Update db_queries.py

backend/db_queries.py

@@ -379,8 +379,28 @@ def list_rag_chunks(post_id: int, page: int = 1, limit: int = 200) -> List[Dict[
     return _rows(response)
 
 
+def _extract_post_row(row: Dict[str, Any]) -> Dict[str, Any]:
+    """
+    Normalize joined post payload from Supabase. It can come back as:
+    - row["audio_posts"] = {...}
+    - row["audio_posts"] = [{...}]
+    - flat fields on row from RPC
+    """
+    post = row.get("audio_posts")
+    if isinstance(post, list):
+        return post[0] if post else {}
+    if isinstance(post, dict):
+        return post
+    return {
+        "user_id": row.get("user_id"),
+        "visibility": row.get("visibility"),
+        "title": row.get("title"),
+        "created_at": row.get("created_at"),
+    }
+
+
 def _can_access_post(row: Dict[str, Any], requester_user_id: int) -> bool:
-    post = row.get("audio_posts") or {}
+    post = _extract_post_row(row)
     visibility = post.get("visibility")
     owner_id = post.get("user_id")
     return visibility == "public" or owner_id == requester_user_id
@@ -399,7 +419,11 @@ def search_rag_chunks(user_id: int, query_text: str, page: int = 1, limit: int =
         .range(0, min(2000, end + 500))
         .execute()
     )
-    rows = [r for r in _rows(response) if _can_access_post(r, user_id)]
+    rows = []
+    for row in _rows(response):
+        if _can_access_post(row, user_id):
+            row["audio_posts"] = _extract_post_row(row)
+            rows.append(row)
     return rows[start:end + 1]
 
 
@@ -432,7 +456,6 @@ def search_rag_chunks_vector(user_id: int, query_embedding: List[float], limit:
             "chunk_id, post_id, start_sec, end_sec, text, confidence, created_at, embedding, "
             "audio_posts!inner(post_id, user_id, title, visibility, created_at)"
         )
-        .eq("audio_posts.user_id", user_id)
         .limit(3000)
         .execute()
     )
@@ -453,6 +476,7 @@ def search_rag_chunks_vector(user_id: int, query_embedding: List[float], limit:
         if score is None:
             continue
         out = dict(row)
+        out["audio_posts"] = _extract_post_row(row)
         out["similarity"] = score
         out.pop("embedding", None)
         ranked.append(out)