minor langsmith notebook fixes (#7814)

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docs/extras/guides/langsmith/walkthrough.ipynb

@@ -47,13 +47,23 @@
     "## Log runs to LangSmith\n",
     "\n",
     "First, configure your environment variables to tell LangChain to log traces. This is done by setting the `LANGCHAIN_TRACING_V2` environment variable to true.\n",
-    "You can tell LangChain which project to log to by setting the `LANGCHAIN_PROJECT` environment variable (if this isn't set, runs will be logged to the `default` project). This will automatically create the project for you if it doesn't exiust. You must also set the `LANGCHAIN_ENDPOINT` and `LANGCHAIN_API_KEY` environment variables.\n",
+    "You can tell LangChain which project to log to by setting the `LANGCHAIN_PROJECT` environment variable (if this isn't set, runs will be logged to the `default` project). This will automatically create the project for you if it doesn't exist. You must also set the `LANGCHAIN_ENDPOINT` and `LANGCHAIN_API_KEY` environment variables.\n",
     "\n",
     "For more information on other ways to set up tracing, please reference the [LangSmith documentation](https://docs.smith.langchain.com/docs/)\n",
     "\n",
     "**NOTE:** You must also set your `OPENAI_API_KEY` and `SERPAPI_API_KEY` environment variables in order to run the following tutorial.\n",
     "\n",
-    "**NOTE:** You can only access an API key when you first create it. Keep it somewhere safe."
+    "**NOTE:** You can only access an API key when you first create it. Keep it somewhere safe.\n",
+    "\n",
+    "**NOTE:** You can also use a context manager in python to log traces using\n",
+    "```python\n",
+    "from langchain.callbacks.manager import tracing_v2_enabled\n",
+    "\n",
+    "with tracing_v2_enabled(project_name=\"My Project\"):\n",
+    "    agent.run(\"How many people live in canada as of 2023?\")\n",
+    "```\n",
+    "\n",
+    "However, in this example, we will use environment variables."
    ]
   },
   {
@@ -229,7 +239,7 @@
    "source": [
     "### 1. Create a LangSmith dataset\n",
     "\n",
-    "Below, we use the LangSmith client to create a dataset from the agent runs you just logged above. You will use these later to measure performance for a new agent. This simple taking the inputs and outputs of the runs and saving them as examples to a dataset. A dataset is a collection of examples, which are nothing more than input-output pairs you can use as test cases to your application.\n",
+    "Below, we use the LangSmith client to create a dataset from the agent runs you just logged above. You will use these later to measure performance for a new agent. This is simply taking the inputs and outputs of the runs and saving them as examples to a dataset. A dataset is a collection of examples, which are nothing more than input-output pairs you can use as test cases to your application.\n",
     "\n",
     "**Note: this is a simple, walkthrough example. In a real-world setting, you'd ideally first validate the outputs before adding them to a benchmark dataset to be used for evaluating other agents.**\n",
     "\n",