diff --git a/examples/streaming-tokens.ipynb b/examples/streaming-tokens.ipynb
index abefd51eb..bed3dbe4e 100644
--- a/examples/streaming-tokens.ipynb
+++ b/examples/streaming-tokens.ipynb
@@ -39,23 +39,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 26,
    "id": "af4ce0ba-7596-4e5f-8bf8-0b0bd6e62833",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.3.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.3.2\u001b[0m\n",
-      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "%%capture --no-stderr\n",
-    "%pip install --quiet -U langgraph langchain_openai"
+    "%pip install --quiet -U langgraph langchain_openai langsmith"
    ]
   },
   {
@@ -68,7 +58,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "id": "a372be6f",
    "metadata": {},
    "outputs": [],
@@ -95,7 +85,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
    "id": "907bf5e8",
    "metadata": {},
    "outputs": [],
@@ -124,7 +114,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 3,
    "id": "17ef4967",
    "metadata": {},
    "outputs": [],
@@ -157,7 +147,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 4,
    "id": "9a8bc61e",
    "metadata": {},
    "outputs": [],
@@ -186,7 +176,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 5,
    "id": "4d6ac180",
    "metadata": {},
    "outputs": [],
@@ -214,7 +204,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 6,
    "id": "42c0af37",
    "metadata": {},
    "outputs": [],
@@ -236,7 +226,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 7,
    "id": "2bbdd3bc",
    "metadata": {},
    "outputs": [],
@@ -283,24 +273,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 8,
    "id": "3b541bb9-900c-40d0-964d-7b5dfee30667",
    "metadata": {},
    "outputs": [],
    "source": [
+    "from langgraph.graph import StateGraph, END, START\n",
     "from langchain_core.runnables import RunnableConfig\n",
+    "from typing import Literal\n",
     "\n",
     "\n",
     "# Define the function that determines whether to continue or not\n",
-    "def should_continue(state: State):\n",
+    "def should_continue(state: State) -> Literal[\"__end__\", \"tools\"]:\n",
     "    messages = state[\"messages\"]\n",
     "    last_message = messages[-1]\n",
     "    # If there is no function call, then we finish\n",
     "    if not last_message.tool_calls:\n",
-    "        return \"end\"\n",
+    "        return END\n",
     "    # Otherwise if there is, we continue\n",
     "    else:\n",
-    "        return \"continue\"\n",
+    "        return \"tools\"\n",
     "\n",
     "\n",
     "# Define the function that calls the model\n",
@@ -308,7 +300,6 @@
     "    messages = state[\"messages\"]\n",
     "    # Note: Passing the config through explicitly is required for python < 3.11\n",
     "    # Since context var support wasn't added before then: https://docs.python.org/3/library/asyncio-task.html#creating-tasks\n",
-    "    # (1)\n",
     "    response = await model.ainvoke(messages, config)\n",
     "    # We return a list, because this will get added to the existing list\n",
     "    return {\"messages\": response}"
@@ -319,8 +310,6 @@
    "id": "ffd6e892-946c-4899-8cc0-7c9291c1f73b",
    "metadata": {},
    "source": [
-    "1.  :man_raising_hand: I'm a code annotation! I can contain `code`, __formatted\n",
-    "    text__, images, ... basically anything that can be written in Markdown.\n",
     "## Define the graph\n",
     "\n",
     "We can now put it all together and define the graph!"
@@ -328,23 +317,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 9,
    "id": "813ae66c-3b58-4283-a02a-36da72a2ab90",
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langgraph.graph import StateGraph, END\n",
-    "\n",
     "# Define a new graph\n",
     "workflow = StateGraph(State)\n",
     "\n",
     "# Define the two nodes we will cycle between\n",
     "workflow.add_node(\"agent\", call_model)\n",
-    "workflow.add_node(\"action\", tool_node)\n",
+    "workflow.add_node(\"tools\", tool_node)\n",
     "\n",
     "# Set the entrypoint as `agent`\n",
     "# This means that this node is the first one called\n",
-    "workflow.set_entry_point(\"agent\")\n",
+    "workflow.add_edge(START, \"agent\")\n",
     "\n",
     "# We now add a conditional edge\n",
     "workflow.add_conditional_edges(\n",
@@ -353,23 +340,9 @@
     "    \"agent\",\n",
     "    # Next, we pass in the function that will determine which node is called next.\n",
     "    should_continue,\n",
-    "    # Finally we pass in a mapping.\n",
-    "    # The keys are strings, and the values are other nodes.\n",
-    "    # END is a special node marking that the graph should finish.\n",
-    "    # What will happen is we will call `should_continue`, and then the output of that\n",
-    "    # will be matched against the keys in this mapping.\n",
-    "    # Based on which one it matches, that node will then be called.\n",
-    "    {\n",
-    "        # If `tools`, then we call the tool node.\n",
-    "        \"continue\": \"action\",\n",
-    "        # Otherwise we finish.\n",
-    "        \"end\": END,\n",
-    "    },\n",
     ")\n",
     "\n",
-    "# We now add a normal edge from `tools` to `agent`.\n",
-    "# This means that after `tools` is called, `agent` node is called next.\n",
-    "workflow.add_edge(\"action\", \"agent\")\n",
+    "workflow.add_edge(\"tools\", \"agent\")\n",
     "\n",
     "# Finally, we compile it!\n",
     "# This compiles it into a LangChain Runnable,\n",
@@ -379,13 +352,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 10,
    "id": "72785b66",
    "metadata": {},
    "outputs": [
     {
      "data": {
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",
       "text/plain": [
        "<IPython.core.display.Image object>"
       ]
@@ -415,10 +388,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 11,
    "id": "cfd140f0-a5a6-4697-8115-322242f197b5",
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/wfh/code/lc/langgraph/.venv/lib/python3.12/site-packages/langchain_core/_api/beta_decorator.py:87: LangChainBetaWarning: This API is in beta and may change in the future.\n",
+      "  warn_beta(\n"
+     ]
+    },
     {
      "name": "stdout",
      "output_type": "stream",
@@ -456,13 +437,84 @@
     "        print(\"--\")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "15c4bd28",
+   "metadata": {},
+   "source": [
+    "## Streaming arbitrary nested content\n",
+    "\n",
+    "The above example streams tokens from a chat model, but you may have other long-running streaming functions you wish to render for the user. While individual nodes in LangGraph cannot return generators (since they are executed to completion for each [superstep](https://langchain-ai.github.io/langgraph/concepts/#core-design)), we can still stream arbitrary custom functions from within a node using a similar tact and calling `astream_events` on the graph.\n",
+    "\n",
+    "We do so using a [RunnableGenerator](https://api.python.langchain.com/en/latest/runnables/langchain_core.runnables.base.RunnableGenerator.html#langchain-core-runnables-base-runnablegenerator) (which your function will automatically behave as if wrapped as a [RunnableLambda](https://api.python.langchain.com/en/latest/runnables/langchain_core.runnables.base.RunnableLambda.html#langchain_core.runnables.base.RunnableLambda)).\n",
+    "\n",
+    "Below is a simple toy example."
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "08ae8246-11d5-40e1-8567-361e5bef8917",
+   "execution_count": 15,
+   "id": "486a01a0",
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "from langgraph.graph import StateGraph, END, START\n",
+    "from langchain_core.runnables import RunnableGenerator\n",
+    "from langchain_core.messages import AIMessage\n",
+    "\n",
+    "# Define a new graph\n",
+    "workflow = StateGraph(State)\n",
+    "\n",
+    "async def my_generator(state: State):\n",
+    "    messages = [\"Four\", \"score\", \"and\", \"seven\", \"years\", \"ago\", \"our\", \"fathers\", \"...\"]\n",
+    "    for message in messages:\n",
+    "        yield message\n",
+    "\n",
+    "async def my_node(state: State, config: RunnableConfig):\n",
+    "    messages = []\n",
+    "    # Tagging a node makes it easy to filter out which events to include in your stream\n",
+    "    # It's completely optional, but useful if you have many functions with similar names\n",
+    "    gen = RunnableGenerator(my_generator).with_config(tags=[\"should_stream\"])\n",
+    "    async for message in gen.astream(state):\n",
+    "        messages.append(message)\n",
+    "    return {\"messages\": [AIMessage(content=\" \".join(messages))]}\n",
+    "\n",
+    "\n",
+    "workflow.add_node(\"model\", my_node)\n",
+    "workflow.add_edge(START, \"model\")\n",
+    "workflow.add_edge(\"model\", END)\n",
+    "app = workflow.compile()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "ce773a40",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'chunk': 'Four'}|{'chunk': 'score'}|{'chunk': 'and'}|{'chunk': 'seven'}|{'chunk': 'years'}|{'chunk': 'ago'}|{'chunk': 'our'}|{'chunk': 'fathers'}|{'chunk': '...'}|"
+     ]
+    }
+   ],
+   "source": [
+    "from langchain_core.messages import HumanMessage\n",
+    "\n",
+    "inputs = [HumanMessage(content=\"What are you thinking about?\")]\n",
+    "async for event in app.astream_events({\"messages\": inputs}, version=\"v1\"):\n",
+    "    kind = event[\"event\"]\n",
+    "    tags = event.get(\"tags\", [])\n",
+    "    if kind == \"on_chain_stream\" and \"should_stream\" in tags:\n",
+    "        data = event[\"data\"]\n",
+    "        if data:\n",
+    "            # Empty content in the context of OpenAI or Anthropic usually means\n",
+    "            # that the model is asking for a tool to be invoked.\n",
+    "            # So we only print non-empty content\n",
+    "            print(data, end=\"|\")"
+   ]
   }
  ],
  "metadata": {
@@ -481,7 +533,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.11"
+   "version": "3.12.2"
   }
  },
  "nbformat": 4,