Fix notebook failures: remove non-existent memory_index_name and metadata references

- Remove redis_config.memory_index_name reference (memory is now handled by Agent Memory Server)
- Remove metadata parameter from ClientMemoryRecord (not supported in agent-memory-client)
- Remove code trying to access memory.metadata on MemoryRecordResult
- Update documentation to reference topics instead of metadata
- Display topics in memory search results instead of metadata

Author: abrookins

python-recipes/context-engineering/notebooks/section-1-introduction/02_role_of_context_engine.ipynb

@@ -132,11 +132,11 @@
     "        # Show configured indexes\n",
     "        print(f\"\\n🗂️ Vector Indexes:\")\n",
     "        print(f\"  • Course Catalog: {redis_config.vector_index_name}\")\n",
-    "        print(f\"  • Agent Memory: {redis_config.memory_index_name}\")\n",
+    "        print(f\"  • Agent Memory: Managed by Agent Memory Server\")\n",
     "        \n",
     "        # Show data types in use\n",
     "        print(f\"\\n📋 Data Types in Use:\")\n",
-    "        print(f\"  • Hashes: Course and memory storage\")\n",
+    "        print(f\"  • Hashes: Course storage\")\n",
     "        print(f\"  • Vectors: Semantic embeddings (1536 dimensions)\")\n",
     "        print(f\"  • Strings: Simple key-value pairs\")\n",
     "        print(f\"  • Sets: Tags and categories\")\n",
@@ -149,7 +149,6 @@
     "    class MockRedisConfig:\n",
     "        def __init__(self):\n",
     "            self.vector_index_name = \"course_catalog_index\"\n",
-    "            self.memory_index_name = \"agent_memory_index\"\n",
     "        \n",
     "        def health_check(self):\n",
     "            return False  # Simulate Redis not available in CI\n",

python-recipes/context-engineering/notebooks/section-3-memory/02_long_term_memory.ipynb

@@ -209,22 +209,19 @@
     "await memory_client.create_long_term_memory([ClientMemoryRecord(\n",
     "    text=\"Student enrolled in CS101: Introduction to Programming on 2024-09-01\",\n",
     "    memory_type=\"episodic\",\n",
-    "    topics=[\"enrollment\", \"courses\"],\n",
-    "    metadata={\"course_code\": \"CS101\", \"date\": \"2024-09-01\"}\n",
+    "    topics=[\"enrollment\", \"courses\", \"CS101\"]\n",
     ")])\n",
     "\n",
     "await memory_client.create_long_term_memory([ClientMemoryRecord(\n",
     "    text=\"Student completed CS101 with grade A on 2024-12-15\",\n",
     "    memory_type=\"episodic\",\n",
-    "    topics=[\"completion\", \"grades\"],\n",
-    "    metadata={\"course_code\": \"CS101\", \"grade\": \"A\", \"date\": \"2024-12-15\"}\n",
+    "    topics=[\"completion\", \"grades\", \"CS101\"]\n",
     ")])\n",
     "\n",
     "await memory_client.create_long_term_memory([ClientMemoryRecord(\n",
     "    text=\"Student asked about machine learning courses on 2024-09-20\",\n",
     "    memory_type=\"episodic\",\n",
-    "    topics=[\"inquiry\", \"machine_learning\"],\n",
-    "    metadata={\"date\": \"2024-09-20\"}\n",
+    "    topics=[\"inquiry\", \"machine_learning\"]\n",
     ")])\n",
     "\n",
     "print(\"✅ Stored 3 episodic memories (events and experiences)\")"
@@ -292,9 +289,7 @@
     "\n",
     "for i, memory in enumerate(results.memories, 1):\n",
     "    print(f\"{i}. {memory.text}\")\n",
-    "    print(f\"   Type: {memory.memory_type}\")\n",
-    "    if memory.metadata:\n",
-    "        print(f\"   Metadata: {memory.metadata}\")\n",
+    "    print(f\"   Type: {memory.memory_type} | Topics: {', '.join(memory.topics or [])}\")\n",
     "    print()"
    ]
   },
@@ -418,8 +413,7 @@
     "\n",
     "for i, memory in enumerate(results.memories, 1):\n",
     "    print(f\"{i}. {memory.text}\")\n",
-    "    if memory.metadata:\n",
-    "        print(f\"   Metadata: {memory.metadata}\")\n",
+    "    print(f\"   Topics: {', '.join(memory.topics or [])}\")\n",
     "    print()"
    ]
   },
@@ -462,9 +456,9 @@
     "\n",
     "### Best Practices\n",
     "\n",
-    "1. **Use descriptive topics** - Makes filtering easier\n",
-    "2. **Add metadata** - Especially for episodic memories\n",
-    "3. **Write clear memory text** - Will be searched semantically\n",
+    "1. **Use descriptive topics** - Makes filtering and categorization easier\n",
+    "2. **Write clear memory text** - Will be searched semantically\n",
+    "3. **Include relevant details in text** - Dates, names, and context help with retrieval\n",
     "4. **Let deduplication work** - Don't worry about duplicates\n",
     "5. **Search before storing** - Check if similar memory exists"
    ]
@@ -479,7 +473,7 @@
     "\n",
     "2. **Test semantic search**: Create memories with different wordings but similar meanings. Search with various queries to see what matches.\n",
     "\n",
-    "3. **Explore metadata**: Add rich metadata to episodic memories. How can you use this in your agent?\n",
+    "3. **Explore topics**: Add rich topics to episodic memories. How can you use topic filtering in your agent?\n",
     "\n",
     "4. **Cross-session test**: Create a memory, close the notebook, restart, and verify the memory persists."
    ]