{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "[](https://colab.research.google.com/github/aurelio-labs/semantic-router/blob/main/docs/02-dynamic-routes.ipynb) [](https://nbviewer.org/github/aurelio-labs/semantic-router/blob/main/docs/02-dynamic-routes.ipynb)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Dynamic Routes" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In semantic-router there are two types of routes that can be chosen. Both routes belong to the `Route` object, the only difference between them is that _static_ routes return a `Route.name` when chosen, whereas _dynamic_ routes use an LLM call to produce parameter input values.\n", "\n", "For example, a _static_ route will tell us if a query is talking about mathematics by returning the route name (which could be `\"math\"` for example). A _dynamic_ route can generate additional values, so it may decide a query is talking about maths, but it can also generate Python code that we can later execute to answer the user's query, this output may look like `\"math\", \"import math; output = math.sqrt(64)`." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Installing the Library" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "!pip install -qU semantic-router==0.0.14" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "_**⚠️ If using Google Colab, install the prerequisites and then restart the notebook before continuing**_" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Initializing Routes and RouteLayer" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Dynamic routes are treated in the same way as static routes, let's begin by initializing a `RouteLayer` consisting of static routes." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/Users/jamesbriggs/opt/anaconda3/envs/decision-layer/lib/python3.11/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", "None of PyTorch, TensorFlow >= 2.0, or Flax have been found. Models won't be available and only tokenizers, configuration and file/data utilities can be used.\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", " \"don't you just love the president\" \"don't you just hate the president\",\n", " \"they're going to destroy this country!\",\n", " \"they will save the country!\",\n", " ],\n", ")\n", "chitchat = Route(\n", " name=\"chitchat\",\n", " utterances=[\n", " \"how's the weather today?\",\n", " \"how are things going?\",\n", " \"lovely weather today\",\n", " \"the weather is horrendous\",\n", " \"let's go to the chippy\",\n", " ],\n", ")\n", "\n", "routes = [politics, chitchat]" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "\u001b[32m2023-12-28 19:19:39 INFO semantic_router.utils.logger Initializing RouteLayer\u001b[0m\n" ] } ], "source": [ "import os\n", "from getpass import getpass\n", "from semantic_router import RouteLayer\n", "\n", "# dashboard.cohere.ai\n", "os.environ[\"COHERE_API_KEY\"] = os.getenv(\"COHERE_API_KEY\") or getpass(\n", " \"Enter Cohere API Key: \"\n", ")\n", "\n", "layer = RouteLayer(routes=routes)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We run the solely static routes layer:" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "RouteChoice(name='chitchat', function_call=None)" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "layer(\"how's the weather today?\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Creating a Dynamic Route" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As with static routes, we must create a dynamic route before adding it to our route layer. To make a route dynamic, we need to provide a `function_schema`. The function schema provides instructions on what a function is, so that an LLM can decide how to use it correctly." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "from datetime import datetime\n", "from zoneinfo import ZoneInfo\n", "\n", "\n", "def get_time(timezone: str) -> str:\n", " \"\"\"Finds the current time in a specific timezone.\n", "\n", " :param timezone: The timezone to find the current time in, should\n", " be a valid timezone from the IANA Time Zone Database like\n", " \"America/New_York\" or \"Europe/London\".\n", " :type timezone: str\n", " :return: The current time in the specified timezone.\"\"\"\n", " now = datetime.now(ZoneInfo(timezone))\n", " return now.strftime(\"%H:%M\")" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'13:19'" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "get_time(\"America/New_York\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To get the function schema we can use the `get_schema` function from the `function_call` module." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'name': 'get_time',\n", " 'description': 'Finds the current time in a specific timezone.\\n\\n:param timezone: The timezone to find the current time in, should\\n be a valid timezone from the IANA Time Zone Database like\\n \"America/New_York\" or \"Europe/London\".\\n:type timezone: str\\n:return: The current time in the specified timezone.',\n", " 'signature': '(timezone: str) -> str',\n", " 'output': \"<class 'str'>\"}" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from semantic_router.utils.function_call import get_schema\n", "\n", "schema = get_schema(get_time)\n", "schema" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We use this to define our dynamic route:" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "time_route = Route(\n", " name=\"get_time\",\n", " utterances=[\n", " \"what is the time in new york city?\",\n", " \"what is the time in london?\",\n", " \"I live in Rome, what time is it?\",\n", " ],\n", " function_schema=schema,\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Add the new route to our `layer`:" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Adding route `get_time`\n", "Adding route to categories\n", "Adding route to index\n" ] } ], "source": [ "layer.add(time_route)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we can ask our layer a time related question to trigger our new dynamic route." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "\u001b[32m2023-12-28 19:21:58 INFO semantic_router.utils.logger Extracting function input...\u001b[0m\n" ] }, { "data": { "text/plain": [ "RouteChoice(name='get_time', function_call={'timezone': 'America/New_York'})" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# https://openrouter.ai/keys\n", "os.environ[\"OPENROUTER_API_KEY\"] = os.getenv(\"OPENROUTER_API_KEY\") or getpass(\n", " \"Enter OpenRouter API Key: \"\n", ")\n", "\n", "layer(\"what is the time in new york city?\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "---" ] } ], "metadata": { "kernelspec": { "display_name": "decision-layer", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.5" } }, "nbformat": 4, "nbformat_minor": 2 }