Update notebooks to use MemoryAPIClient directly (partial)

abrookins · abrookins · commit 4e1c4c248eff · 2025-09-30T21:06:05.000-07:00
- Updated imports to use agent_memory_client
- Fixed get_or_create_working_memory to unpack tuple
- Fixed search_long_term_memory parameter (text= instead of query=)
- Added script to automate notebook fixes

Note: Some notebooks still need manual fixes for save_working_memory
calls which need to be converted to put_working_memory with
WorkingMemory objects. This will be done in follow-up commits.
diff --git a/python-recipes/context-engineering/notebooks/section-3-memory/01_working_memory_with_extraction_strategies.ipynb b/python-recipes/context-engineering/notebooks/section-3-memory/01_working_memory_with_extraction_strategies.ipynb
@@ -182,7 +182,7 @@
       "outputs": [],
       "source": [
         "# Simulate a conversation using working memory\n",
-        "from redis_context_course import MemoryClient, MemoryClientConfig\n",
+        "from agent_memory_client import MemoryAPIClient as MemoryClient, MemoryClientConfig\n",
         "\n",
         "# Ensure memory_client and session_id are defined (in case cells are run out of order)\n",
         "if 'memory_client' not in globals():\n",
@@ -220,7 +220,7 @@
         "print(\"like preferences and goals to long-term memory.\")\n",
         "\n",
         "# Retrieve working memory\n",
-        "working_memory = await memory_client.get_or_create_working_memory(\n",
+        "_, working_memory = await memory_client.get_or_create_working_memory(\n",
         "    session_id=session_id,\n",
         "    model_name=\"gpt-4o\"\n",
         ")\n",
@@ -292,7 +292,7 @@
       "source": [
         "# Check what was extracted to long-term memory\n",
         "import asyncio\n",
-        "from redis_context_course import MemoryClient, MemoryClientConfig\n",
+        "from agent_memory_client import MemoryAPIClient as MemoryClient, MemoryClientConfig\n",
         "\n",
         "# Ensure memory_client is defined (in case cells are run out of order)\n",
         "if 'memory_client' not in globals():\n",
@@ -307,15 +307,15 @@
         "await asyncio.sleep(2)  # Give the extraction process time to complete\n",
         "\n",
         "# Search for extracted memories\n",
-        "extracted_memories = await memory_client.search_memories(\n",
+        "extracted_memories = await memory_client.search_long_term_memory(\n",
         "    query=\"preferences goals\",\n",
         "    limit=10\n",
         ")\n",
         "\n",
         "print(\"🧠 Extracted to Long-term Memory\")\n",
         "print(\"=\" * 50)\n",
         "\n",
-        "if extracted_memories:\n",
+        "if extracted_memories.memories:\n",
         "    for i, memory in enumerate(extracted_memories, 1):\n",
         "        print(f\"{i}. {memory.text}\")\n",
         "        print(f\"   Type: {memory.memory_type} | Topics: {', '.join(memory.topics)}\")\n",
diff --git a/python-recipes/context-engineering/notebooks/section-3-memory/02_long_term_memory.ipynb b/python-recipes/context-engineering/notebooks/section-3-memory/02_long_term_memory.ipynb
@@ -104,7 +104,7 @@
         "import os\n",
         "import asyncio\n",
         "from datetime import datetime\n",
-        "from redis_context_course import MemoryClient, MemoryClientConfig\n",
+        "from agent_memory_client import MemoryAPIClient as MemoryClient, MemoryClientConfig\n",
         "\n",
         "# Initialize memory client\n",
         "student_id = \"student_123\"\n",
@@ -226,7 +226,7 @@
       "source": [
         "# Search for preferences\n",
         "print(\"Query: 'What does the student prefer?'\\n\")\n",
-        "results = await memory_client.search_memories(\n",
+        "results = await memory_client.search_long_term_memory(\n",
         "    query=\"What does the student prefer?\",\n",
         "    limit=3\n",
         ")\n",
@@ -245,7 +245,7 @@
       "source": [
         "# Search for academic information\n",
         "print(\"Query: 'What is the student studying?'\\n\")\n",
-        "results = await memory_client.search_memories(\n",
+        "results = await memory_client.search_long_term_memory(\n",
         "    query=\"What is the student studying?\",\n",
         "    limit=3\n",
         ")\n",
@@ -264,7 +264,7 @@
       "source": [
         "# Search for course history\n",
         "print(\"Query: 'What courses has the student taken?'\\n\")\n",
-        "results = await memory_client.search_memories(\n",
+        "results = await memory_client.search_long_term_memory(\n",
         "    query=\"What courses has the student taken?\",\n",
         "    limit=3\n",
         ")\n",
@@ -368,7 +368,7 @@
       "source": [
         "# Get all semantic memories\n",
         "print(\"All semantic memories (facts):\\n\")\n",
-        "results = await memory_client.search_memories(\n",
+        "results = await memory_client.search_long_term_memory(\n",
         "    query=\"\",  # Empty query returns all\n",
         "    memory_types=\"semantic\",\n",
         "    limit=10\n",
@@ -388,7 +388,7 @@
       "source": [
         "# Get all episodic memories\n",
         "print(\"All episodic memories (events):\\n\")\n",
-        "results = await memory_client.search_memories(\n",
+        "results = await memory_client.search_long_term_memory(\n",
         "    query=\"\",\n",
         "    memory_types=\"episodic\",\n",
         "    limit=10\n",
diff --git a/python-recipes/context-engineering/notebooks/section-3-memory/03_memory_integration.ipynb b/python-recipes/context-engineering/notebooks/section-3-memory/03_memory_integration.ipynb
@@ -113,7 +113,7 @@
         "from datetime import datetime\n",
         "from langchain_openai import ChatOpenAI\n",
         "from langchain_core.messages import SystemMessage, HumanMessage, AIMessage\n",
-        "from redis_context_course import MemoryClient, MemoryClientConfig\n",
+        "from agent_memory_client import MemoryAPIClient as MemoryClient, MemoryClientConfig\n",
         "\n",
         "# Initialize\n",
         "student_id = \"student_456\"\n",
@@ -161,7 +161,7 @@
         "\n",
         "# Step 1: Load working memory (empty for first turn)\n",
         "print(\"\\n1. Loading working memory...\")\n",
-        "working_memory = await memory_client.get_or_create_working_memory(\n",
+        "_, working_memory = await memory_client.get_or_create_working_memory(\n",
         "    session_id=session_id_1,\n",
         "    model_name=\"gpt-4o\"\n",
         ")\n",
@@ -170,7 +170,7 @@
         "# Step 2: Search long-term memory (empty for first interaction)\n",
         "print(\"\\n2. Searching long-term memory...\")\n",
         "user_query = \"Hi! I'm interested in learning about databases.\"\n",
-        "long_term_memories = await memory_client.search_memories(\n",
+        "long_term_memories = await memory_client.search_long_term_memory(\n",
         "    query=user_query,\n",
         "    limit=3\n",
         ")\n",
@@ -220,7 +220,7 @@
         "\n",
         "# Step 1: Load working memory (now has Turn 1)\n",
         "print(\"\\n1. Loading working memory...\")\n",
-        "working_memory = await memory_client.get_or_create_working_memory(\n",
+        "_, working_memory = await memory_client.get_or_create_working_memory(\n",
         "    session_id=session_id_1,\n",
         "    model_name=\"gpt-4o\"\n",
         ")\n",
@@ -230,7 +230,7 @@
         "# Step 2: Search long-term memory\n",
         "print(\"\\n2. Searching long-term memory...\")\n",
         "user_query_2 = \"I prefer online courses and morning classes.\"\n",
-        "long_term_memories = await memory_client.search_memories(\n",
+        "long_term_memories = await memory_client.search_long_term_memory(\n",
         "    query=user_query_2,\n",
         "    limit=3\n",
         ")\n",
@@ -296,7 +296,7 @@
         "\n",
         "# Search for extracted memories\n",
         "print(\"\\nSearching for extracted memories...\\n\")\n",
-        "memories = await memory_client.search_memories(\n",
+        "memories = await memory_client.search_long_term_memory(\n",
         "    query=\"student preferences\",\n",
         "    limit=5\n",
         ")\n",
@@ -332,7 +332,7 @@
         "\n",
         "# Step 1: Load working memory (empty - new session)\n",
         "print(\"\\n1. Loading working memory...\")\n",
-        "working_memory = await memory_client.get_or_create_working_memory(\n",
+        "_, working_memory = await memory_client.get_or_create_working_memory(\n",
         "    session_id=session_id_2,\n",
         "    model_name=\"gpt-4o\"\n",
         ")\n",
@@ -342,7 +342,7 @@
         "# Step 2: Search long-term memory (has data from Session 1)\n",
         "print(\"\\n2. Searching long-term memory...\")\n",
         "user_query_3 = \"What database courses do you recommend for me?\"\n",
-        "long_term_memories = await memory_client.search_memories(\n",
+        "long_term_memories = await memory_client.search_long_term_memory(\n",
         "    query=user_query_3,\n",
         "    limit=5\n",
         ")\n",
@@ -404,16 +404,16 @@
         "\n",
         "# Check all memories about the student\n",
         "print(\"\\nAll memories about this student:\\n\")\n",
-        "all_memories = await memory_client.search_memories(\n",
+        "all_memories = await memory_client.search_long_term_memory(\n",
         "    query=\"\",  # Empty query returns all\n",
         "    limit=20\n",
         ")\n",
         "\n",
-        "semantic_memories = [m for m in all_memories if m.memory_type == \"semantic\"]\n",
-        "episodic_memories = [m for m in all_memories if m.memory_type == \"episodic\"]\n",
+        "semantic_memories = [m for m in all_memories if m.memory_type == \"semantic\"].memories\n",
+        "episodic_memories = [m for m in all_memories if m.memory_type == \"episodic\"].memories\n",
         "\n",
         "print(f\"Semantic memories (facts): {len(semantic_memories)}\")\n",
-        "for memory in semantic_memories:\n",
+        "for memory in semantic_memories.memories:\n",
         "    print(f\"  - {memory.text}\")\n",
         "\n",
         "print(f\"\\nEpisodic memories (events): {len(episodic_memories)}\")\n",
diff --git a/python-recipes/context-engineering/notebooks/section-3-memory/04_memory_tools.ipynb b/python-recipes/context-engineering/notebooks/section-3-memory/04_memory_tools.ipynb
@@ -127,7 +127,7 @@
         "from langchain_core.tools import tool\n",
         "from pydantic import BaseModel, Field\n",
         "from typing import List, Optional\n",
-        "from redis_context_course import MemoryClient, MemoryClientConfig\n",
+        "from agent_memory_client import MemoryAPIClient as MemoryClient, MemoryClientConfig\n",
         "\n",
         "# Initialize\n",
         "student_id = \"student_memory_tools\"\n",
@@ -248,7 +248,7 @@
         "    - query=\"goals\" → finds student's stated goals\n",
         "    \"\"\"\n",
         "    try:\n",
-        "        memories = await memory_client.search_memories(\n",
+        "        memories = await memory_client.search_long_term_memory(\n",
         "            query=query,\n",
         "            limit=limit\n",
         "        )\n",
diff --git a/python-recipes/context-engineering/notebooks/section-4-optimizations/01_context_window_management.ipynb b/python-recipes/context-engineering/notebooks/section-4-optimizations/01_context_window_management.ipynb
@@ -124,7 +124,7 @@
         "import tiktoken\n",
         "from langchain_openai import ChatOpenAI\n",
         "from langchain_core.messages import SystemMessage, HumanMessage, AIMessage\n",
-        "from redis_context_course import MemoryClient, MemoryClientConfig\n",
+        "from agent_memory_client import MemoryAPIClient as MemoryClient, MemoryClientConfig\n",
         "\n",
         "# Initialize\n",
         "student_id = \"student_context_demo\"\n",
@@ -301,7 +301,7 @@
         "async def have_conversation_turn(user_message, session_id):\n",
         "    \"\"\"Simulate a conversation turn.\"\"\"\n",
         "    # Get working memory\n",
-        "    working_memory = await memory_client.get_or_create_working_memory(\n",
+        "    _, working_memory = await memory_client.get_or_create_working_memory(\n",
         "        session_id=session_id,\n",
         "        model_name=\"gpt-4o\"\n",
         "    )\n",
@@ -401,7 +401,7 @@
         "# Check working memory state\n",
         "print(\"\\nChecking working memory state...\\n\")\n",
         "\n",
-        "working_memory = await memory_client.get_or_create_working_memory(\n",
+        "_, working_memory = await memory_client.get_or_create_working_memory(\n",
         "    session_id=session_id,\n",
         "    model_name=\"gpt-4o\"\n",
         ")\n",
diff --git a/python-recipes/context-engineering/notebooks/section-4-optimizations/03_grounding_with_memory.ipynb b/python-recipes/context-engineering/notebooks/section-4-optimizations/03_grounding_with_memory.ipynb
@@ -105,7 +105,7 @@
         "import asyncio\n",
         "from langchain_openai import ChatOpenAI\n",
         "from langchain_core.messages import SystemMessage, HumanMessage, AIMessage\n",
-        "from redis_context_course import MemoryClient, MemoryClientConfig\n",
+        "from agent_memory_client import MemoryAPIClient as MemoryClient, MemoryClientConfig\n",
         "\n",
         "# Initialize\n",
         "student_id = \"student_789\"\n",
@@ -150,13 +150,13 @@
         "    \"\"\"Helper function to process a conversation turn.\"\"\"\n",
         "    \n",
         "    # Search long-term memory for context\n",
-        "    memories = await memory_client.search_memories(\n",
+        "    memories = await memory_client.search_long_term_memory(\n",
         "        query=user_message,\n",
         "        limit=5\n",
         "    )\n",
         "    \n",
         "    # Build context from memories\n",
-        "    memory_context = \"\\n\".join([f\"- {m.text}\" for m in memories]) if memories else \"None\"\n",
+        "    memory_context = \"\\n\".join([f\"- {m.text}\" for m in memories]) if memories else \"None\".memories\n",
         "    \n",
         "    system_prompt = f\"\"\"You are a helpful class scheduling agent for Redis University.\n",
         "\n",
@@ -409,13 +409,13 @@
         "print(\"=\" * 80)\n",
         "\n",
         "# Get all memories\n",
-        "all_memories = await memory_client.search_memories(\n",
+        "all_memories = await memory_client.search_long_term_memory(\n",
         "    query=\"\",\n",
         "    limit=20\n",
         ")\n",
         "\n",
         "print(\"\\nMemories that enable grounding:\\n\")\n",
-        "for i, memory in enumerate(all_memories, 1):\n",
+        "for i, memory in enumerate(all_memories, 1).memories:\n",
         "    print(f\"{i}. {memory.text}\")\n",
         "    print(f\"   Type: {memory.memory_type} | Topics: {', '.join(memory.topics)}\")\n",
         "    print()\n",
diff --git a/python-recipes/context-engineering/notebooks/section-4-optimizations/05_crafting_data_for_llms.ipynb b/python-recipes/context-engineering/notebooks/section-4-optimizations/05_crafting_data_for_llms.ipynb
@@ -437,7 +437,7 @@
         "}\n",
         "\n",
         "# Get memories\n",
-        "memories = await memory_client.search_memories(\n",
+        "memories = await memory_client.search_long_term_memory(\n",
         "    query=\"\",  # Get all\n",
         "    limit=20\n",
         ")\n",
diff --git a/python-recipes/context-engineering/scripts/fix_notebooks_api.py b/python-recipes/context-engineering/scripts/fix_notebooks_api.py
