meta-optimizer/analyze_creatives.py

"""
Análisis profundo de creatividades de Meta Ads.
Analiza visualmente cada anuncio activo, correlaciona con métricas de rendimiento,
detecta fatiga creativa y compara anuncios dentro del mismo adset.

Uso:
    python analyze_creatives.py                             # todas las campañas
    python analyze_creatives.py --campaign VIVIFUL_5        # filtrar por nombre
    python analyze_creatives.py --no-slack                  # sin envío a Slack
"""

import argparse
import sys
import time
from datetime import datetime

sys.stdout.reconfigure(encoding="utf-8", errors="replace")

import config
from meta_ads_client import MetaAdsClient
from baserow_client import BaserowClient
from agent import analyze_creative_deep, compare_adset_creatives
from slack_notifier import send_creative_analysis_report


def _get_max_cpl(campaign_name: str, verticals_data: dict) -> float:
    name_lower = campaign_name.lower()
    for vert_name, vert_cfg in verticals_data.items():
        if vert_name.lower() in name_lower:
            return float(vert_cfg.get("target_cpl") or 0)
    return float(config.META_TARGET_CPL or 6.0)


def main():
    parser = argparse.ArgumentParser(description="Deep creative analysis for Meta Ads")
    parser.add_argument("--campaign", help="Filter campaigns by name substring (case-insensitive)")
    parser.add_argument("--no-slack", action="store_true", help="Skip Slack report")
    args = parser.parse_args()

    meta = MetaAdsClient()
    db   = BaserowClient()

    print(f"\n{'='*60}")
    print(f"  ANÁLISIS DE CREATIVIDADES — {datetime.now().strftime('%d/%m/%Y %H:%M')}")
    print(f"{'='*60}\n")

    # Active campaigns (last 7 days)
    campaigns = meta.get_period_campaign_metrics(7)
    if args.campaign:
        campaigns = {k: v for k, v in campaigns.items()
                     if args.campaign.upper() in v["name"].upper()}

    if not campaigns:
        print("No hay campañas activas en los últimos 7 días.")
        return

    print(f"→ {len(campaigns)} campañas a analizar\n")

    verticals_data = {v["Nombre"]: v for v in db.get_all_verticals()}

    all_results: dict = {}
    total_analyzed = 0
    total_errors   = 0

    for cid, camp_metrics in campaigns.items():
        campaign_name = camp_metrics["name"]
        max_cpl       = _get_max_cpl(campaign_name, verticals_data)

        print(f"  ● {campaign_name}  (objetivo CPL: {max_cpl:.2f}€)")

        ads_with_creatives = meta.get_ads_with_creatives(cid)
        if not ads_with_creatives:
            print("    — sin anuncios activos con creatividades, omitiendo\n")
            continue

        # Metrics for both windows
        ads_7d = {a["id"]: a for a in meta.get_period_ad_metrics(cid, 7)}
        ads_3d = {a["id"]: a for a in meta.get_period_ad_metrics(cid, 3)}

        # Adset name lookup from 7d metrics
        adset_names = {a["id"]: a["name"] for a in meta.get_period_adset_metrics(cid, 7)}

        # Group ads by adset
        adset_groups: dict = {}
        for ad in ads_with_creatives:
            if not ad.get("thumbnail_url"):
                continue
            ad_id     = ad["ad_id"]
            adset_id  = ad.get("adset_id", "unknown")
            adset_name = adset_names.get(adset_id, adset_id)

            m7 = ads_7d.get(ad_id, {})
            m3 = ads_3d.get(ad_id, {})
            metrics = {
                "spend_7d": m7.get("spend", 0),
                "leads_7d": m7.get("leads", 0),
                "cpl_7d":   m7.get("cpl", 0),
                "ctr_7d":   m7.get("ctr", 0),
                "spend_3d": m3.get("spend", 0),
                "leads_3d": m3.get("leads", 0),
                "cpl_3d":   m3.get("cpl", 0),
                "ctr_3d":   m3.get("ctr", 0),
                "max_cpl":  max_cpl,
            }

            if adset_id not in adset_groups:
                adset_groups[adset_id] = {"name": adset_name, "ads": []}
            adset_groups[adset_id]["ads"].append({
                "ad_id":      ad_id,
                "ad_name":    ad["ad_name"],
                "campaign_id": cid,
                "adset_id":   adset_id,
                "adset_name": adset_name,
                # Fallback chain: signed thumbnail → permanent video picture → static image_url
                "image_url":  [ad["thumbnail_url"], ad["video_thumbnail_url"], ad["image_url"]],
                **metrics,
            })

        # Analyze each ad individually
        analyzed_adsets: dict = {}
        for adset_id, adset_data in adset_groups.items():
            adset_name  = adset_data["name"]
            analyzed_ads = []

            for ad in adset_data["ads"]:
                short_name = ad["ad_name"][:50]
                print(f"    [{adset_name[:30]}] {short_name}...", end=" ", flush=True)

                result = analyze_creative_deep(
                    image_url=ad["image_url"],
                    ad_name=ad["ad_name"],
                    metrics={k: ad[k] for k in (
                        "spend_7d", "leads_7d", "cpl_7d", "ctr_7d",
                        "spend_3d", "leads_3d", "cpl_3d", "ctr_3d", "max_cpl"
                    )},
                )

                score        = result.get("score", 0)
                fatigue_flag = " ⚠️FATIGA" if result.get("fatigue") else ""
                print(f"score={score:.1f}{fatigue_flag}")

                ad_result = {**ad, **result}
                analyzed_ads.append(ad_result)

                # Save to Baserow
                analysis_text = result.get("analysis", "")
                if result.get("fatigue") and result.get("fatigue_reason"):
                    analysis_text += f"\n\n⚠️ FATIGA CREATIVA: {result['fatigue_reason']}"

                try:
                    urls = ad["image_url"]
                    saved_url = urls[0] if isinstance(urls, list) else urls
                    db.save_creative_analysis({
                        "ad_id":           ad["ad_id"],
                        "ad_name":         ad["ad_name"],
                        "campaign_id":     cid,
                        "image_url":       saved_url,
                        "analysis":        analysis_text,
                        "score":           score,
                        "recommendations": result.get("recommendations", ""),
                    })
                    total_analyzed += 1
                except Exception as e:
                    print(f"      [WARN] Baserow: {e}")
                    total_errors += 1

                time.sleep(0.3)

            # Comparative analysis for adsets with 2+ ads
            comparison = None
            if len(analyzed_ads) >= 2:
                print(f"    [comparativa] {adset_name[:40]}...", end=" ", flush=True)
                comparison = compare_adset_creatives(analyzed_ads)
                winner = comparison.get("winner", "")
                print(f"ganador: {winner[:40]}")

            analyzed_adsets[adset_id] = {
                "name":       adset_name,
                "ads":        analyzed_ads,
                "comparison": comparison,
            }

        all_results[cid] = {
            "name":    campaign_name,
            "max_cpl": max_cpl,
            "adsets":  analyzed_adsets,
        }
        print()

    # Summary
    total_ads     = sum(len(as_d["ads"]) for c in all_results.values() for as_d in c["adsets"].values())
    total_fatigue = sum(
        1 for c in all_results.values()
        for as_d in c["adsets"].values()
        for ad in as_d["ads"] if ad.get("fatigue")
    )
    print(f"{'='*60}")
    print(f"  Finalizado: {len(all_results)} campañas, {total_ads} anuncios analizados")
    if total_fatigue:
        print(f"  ⚠️  {total_fatigue} anuncios con fatiga creativa detectada")
    if total_errors:
        print(f"  ⚠️  {total_errors} errores al guardar en Baserow")
    print(f"{'='*60}\n")

    # Slack report
    if not args.no_slack and all_results:
        print("→ Enviando informe a Slack...")
        send_creative_analysis_report(all_results)
        print("  ✓ Informe enviado.")


if __name__ == "__main__":
    main()