Fix ALL remaining query= to text= in notebooks

Fixed 6 notebooks that still had query= instead of text= in
search_long_term_memory calls:
- section-3-memory/01_working_memory_with_extraction_strategies.ipynb
- section-3-memory/03_memory_integration.ipynb
- section-3-memory/04_memory_tools.ipynb
- section-4-optimizations/01_context_window_management.ipynb
- section-4-optimizations/03_grounding_with_memory.ipynb
- section-4-optimizations/05_crafting_data_for_llms.ipynb

Also fixed WorkingMemory and MemoryMessage imports to use
agent_memory_client.models

Author: abrookins

python-recipes/context-engineering/notebooks/section-3-memory/01_working_memory_with_extraction_strategies.ipynb

@@ -209,7 +209,7 @@
         "]\n",
         "\n",
         "# Save to working memory\n",
-        "from agent_memory_client import WorkingMemory, MemoryMessage\n",
+        "from agent_memory_client.models import WorkingMemory, MemoryMessage\n",
         "\n",
         "# Convert messages to MemoryMessage format\n",
         "memory_messages = [MemoryMessage(**msg) for msg in messages]\n",
@@ -324,7 +324,7 @@
         "\n",
         "# Search for extracted memories\n",
         "extracted_memories = await memory_client.search_long_term_memory(\n",
-        "    query=\"preferences goals\",\n",
+        "    text=\"preferences goals\",\n",
         "    limit=10\n",
         ")\n",
         "\n",

python-recipes/context-engineering/notebooks/section-3-memory/03_memory_integration.ipynb

@@ -171,7 +171,7 @@
         "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_long_term_memory(\n",
-        "    query=user_query,\n",
+        "    text=user_query,\n",
         "    limit=3\n",
         ")\n",
         "print(f\"   Relevant memories found: {len(long_term_memories)}\")\n",
@@ -188,7 +188,7 @@
         "\n",
         "# Step 4: Save working memory\n",
         "print(\"\\n4. Saving working memory...\")\n",
-        "from agent_memory_client import WorkingMemory, MemoryMessage\n",
+        "from agent_memory_client.models import WorkingMemory, MemoryMessage\n",
         "\n",
         "# Convert messages to MemoryMessage format\n",
         "memory_messages = [MemoryMessage(**msg) for msg in []\n",
@@ -244,7 +244,7 @@
         "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_long_term_memory(\n",
-        "    query=user_query_2,\n",
+        "    text=user_query_2,\n",
         "    limit=3\n",
         ")\n",
         "print(f\"   Relevant memories found: {len(long_term_memories)}\")\n",
@@ -280,7 +280,7 @@
         "    {\"role\": \"assistant\", \"content\": response.content}\n",
         "])\n",
         "\n",
-        "from agent_memory_client import WorkingMemory, MemoryMessage\n",
+        "from agent_memory_client.models import WorkingMemory, MemoryMessage\n",
         "\n",
         "# Convert messages to MemoryMessage format\n",
         "memory_messages = [MemoryMessage(**msg) for msg in all_messages]\n",
@@ -326,7 +326,7 @@
         "# Search for extracted memories\n",
         "print(\"\\nSearching for extracted memories...\\n\")\n",
         "memories = await memory_client.search_long_term_memory(\n",
-        "    query=\"student preferences\",\n",
+        "    text=\"student preferences\",\n",
         "    limit=5\n",
         ")\n",
         "\n",
@@ -372,7 +372,7 @@
         "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_long_term_memory(\n",
-        "    query=user_query_3,\n",
+        "    text=user_query_3,\n",
         "    limit=5\n",
         ")\n",
         "print(f\"   Relevant memories found: {len(long_term_memories)}\")\n",
@@ -402,7 +402,7 @@
         "\n",
         "# Step 4: Save working memory\n",
         "print(\"\\n4. Saving working memory...\")\n",
-        "from agent_memory_client import WorkingMemory, MemoryMessage\n",
+        "from agent_memory_client.models import WorkingMemory, MemoryMessage\n",
         "\n",
         "# Convert messages to MemoryMessage format\n",
         "memory_messages = [MemoryMessage(**msg) for msg in []\n",
@@ -447,7 +447,7 @@
         "# Check all memories about the student\n",
         "print(\"\\nAll memories about this student:\\n\")\n",
         "all_memories = await memory_client.search_long_term_memory(\n",
-        "    query=\"\",  # Empty query returns all\n",
+        "    text=\"\",  # Empty query returns all\n",
         "    limit=20\n",
         ")\n",
         "\n",

python-recipes/context-engineering/notebooks/section-3-memory/04_memory_tools.ipynb

@@ -249,7 +249,7 @@
         "    \"\"\"\n",
         "    try:\n",
         "        memories = await memory_client.search_long_term_memory(\n",
-        "            query=query,\n",
+        "            text=query,\n",
         "            limit=limit\n",
         "        )\n",
         "        \n",

python-recipes/context-engineering/notebooks/section-4-optimizations/01_context_window_management.ipynb

@@ -331,7 +331,7 @@
         "        {\"role\": \"assistant\", \"content\": response.content}\n",
         "    ])\n",
         "    \n",
-        "    from agent_memory_client import WorkingMemory, MemoryMessage\n",
+        "    from agent_memory_client.models import WorkingMemory, MemoryMessage\n",
         "    \n",
         "    # Convert messages to MemoryMessage format\n",
         "    memory_messages = [MemoryMessage(**msg) for msg in all_messages]\n",

python-recipes/context-engineering/notebooks/section-4-optimizations/03_grounding_with_memory.ipynb

@@ -151,7 +151,7 @@
         "    \n",
         "    # Search long-term memory for context\n",
         "    memories = await memory_client.search_long_term_memory(\n",
-        "        query=user_message,\n",
+        "        text=user_message,\n",
         "        limit=5\n",
         "    )\n",
         "    \n",
@@ -183,7 +183,7 @@
         "        {\"role\": \"user\" if isinstance(m, HumanMessage) else \"assistant\", \"content\": m.content}\n",
         "        for m in conversation_history\n",
         "    ]\n",
-        "    from agent_memory_client import WorkingMemory, MemoryMessage\n",
+        "    from agent_memory_client.models import WorkingMemory, MemoryMessage\n",
         "    \n",
         "    # Convert messages to MemoryMessage format\n",
         "    memory_messages = [MemoryMessage(**msg) for msg in messages_to_save]\n",
@@ -426,7 +426,7 @@
         "\n",
         "# Get all memories\n",
         "all_memories = await memory_client.search_long_term_memory(\n",
-        "    query=\"\",\n",
+        "    text=\"\",\n",
         "    limit=20\n",
         ")\n",
         "\n",

python-recipes/context-engineering/notebooks/section-4-optimizations/05_crafting_data_for_llms.ipynb

@@ -438,7 +438,7 @@
         "\n",
         "# Get memories\n",
         "memories = await memory_client.search_long_term_memory(\n",
-        "    query=\"\",  # Get all\n",
+        "    text=\"\",  # Get all\n",
         "    limit=20\n",
         ")\n",
         "\n",

python-recipes/context-engineering/scripts/fix_all_query_params.py

@@ -0,0 +1,63 @@
+#!/usr/bin/env python3
+"""
+Fix all query= to text= in search_long_term_memory calls across all notebooks.
+Also fix missing imports.
+"""
+
+import json
+import glob
+from pathlib import Path
+
+
+def fix_notebook(notebook_path):
+    """Fix a single notebook."""
+    with open(notebook_path, 'r') as f:
+        nb = json.load(f)
+    
+    modified = False
+    for cell in nb['cells']:
+        if cell['cell_type'] == 'code':
+            new_source = []
+            for line in cell['source']:
+                original = line
+                # Fix query= to text= in search_long_term_memory calls
+                if 'search_long_term_memory' in line or (len(new_source) > 0 and 'search_long_term_memory' in ''.join(new_source[-3:])):
+                    line = line.replace('query=', 'text=')
+                
+                # Fix missing imports
+                if 'from agent_memory_client import WorkingMemory' in line:
+                    line = line.replace('from agent_memory_client import WorkingMemory', 'from agent_memory_client.models import WorkingMemory')
+                if 'from agent_memory_client import MemoryMessage' in line:
+                    line = line.replace('from agent_memory_client import MemoryMessage', 'from agent_memory_client.models import MemoryMessage')
+                
+                new_source.append(line)
+                if line != original:
+                    modified = True
+            cell['source'] = new_source
+    
+    if modified:
+        with open(notebook_path, 'w') as f:
+            json.dump(nb, f, indent=2, ensure_ascii=False)
+            f.write('\n')
+        return True
+    return False
+
+
+def main():
+    notebooks_dir = Path(__file__).parent.parent / 'notebooks'
+    
+    fixed_count = 0
+    for notebook_path in notebooks_dir.glob('**/*.ipynb'):
+        if '.ipynb_checkpoints' in str(notebook_path):
+            continue
+        
+        if fix_notebook(notebook_path):
+            print(f"Fixed: {notebook_path.relative_to(notebooks_dir)}")
+            fixed_count += 1
+    
+    print(f"\nFixed {fixed_count} notebooks")
+
+
+if __name__ == '__main__':
+    main()
+