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standardized port and also included pre-req for all notebooks

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Justin Lee 2024-11-05 16:38:46 -08:00
parent d0baf24999
commit b556cd91fd
8 changed files with 177 additions and 42 deletions
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23
docs/zero_to_hero_guide/06_Agents101.ipynb
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@ -21,7 +21,9 @@
"- ability to run safety checks using the Llama Guard series of models\n",
"- ability to execute tools, including a code execution environment, and loop using the model's multi-step reasoning process\n",
"\n",
"All of these components are now offered by a single Llama Stack Distribution. Llama Stack defines and standardizes these components and many others that are needed to make building Generative AI applications smoother. Various implementations of these APIs are then assembled together via a **Llama Stack Distribution**."
"All of these components are now offered by a single Llama Stack Distribution. Llama Stack defines and standardizes these components and many others that are needed to make building Generative AI applications smoother. Various implementations of these APIs are then assembled together via a **Llama Stack Distribution**.\n",
"\n",
"Before you begin, please ensure Llama Stack is installed and set up by following the [Getting Started Guide](https://llama-stack.readthedocs.io/en/latest/getting_started/index.html)."
]
},
{
@ -35,6 +37,23 @@
"In this tutorial, with the `Llama3.1-8B-Instruct` server running, we can use the following code to run a simple agent example:"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Set up your connection parameters:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"HOST = \"localhost\" # Replace with your host\n",
"PORT = 5001 # Replace with your port"
]
},
{
"cell_type": "code",
"execution_count": 14,
@ -99,7 +118,7 @@
"os.environ[\"BRAVE_SEARCH_API_KEY\"] = \"YOUR_SEARCH_API_KEY\"\n",
"\n",
"async def agent_example():\n",
" client = LlamaStackClient(base_url=\"http://localhost:5000\")\n",
" client = LlamaStackClient(base_url=\"http://{HOST}:{PORT}\")\n",
" models_response = client.models.list()\n",
" for model in models_response:\n",
" if model.identifier.endswith(\"Instruct\"):\n",