Update app.py

app.py

@@ -1,6 +1,5 @@
 import os
 from flask import Flask, render_template, request, jsonify
-# Using the imports and init logic you confirmed works
 from memvid_sdk import create, open as open_memvid
 from huggingface_hub import hf_hub_download, upload_file, HfApi
 
@@ -71,7 +70,6 @@ def init_db():
         except Exception as e:
             print(f"⚠️ Cloud sync warning: {e}")
 
-    # 2. Initialize Memvid (YOUR WORKING LOGIC)
     try:
         if os.path.exists(DB_PATH):
             db = open_memvid(DB_PATH, read_only=False) 
@@ -130,11 +128,9 @@ def add_memory():
         return jsonify({"error": "No content provided"}), 400
 
     try:
-        # FIX: The error "requires either 'label' or 'labels'" implies 
-        # the dict must contain both the text AND a label field.
         payload = {
             "text": content,
-            "labels": ["web-entry"], # Required by the validation logic
+            "labels": ["web-entry"], 
             "title": "User Memory"
         }
 
@@ -174,11 +170,8 @@ def search_memory():
             if score < 0.65: continue
 
             # --- CLEANING LOGIC ---
-            # 1. Get raw snippet
             raw_snippet = hit.get('snippet', '')
             
-            # 2. Split by lines and remove technical metadata headers
-            # (The raw snippet appends metadata at the bottom)
             lines = raw_snippet.split('\n')
             content_lines = [
                 line for line in lines 
@@ -186,16 +179,14 @@ def search_memory():
             ]
             clean_text = "\n".join(content_lines).strip()
             
-            # 3. Use the explicit arrays provided by the SDK for tags/labels
-            # (These are much cleaner than parsing the string)
             tags = hit.get('tags', [])
             labels = hit.get('labels', [])
 
             clean_results.append({
                 "title": hit.get('title') or "Untitled Memory",
-                "text": clean_text,          # The cleaned up content
-                "tags": tags,                # List of strings ['blue', 'dog']
-                "labels": labels,            # List of strings ['text', 'Blue']
+                "text": clean_text,         
+                "tags": tags,               
+                "labels": labels,            
                 "date": hit.get('created_at', ''),
                 "score": f"{score:.2f}"
             })