feat(suggest): Typesense rows for autosuggest, no DataFrame

search_schools_typesense returns URNs, which forces the caller to
hydrate from the 25,000-row in-memory frame. Every field a suggestion
needs is already in the Typesense document, so this returns documents
and the caller needs no pandas at all — the difference between a query
that can run per keystroke and one that cannot.

Never raises. Typesense unreachable or erroring gives an empty list,
because a dropdown that quietly stops appearing is the right failure for
a keystroke path.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_015mWQnpye9F299NVRCCSRvj

backend/data_loader.py

@@ -100,6 +100,46 @@ def search_schools_typesense(query: str, limit: int = 250) -> List[int]:
         return []
 
 
+# The most a public endpoint will return in one response.
+SUGGEST_MAX_LIMIT = 20
+
+# Fields a suggestion row carries, and the default when the document omits an
+# optional one. phase and school_type are optional in the Typesense schema.
+_SUGGEST_FIELDS = ("school_name", "local_authority", "postcode",
+                   "phase", "school_type")
+
+
+def suggest_schools_typesense(query: str, limit: int = 8) -> List[dict]:
+    """Autosuggest rows straight from Typesense. Never raises.
+
+    Returns documents rather than URNs, unlike search_schools_typesense, so the
+    caller needs no DataFrame. Every field below is already in the index — see
+    pipeline/scripts/sync_typesense.py — which is what makes this cheap enough
+    to run per keystroke.
+    """
+    client = _get_typesense_client()
+    if client is None:
+        return []
+    try:
+        result = client.collections["schools"].documents.search({
+            "q": query,
+            "query_by": "school_name,local_authority",
+            "per_page": max(1, min(limit, SUGGEST_MAX_LIMIT)),
+            "typo_tokens_threshold": 1,
+        })
+    except Exception:
+        # A dropdown that quietly stops appearing is the right failure here.
+        return []
+
+    rows = []
+    for hit in result.get("hits", []):
+        doc = hit.get("document", {})
+        row = {"urn": int(doc.get("urn", 0))}
+        row.update({f: str(doc.get(f, "") or "") for f in _SUGGEST_FIELDS})
+        rows.append(row)
+    return rows
+
+
 def normalize_school_type(school_type: Optional[str]) -> Optional[str]:
     """Convert cryptic school type codes to user-friendly names."""
     if not school_type: