generowanie raportów z wyborem preagregatów

modules/EcmInvoiceOuts/ai/analysisAI.py

@@ -2,60 +2,117 @@
 # -*- coding: utf-8 -*-
 
 """
-analysisAI.py — pobiera dane z MySQL, liczy preagregaty, renderuje HTML i dodaje analizę AI.
+analysisAI.py — pobiera dane z MySQL, liczy wyłącznie WSKAZANE preagregaty,
+renderuje HTML i (opcjonalnie) dodaje analizę AI — tylko jeśli ją zaznaczysz.
 
-ZMIENNE ŚRODOWISKOWE (wszystkie mają domyślne wartości):
-  OPENAI_API_KEY      - klucz do OpenAI (gdy pusty -> fallback bez AI)
-  OPENAI_MODEL        - np. gpt-4.1 (domyślnie), alternatywnie gpt-4.1-mini
-  MYSQL_HOST          - host MySQL (domyślnie: twinpol-mysql56 lub 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 -> 1. dzień bieżącego miesiąca
-  INVOICE_TYPE        - typ dokumentu (domyślnie: normal)
+Parametry CLI (z formularza PHP):
+  --date-from YYYY-MM-DD
+  --date-to   YYYY-MM-DD     (zamieniane wewnętrznie na +1 dzień, bo SQL ma warunek '< date_to')
+  --metric    NAZWA          (można podać wiele razy: --metric a --metric b ...)
+  --metrics   CSV            (opcjonalnie alternatywnie: --metrics a,b,c)
+  --ai        true|false     (czy uruchomić analizę AI — tylko gdy są preagregaty z danymi)
+
+Preagregaty:
+  - kpis (aliasy: basic, basic_totals) — podstawowe KPI: sprzedaż, ilość, dokumenty, ASP
+  - daily_sales, product_summary, customer_summary, product_daily,
+    top10_products_by_sales, top10_customers_by_sales  (z preaggregates.py)
 """
 
-import os, sys, json, math, time, warnings
-from datetime import date, timedelta
+import os, sys, json, math, time, warnings, argparse, traceback, html
+from datetime import date, timedelta, datetime
 
-API_KEY = "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"
-
-#5 pro
-#API_KEY = "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"
-# ──(1) Wycisz ostrzeżenia urllib3 (LibreSSL / stary OpenSSL) ───────────────────
+# (1) Wycisza ostrzeżenia urllib3 (LibreSSL / stary OpenSSL)
 try:
     from urllib3.exceptions import NotOpenSSLWarning
     warnings.filterwarnings("ignore", category=NotOpenSSLWarning)
 except Exception:
     pass
 
-# ──(2) Importy zewnętrzne ──────────────────────────────────────────────────────
+# (2) Importy zewnętrzne
 import requests
 import mysql.connector
+import pandas as pd
 
-# Twoje preagregaty (muszą być w tym samym katalogu / PYTHONPATH)
-from preaggregates import compute_preaggregates, serialize_for_ai
+LOOKER_URL = "https://lookerstudio.google.com/u/0/reporting/107d4ccc-e7eb-4c38-8dce-00700b44f60e/page/ba1YF"
 
-# ──(3) Konfiguracja klucza AI ──────────────────────────────────────────────────
-# Wpisz tutaj klucz jeśli chcesz mieć go „na sztywno”, inaczej zostaw pusty:
-API_KEY_HARDCODE = API_KEY   # np. "sk-xxxx..." (NIEZALECANE w produkcji)
+# ========== KONFIGURACJA KLUCZA AI ==========
+API_KEY = "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"
+API_KEY_HARDCODE = API_KEY
+
+# === Import preagregatów ===
+from preaggregates import serialize_for_ai
+import preaggregates as pre  # pre.AGGREGATORS, pre.to_df
+
+# ========== UTILKI ==========
+
+def html_fatal(msg, title="Błąd"):
+    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;">'
+        f'<h3 style="margin:0 0 8px;font-size:18px;">{html.escape(title)}</h3>'
+        f'<pre style="white-space:pre-wrap;margin:0;">{html.escape(msg)}</pre>'
+        '</div>'
+    )
+    sys.exit(1)
+
+def connect_html_or_die(cfg, label="MySQL"):
+    try:
+        return mysql.connector.connect(**cfg)
+    except mysql.connector.Error as e:
+        host = cfg.get("host"); port = cfg.get("port"); user = cfg.get("user")
+        base = (f"[{label}] Błąd połączenia ({host}:{port} jako '{user}').\n"
+                f"errno={getattr(e,'errno',None)} sqlstate={getattr(e,'sqlstate',None)}\n"
+                f"msg={getattr(e,'msg',str(e))}")
+        if os.environ.get("DEBUG"):
+            base += "\n\n" + traceback.format_exc()
+        html_fatal(base, title="Błąd połączenia MySQL")
 
-# ──(4) 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 add_one_day(iso_date):
+    try:
+        return (datetime.strptime(iso_date, "%Y-%m-%d") + timedelta(days=1)).strftime("%Y-%m-%d")
+    except Exception:
+        return iso_date  # w razie czego oddaj wejście
+
+def safe_num(v, ndigits=None):
+    try:
+        f = float(v)
+        if not math.isfinite(f):
+            return None
+        return round(f, ndigits) if ndigits is not None else f
+    except Exception:
+        return None
+
+def safe_date(v):
+    if v is None:
+        return None
+    try:
+        if hasattr(v, "date"):
+            return str(v.date())
+        s = str(v)
+        if len(s) >= 10 and s[4] == '-' and s[7] == '-':
+            return s[:10]
+        return s
+    except Exception:
+        return None
+
+def fmt_money(v):
+    try:
+        return "{:,.2f}".format(float(v)).replace(",", " ").replace(".", ",")
+    except Exception:
+        return str(v)
+
 def compact_table(table, limit=30):
-    """Przytnij listę rekordów (list[dict]) i znormalizuj liczby (NaN/Inf -> None)."""
     out = []
     if not table:
         return out
@@ -71,21 +128,8 @@ def compact_table(table, limit=30):
         out.append(new)
     return out
 
-def build_ai_payload(serialized, period_label):
-    """Kompaktowy JSON do AI (rozmiar przycięty, ale zawiera wszystkie główne tabele)."""
-    return {
-        "kpis_hint": {"period_label": period_label},
-        "daily_sales": compact_table(serialized.get("daily_sales"), 60),
-        "product_summary": compact_table(serialized.get("product_summary"), 100),
-        "customer_summary": compact_table(serialized.get("customer_summary"), 100),
-        "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"), 100),
-    }
-
 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 = {
@@ -95,7 +139,6 @@ def call_openai_chat(api_key, model, system_prompt, user_payload_json,
             {"role": "user", "content": "Dane (JSON):\n\n" + user_payload_json},
         ],
         "temperature": temperature,
-        # "max_tokens": 1200,  # opcjonalnie ogranicz długość odpowiedzi
     }
     last_err = None
     for attempt in range(1, int(max_retries) + 1):
@@ -110,14 +153,7 @@ def call_openai_chat(api_key, model, system_prompt, user_payload_json,
         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 (lekki CSS inline w <style> poniżej)."""
     if not records:
         return '<div class="empty">Brak danych</div>'
     cols = list(records[0].keys())
@@ -144,7 +180,6 @@ def html_table(records, title=None, max_rows=20):
     )
 
 def render_report_html(period_label, kpis, parts, ai_section, model_alias):
-    """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;"
@@ -165,10 +200,19 @@ def render_report_html(period_label, kpis, parts, ai_section, model_alias):
   <div style="display:grid;grid-template-columns:repeat(4,minmax(0,1fr));gap:12px;margin:12px 0 20px;">
     {kpi_html}
   </div>
-  {sections_html}
+  {sections_html if sections_html.strip() else '<div class="empty">Nie wybrano żadnych preagregatów — brak sekcji do wyświetlenia.</div>'}
   <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{(' · ' + model_alias) if model_alias else ''})</h3>
-    {ai_section if ai_section else '<div style="color:#6b7280">Brak odpowiedzi AI</div>'}
+    <h3 style="margin:0 0 8px;font-size:18px;">Analiza i rekomendacje{(' (AI · ' + model_alias + ')') if model_alias else ''}</h3>
+    {ai_section if ai_section else '<div style="color:#6b7280">Analiza AI wyłączona lub brak danych.</div>'}
+  </div>
+
+  <!-- STOPKA z linkiem do Looker Studio -->
+  <div style="margin-top:20px;border-top:1px dashed #e5e7eb;padding-top:12px;display:flex;justify-content:flex-end;">
+    <a href="{LOOKER_URL}" target="_blank" rel="noopener"
+       style="text-decoration:none;padding:8px 12px;border:1px solid #d1d5db;border-radius:8px;
+              background:#f9fafb;color:#111827;font-weight:600;">
+      → Otwórz pełny raport w Looker Studio
+    </a>
   </div>
 </div>
 <style>
@@ -186,9 +230,280 @@ def render_report_html(period_label, kpis, parts, ai_section, model_alias):
 </style>
 """
 
-# ──(5) Główna logika ───────────────────────────────────────────────────────────
+
+# ========== UPSerTY DO REPORTING (jak u Ciebie) ==========
+
+def _ensure_rank_and_share(items, key_sales="sales"):
+    if not items: return
+    total_sales = sum((x.get(key_sales) or 0) for x in items)
+    sorted_items = sorted(
+        items,
+        key=lambda x: ((x.get(key_sales) or 0), str(x.get("product_code") or x.get("customer_name") or "")),
+        reverse=True
+    )
+    rank_map, rank = {}, 1
+    for x in sorted_items:
+        key = x.get("product_code") or x.get("customer_name") or ""
+        if key not in rank_map:
+            rank_map[key] = rank
+            rank += 1
+    for x in items:
+        key = x.get("product_code") or x.get("customer_name") or ""
+        if not x.get("rank_in_period"):
+            x["rank_in_period"] = rank_map.get(key, 0)
+        if "mix_share_sales" not in x:
+            x["mix_share_sales"] = ((x.get(key_sales) or 0) / total_sales) if total_sales else 0.0
+
+def upsert_daily_sales(cur, daily):
+    if not daily: return 0
+    sql = """
+    INSERT INTO reporting_daily_sales
+      (period_date, qty, sales, docs, asp, sales_rolling7, sales_dod_pct)
+    VALUES (%s,%s,%s,%s,%s,%s,%s)
+    ON DUPLICATE KEY UPDATE
+      qty=VALUES(qty), sales=VALUES(sales), docs=VALUES(docs),
+      asp=VALUES(asp), sales_rolling7=VALUES(sales_rolling7), sales_dod_pct=VALUES(sales_dod_pct),
+      generated_at=CURRENT_TIMESTAMP
+    """
+    rows = []
+    for r in daily:
+        period_date = safe_date(r.get("register_date") or r.get("period_date") or r.get("date"))
+        rows.append((
+            period_date,
+            safe_num(r.get("qty")),
+            safe_num(r.get("sales")),
+            safe_num(r.get("docs")),
+            safe_num(r.get("asp"), 6),
+            safe_num(r.get("sales_rolling7"), 6),
+            safe_num(r.get("sales_pct_change_dod") or r.get("sales_dod_pct"), 6),
+        ))
+    cur.executemany(sql, rows)
+    return len(rows)
+
+def upsert_product_summary(cur, prod, period_from, period_to):
+    if not prod: return 0
+    _ensure_rank_and_share(prod, key_sales="sales")
+    sql = """
+    INSERT INTO reporting_product_summary
+      (period_start, period_end, product_code, product_name, qty, sales, docs,
+       asp_weighted, mix_share_sales, rank_in_period)
+    VALUES (%s,%s,%s,%s,%s,%s,%s,%s,%s,%s)
+    ON DUPLICATE KEY UPDATE
+      qty=VALUES(qty), sales=VALUES(sales), docs=VALUES(docs),
+      asp_weighted=VALUES(asp_weighted), mix_share_sales=VALUES(mix_share_sales),
+      rank_in_period=VALUES(rank_in_period), generated_at=CURRENT_TIMESTAMP
+    """
+    rows = []
+    for r in prod:
+        rows.append((
+            period_from, period_to,
+            r.get("product_code"), r.get("product_name"),
+            safe_num(r.get("qty")),
+            safe_num(r.get("sales")),
+            safe_num(r.get("docs")),
+            safe_num(r.get("asp_weighted"), 6),
+            safe_num(r.get("mix_share_sales"), 6),
+            int(r.get("rank_in_period") or 0),
+        ))
+    cur.executemany(sql, rows)
+    return len(rows)
+
+def upsert_customer_summary(cur, cust, period_from, period_to):
+    if not cust: return 0
+    _ensure_rank_and_share(cust, key_sales="sales")
+    sql = """
+    INSERT INTO reporting_customer_summary
+      (period_start, period_end, customer_name, qty, sales, docs,
+       asp_weighted, mix_share_sales, rank_in_period)
+    VALUES (%s,%s,%s,%s,%s,%s,%s,%s,%s)
+    ON DUPLICATE KEY UPDATE
+      qty=VALUES(qty), sales=VALUES(sales), docs=VALUES(docs),
+      asp_weighted=VALUES(asp_weighted), mix_share_sales=VALUES(mix_share_sales),
+      rank_in_period=VALUES(rank_in_period), generated_at=CURRENT_TIMESTAMP
+    """
+    rows = []
+    for r in cust:
+        rows.append((
+            period_from, period_to,
+            r.get("customer_name"),
+            safe_num(r.get("qty")),
+            safe_num(r.get("sales")),
+            safe_num(r.get("docs")),
+            safe_num(r.get("asp_weighted"), 6),
+            safe_num(r.get("mix_share_sales"), 6),
+            int(r.get("rank_in_period") or 0),
+        ))
+    cur.executemany(sql, rows)
+    return len(rows)
+
+def upsert_product_daily(cur, prod_daily):
+    if not prod_daily: return 0
+    sql = """
+    INSERT INTO reporting_product_daily
+      (period_date, product_code, product_name, qty, sales, asp)
+    VALUES (%s,%s,%s,%s,%s,%s)
+    ON DUPLICATE KEY UPDATE
+      qty=VALUES(qty), sales=VALUES(sales), asp=VALUES(asp),
+      generated_at=CURRENT_TIMESTAMP
+    """
+    rows = []
+    for r in prod_daily:
+        period_date = safe_date(r.get("register_date") or r.get("period_date") or r.get("date"))
+        qty = safe_num(r.get("qty"))
+        sales = safe_num(r.get("sales"))
+        asp = safe_num((sales / qty) if (qty and sales is not None and qty != 0) else r.get("asp"), 6)
+        rows.append((
+            period_date,
+            r.get("product_code"),
+            r.get("product_name"),
+            qty, sales, asp
+        ))
+    cur.executemany(sql, rows)
+    return len(rows)
+
+# ========== ARGPARSE & LOGIKA WYBORU ==========
+
+def parse_cli_args():
+    p = argparse.ArgumentParser()
+    p.add_argument('--date-from', dest='date_from', required=False, help='YYYY-MM-DD')
+    p.add_argument('--date-to',   dest='date_to',   required=False, help='YYYY-MM-DD (inclusive, we add +1 day internally)')
+    # akceptuj obie formy: wielokrotne --metric oraz (opcjonalnie) --metrics CSV
+    p.add_argument('--metric',    dest='metric', action='append', default=[], help='Nazwa preagregatu; można podać wiele razy')
+    p.add_argument('--metrics',   dest='metrics', action='append', default=[], help='CSV: a,b,c (można podać wiele razy)')
+    p.add_argument('--ai',        dest='ai', choices=['true','false'], default='false')
+    return p.parse_args()
+
+def collect_metric_names(args):
+    names = []
+    # z --metric (powtarzalne)
+    if args.metric:
+        names.extend([s.strip() for s in args.metric if s and s.strip()])
+    # z --metrics (może być kilka wystąpień; każde może być CSV)
+    for entry in (args.metrics or []):
+        if not entry:
+            continue
+        for part in str(entry).replace(';', ',').replace(' ', ',').split(','):
+            part = part.strip()
+            if part:
+                names.append(part)
+    # aliasy dla kpis
+    alias_map = {'basic': 'kpis', 'basic_totals': 'kpis'}
+    names = [alias_map.get(n, n) for n in names]
+    # deduplikacja z zachowaniem kolejności
+    seen = set()
+    uniq = []
+    for n in names:
+        if n not in seen:
+            seen.add(n)
+            uniq.append(n)
+    return uniq
+
+def compute_selected_preaggs(rows, names):
+    """
+    Liczy TYLKO wskazane preagregaty. ZAWSZE zwraca DataFrame'y (nigdy listy).
+    Obsługuje pseudo-agregat 'kpis' (podstawowe KPI).
+    """
+    results = {}
+    if not names:
+        return results
+    df = pre.to_df(rows)
+
+    # kpis — pseudoagregat
+    def compute_kpis_df(dfx):
+        if dfx is None or dfx.empty:
+            return pd.DataFrame([{
+                "total_sales": 0.0,
+                "total_qty": 0.0,
+                "total_docs": 0,
+                "asp": None,
+            }])
+        total_sales = float(dfx["total_netto"].sum())
+        total_qty   = float(dfx["quantity"].sum())
+        total_docs  = int(dfx["document_no"].nunique())
+        asp = (total_sales / total_qty) if total_qty else None
+        return pd.DataFrame([{
+            "total_sales": total_sales,
+            "total_qty": total_qty,
+            "total_docs": total_docs,
+            "asp": asp,
+        }])
+
+    for name in names:
+        if name == 'kpis':
+            results[name] = compute_kpis_df(df)
+            continue
+
+        fn = pre.AGGREGATORS.get(name)
+        if not fn:
+            results[name] = pd.DataFrame()  # nieznany agregat -> pusty
+            continue
+        try:
+            out = fn(df)
+            if out is None:
+                results[name] = pd.DataFrame()
+            elif hasattr(out, "copy"):
+                results[name] = out.copy()
+            else:
+                results[name] = pd.DataFrame(out)
+        except Exception:
+            # np. top10_* na pustych danych -> zwróć pusty wynik
+            results[name] = pd.DataFrame()
+
+    return results
+
+def sanitize_serialized(serialized_dict):
+    """
+    Jeśli jakikolwiek agregat zwrócił błąd (np. _error), zamieniamy na pustą listę.
+    """
+    clean = {}
+    for k, records in (serialized_dict or {}).items():
+        if not records:
+            clean[k] = []
+            continue
+        if isinstance(records, list) and isinstance(records[0], dict) and ('_error' in records[0]):
+            clean[k] = []
+        else:
+            clean[k] = records
+    return clean
+
+def has_any_rows(serialized_dict):
+    for records in (serialized_dict or {}).values():
+        if records:  # lista niepusta
+            return True
+    return False
+
+# ========== MAIN ==========
+
 def main():
-    # Konfiguracja DB
+    # --- CLI ---
+    args = parse_cli_args()
+    with_ai      = (args.ai == 'true')
+    metric_names = collect_metric_names(args)
+
+    # --- Daty: preferuj CLI; 'date_to' inkluzywne (dodajemy +1 dzień dla SQL '<') ---
+    if args.date_from and args.date_to:
+        period_from, period_to = args.date_from, add_one_day(args.date_to)
+        shown_label = "{} .. {}".format(args.date_from, args.date_to)
+    else:
+        env_from, env_to = getenv("PERIOD_FROM"), getenv("PERIOD_TO")
+        if env_from and env_to:
+            period_from, period_to = env_from, env_to
+            # label dla czytelności: to-1d
+            try:
+                to_label = (datetime.strptime(period_to, "%Y-%m-%d") - timedelta(days=1)).strftime("%Y-%m-%d")
+            except Exception:
+                to_label = period_to
+            shown_label = "{} .. {}".format(period_from, to_label)
+        else:
+            period_from, period_to = last_full_month_bounds()
+            # label: poprzedni pełny miesiąc
+            try:
+                to_label = (datetime.strptime(period_to, "%Y-%m-%d") - timedelta(days=1)).strftime("%Y-%m-%d")
+            except Exception:
+                to_label = period_to
+            shown_label = "{} .. {}".format(period_from, to_label)
+
+    # --- DB ---
     cfg = {
         "host": getenv("MYSQL_HOST", "twinpol-mysql56"),
         "user": getenv("MYSQL_USER", "root"),
@@ -196,16 +511,135 @@ def main():
         "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 (model do API + alias do UI)
+    # --- SQL -> rows (UWZGLĘDNIJ DATY; typ wg ENV) ---
+    try:
+        cnx = mysql.connector.connect(**cfg)
+        cur = cnx.cursor()
+        if invoice_type:
+            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),
+            )
+        else:
+            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
+                """,
+                (period_from, period_to),
+            )
+        rows = cur.fetchall()
+        cur.close()
+        cnx.close()
+    except Exception as e:
+        html_fatal(str(e), title="Błąd połączenia/zapytania MySQL")
+
+    # --- LICZ TYLKO WYBRANE PREAGREGATY (w tym pseudo 'kpis') ---
+    results = {}
+    serialized = {}
+    if metric_names:
+        results = compute_selected_preaggs(rows, metric_names)
+        serialized = serialize_for_ai(results)
+        serialized = sanitize_serialized(serialized)  # usuń ewentualne _error -> traktuj jako puste
+    else:
+        serialized = {}
+
+    # --- ZAPIS do reporting (tylko to, co faktycznie policzyłeś) ---
+    try:
+        if serialized:
+            rep_cfg = {
+                "host": "host.docker.internal",
+                "port": 3307,
+                "user": "remote",
+                "password": os.environ.get("REPORTING_PASSWORD", "areiufh*&^yhdua"),
+                "database": "ai",
+            }
+            if os.environ.get("REPORTING_SSL_CA"):
+                rep_cfg["ssl_ca"] = os.environ["REPORTING_SSL_CA"]
+            if os.environ.get("REPORTING_SSL_CERT"):
+                rep_cfg["ssl_cert"] = os.environ["REPORTING_SSL_CERT"]
+            if os.environ.get("REPORTING_SSL_KEY"):
+                rep_cfg["ssl_key"]  = os.environ["REPORTING_SSL_KEY"]
+
+            cnx2 = connect_html_or_die(rep_cfg, label="ReportingDB")
+            cur2 = cnx2.cursor()
+
+            if "daily_sales" in serialized:
+                upsert_daily_sales(cur2, serialized.get("daily_sales") or [])
+            if "product_summary" in serialized:
+                upsert_product_summary(cur2, serialized.get("product_summary") or [], period_from, period_to)
+            if "customer_summary" in serialized:
+                upsert_customer_summary(cur2, serialized.get("customer_summary") or [], period_from, period_to)
+            if "product_daily" in serialized:
+                upsert_product_daily(cur2, serialized.get("product_daily") or [])
+
+            cnx2.commit()
+            cur2.close(); cnx2.close()
+    except Exception as e:
+        sys.stderr.write(f"[reporting] ERROR: {e}\n")
+
+    # --- KPI: jeśli wybrano 'kpis' -> bierz z wyników; w przeciwnym razie spróbuj z daily_sales; inaczej zera ---
+    kpis = []
+    if "kpis" in results and isinstance(results["kpis"], pd.DataFrame) and not results["kpis"].empty:
+        r = results["kpis"].iloc[0]
+        total_sales = r.get("total_sales") or 0
+        total_qty   = r.get("total_qty") or 0
+        total_docs  = r.get("total_docs") or 0
+        asp         = r.get("asp")
+    else:
+        daily = serialized.get("daily_sales") or []
+        total_sales = sum((x.get("sales") or 0) for x in daily) if daily else 0
+        total_qty   = sum((x.get("qty") or 0) for x in daily) if daily else 0
+        total_docs  = sum((x.get("docs") or 0) for x in daily) if daily else 0
+        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: renderuj tylko te, które policzyłeś ---
+    parts = []
+    if "top10_products_by_sales" in serialized:
+        parts.append(html_table(serialized.get("top10_products_by_sales") or [], title="Top 10 produktów (po sprzedaży)", max_rows=10))
+    if "top10_customers_by_sales" in serialized:
+        parts.append(html_table(serialized.get("top10_customers_by_sales") or [], title="Top 10 klientów (po sprzedaży)",  max_rows=10))
+    if "daily_sales" in serialized:
+        parts.append(html_table(serialized.get("daily_sales") or [], title="Sprzedaż dzienna (skrót)", max_rows=30))
+    if "product_summary" in serialized:
+        parts.append(html_table(serialized.get("product_summary") or [], title="Podsumowanie produktów (skrót)", max_rows=30))
+    if "customer_summary" in serialized:
+        parts.append(html_table(serialized.get("customer_summary") or [], title="Podsumowanie klientów (skrót)", max_rows=30))
+    if "product_daily" in serialized:
+        parts.append(html_table(serialized.get("product_daily") or [], title="Produkt × Dzień (próbka)", max_rows=30))
+
+    # --- AI tylko gdy: --ai true ORAZ jest co najmniej jeden rekord w którymś z wybranych agregatów ---
     api_key = API_KEY_HARDCODE or getenv("OPENAI_API_KEY", "")
     model = getenv("OPENAI_MODEL", "gpt-4.1")
     MODEL_ALIAS = {
@@ -216,95 +650,19 @@ def main():
     }
     model_alias = MODEL_ALIAS.get(model, model)
 
-    system_prompt = (
-        "Jesteś analitykiem sprzedaży. Zwróć TYLKO jedną sekcję HTML (bez <html>/<head>/<body>), "
-        "może być pojedynczy <div> z nagłówkami i listami. Podsumuj kluczowe trendy (dzień, mix), wskaż top produkty/klientów, "
-        "anomalia/odchylenia oraz daj 3–6 praktycznych rekomendacji dla sprzedaży/zaopatrzenia/marketingu. Krótko i 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>'
-            f'<p style="margin:0;">{str(e)}</p></div>'
-        )
-        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>'
-            f'<p style="margin:0;">{str(e)}</p></div>'
-        )
-        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 — WYŚWIETLAMY WSZYSTKIE KLUCZOWE PREAGREGATY
-    top_prod = serialized.get("top10_products_by_sales") or []
-    top_cli  = serialized.get("top10_customers_by_sales") or []
-    daily_tbl     = html_table(serialized.get("daily_sales") or [], title="Sprzedaż dzienna (skrót)", max_rows=30)
-    prod_sum_tbl  = html_table(serialized.get("product_summary") or [], title="Podsumowanie produktów (skrót)", max_rows=30)
-    cust_sum_tbl  = html_table(serialized.get("customer_summary") or [], title="Podsumowanie klientów (skrót)", max_rows=30)
-    prod_daily_tbl= html_table(serialized.get("product_daily") or [], title="Produkt × Dzień (próbka)", max_rows=30)
-    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 (z fallbackiem na mini model przy 429: insufficient_quota)
     ai_section = ""
-    if api_key:
+    if with_ai and has_any_rows(serialized):
         try:
+            ai_data = {"kpis_hint": {"period_label": shown_label}}
+            for name, records in serialized.items():
+                ai_data[name] = compact_table(records, 100)
+            ai_json = json.dumps(ai_data, ensure_ascii=False, separators=(",", ":"), default=str)
+
             ai_section = call_openai_chat(
-                api_key=api_key,
+                api_key=(api_key or ""),
                 model=model,
-                system_prompt=system_prompt,
+                system_prompt=("Jesteś analitykiem sprzedaży. Zwróć TYLKO jedną sekcję HTML (bez <html>/<head>/<body>). "
+                               "Streszcz kluczowe trendy i daj 3–6 zaleceń. Po polsku."),
                 user_payload_json=ai_json,
                 temperature=0.3,
                 connect_timeout=10,
@@ -314,39 +672,40 @@ def main():
         except Exception as e:
             err = str(e)
             if "insufficient_quota" in err or "You exceeded your current quota" in err:
-                # spróbuj tańszego modelu
                 try:
                     ai_section = call_openai_chat(
-                        api_key=api_key,
+                        api_key=(api_key or ""),
                         model="gpt-4.1-mini",
-                        system_prompt=system_prompt,
+                        system_prompt=("Jesteś analitykiem sprzedaży. Zwróć TYLKO jedną sekcję HTML (bez <html>/<head>/<body>). "
+                                       "Streszcz kluczowe trendy i daj 3–6 zaleceń. Po polsku."),
                         user_payload_json=ai_json,
                         temperature=0.3,
                         connect_timeout=10,
                         read_timeout=90,
                         max_retries=2,
                     )
-                    model_alias = "GPT-5 Mini"
+                    model_alias = "GPT-4.1-mini"
                 except Exception as ee:
                     ai_section = (
                         '<div style="color:#991b1b;background:#fff5f5;border:1px solid #fecaca;'
-                        'padding:10px;border-radius:8px;">'
-                        f'Brak dostępnego limitu API. {str(ee)}</div>'
+                        'padding:10px;border-radius:8px;">Brak dostępnego limitu API. {}</div>'.format(str(ee))
                     )
             else:
                 ai_section = (
                     '<div style="color:#991b1b;background:#fff5f5;border:1px solid #fecaca;'
-                    'padding:10px;border-radius:8px;">'
-                    f'Błąd wywołania AI: {err}</div>'
+                    'padding:10px;border-radius:8px;">Błąd wywołania AI: {}</div>'.format(err)
                 )
+    else:
+        ai_section = '<div style="color:#6b7280">Analiza AI wyłączona lub brak wybranych danych.</div>'
+        model_alias = ""
 
-    # Finalny HTML (jeden <div>)
+    # --- Finalny HTML ---
     report_html = render_report_html(
-        period_label=period_label,
+        period_label=shown_label,
         kpis=kpis,
-        parts=[prod_tbl, cust_tbl, daily_tbl, prod_sum_tbl, cust_sum_tbl, prod_daily_tbl],
+        parts=parts,
         ai_section=ai_section,
-        model_alias=model_alias if api_key else ""
+        model_alias=(model_alias if (with_ai and has_any_rows(serialized)) else "")
     )
     sys.stdout.write(report_html)
 

modules/EcmInvoiceOuts/report_form.php

@@ -0,0 +1,177 @@
+<?php
+/**
+ * report_form.php — formularz + uruchomienie analysisAI.py z parametrami
+ * ZGODNE z PHP 5.6 i Sugar 6 (wyciszone E_STRICT/E_DEPRECATED/NOTICE).
+ */
+
+// --- wycisz „hałas” Sugar CRM ---
+error_reporting(E_ALL & ~E_STRICT & ~E_DEPRECATED & ~E_NOTICE);
+ini_set('display_errors', '0');
+// (opcjonalnie) loguj do pliku
+// ini_set('log_errors', '1');
+// ini_set('error_log', '/var/log/php_form_errors.log');
+
+// --- ŚCIEŻKI (dostosuj do swojej instalacji) ---
+$python = '/usr/local/bin/python3';
+$script = '/var/www/html/modules/EcmInvoiceOuts/ai/analysisAI.py';
+$baseDir = dirname($script);
+
+// --- domyślne wartości pól ---
+$defaultDateTo   = date('Y-m-d');
+$defaultDateFrom = date('Y-m-d', strtotime('-7 days'));
+
+// --- zbieranie POST (PHP 5.6 friendly) ---
+$submitted      = (isset($_SERVER['REQUEST_METHOD']) && $_SERVER['REQUEST_METHOD'] === 'POST');
+$post_date_from = isset($_POST['date_from']) ? $_POST['date_from'] : $defaultDateFrom;
+$post_date_to   = isset($_POST['date_to'])   ? $_POST['date_to']   : $defaultDateTo;
+$post_preaggs   = (isset($_POST['preaggs']) && is_array($_POST['preaggs'])) ? $_POST['preaggs'] : array();
+$post_with_ai   = !empty($_POST['with_ai']);
+
+function h($v) { return htmlspecialchars($v, ENT_QUOTES, 'UTF-8'); }
+function is_valid_date_yyyy_mm_dd($d) {
+    return (bool)preg_match('/^\d{4}-\d{2}-\d{2}$/', $d);
+}
+
+// --- wykonanie skryptu Pythona, jeśli formularz został wysłany ---
+$ran = false;
+$ok  = false;
+$rc  = 0;
+$out = '';
+$err = '';
+
+if ($submitted) {
+    // prosta walidacja dat
+    if (!is_valid_date_yyyy_mm_dd($post_date_from) || !is_valid_date_yyyy_mm_dd($post_date_to)) {
+        $err = "Nieprawidłowy format daty. Użyj YYYY-MM-DD.";
+        $ran = true;
+    } else {
+        // zbuduj argumenty
+        $args = array(
+                '--date-from', $post_date_from,
+                '--date-to',   $post_date_to,
+                '--ai',        ($post_with_ai ? 'true' : 'false')
+        );
+        if (!empty($post_preaggs)) {
+            // CSV z zaznaczonych preagregatów
+            $args[] = '--metrics';
+            $args[] = implode(',', $post_preaggs);
+        }
+
+        // komenda: przejdź do katalogu skryptu, uruchom pythona; zbierz stdout+stderr
+        $cmd = 'cd ' . escapeshellarg($baseDir) . ' && ' .
+                escapeshellcmd($python) . ' ' . escapeshellarg($script);
+
+        foreach ($args as $a) {
+            $cmd .= ' ' . escapeshellarg($a);
+        }
+
+        $output = array();
+        $returnVar = 0;
+        exec($cmd . ' 2>&1', $output, $returnVar);
+
+        $ran = true;
+        $rc  = $returnVar;
+        $out = implode("\n", $output);
+        $ok  = ($returnVar === 0);
+
+        if (!$ok && $err === '') {
+            $err = "Błąd uruchamiania skryptu Python (kod: " . $rc . "):\n" . $out;
+        }
+    }
+}
+?>
+<!doctype html>
+<html lang="pl">
+<head>
+    <meta charset="utf-8">
+    <title>Generator raportu sprzedaży</title>
+    <meta name="viewport" content="width=device-width, initial-scale=1">
+    <style>
+        body { font: 14px/1.4 system-ui, Arial, sans-serif; padding: 20px; }
+        fieldset { margin-bottom: 16px; padding: 12px; border-radius: 6px; border:1px solid #e5e5e5; }
+        .row { display: flex; gap: 16px; flex-wrap: wrap; }
+        .col { min-width: 220px; flex: 1; }
+        label { display:block; margin: 6px 0; }
+        input[type="date"], button { padding: 6px 10px; font-size:14px; }
+        button { margin-top: 10px; cursor: pointer; border:1px solid #0a66c2; background:#0a66c2; color:#fff; border-radius:8px; }
+        .pill { display:inline-block; padding:2px 8px; border-radius:999px; background:#eee; margin:4px 6px 0 0; }
+        .out { white-space: normal; background: #fff; border:1px solid #ddd; padding:12px; border-radius:6px; }
+        .error { white-space: pre-wrap; background: #fff3f3; border:1px solid #f3c2c2; padding:12px; border-radius:6px; color:#b00020; }
+        .muted { color:#666; }
+    </style>
+</head>
+<body>
+
+<h1>Raport sprzedaży — parametry</h1>
+
+<form method="post">
+    <!-- zakres dat -->
+    <fieldset>
+        <legend>Zakres dat</legend>
+        <div class="row">
+            <div class="col">
+                <label>Data od:
+                    <input type="date" name="date_from" value="<?php echo h($post_date_from); ?>" required>
+                </label>
+            </div>
+            <div class="col">
+                <label>Data do:
+                    <input type="date" name="date_to" value="<?php echo h($post_date_to); ?>" required>
+                </label>
+            </div>
+        </div>
+    </fieldset>
+
+    <!-- preagregaty -->
+    <fieldset>
+        <legend>Preagregaty do analizy</legend>
+        <label><input type="checkbox" name="preaggs[]" value="daily_sales"             <?php echo in_array('daily_sales', $post_preaggs, true) ? 'checked' : ''; ?>> Dzienne sprzedaże</label>
+        <label><input type="checkbox" name="preaggs[]" value="product_summary"         <?php echo in_array('product_summary', $post_preaggs, true) ? 'checked' : ''; ?>> Podsumowanie produktów</label>
+        <label><input type="checkbox" name="preaggs[]" value="customer_summary"        <?php echo in_array('customer_summary', $post_preaggs, true) ? 'checked' : ''; ?>> Podsumowanie klientów</label>
+        <label><input type="checkbox" name="preaggs[]" value="product_daily"           <?php echo in_array('product_daily', $post_preaggs, true) ? 'checked' : ''; ?>> Sprzedaż produktu dziennie</label>
+        <label><input type="checkbox" name="preaggs[]" value="top10_products_by_sales" <?php echo in_array('top10_products_by_sales', $post_preaggs, true) ? 'checked' : ''; ?>> Top10 produktów</label>
+        <label><input type="checkbox" name="preaggs[]" value="top10_customers_by_sales"<?php echo in_array('top10_customers_by_sales', $post_preaggs, true) ? 'checked' : ''; ?>> Top10 klientów</label>
+    </fieldset>
+
+    <!-- AI -->
+    <fieldset>
+        <legend>Analiza AI</legend>
+        <label>
+            <input type="checkbox" name="with_ai" <?php echo $post_with_ai ? 'checked' : ''; ?>> Dołącz analizę AI
+        </label>
+    </fieldset>
+
+    <button type="submit">Generuj</button>
+</form>
+
+<?php if ($submitted): ?>
+    <hr>
+    <h2>Użyte parametry</h2>
+    <p>
+        <span class="pill">Od: <?php echo h($post_date_from); ?></span>
+        <span class="pill">Do: <?php echo h($post_date_to); ?></span>
+        <span class="pill">AI: <?php echo $post_with_ai ? 'tak' : 'nie'; ?></span>
+    </p>
+    <p>Preagregaty:
+        <?php
+        if (!empty($post_preaggs)) {
+            foreach ($post_preaggs as $p) {
+                echo '<span class="pill">'.h($p).'</span>';
+            }
+        } else {
+            echo '<span class="muted">brak</span>';
+        }
+        ?>
+    </p>
+
+    <h2>Wynik analizy</h2>
+    <?php if (!$ok): ?>
+        <div class="error"><?php echo h($err); ?></div>
+    <?php else: ?>
+        <!-- Zakładamy, że Python zwraca gotowy HTML -->
+        <div class="out"><?php echo $out; ?></div>
+    <?php endif; ?>
+<?php endif; ?>
+
+</body>
+</html>