ntbk updates

cookbook/structured_report_generation.ipynb

@@ -104,8 +104,7 @@
     "\n",
     "Save these API Keys as environment variables.\n",
     "\n",
-    "First, set the NVIDIA API Key as the environment variable and then define the LLM. \n",
-    "In this tutorial we use the newest llama model, but you can browse through all available models on the NVIDIA API Catalog."
+    "First, set the NVIDIA API Key as the environment variable."
    ]
   },
   {
@@ -122,13 +121,7 @@
     "if not os.environ.get(\"NVIDIA_API_KEY\", \"\").startswith(\"nvapi-\"):\n",
     "    nvapi_key = getpass.getpass(\"Enter your NVIDIA API key: \")\n",
     "    assert nvapi_key.startswith(\"nvapi-\"), f\"{nvapi_key[:5]}... is not a valid key\"\n",
-    "    os.environ[\"NVIDIA_API_KEY\"] = nvapi_key\n",
-    "\n",
-    "from langchain_nvidia_ai_endpoints import ChatNVIDIA\n",
-    "tool_models = [model for model in ChatNVIDIA.get_available_models() if model.supports_tools]\n",
-    "print(\"NVDA tool models:\")\n",
-    "print(tool_models)\n",
-    "llm = ChatNVIDIA(model=\"meta/llama-3.3-70b-instruct\", temperature=0)"
+    "    os.environ[\"NVIDIA_API_KEY\"] = nvapi_key"
    ]
   },
   {
@@ -192,7 +185,9 @@
    "source": [
     "### Working with the NVIDIA API Catalog\n",
     "\n",
-    "Let's test the API endpoint of the model chosen earlier."
+    "Let's test the API endpoint.\n",
+    "\n",
+    "In this notebook, you will use the newest llama model, llama-3.3-70b-instruct, as the LLM. Define the LLM below and test the API Catalog.\n"
    ]
   },
   {