"[](https://colab.research.google.com/github/aurelio-labs/semantic-router/blob/main/docs/00-introduction.ipynb) [](https://nbviewer.org/github/aurelio-labs/semantic-router/blob/main/docs/00-introduction.ipynb)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Semantic Router Intro"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The Semantic Router library can be used as a super fast route making layer on top of LLMs. That means rather than waiting on a slow agent to decide what to do, we can use the magic of semantic vector space to make routes. Cutting route making time down from seconds to milliseconds."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Getting Started"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We start by installing the library:"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"!pip install -qU semantic-router"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We start by defining a dictionary mapping routes to example phrases that should trigger those routes."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
"cells": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"c:\\Users\\Siraj\\Documents\\Personal\\Work\\Aurelio\\Virtual Environments\\semantic_router_3\\Lib\\site-packages\\tqdm\\auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
" from .autonotebook import tqdm as notebook_tqdm\n"
]
}
],
"source": [
"from semantic_router import Route\n",
"\n",
"politics = Route(\n",
" name=\"politics\",\n",
" utterances=[\n",
" \"isn't politics the best thing ever\",\n",
" \"why don't you tell me about your political opinions\",\n",
"# os.environ[\"COHERE_API_KEY\"] = os.getenv(\"COHERE_API_KEY\") or getpass(\n",
"# \"Enter Cohere API Key: \"\n",
"# )\n",
"os.environ[\"OPENAI_API_KEY\"] = os.getenv(\"OPENAI_API_KEY\") or getpass(\n",
" \"Enter OpenAI API Key: \"\n",
")\n",
"\n",
"# encoder = CohereEncoder()\n",
"encoder = OpenAIEncoder()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now we define the `RouteLayer`. When called, the route layer will consume text (a query) and output the category (`Route`) it belongs to — to initialize a `RouteLayer` we need our `encoder` model and a list of `routes`."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
"cell_type": "markdown",
"metadata": {
"id": "K7NsuSPNf3px"
},
"source": [
"[](https://colab.research.google.com/github/aurelio-labs/semantic-router/blob/main/docs/00-introduction.ipynb) [](https://nbviewer.org/github/aurelio-labs/semantic-router/blob/main/docs/00-introduction.ipynb)"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\u001b[32m2024-05-07 15:02:46 INFO semantic_router.utils.logger local\u001b[0m\n"
"The Semantic Router library can be used as a super fast route making layer on top of LLMs. That means rather than waiting on a slow agent to decide what to do, we can use the magic of semantic vector space to make routes. Cutting route making time down from seconds to milliseconds."
"c:\\Users\\Siraj\\Documents\\Personal\\Work\\Aurelio\\Virtual Environments\\semantic_router_3\\Lib\\site-packages\\tqdm\\auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
" from .autonotebook import tqdm as notebook_tqdm\n"
]
}
],
"source": [
"from semantic_router import Route\n",
"\n",
"politics = Route(\n",
" name=\"politics\",\n",
" utterances=[\n",
" \"isn't politics the best thing ever\",\n",
" \"why don't you tell me about your political opinions\",\n",
"# os.environ[\"COHERE_API_KEY\"] = os.getenv(\"COHERE_API_KEY\") or getpass(\n",
"# \"Enter Cohere API Key: \"\n",
"# )\n",
"os.environ[\"OPENAI_API_KEY\"] = os.getenv(\"OPENAI_API_KEY\") or getpass(\n",
" \"Enter OpenAI API Key: \"\n",
")\n",
"\n",
"# encoder = CohereEncoder()\n",
"encoder = OpenAIEncoder()"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "lYuLO0l9f3p3"
},
"source": [
"Now we define the `RouteLayer`. When called, the route layer will consume text (a query) and output the category (`Route`) it belongs to — to initialize a `RouteLayer` we need our `encoder` model and a list of `routes`."
