Fix extraction for companies and religious entities

routers/review.py

@@ -8,7 +8,12 @@ from fastapi.templating import Jinja2Templates
 
 from config import UPLOAD_DIR
 from database.connection import get_db
-from services.extractor import extract_document
+from services.extractor import (
+    extract_document,
+    get_available_providers,
+    get_default_provider,
+    verify_page_correlation,
+)
 from services.search_service import normalize_arabic, _normalize_scope
 
 router = APIRouter()
@@ -36,6 +41,60 @@ def _is_subsequent_page(page_info: str) -> bool:
     return False
 
 
+def _find_page1_candidate(conn, doc: dict) -> tuple[bool, dict | None]:
+    """Return whether the doc looks like a later page and the best page-1 candidate."""
+    is_subsequent_page = False
+    sibling_doc = None
+
+    if doc.get("pdf_group_id") and (doc.get("page_number") or 0) > 1:
+        is_subsequent_page = True
+        sibling_doc = conn.execute(
+            """SELECT * FROM documents
+               WHERE pdf_group_id=? AND page_number=1""",
+            (doc["pdf_group_id"],),
+        ).fetchone()
+
+    if not sibling_doc:
+        page_info_str = doc.get("page_info") or ""
+        req_num = (doc.get("request_number") or "").strip()
+        doc_scope = (doc.get("search_scope") or "").strip()
+        if req_num and _is_subsequent_page(page_info_str):
+            is_subsequent_page = True
+            if doc_scope:
+                sibling_doc = conn.execute(
+                    """SELECT * FROM documents
+                       WHERE request_number=? AND search_scope=? AND id != ?
+                       ORDER BY CASE WHEN page_number=1 THEN 0 ELSE 1 END,
+                                CASE WHEN person_id IS NOT NULL THEN 0 ELSE 1 END,
+                                id
+                       LIMIT 1""",
+                    (req_num, doc_scope, doc["id"]),
+                ).fetchone()
+
+    return is_subsequent_page, dict(sibling_doc) if sibling_doc else None
+
+
+def _build_correlation_context(doc: dict) -> dict:
+    person = doc.get("person") or {}
+    return {
+        "document_id": doc.get("id"),
+        "request_number": doc.get("request_number"),
+        "request_date": doc.get("request_date"),
+        "page_info": doc.get("page_info"),
+        "page_number": doc.get("page_number"),
+        "search_scope": doc.get("search_scope"),
+        "applicant_name_raw": doc.get("applicant_name_raw"),
+        "person": {
+            "first_name": person.get("first_name"),
+            "father_name": person.get("father_name"),
+            "mother_name": person.get("mother_name"),
+            "family_name": person.get("family_name"),
+            "registry_number": person.get("registry_number"),
+            "registry_place": person.get("registry_place"),
+        },
+    }
+
+
 def _get_document(doc_id: int) -> dict | None:
     with get_db() as conn:
         row = conn.execute("SELECT * FROM documents WHERE id=?", (doc_id,)).fetchone()
@@ -66,58 +125,24 @@ def _get_document(doc_id: int) -> dict | None:
         # Works for both PDF splits (pdf_group_id) and individually uploaded images (via request_number + page_info).
         doc["inherited_from_page1"] = False
         doc["page1_person_id"] = None
+        doc["page1_doc_id"] = None
 
         current_first = (doc["person"].get("first_name") or "").strip()
-        is_subsequent_page = False
+        is_subsequent_page, sibling_doc = _find_page1_candidate(conn, doc)
-        sibling_doc = None
 
-        # Method 1: PDF group link (reliable, unique grouping)
+        if sibling_doc:
-        if doc.get("pdf_group_id") and (doc.get("page_number") or 0) > 1:
+            doc["page1_doc_id"] = sibling_doc.get("id")
-            is_subsequent_page = True
-            sibling_doc = conn.execute(
-                """SELECT * FROM documents
-                   WHERE pdf_group_id=? AND page_number=1""",
-                (doc["pdf_group_id"],),
-            ).fetchone()
-
-        # Method 2: Same request_number + search_scope + page_info indicates page 2+
-        # MUST match on BOTH request_number AND search_scope to avoid cross-person contamination
-        if not sibling_doc and not current_first:
-            page_info_str = doc.get("page_info") or ""
-            req_num = (doc.get("request_number") or "").strip()
-            doc_scope = (doc.get("search_scope") or "").strip()
-            if req_num and _is_subsequent_page(page_info_str):
-                is_subsequent_page = True
-                if doc_scope:
-                    # Match by request_number + search_scope (safe)
-                    sibling_doc = conn.execute(
-                        """SELECT * FROM documents
-                           WHERE request_number=? AND search_scope=? AND id != ?
-                             AND person_id IS NOT NULL
-                           ORDER BY id LIMIT 1""",
-                        (req_num, doc_scope, doc["id"]),
-                    ).fetchone()
-                    if not sibling_doc:
-                        sibling_doc = conn.execute(
-                            """SELECT * FROM documents
-                               WHERE request_number=? AND search_scope=? AND id != ?
-                                 AND raw_extraction_json IS NOT NULL
-                               ORDER BY id LIMIT 1""",
-                            (req_num, doc_scope, doc["id"]),
-                        ).fetchone()
-                # If no search_scope on this doc, DON'T guess — leave it for manual entry
-
-        if sibling_doc and not current_first:
-            sibling_doc = dict(sibling_doc)
             if sibling_doc.get("person_id"):
+                doc["page1_person_id"] = sibling_doc["person_id"]
+
+            if sibling_doc.get("person_id") and not current_first:
                 person = conn.execute(
                     "SELECT * FROM persons WHERE id=?", (sibling_doc["person_id"],)
                 ).fetchone()
                 if person:
                     doc["person"] = dict(person)
                     doc["inherited_from_page1"] = True
-                    doc["page1_person_id"] = sibling_doc["person_id"]
+            elif sibling_doc.get("raw_extraction_json") and not current_first:
-            elif sibling_doc.get("raw_extraction_json"):
                 try:
                     sib_extracted = json.loads(sibling_doc["raw_extraction_json"])
                     sib_person = sib_extracted.get("person", {})
@@ -282,7 +307,64 @@ async def review_document(request: Request, doc_id: int, wait: int = 0):
         )
 
     return templates.TemplateResponse(
-        request, "review.html", {"doc": doc, "upload_dir": "/uploads"}
+        request,
+        "review.html",
+        {
+            "doc": doc,
+            "upload_dir": "/uploads",
+            "providers": get_available_providers(),
+            "current_provider": doc.get("provider") or get_default_provider(),
+            "ai_verification_available": any(
+                provider["id"] in {"claude", "gemini"} for provider in get_available_providers()
+            ),
+        },
+    )
+
+
+@router.post("/review/{doc_id}/verify-correlation")
+async def review_verify_correlation(doc_id: int):
+    with get_db() as conn:
+        row = conn.execute("SELECT * FROM documents WHERE id=?", (doc_id,)).fetchone()
+        if not row:
+            return JSONResponse({"error": "Document not found"}, status_code=404)
+
+        current_doc = _get_document(doc_id)
+        if not current_doc:
+            return JSONResponse({"error": "Document not found"}, status_code=404)
+
+        is_subsequent_page, sibling_doc = _find_page1_candidate(conn, dict(row))
+        if not is_subsequent_page:
+            return JSONResponse(
+                {"error": "This document is not identified as page 2 or later."},
+                status_code=400,
+            )
+        if not sibling_doc:
+            return JSONResponse(
+                {"error": "No page 1 candidate was found for AI verification."},
+                status_code=404,
+            )
+
+        candidate_doc = _get_document(sibling_doc["id"])
+        if not candidate_doc:
+            return JSONResponse({"error": "Candidate page not found"}, status_code=404)
+
+    try:
+        result = await verify_page_correlation(
+            current_doc["image_path"],
+            candidate_doc["image_path"],
+            _build_correlation_context(current_doc),
+            _build_correlation_context(candidate_doc),
+        )
+    except Exception as exc:
+        return JSONResponse({"error": str(exc)}, status_code=400)
+
+    return JSONResponse(
+        {
+            "ok": True,
+            "current_doc_id": current_doc["id"],
+            "candidate_doc_id": candidate_doc["id"],
+            **result,
+        }
     )
 
 
@@ -353,43 +435,8 @@ async def confirm_document(doc_id: int, request: Request):
         # For multi-page documents (page 2+), resolve sibling document's person
         # Works via pdf_group_id OR request_number+search_scope + page_info
         page1_person_id = None
-        is_subsequent = (
+        is_subsequent, sibling = _find_page1_candidate(conn, current_doc)
-            current_doc.get("pdf_group_id")
+        if sibling and sibling.get("person_id"):
-            and (current_doc.get("page_number") or 0) > 1
-        )
-
-        # Method 1: PDF group link
-        if is_subsequent:
-            page1_doc = conn.execute(
-                """SELECT d.person_id, p.first_name, p.father_name, p.family_name,
-                          p.registry_number
-                   FROM documents d
-                   LEFT JOIN persons p ON p.id = d.person_id
-                   WHERE d.pdf_group_id=? AND d.page_number=1 AND d.person_id IS NOT NULL""",
-                (current_doc["pdf_group_id"],),
-            ).fetchone()
-            if page1_doc and page1_doc["person_id"]:
-                page1_person_id = page1_doc["person_id"]
-
-        # Method 2: Same request_number + search_scope + page_info indicates page 2+
-        if not page1_person_id and not first_name:
-            req_num = (current_doc.get("request_number") or "").strip()
-            page_info_val = current_doc.get("page_info") or ""
-            doc_scope = (current_doc.get("search_scope") or "").strip()
-            if req_num and _is_subsequent_page(page_info_val):
-                is_subsequent = True
-                if doc_scope:
-                    sibling = conn.execute(
-                        """SELECT d.person_id, p.first_name, p.father_name, p.family_name,
-                                  p.registry_number
-                           FROM documents d
-                           LEFT JOIN persons p ON p.id = d.person_id
-                           WHERE d.request_number=? AND d.search_scope=? AND d.id != ?
-                             AND d.person_id IS NOT NULL
-                           ORDER BY d.id LIMIT 1""",
-                        (req_num, doc_scope, doc_id),
-                    ).fetchone()
-                    if sibling and sibling["person_id"]:
             page1_person_id = sibling["person_id"]
 
         # Inherit person fields from sibling if not provided
@@ -658,7 +705,7 @@ async def confirm_document(doc_id: int, request: Request):
 
 @router.post("/extract/{doc_id}")
 async def retrigger_extraction(doc_id: int, provider: str = ""):
-    """Re-run extraction for a document (retry after error)."""
+    """Re-run extraction for a document and reset the extracted state first."""
     with get_db() as conn:
         doc = conn.execute(
             "SELECT image_path, provider FROM documents WHERE id=?", (doc_id,)
@@ -666,14 +713,32 @@ async def retrigger_extraction(doc_id: int, provider: str = ""):
     if not doc:
         return JSONResponse({"error": "not found"}, status_code=404)
 
+    use_provider = provider or doc["provider"] or get_default_provider()
+
     with get_db() as conn:
         conn.execute(
-            "UPDATE documents SET status='pending', extraction_error=NULL WHERE id=?",
+            """UPDATE documents
-            (doc_id,),
+               SET status='pending',
+                   person_id=NULL,
+                   request_number=NULL,
+                   request_date=NULL,
+                   applicant_name_raw=NULL,
+                   request_purpose=NULL,
+                   data_valid_until=NULL,
+                   registry_office=NULL,
+                   owns_properties=NULL,
+                   declared_property_count=NULL,
+                   page_info=NULL,
+                   search_scope=NULL,
+                   raw_extraction_json=NULL,
+                   extraction_error=NULL,
+                   provider=?,
+                   updated_at=CURRENT_TIMESTAMP
+               WHERE id=?""",
+            (use_provider, doc_id),
         )
         conn.execute("DELETE FROM properties WHERE document_id=?", (doc_id,))
 
     from routers.upload import _extract_and_save
-    use_provider = provider or doc["provider"] or ""
     asyncio.create_task(_extract_and_save(doc_id, doc["image_path"], use_provider))
     return JSONResponse({"ok": True, "message": "Extraction started"})

services/extractor.py

@@ -28,18 +28,19 @@ CRITICAL INSTRUCTIONS:
    - معلومات محولة لغاية (data_valid_until) found near the bottom.
    - أمانة السجل (registry_office) found at the bottom right.
    - عدد العقارات: (declared_property_count) located right under the properties table.
-7. The properties table has 8 columns in order from RIGHT to LEFT as they appear on the page:
+7. If the property owner is a company, religious entity, or organization (e.g., شركة, وقف, مطرانية, جمعية) rather than a natural person, extract its full name into the `first_name` field and leave `father_name`, `mother_name`, `family_name`, etc. as null.
+8. The properties table has 8 columns in order from RIGHT to LEFT as they appear on the page:
    col1(rightmost)=اسم الفريق, col2=رقم العقار, col3=القسم, col4=البلوك,        
    col5=المنطقة العقارية, col6=القضاء, col7=عدد الأسهم, col8(leftmost)=نوع الملكية
    Map these to JSON keys: party_name, property_number, section, block, real_estate_district, qaza, num_shares, ownership_type
-8. Return ONLY valid JSON matching the schema. No markdown, no explanation."""  
+9. Return ONLY valid JSON matching the schema. No markdown, no explanation."""  
 
 USER_PROMPT = (
     "Extract all data from this Lebanese real estate property card. "
     "Return a single JSON object with these keys: "
     "request_number, request_date, applicant_name_raw, request_purpose, data_valid_until, "
     "registry_office, page_info, search_scope, owns_properties, declared_property_count, "
-    "person (object with: first_name, father_name, mother_name, family_name, "  
+    "person (object with: first_name (or company/entity name), father_name, mother_name, family_name, "  
     "family_origin, nationality, birth_date, registry_number, registry_place), "
     "properties (array of objects with: party_name, property_number, section, block, "
     "real_estate_district, qaza, num_shares, ownership_type), "
@@ -47,6 +48,149 @@ USER_PROMPT = (
     "Use null for missing fields. Include every property row from the table (or empty array if none)."   
 )
 
+CORRELATION_SYSTEM_PROMPT = """You are verifying whether two scanned Lebanese real estate document pages belong to the same multi-page request and the same person.
+
+Rules:
+1. Compare both page images and the extracted metadata together.
+2. Strong signals: matching request number, matching search scope, matching page numbering in the same sequence, matching applicant/person names, matching footer/header identifiers, and obvious continuation of the same document layout.
+3. Weak OCR differences are common in Arabic letters such as س and ن, ب and ت, or Arabic-Indic digits. Do not reject a match solely because of one likely OCR confusion.
+4. Reject when there are clear contradictions in request number, search scope, person identity, or unrelated page numbering.
+5. Return JSON only.
+"""
+
+
+def _get_ai_verification_provider(preferred_provider: str = "") -> str:
+    """Return a provider capable of vision reasoning for verification."""
+    providers = [p["id"] for p in get_available_providers() if p["id"] in {"claude", "gemini"}]
+    if preferred_provider in providers:
+        return preferred_provider
+    if DEFAULT_PROVIDER in providers:
+        return DEFAULT_PROVIDER
+    if providers:
+        return providers[0]
+    raise ValueError("No AI verification provider configured")
+
+
+def _build_correlation_user_prompt(current_context: dict, candidate_context: dict) -> str:
+    return (
+        "Determine whether PAGE_A and PAGE_B belong to the same multi-page request/document for the same person. "
+        "Treat minor OCR mistakes as possible noise. Return one JSON object with keys: "
+        "same_document (boolean), confidence ('high'|'medium'|'low'), verdict_ar (short Arabic sentence), "
+        "reasons_ar (array of short Arabic bullet strings), mismatch_flags (array of short Arabic strings), "
+        "recommended_action ('auto-link'|'manual-review').\n\n"
+        f"PAGE_A_CONTEXT={json.dumps(current_context, ensure_ascii=False)}\n"
+        f"PAGE_B_CONTEXT={json.dumps(candidate_context, ensure_ascii=False)}"
+    )
+
+
+async def verify_page_correlation(
+    current_image_path: str,
+    candidate_image_path: str,
+    current_context: dict,
+    candidate_context: dict,
+    provider: str = "",
+) -> dict:
+    """Ask a vision model if two pages belong to the same multi-page request."""
+    provider = _get_ai_verification_provider(provider)
+
+    if provider == "claude":
+        import anthropic
+
+        client = anthropic.AsyncAnthropic(api_key=ANTHROPIC_API_KEY)
+        current_full_path = _resolve_path(current_image_path)
+        candidate_full_path = _resolve_path(candidate_image_path)
+        current_img_data, current_media_type = _encode_image(current_full_path)
+        candidate_img_data, candidate_media_type = _encode_image(candidate_full_path)
+
+        message = await client.messages.create(
+            model=CLAUDE_MODEL,
+            max_tokens=1200,
+            system=[{"type": "text", "text": CORRELATION_SYSTEM_PROMPT}],
+            messages=[
+                {
+                    "role": "user",
+                    "content": [
+                        {"type": "text", "text": _build_correlation_user_prompt(current_context, candidate_context)},
+                        {
+                            "type": "image",
+                            "source": {
+                                "type": "base64",
+                                "media_type": current_media_type,
+                                "data": current_img_data,
+                            },
+                        },
+                        {
+                            "type": "image",
+                            "source": {
+                                "type": "base64",
+                                "media_type": candidate_media_type,
+                                "data": candidate_img_data,
+                            },
+                        },
+                    ],
+                }
+            ],
+        )
+        raw_text = _strip_code_fences(message.content[0].text)
+        result = json.loads(raw_text)
+    elif provider == "gemini":
+        import asyncio
+        from google import genai
+        from google.genai import types
+
+        client = genai.Client(api_key=GEMINI_API_KEY)
+        current_full_path = _resolve_path(current_image_path)
+        candidate_full_path = _resolve_path(candidate_image_path)
+
+        with open(current_full_path, "rb") as f:
+            current_bytes = f.read()
+        with open(candidate_full_path, "rb") as f:
+            candidate_bytes = f.read()
+
+        mime_map = {
+            ".jpg": "image/jpeg",
+            ".jpeg": "image/jpeg",
+            ".png": "image/png",
+            ".webp": "image/webp",
+        }
+        current_mime = mime_map.get(Path(current_full_path).suffix.lower(), "image/jpeg")
+        candidate_mime = mime_map.get(Path(candidate_full_path).suffix.lower(), "image/jpeg")
+
+        def _call():
+            response = client.models.generate_content(
+                model=GEMINI_MODEL,
+                contents=[
+                    types.Content(
+                        parts=[
+                            types.Part(text=CORRELATION_SYSTEM_PROMPT + "\n\n" + _build_correlation_user_prompt(current_context, candidate_context)),
+                            types.Part(inline_data=types.Blob(mime_type=current_mime, data=current_bytes)),
+                            types.Part(inline_data=types.Blob(mime_type=candidate_mime, data=candidate_bytes)),
+                        ]
+                    )
+                ],
+                config=types.GenerateContentConfig(
+                    temperature=0.1,
+                    max_output_tokens=1600,
+                ),
+            )
+            return response.text
+
+        raw_text = await asyncio.get_event_loop().run_in_executor(None, _call)
+        raw_text = _strip_code_fences(raw_text)
+        result = json.loads(raw_text)
+    else:
+        raise ValueError(f"Provider {provider} does not support AI correlation verification")
+
+    return {
+        "provider": provider,
+        "same_document": bool(result.get("same_document")),
+        "confidence": result.get("confidence") or "medium",
+        "verdict_ar": result.get("verdict_ar") or "تعذر توليد خلاصة واضحة.",
+        "reasons_ar": result.get("reasons_ar") or [],
+        "mismatch_flags": result.get("mismatch_flags") or [],
+        "recommended_action": result.get("recommended_action") or "manual-review",
+    }
+
 def _resolve_path(image_path: str) -> str:
     if Path(image_path).is_absolute():
         return image_path

static/css/review.css

@@ -75,6 +75,87 @@
   line-height: 1.35;
 }
 
+.page-group-banner {
+  align-items: flex-start;
+}
+
+.page-group-copy {
+  display: flex;
+  flex: 1;
+  gap: .9rem;
+  align-items: flex-start;
+  justify-content: space-between;
+  flex-wrap: wrap;
+}
+
+.page-group-actions {
+  margin-inline-start: auto;
+}
+
+.rescan-banner {
+  justify-content: space-between;
+  flex-wrap: wrap;
+}
+
+.rescan-copy {
+  display: inline-block;
+  margin-inline-start: .35rem;
+}
+
+.rescan-controls {
+  display: flex;
+  align-items: center;
+  gap: .65rem;
+  margin-inline-start: auto;
+}
+
+.rescan-controls select {
+  min-width: 220px;
+  padding: .62rem .8rem;
+  border: 1px solid rgba(59, 130, 246, .28);
+  border-radius: 12px;
+  background: rgba(255,255,255,.96);
+  color: var(--text);
+}
+
+.sr-only {
+  position: absolute;
+  width: 1px;
+  height: 1px;
+  padding: 0;
+  margin: -1px;
+  overflow: hidden;
+  clip: rect(0, 0, 0, 0);
+  white-space: nowrap;
+  border: 0;
+}
+
+.correlation-result {
+  margin-bottom: 1rem;
+}
+
+.correlation-heading {
+  display: flex;
+  justify-content: space-between;
+  gap: .75rem;
+  align-items: baseline;
+  flex-wrap: wrap;
+}
+
+.correlation-meta {
+  font-size: .82rem;
+  opacity: .9;
+}
+
+.correlation-list {
+  margin: .6rem 0 0;
+  padding-inline-start: 1.25rem;
+}
+
+.correlation-warnings {
+  margin-top: .4rem;
+}
+
 /* ============================
    Review — Responsive
    ============================ */
@@ -95,6 +176,18 @@
   .review-nav .btn {
     flex: 1 1 calc(50% - .5rem);
   }
+  .page-group-actions {
+    width: 100%;
+    margin-inline-start: 0;
+  }
+  .rescan-controls {
+    width: 100%;
+    margin-inline-start: 0;
+  }
+  .rescan-controls select,
+  .rescan-controls .btn {
+    flex: 1 1 0;
+  }
 }
 
 @media (max-width: 640px) {
@@ -111,6 +204,17 @@
   .review-nav .btn {
     flex-basis: 100%;
   }
+  .page-group-actions .btn {
+    width: 100%;
+  }
+  .rescan-controls {
+    flex-direction: column;
+    align-items: stretch;
+  }
+  .rescan-controls select {
+    min-width: 0;
+    width: 100%;
+  }
   .form-section {
     padding: 1rem;
   }

templates/review.html

@@ -24,6 +24,28 @@
   </div>
 </div>
 
+{% if doc.status in ['extracted', 'confirmed', 'error'] %}
+<div class="info-banner rescan-banner">
+  <div>
+    <strong>إعادة المسح</strong>
+    <span class="rescan-copy">إذا خلط الذكاء الاصطناعي بين أحرف مثل س و ن، يمكنك إعادة القراءة بنفس المحرك أو بمحرك آخر.</span>
+  </div>
+  <div class="rescan-controls">
+    <label for="providerSelect" class="sr-only">محرك الاستخراج</label>
+    <select id="providerSelect" title="محرك الاستخراج">
+      {% for provider in providers %}
+      <option value="{{ provider.id }}" {{ 'selected' if provider.id == current_provider else '' }}>
+        {{ provider.name }}
+      </option>
+      {% endfor %}
+    </select>
+    <button type="button" class="btn btn-warning btn-sm" id="rescanBtn" onclick="retriggerExtraction({{ doc.id }})">
+      إعادة المسح
+    </button>
+  </div>
+</div>
+{% endif %}
+
 {% if doc.status == 'error' %}
 <div class="error-banner">
   ⚠ خطأ في الاستخراج: {{ doc.extraction_error }}
@@ -57,6 +79,8 @@
       {% if doc.get('is_subsequent_page') %}
       <div class="info-banner page-group-banner">
         <svg width="18" height="18" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"><circle cx="12" cy="12" r="10"/><line x1="12" y1="16" x2="12" y2="12"/><line x1="12" y1="8" x2="12.01" y2="8"/></svg>
+        <div class="page-group-copy">
+          <div>
             هذه صفحة تكميلية ({{ doc.get('page_info') or doc.get('page_number') or '' }}) من مستند متعدد الصفحات.
             {% if doc.get('inherited_from_page1') %}
             بيانات الشخص مستوردة تلقائياً من الصفحة الأولى.
@@ -64,6 +88,16 @@
             يرجى التأكد من بيانات الشخص يدوياً — لم يتم العثور على صفحة أولى مؤكدة بعد.
             {% endif %}
           </div>
+          {% if doc.get('page1_doc_id') and ai_verification_available %}
+          <div class="page-group-actions">
+            <button type="button" class="btn btn-secondary btn-sm" id="verifyCorrelationBtn" onclick="verifyCorrelation({{ doc.id }})">
+              تحقق بالذكاء الاصطناعي
+            </button>
+          </div>
+          {% endif %}
+        </div>
+      </div>
+      <div id="correlationResult" class="hidden"></div>
       {% endif %}
 
       <!-- Person Info -->
@@ -418,9 +452,70 @@ async function confirmDocument() {
 }
 
 async function retriggerExtraction(docId) {
-  if (!confirm('إعادة استخراج البيانات بالذكاء الاصطناعي؟')) return;
+  const provider = document.getElementById('providerSelect')?.value || '';
-  await fetch(`/extract/${docId}`, { method: 'POST' });
+  const btn = document.getElementById('rescanBtn');
-  location.reload();
+  const providerLabel = document.getElementById('providerSelect')?.selectedOptions?.[0]?.text || 'المحرك الحالي';
+  if (!confirm(`إعادة استخراج البيانات باستخدام ${providerLabel}؟ سيتم استبدال النتائج الحالية.`)) return;
+
+  if (btn) {
+    btn.disabled = true;
+    btn.textContent = 'جارٍ إعادة المسح...';
+  }
+
+  try {
+    const params = new URLSearchParams();
+    if (provider) params.set('provider', provider);
+    const res = await fetch(`/extract/${docId}?${params.toString()}`, { method: 'POST' });
+    const data = await res.json();
+    if (!res.ok || !data.ok) {
+      throw new Error(data.error || data.detail || 'تعذر بدء إعادة المسح.');
+    }
+    window.location.href = `/review/${docId}?wait=1`;
+  } catch (e) {
+    alert('حدث خطأ أثناء إعادة المسح: ' + e.message);
+    if (btn) {
+      btn.disabled = false;
+      btn.textContent = 'إعادة المسح';
+    }
+  }
+}
+
+async function verifyCorrelation(docId) {
+  const btn = document.getElementById('verifyCorrelationBtn');
+  const resultEl = document.getElementById('correlationResult');
+  if (!btn || !resultEl) return;
+
+  btn.disabled = true;
+  btn.textContent = 'جارٍ التحقق...';
+  resultEl.className = 'info-banner correlation-result';
+  resultEl.innerHTML = 'جارٍ فحص الترابط بين الصفحة الحالية والصفحة الأولى...';
+
+  try {
+    const res = await fetch(`/review/${docId}/verify-correlation`, { method: 'POST' });
+    const data = await res.json();
+    if (!res.ok || !data.ok) {
+      throw new Error(data.error || 'تعذر التحقق من الترابط.');
+    }
+
+    const statusClass = data.same_document ? 'success-banner' : 'error-banner';
+    const reasons = (data.reasons_ar || []).map(item => `<li>${item}</li>`).join('');
+    const mismatches = (data.mismatch_flags || []).map(item => `<li>${item}</li>`).join('');
+    resultEl.className = `${statusClass} correlation-result`;
+    resultEl.innerHTML = `
+      <div class="correlation-heading">
+        <strong>${data.verdict_ar}</strong>
+        <span class="correlation-meta">الثقة: ${data.confidence} | المحرك: ${data.provider}</span>
+      </div>
+      ${reasons ? `<ul class="correlation-list">${reasons}</ul>` : ''}
+      ${mismatches ? `<ul class="correlation-list correlation-warnings">${mismatches}</ul>` : ''}
+    `;
+  } catch (e) {
+    resultEl.className = 'error-banner correlation-result';
+    resultEl.textContent = 'فشل التحقق: ' + e.message;
+  } finally {
+    btn.disabled = false;
+    btn.textContent = 'تحقق بالذكاء الاصطناعي';
+  }
 }
 
 async function deleteDoc(docId) {