docs: more notebook examples

Author: bsbodden

langgraph/docs/create-react-agent-memory.ipynb

@@ -58,7 +58,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 9,
    "id": "a213e11a-5c62-4ddb-a707-490d91add383",
    "metadata": {},
    "outputs": [],
@@ -69,18 +69,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 10,
    "id": "23a1885c-04ab-4750-aefa-105891fddf3e",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdin",
-     "output_type": "stream",
-     "text": [
-      "OPENAI_API_KEY:  ········\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "import getpass\n",
     "import os\n",
@@ -117,35 +109,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 11,
    "id": "7a154152-973e-4b5d-aa13-48c617744a4c",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "22:31:51 redisvl.index.index INFO   Index already exists, not overwriting.\n",
-      "22:31:51 redisvl.index.index INFO   Index already exists, not overwriting.\n",
-      "22:31:51 redisvl.index.index INFO   Index already exists, not overwriting.\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
-    "from typing import Literal\n",
-    "\n",
-    "from langchain_core.tools import tool\n",
-    "\n",
     "# First we initialize the model we want to use.\n",
     "from langchain_openai import ChatOpenAI\n",
     "\n",
-    "from langgraph.checkpoint.redis import RedisSaver\n",
-    "from langgraph.prebuilt import create_react_agent\n",
-    "\n",
     "model = ChatOpenAI(model=\"gpt-4o\", temperature=0)\n",
     "\n",
     "\n",
     "# For this tutorial we will use custom tool that returns pre-defined values for weather in two cities (NYC & SF)\n",
+    "\n",
+    "from typing import Literal\n",
+    "\n",
+    "from langchain_core.tools import tool\n",
+    "\n",
+    "\n",
     "@tool\n",
     "def get_weather(city: Literal[\"nyc\", \"sf\"]):\n",
     "    \"\"\"Use this to get weather information.\"\"\"\n",
@@ -159,18 +140,19 @@
     "\n",
     "tools = [get_weather]\n",
     "\n",
-    "# We can add \"chat memory\" to the graph with LangGraph's Redis checkpointer\n",
+    "# We can add \"chat memory\" to the graph with LangGraph's Redi checkpointer\n",
     "# to retain the chat context between interactions\n",
-    "\n",
+    "from langgraph.checkpoint.redis import RedisSaver\n",
     "\n",
     "REDIS_URI = \"redis://redis:6379\"\n",
     "memory = None\n",
     "with RedisSaver.from_conn_string(REDIS_URI) as cp:\n",
-    "    cp.setup()\n",
-    "    memory = cp\n",
+    "  cp.setup()\n",
+    "  memory = cp\n",
     "\n",
     "# Define the graph\n",
     "\n",
+    "from langgraph.prebuilt import create_react_agent\n",
     "\n",
     "graph = create_react_agent(model, tools=tools, checkpointer=memory)"
    ]
@@ -187,7 +169,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 12,
    "id": "16636975-5f2d-4dc7-ab8e-d0bea0830a28",
    "metadata": {},
    "outputs": [],
@@ -203,7 +185,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 13,
    "id": "9ffff6c3-a4f5-47c9-b51d-97caaee85cd6",
    "metadata": {},
    "outputs": [
@@ -216,8 +198,8 @@
       "What's the weather in NYC?\n",
       "==================================\u001b[1m Ai Message \u001b[0m==================================\n",
       "Tool Calls:\n",
-      "  get_weather (call_Edwfw0WiyIJ7vt9xzU9xvyeg)\n",
-      " Call ID: call_Edwfw0WiyIJ7vt9xzU9xvyeg\n",
+      "  get_weather (call_RHv6T6OBCn7eKOlm5qEpLK4P)\n",
+      " Call ID: call_RHv6T6OBCn7eKOlm5qEpLK4P\n",
       "  Args:\n",
       "    city: nyc\n",
       "=================================\u001b[1m Tool Message \u001b[0m=================================\n",
@@ -247,7 +229,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 14,
    "id": "187479f9-32fa-4611-9487-cf816ba2e147",
    "metadata": {},
    "outputs": [
@@ -260,7 +242,7 @@
       "What's it known for?\n",
       "==================================\u001b[1m Ai Message \u001b[0m==================================\n",
       "\n",
-      "Could you please specify what \"it\" refers to? Are you asking about a specific city, person, event, or something else?\n"
+      "Could you please specify what \"it\" refers to? Are you asking about a specific place, person, event, or something else?\n"
      ]
     }
    ],