# preagregaty i analiza AI

modules/EcmInvoiceOuts/ai/analysisAI.py

@@ -1,31 +1,224 @@
 #!/usr/bin/env python3
-import os, sys, json
+# -*- 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
 
-try:
-    import mysql.connector
-except Exception as e:
-    sys.stderr.write("MySQL connector not available: %s\n" % e)
-    sys.exit(1)
+# --------- utils ---------
 
-def getenv(key, default=None):
-    return os.environ.get(key, default)
+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"),
+        "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 COUNT(*) FROM ecminvoiceouts WHERE YEAR(register_date)=2025")
-        cur.execute("""
+        cur.execute(
+            """
             SELECT i.document_no,
                    i.parent_name,
                    DATE(i.register_date) AS register_date,
@@ -38,37 +231,88 @@ def main():
             WHERE i.register_date >= %s
               AND i.register_date <  %s
               AND i.type = %s
-        """, ("2025-07-01", "2025-08-01", "normal"))
+            """,
+            (period_from, period_to, invoice_type),
+        )
         rows = cur.fetchall()
-
-        results = compute_preaggregates(rows)
-
-        # 2) podejrzyj wyniki
-        #  ['daily_sales', 'product_summary', 'customer_summary', 'product_daily',
-        #   'top10_products_by_sales', 'top10_customers_by_sales']
-        print(">> available tables:", list(results.keys()))
-#         print(results["daily_sales"].head(10))
-#         print(results["product_summary"])
-#         print(results["customer_summary"])
-#         print(results["product_daily"])
-#         print(results["top10_products_by_sales"])
-#         print(results["top10_customers_by_sales"])
-        results["daily_sales"].head(10)
-        results["product_summary"]
-        results["customer_summary"]
-        results["product_daily"]
-        results["top10_products_by_sales"]
-        results["top10_customers_by_sales"]
-
-        # 3) zserializuj do lekkiego JSON-a (np. do AI lub do pliku)
-        ai_payload = serialize_for_ai(results)
-        print(json.dumps(ai_payload, ensure_ascii=False, indent=2, default=str))
-
         cur.close()
         cnx.close()
     except Exception as e:
-        sys.stderr.write("Query error: %s\n" % 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()
+    main()

modules/EcmInvoiceOuts/ai/preaggregates.py

@@ -117,8 +117,8 @@ def top10_customers_by_sales(df: pd.DataFrame) -> pd.DataFrame:
 
 # ------------------- Runner -------------------
 
-# def compute_preaggregates(rows: List[tuple]) -> dict[str, pd.DataFrame]:
-def compute_preaggregates(rows):
+def compute_preaggregates(rows: List[tuple]) -> dict[str, pd.DataFrame]:
+#def compute_preaggregates(rows):
     """Główny punkt wejścia: rows -> df -> uruchom wszystkie agregatory."""
     df = to_df(rows)
 #     results: dict[str, pd.DataFrame] = {}

modules/EcmInvoiceOuts/test.php

@@ -1,44 +1,28 @@
 <?php
-$bins = [
-    '/var/www/venv/bin/python',
-    '/usr/bin/python3.11',
-    '/usr/bin/python3.10',
-    '/usr/bin/python3.9',
-    '/usr/local/bin/python3.11',
-    '/usr/local/bin/python3.10',
-    '/usr/local/bin/python3.9',
-    '/usr/bin/python3',
-    'python3',
-];
-foreach ($bins as $b) {
-    $out = []; $ret = 0;
-    exec("$b -V 2>&1", $out, $ret);
-    echo htmlspecialchars("$b -> ".($out ? implode(' ', $out) : "not found / not executable")." (ret=$ret)")."<br>";
+$python = '/usr/local/bin/python3';
+$script = '/var/www/html/modules/EcmInvoiceOuts/ai/analysisAI.py';
+$cmd = escapeshellcmd("$python $script");
+
+// odczyt
+$output = [];
+$returnVar = 0;
+exec($cmd . ' 2>&1', $output, $returnVar);
+$body = implode("\n", $output);
+
+// błąd Pythona
+if ($returnVar !== 0) {
+    // pokaż błąd jako tekst
+    while (ob_get_level()) { ob_end_clean(); }
+    header_remove();
+    header('Content-Type: text/plain; charset=utf-8');
+    http_response_code(500);
+    echo "Error running Python script:\n".$body;
+    exit;
 }
-//$python = '/usr/bin/python3';
-//$script = '/var/www/html/modules/EcmInvoiceOuts/ai/analysisAI.py';
-//$cmd = escapeshellcmd("$python $script");
-//
-//// odczyt
-//$output = [];
-//$returnVar = 0;
-//exec($cmd . ' 2>&1', $output, $returnVar);
-//$body = implode("\n", $output);
-//
-//// błąd Pythona
-//if ($returnVar !== 0) {
-//    // pokaż błąd jako tekst
-//    while (ob_get_level()) { ob_end_clean(); }
-//    header_remove();
-//    header('Content-Type: text/plain; charset=utf-8');
-//    http_response_code(500);
-//    echo "Error running Python script:\n".$body;
-//    exit;
-//}
-//
-//// --- WYMUSZENIE RENDEROWANIA HTML ---
-//while (ob_get_level()) { ob_end_clean(); }  // wyczyść wszystkie bufory
-//header_remove();                             // usuń nagłówki ustawione wcześniej przez framework
-//header('Content-Type: text/html; charset=utf-8');
-//echo $body;
-//exit; // ZATRZYMAJ framework (np. SugarCRM), żeby nic już nie dopisywał
+
+// --- WYMUSZENIE RENDEROWANIA HTML ---
+while (ob_get_level()) { ob_end_clean(); }  // wyczyść wszystkie bufory
+header_remove();                             // usuń nagłówki ustawione wcześniej przez framework
+header('Content-Type: text/html; charset=utf-8');
+echo $body;
+exit; // ZATRZYMAJ framework (np. SugarCRM), żeby nic już nie dopisywał