Upload 9 files

core.py

@@ -8,7 +8,7 @@ from fastapi.encoders import ENCODERS_BY_TYPE
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.staticfiles import StaticFiles
 from google import genai
-from pymongo import MongoClient
+from pymongo import ASCENDING, MongoClient
 
 app = FastAPI(title="Nomus AI Agent Calendar V3 – Streaming + Proposals")
 
@@ -41,6 +41,26 @@ team_chat_collection = db.team_chat_history
 team_docs_collection = db.team_documents
 team_doc_chunks_collection = db.team_document_chunks
 
+
+def _ensure_indexes() -> None:
+    try:
+        team_doc_chunks_collection.create_index(
+            [("doc_id", ASCENDING), ("chunk_index", ASCENDING)],
+            name="idx_team_doc_chunks_doc_id_chunk",
+            background=True,
+        )
+        team_docs_collection.create_index(
+            [("team_id", ASCENDING), ("project_id", ASCENDING), ("updated_at", ASCENDING)],
+            name="idx_team_docs_team_project_updated",
+            background=True,
+        )
+    except Exception:
+        # Index creation failure should not block app startup.
+        pass
+
+
+_ensure_indexes()
+
 UPLOAD_DIR = os.environ.get("UPLOAD_DIR", os.path.join(os.path.dirname(__file__), "uploads"))
 os.makedirs(UPLOAD_DIR, exist_ok=True)
 app.mount("/uploads", StaticFiles(directory=UPLOAD_DIR), name="uploads")

services_legacy.py

@@ -23,6 +23,7 @@ import whisper
 from fastapi import HTTPException
 from google.genai import types
 from PIL import Image, ImageOps
+from pymongo.errors import OperationFailure
 from transformers import AutoTokenizer, VitsModel
 
 from core import (
@@ -736,12 +737,31 @@ def _store_team_document_chunks(doc_id: str, nodes: List[Dict[str, Any]], create
 
 
 def _load_team_document_nodes(doc_id: str) -> List[Dict[str, Any]]:
-    rows = list(
-        team_doc_chunks_collection.find(
-            {"doc_id": doc_id},
-            {"_id": 0, "nodes": 1},
-        ).sort("chunk_index", 1)
-    )
+    normalized_doc_id = str(doc_id or "").strip()
+    if not normalized_doc_id:
+        return []
+
+    projection = {"_id": 0, "chunk_index": 1, "nodes": 1}
+    try:
+        # Prefer index-backed sort. If index is not ready yet, fallback below.
+        cursor = team_doc_chunks_collection.find(
+            {"doc_id": normalized_doc_id},
+            projection,
+        ).hint("idx_team_doc_chunks_doc_id_chunk").sort("chunk_index", 1)
+
+        if hasattr(cursor, "allow_disk_use"):
+            cursor = cursor.allow_disk_use(True)
+
+        rows = list(cursor)
+    except (OperationFailure, ValueError):
+        rows = list(
+            team_doc_chunks_collection.find(
+                {"doc_id": normalized_doc_id},
+                projection,
+            )
+        )
+        rows.sort(key=lambda row: int(row.get("chunk_index", 0)))
+
     nodes: List[Dict[str, Any]] = []
     for row in rows:
         chunk_nodes = row.get("nodes")