diff --git a/docs/00-introduction.ipynb b/docs/00-introduction.ipynb
index 4d672f379a44b236ad60a04eaf439c7a0c29ec94..0665070391a00545a4230aead9f22bd9b22717b3 100644
--- a/docs/00-introduction.ipynb
+++ b/docs/00-introduction.ipynb
@@ -44,13 +44,6 @@
"!pip install -qU semantic-router==0.0.15"
]
},
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "_**âš ï¸ If using Google Colab, install the prerequisites and then restart the notebook before continuing**_"
- ]
- },
{
"cell_type": "markdown",
"metadata": {},
diff --git a/docs/01-save-load-from-file.ipynb b/docs/01-save-load-from-file.ipynb
index 43937d2b7d74f1161073d866128df7b43ce87dca..6c5945cb9020a5d2296b86a1c282553abfb15736 100644
--- a/docs/01-save-load-from-file.ipynb
+++ b/docs/01-save-load-from-file.ipynb
@@ -39,13 +39,6 @@
"!pip install -qU semantic-router==0.0.15"
]
},
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "_**âš ï¸ If using Google Colab, install the prerequisites and then restart the notebook before continuing**_"
- ]
- },
{
"cell_type": "markdown",
"metadata": {},
diff --git a/docs/02-dynamic-routes.ipynb b/docs/02-dynamic-routes.ipynb
index 70c5eced9ece37a822ac0af0174f03f9ec07768a..88b7794aadac761ec74dc872d2203203208791e7 100644
--- a/docs/02-dynamic-routes.ipynb
+++ b/docs/02-dynamic-routes.ipynb
@@ -1,376 +1,453 @@
{
- "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==0.0.15"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "_**âš ï¸ 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": [],
- "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": "markdown",
- "metadata": {},
- "source": [
- "We initialize our `RouteLayer` with our `encoder` and `routes`. We can use popular encoder APIs like `CohereEncoder` and `OpenAIEncoder`, or local alternatives like `FastEmbedEncoder`."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {},
- "outputs": [
+ "cells": [
{
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\u001b[32m2024-01-07 18:11:05 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",
- "from semantic_router.encoders import CohereEncoder, OpenAIEncoder\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",
- "# platform.openai.com\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()\n",
- "\n",
- "rl = RouteLayer(encoder=encoder, routes=routes)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "We run the solely static routes layer:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {},
- "outputs": [
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "UxqB7_Ieur0s"
+ },
+ "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)"
+ ]
+ },
{
- "data": {
- "text/plain": [
- "RouteChoice(name='chitchat', function_call=None)"
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "EduhQaNAur0u"
+ },
+ "source": [
+ "# Dynamic Routes"
]
- },
- "execution_count": 3,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "rl(\"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": 4,
- "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": 5,
- "metadata": {},
- "outputs": [
+ },
{
- "data": {
- "text/plain": [
- "'12:11'"
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "_4JgNeX4ur0v"
+ },
+ "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)`."
]
- },
- "execution_count": 5,
- "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": 6,
- "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'>\"}"
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "bbmw8CO4ur0v"
+ },
+ "source": [
+ "## Installing the Library"
]
- },
- "execution_count": 6,
- "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": 7,
- "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": 8,
- "metadata": {},
- "outputs": [
+ },
{
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\u001b[32m2024-01-07 18:11:20 INFO semantic_router.utils.logger Adding `get_time` route\u001b[0m\n"
- ]
- }
- ],
- "source": [
- "rl.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": 9,
- "metadata": {},
- "outputs": [
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "dLElfRhgur0v"
+ },
+ "outputs": [],
+ "source": [
+ "!pip install -qU semantic-router==0.0.15"
+ ]
+ },
{
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\u001b[33m2024-01-07 18:11:23 WARNING semantic_router.utils.logger No LLM provided for dynamic route, will use OpenAI LLM default. Ensure API key is set in OPENAI_API_KEY environment variable.\u001b[0m\n",
- "\u001b[32m2024-01-07 18:11:23 INFO semantic_router.utils.logger Extracting function input...\u001b[0m\n"
- ]
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "BixZd6Eour0w"
+ },
+ "source": [
+ "## Initializing Routes and RouteLayer"
+ ]
},
{
- "data": {
- "text/plain": [
- "RouteChoice(name='get_time', function_call={'timezone': 'new york city'})"
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "PxnW9qBvur0x"
+ },
+ "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": {
+ "id": "kc9Ty6Lgur0x"
+ },
+ "outputs": [],
+ "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": "markdown",
+ "metadata": {
+ "id": "voWyqmffur0x"
+ },
+ "source": [
+ "We initialize our `RouteLayer` with our `encoder` and `routes`. We can use popular encoder APIs like `CohereEncoder` and `OpenAIEncoder`, or local alternatives like `FastEmbedEncoder`."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "id": "BI9AiDspur0y",
+ "outputId": "27329a54-3f16-44a5-ac20-13a6b26afb97",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ }
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "\u001b[32m2024-01-08 11:12:24 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",
+ "from semantic_router.encoders import CohereEncoder, OpenAIEncoder\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",
+ "# platform.openai.com\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()\n",
+ "\n",
+ "rl = RouteLayer(encoder=encoder, routes=routes)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "GuLCeIS5ur0y"
+ },
+ "source": [
+ "We run the solely static routes layer:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "id": "_rNREh7gur0y",
+ "outputId": "f3a1dc0b-d760-4efb-b634-d3547011dcb7",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ }
+ },
+ "outputs": [
+ {
+ "output_type": "execute_result",
+ "data": {
+ "text/plain": [
+ "RouteChoice(name='chitchat', function_call=None)"
+ ]
+ },
+ "metadata": {},
+ "execution_count": 4
+ }
+ ],
+ "source": [
+ "rl(\"how's the weather today?\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "McbLKO26ur0y"
+ },
+ "source": [
+ "## Creating a Dynamic Route"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "ANAoEjxYur0y"
+ },
+ "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": 5,
+ "metadata": {
+ "id": "5jaF1Xa5ur0y"
+ },
+ "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\". Do NOT put the place\n",
+ " name itself like \"rome\", or \"new york\", you must provide\n",
+ " the IANA format.\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": 6,
+ "metadata": {
+ "id": "YyFKV8jMur0z",
+ "outputId": "29cf80f4-552c-47bb-fbf9-019f5dfdf00a",
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 35
+ }
+ },
+ "outputs": [
+ {
+ "output_type": "execute_result",
+ "data": {
+ "text/plain": [
+ "'06:13'"
+ ],
+ "application/vnd.google.colaboratory.intrinsic+json": {
+ "type": "string"
+ }
+ },
+ "metadata": {},
+ "execution_count": 6
+ }
+ ],
+ "source": [
+ "get_time(\"America/New_York\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "4qyaRuNXur0z"
+ },
+ "source": [
+ "To get the function schema we can use the `get_schema` function from the `function_call` module."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {
+ "id": "tOjuhp5Xur0z",
+ "outputId": "ca88a3ea-d70a-4950-be9a-63fab699de3b",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ }
+ },
+ "outputs": [
+ {
+ "output_type": "execute_result",
+ "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\". Do NOT put the place\\n name itself like \"rome\", or \"new york\", you must provide\\n the IANA format.\\n:type timezone: str\\n:return: The current time in the specified timezone.',\n",
+ " 'signature': '(timezone: str) -> str',\n",
+ " 'output': \"<class 'str'>\"}"
+ ]
+ },
+ "metadata": {},
+ "execution_count": 7
+ }
+ ],
+ "source": [
+ "from semantic_router.utils.function_call import get_schema\n",
+ "\n",
+ "schema = get_schema(get_time)\n",
+ "schema"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "HcF7jGjAur0z"
+ },
+ "source": [
+ "We use this to define our dynamic route:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {
+ "id": "iesBG9P3ur0z"
+ },
+ "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": {
+ "id": "ZiUs3ovpur0z"
+ },
+ "source": [
+ "Add the new route to our `layer`:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "metadata": {
+ "id": "-0vY8PRXur0z",
+ "outputId": "db01e14c-eab3-4f93-f4c2-e30f508c8b5d",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ }
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "\u001b[32m2024-01-08 11:15:26 INFO semantic_router.utils.logger Adding `get_time` route\u001b[0m\n"
+ ]
+ }
+ ],
+ "source": [
+ "rl.add(time_route)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "7yoE0IrNur0z"
+ },
+ "source": [
+ "Now we can ask our layer a time related question to trigger our new dynamic route."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "metadata": {
+ "id": "Wfb68M0-ur0z",
+ "outputId": "79923883-2a4d-4744-f8ce-e818cb5f14c3",
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 53
+ }
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "\u001b[32m2024-01-08 11:16:24 INFO semantic_router.utils.logger Extracting function input...\u001b[0m\n"
+ ]
+ },
+ {
+ "output_type": "execute_result",
+ "data": {
+ "text/plain": [
+ "'06:16'"
+ ],
+ "application/vnd.google.colaboratory.intrinsic+json": {
+ "type": "string"
+ }
+ },
+ "metadata": {},
+ "execution_count": 11
+ }
+ ],
+ "source": [
+ "out = rl(\"what is the time in new york city?\")\n",
+ "get_time(**out.function_call)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "Qt0vkq2Xur00"
+ },
+ "source": [
+ "Our dynamic route provides both the route itself _and_ the input parameters required to use the route."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "J0oD1dxIur00"
+ },
+ "source": [
+ "---"
]
- },
- "execution_count": 9,
- "metadata": {},
- "output_type": "execute_result"
}
- ],
- "source": [
- "# https://platform.openai.com/\n",
- "os.environ[\"OPENAI_API_KEY\"] = os.getenv(\"OPENAI_API_KEY\") or getpass(\n",
- " \"Enter OpenAI API Key: \"\n",
- ")\n",
- "\n",
- "rl(\"what is the time in new york city?\")"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Our dynamic route provides both the route itself _and_ the input parameters required to use the route."
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "---"
- ]
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "decision-layer",
- "language": "python",
- "name": "python3"
+ ],
+ "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"
+ },
+ "colab": {
+ "provenance": []
+ }
},
- "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
-}
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
\ No newline at end of file
diff --git a/docs/03-basic-langchain-agent.ipynb b/docs/03-basic-langchain-agent.ipynb
index c8c48b3dbedf5c6a09243ff2c93a1071f40c916d..dc728495136a804a79340026d14f56807929e443 100644
--- a/docs/03-basic-langchain-agent.ipynb
+++ b/docs/03-basic-langchain-agent.ipynb
@@ -83,15 +83,6 @@
" openai==1.6.1"
]
},
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "cHtVnoJPA04x"
- },
- "source": [
- "_**âš ï¸ If using Google Colab, install the prerequisites and then restart the notebook before continuing**_"
- ]
- },
{
"cell_type": "markdown",
"metadata": {
diff --git a/docs/04-chat-history.ipynb b/docs/04-chat-history.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..4ac533b1ef4126ac63cb6b8cacf2441d73a538ea
--- /dev/null
+++ b/docs/04-chat-history.ipynb
@@ -0,0 +1,139 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "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)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Considering Chat History"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Applying semantic-router to the most recent interaction in a conversation can work for many cases but it misses scenarios where information provided in the latest interaction."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": []
+ },
+ {
+ "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",
+ "100%|██████████| 83.2M/83.2M [00:09<00:00, 8.45MiB/s]\n"
+ ]
+ },
+ {
+ "data": {
+ "text/plain": [
+ "{'split 1': ['User: Hello! Can you tell me the latest news headlines?',\n",
+ " 'Bot: Hi! Sure, here are the top news headlines for today...'],\n",
+ " 'split 2': [\"User: That's quite interesting. I'm also looking for some new music to listen to.\",\n",
+ " 'Bot: What genre do you prefer?',\n",
+ " 'User: I like pop music.',\n",
+ " 'Bot: You might enjoy the latest album by Dua Lipa.',\n",
+ " \"User: I'll give it a listen. Also, I'm planning a trip and need some travel tips.\",\n",
+ " 'Bot: Sure, where are you planning to go?'],\n",
+ " 'split 3': [\"User: I'm thinking of visiting Italy.\",\n",
+ " 'Bot: Italy is a beautiful country. Make sure to visit the Colosseum in Rome and the canals in Venice.'],\n",
+ " 'split 4': ['User: Those sound like great suggestions. I also need some help with my diet.',\n",
+ " 'Bot: What kind of diet are you following?',\n",
+ " \"User: I'm trying to eat more protein.\",\n",
+ " 'Bot: Include lean meats, eggs, and legumes in your diet for a protein boost.',\n",
+ " \"User: Thanks for the tips! I'll talk to you later.\",\n",
+ " \"Bot: You're welcome! Don't hesitate to reach out if you need more help.\",\n",
+ " 'User: I appreciate it. Goodbye!',\n",
+ " 'Bot: Goodbye! Take care!']}"
+ ]
+ },
+ "execution_count": 1,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "from semantic_router.schema import Conversation, Message\n",
+ "from semantic_router.encoders import FastEmbedEncoder\n",
+ "\n",
+ "\n",
+ "messages = [\n",
+ " \"User: Hello! Can you tell me the latest news headlines?\",\n",
+ " \"Bot: Hi! Sure, here are the top news headlines for today...\",\n",
+ " \"User: That's quite interesting. I'm also looking for some new music to listen to.\",\n",
+ " \"Bot: What genre do you prefer?\",\n",
+ " \"User: I like pop music.\",\n",
+ " \"Bot: You might enjoy the latest album by Dua Lipa.\",\n",
+ " \"User: I'll give it a listen. Also, I'm planning a trip and need some travel tips.\",\n",
+ " \"Bot: Sure, where are you planning to go?\",\n",
+ " \"User: I'm thinking of visiting Italy.\",\n",
+ " \"Bot: Italy is a beautiful country. Make sure to visit the Colosseum in Rome and the canals in Venice.\",\n",
+ " \"User: Those sound like great suggestions. I also need some help with my diet.\",\n",
+ " \"Bot: What kind of diet are you following?\",\n",
+ " \"User: I'm trying to eat more protein.\",\n",
+ " \"Bot: Include lean meats, eggs, and legumes in your diet for a protein boost.\",\n",
+ " \"User: Thanks for the tips! I'll talk to you later.\",\n",
+ " \"Bot: You're welcome! Don't hesitate to reach out if you need more help.\",\n",
+ " \"User: I appreciate it. Goodbye!\",\n",
+ " \"Bot: Goodbye! Take care!\",\n",
+ "]\n",
+ "\n",
+ "encoder = FastEmbedEncoder(model_name=\"sentence-transformers/all-MiniLM-L6-v2\")\n",
+ "\n",
+ "convo = Conversation(\n",
+ " messages=[\n",
+ " Message(role=m.split(\": \")[0], content=m.split(\": \")[1]) for m in messages\n",
+ " ]\n",
+ ")\n",
+ "\n",
+ "convo.split_by_topic(\n",
+ " encoder=encoder, threshold=0.72, split_method=\"cumulative_similarity_drop\"\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "ml",
+ "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
+}