
            ai_section = (
                '<div style="color:#991b1b;background:#fff5f5;border:1px solid #fecaca;'
                'padding:10px;border-radius:8px;">Błąd wywołania AI: {}</div>'.format(str(e))
            )

    # Finalny HTML (jeden <div>)
    report_html = render_report_html(
        period_label=period_label,
        kpis=kpis,
        parts=[prod_tbl, cust_tbl],
        ai_section=ai_section
    )

    sys.stdout.write(report_html)

if __name__ == "__main__":
    main()