feat: Gemini AI assessment, Kit Digital detection, contact extraction

Kit Digital detection (enricher.py):
- Scans img src/alt/srcset for digitalizadores, kit-digital, fondos-europeos etc
- Scans page text for Kit Digital, Agente Digitalizador, Next Generation EU, PRTR
- Scans links for acelerapyme.es, red.es, kit-digital refs
- +20 score bonus for Kit Digital confirmed sites (proven IT buyers)

Contact extraction (enricher.py):
- Pulls mailto/tel/wa.me links from HTML
- Extracts email addresses via regex, phone numbers (ES format)
- Detects social media links (FB, IG, LinkedIn, Twitter, TikTok)
- Stored as JSON in contact_info column

Gemini via Replicate (replicate_ai.py):
- Assesses lead quality (HOT/WARM/COLD), Kit Digital confirmation
- Identifies best contact channel + actual value (email/phone/WA)
- Writes Spanish cold-call/email pitch angle
- Lists services likely needed + outreach notes
- 3 concurrent requests, 90s timeout, JSON output parsing

DB: migration adds kit_digital, kit_digital_signals, contact_info,
    ai_assessment, ai_lead_quality, ai_pitch, ai_contact_channel/value,
    ai_queue table

UI: Kit Digital 🏅 badge, AI quality pill (clickable modal with full
    assessment), contact chips (email/phone/WA/social), AI Assess button,
    Kit Digital only filter, AI queue status in enrichment tab

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

app/replicate_ai.py

@@ -0,0 +1,142 @@
+"""Replicate / Gemini integration for domain lead assessment."""
+import asyncio
+import json
+import logging
+import os
+import re
+from typing import Optional
+
+import httpx
+
+logger = logging.getLogger(__name__)
+
+REPLICATE_TOKEN = os.getenv("REPLICATE_API_TOKEN", "r8_6kV2NWMQyPVB9JILHJprrXJJh4vWazA22Osyj")
+REPLICATE_MODEL = "https://api.replicate.com/v1/models/google/gemini-3-pro/predictions"
+AI_CONCURRENCY = int(os.getenv("AI_CONCURRENCY", "3"))
+
+_ai_sem: Optional[asyncio.Semaphore] = None
+
+
+def _sem() -> asyncio.Semaphore:
+    global _ai_sem
+    if _ai_sem is None:
+        _ai_sem = asyncio.Semaphore(AI_CONCURRENCY)
+    return _ai_sem
+
+
+def _build_prompt(row: dict) -> str:
+    kit_signals = row.get("kit_digital_signals") or "[]"
+    try:
+        sigs = json.loads(kit_signals)
+        kit_block = "\n".join(f"  - {s}" for s in sigs) if sigs else "  None detected"
+    except Exception:
+        kit_block = f"  {kit_signals}"
+
+    contact_raw = row.get("contact_info") or "{}"
+    try:
+        contacts = json.loads(contact_raw)
+    except Exception:
+        contacts = {}
+
+    contact_block = []
+    if contacts.get("emails"):
+        contact_block.append(f"  Emails: {', '.join(contacts['emails'][:3])}")
+    if contacts.get("phones"):
+        contact_block.append(f"  Phones: {', '.join(contacts['phones'][:3])}")
+    if contacts.get("whatsapp"):
+        contact_block.append(f"  WhatsApp: {', '.join(contacts['whatsapp'][:2])}")
+    if contacts.get("social"):
+        contact_block.append(f"  Social: {', '.join(contacts['social'][:4])}")
+    contact_str = "\n".join(contact_block) if contact_block else "  None found"
+
+    return f"""You are a sales intelligence analyst evaluating Spanish SME websites for IT services upsell.
+
+DOMAIN DATA:
+- Domain: {row.get("domain")}
+- Page title: {row.get("page_title") or "N/A"}
+- CMS: {row.get("cms") or "unknown"}
+- Server: {row.get("server") or "unknown"}
+- Country: {row.get("ip_country") or "unknown"}
+- SSL valid: {row.get("ssl_valid")}, expires in {row.get("ssl_expiry_days") or "?"} days
+- Has email (MX): {bool(row.get("has_mx"))}
+- Is live: {bool(row.get("is_live"))}
+- Kit Digital signals found on page:
+{kit_block}
+- Contact channels found on page:
+{contact_str}
+
+Kit Digital is a Spanish government program (up to €12k grants for SME digitalization). Sites that received it MUST display EU/digitalizadores logos. These businesses have proven they invest in IT services and may need follow-up: new website, SEO, hosting migration, security, maintenance contracts.
+
+Assess this lead and respond ONLY with valid JSON (no markdown, no explanation outside the JSON):
+{{
+  "is_local_sme": true/false,
+  "kit_digital_confirmed": true/false,
+  "kit_digital_reasoning": "1 sentence explaining why or why not",
+  "lead_quality": "HOT|WARM|COLD",
+  "lead_reasoning": "1-2 sentences on why this is a good/bad lead for IT services sales",
+  "best_contact_channel": "email|phone|whatsapp|social|web_form|unknown",
+  "best_contact_value": "the actual email/phone/URL to use, or empty string",
+  "pitch_angle": "One concrete opening sentence for a cold email or call in Spanish",
+  "services_likely_needed": ["service1", "service2"],
+  "outreach_notes": "Any useful context for the sales rep (language, business type, urgency)"
+}}"""
+
+
+def _parse_output(raw: str) -> dict:
+    """Extract JSON from Gemini text output."""
+    text = re.sub(r"```(?:json)?", "", raw).strip().rstrip("`").strip()
+    m = re.search(r"\{[\s\S]+\}", text)
+    if m:
+        try:
+            return json.loads(m.group(0))
+        except json.JSONDecodeError:
+            pass
+    return {
+        "raw": raw[:500],
+        "lead_quality": "COLD",
+        "best_contact_channel": "unknown",
+        "best_contact_value": "",
+        "parse_error": True,
+    }
+
+
+async def assess_domain(row: dict) -> dict:
+    """Call Gemini via Replicate to assess a domain. Returns parsed assessment dict."""
+    async with _sem():
+        payload = {
+            "input": {
+                "prompt": _build_prompt(row),
+                "images": [],
+                "videos": [],
+                "top_p": 0.9,
+                "temperature": 0.2,
+                "thinking_level": "low",
+                "max_output_tokens": 1024,
+            }
+        }
+        try:
+            async with httpx.AsyncClient(timeout=90) as client:
+                resp = await client.post(
+                    REPLICATE_MODEL,
+                    headers={
+                        "Authorization": f"Bearer {REPLICATE_TOKEN}",
+                        "Content-Type": "application/json",
+                        "Prefer": "wait",
+                    },
+                    json=payload,
+                )
+                resp.raise_for_status()
+                data = resp.json()
+
+            output = data.get("output", "")
+            if isinstance(output, list):
+                output = "".join(output)
+
+            result = _parse_output(output)
+            logger.info("AI %s → %s / contact: %s",
+                        row.get("domain"), result.get("lead_quality"), result.get("best_contact_channel"))
+            return result
+
+        except Exception as e:
+            logger.error("Replicate error %s: %s", row.get("domain"), e)
+            return {"error": str(e)[:300], "lead_quality": "COLD", "best_contact_channel": "unknown", "best_contact_value": ""}