examples

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{
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  "cells": [
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    {
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      "attachments": {},
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      "cell_type": "markdown",
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      "metadata": {
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        "id": "hNbFoillfVmR"
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      },
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      "source": [
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        "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/pinecone-io/examples/blob/master/learn/generation/chatbots/nemo-guardrails/02a-actions-weather-api.ipynb) [![Open nbviewer](https://raw.githubusercontent.com/pinecone-io/examples/master/assets/nbviewer-shield.svg)](https://nbviewer.org/github/pinecone-io/examples/blob/master/learn/generation/chatbots/nemo-guardrails/02a-actions-weather-api.ipynb)"
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      ]
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    },
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    {
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      "cell_type": "code",
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      "execution_count": 11,
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      "metadata": {
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        "colab": {
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          "base_uri": "https://localhost:8080/"
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        },
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        "id": "pZ8GfhOHfVmS",
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        "outputId": "3d0bbb9b-2546-4b51-dc15-cba48e07b4ab"
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      },
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      "outputs": [
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        {
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          "name": "stdout",
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          "output_type": "stream",
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          "text": [
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            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m13.9/13.9 MB\u001b[0m \u001b[31m41.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m73.6/73.6 kB\u001b[0m \u001b[31m7.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.0/1.0 MB\u001b[0m \u001b[31m50.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.4/1.4 MB\u001b[0m \u001b[31m55.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.2/1.2 MB\u001b[0m \u001b[31m60.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m647.5/647.5 kB\u001b[0m \u001b[31m39.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m86.0/86.0 kB\u001b[0m \u001b[31m7.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m57.1/57.1 kB\u001b[0m \u001b[31m6.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m67.0/67.0 kB\u001b[0m \u001b[31m6.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m58.3/58.3 kB\u001b[0m \u001b[31m5.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m71.5/71.5 kB\u001b[0m \u001b[31m7.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m69.6/69.6 kB\u001b[0m \u001b[31m6.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m90.0/90.0 kB\u001b[0m \u001b[31m9.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.4/7.4 MB\u001b[0m \u001b[31m69.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.3/1.3 MB\u001b[0m \u001b[31m52.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m268.8/268.8 kB\u001b[0m \u001b[31m24.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m58.3/58.3 kB\u001b[0m \u001b[31m5.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m49.4/49.4 kB\u001b[0m \u001b[31m3.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.8/7.8 MB\u001b[0m \u001b[31m42.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.3/1.3 MB\u001b[0m \u001b[31m46.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[?25h  Building wheel for annoy (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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            "  Building wheel for sentence-transformers (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
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            "ipython 7.34.0 requires jedi>=0.16, which is not installed.\n",
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            "cvxpy 1.3.2 requires setuptools>65.5.1, but you have setuptools 65.5.1 which is incompatible.\u001b[0m\u001b[31m\n",
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            "\u001b[0m"
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          ]
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        }
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      ],
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      "source": [
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        "!pip install -qU \\\n",
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        "    nemoguardrails==0.4.0 \\\n",
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        "    openai==0.27.8"
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      ]
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    },
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    {
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      "attachments": {},
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      "cell_type": "markdown",
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      "metadata": {
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        "id": "GZXGTSv2f_Fy"
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      },
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      "source": [
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        "Set your OpenAI API key:"
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      ]
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    },
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    {
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      "cell_type": "code",
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      "execution_count": 12,
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      "metadata": {
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        "id": "Oc4N2tXxgBMp"
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      },
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      "outputs": [],
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      "source": [
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        "import os\n",
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        "\n",
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        "os.environ[\"OPENAI_API_KEY\"] = \"sk-...\""
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      ]
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    },
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    {
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      "attachments": {},
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      "cell_type": "markdown",
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      "metadata": {
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        "id": "WuVyO37cfVmT"
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      },
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      "source": [
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        "# Adding Actions: Weather API\n",
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        "\n",
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        "In Guardrails we can add _actions_ to our colang files. These actions allow us to execute code, for example:\n",
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        "\n",
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        "```\n",
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        "define flow\n",
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        "    user ask question\n",
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        "    $answer = execute qa_func(prompt=$last_user_message)\n",
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        "    bot $answer\n",
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        "```\n",
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        "\n",
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        "In this Colang flow we expect the user to ask some question (`user ask question`), if so we run an _action_ (equivalent to a Python function) called `qa_func`, we also pass the `$last_user_message` (a default variable set by Guardrails) to this function via the function's `prompt` parameter.\n",
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        "\n",
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        "The function/action returns a value which we store in the `$answer` context variable, we then tell the bot to return this answer to the user (`bot $answer`).\n",
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        "\n",
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        "Let's take a look at an example colang file for this:"
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      ]
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    },
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    {
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      "cell_type": "code",
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      "execution_count": 43,
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      "metadata": {
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        "id": "F41pofCJfVmT"
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      },
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      "outputs": [],
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      "source": [
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        "colang_content = \"\"\"\n",
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        "# define limits\n",
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        "define user ask weather\n",
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        "    \"how is the weather today?\"\n",
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        "    \"should I wear a coat?\"\n",
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        "\n",
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        "define bot answer weather\n",
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        "    bot report weather\n",
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        "\n",
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        "define flow weather\n",
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        "    user ask weather\n",
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        "    $coords = execute location_api()\n",
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        "    $weather = execute weather_api(coords=$coords)\n",
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        "    bot answer weather\n",
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        "\n",
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        "# here we use the chatbot for anything else\n",
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        "define flow\n",
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        "    user ...\n",
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        "    bot greeting\n",
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        "\"\"\"\n",
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        "yaml_content = \"\"\"\n",
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        "models:\n",
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        "- type: main\n",
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        "  engine: openai\n",
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        "  model: text-davinci-003\n",
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        "\"\"\""
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      ]
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    },
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    {
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      "attachments": {},
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      "cell_type": "markdown",
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      "metadata": {
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        "id": "sKS-7hfjIR2h"
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      },
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      "source": [
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        "In our Colang we specify the `weather` dialogue flow with two calls to actions, one for a location API and the next for a weather API (using info from the location API)."
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      ]
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    },
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    {
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      "cell_type": "code",
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      "execution_count": 44,
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      "metadata": {
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        "id": "JQQEhEZtsHBQ"
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      },
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      "outputs": [],
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      "source": [
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        "import requests\n",
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        "\n",
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        "async def weather_api(coords: list):\n",
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        "    latitude, longitude = coords\n",
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        "    res = requests.get(\n",
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        "        \"https://api.open-meteo.com/v1/forecast\",\n",
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        "        params={\n",
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        "            \"latitude\": latitude,\n",
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        "            \"longitude\": longitude,\n",
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        "            \"current_weather\": \"true\"\n",
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        "        }\n",
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        "    )\n",
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        "    weather = res.json()[\"current_weather\"]\n",
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        "    weather_report = f\"\"\"The current weather is:\n",
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        "    temperature: {weather[\"temperature\"]}\n",
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        "    windspeed: {weather[\"windspeed\"]}\n",
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        "    wind direction: {weather[\"winddirection\"]} degrees\n",
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        "    And it is {\"daytime\" if weather[\"is_day\"] else \"nightime\"}\"\"\"\n",
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        "    return weather_report\n",
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        "\n",
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        "async def location_api():\n",
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        "    res = requests.get(\"http://ip-api.com/json/\")\n",
189
        "    return res.json()['lat'], res.json()['lon']"
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      ]
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    },
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    {
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      "attachments": {},
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      "cell_type": "markdown",
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      "metadata": {
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        "id": "83ZFNkebfVmT"
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      },
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      "source": [
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        "We've defined our location and weather APIs required for our bot to give us up to date advice on the weather in our current location."
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      ]
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    },
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    {
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      "cell_type": "code",
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      "execution_count": 45,
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      "metadata": {
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        "id": "GGEaBLR9fVmU"
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      },
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      "outputs": [],
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      "source": [
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        "from nemoguardrails import LLMRails, RailsConfig\n",
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        "\n",
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        "# initialize rails config\n",
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        "config = RailsConfig.from_content(\n",
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        "    colang_content=colang_content,\n",
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        "    yaml_content=yaml_content\n",
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        ")\n",
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        "# create rails\n",
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        "rails = LLMRails(config, verbose=True)"
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      ]
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    },
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    {
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      "attachments": {},
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      "cell_type": "markdown",
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      "metadata": {
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        "id": "Dkzl4ZU7fVmU"
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      },
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      "source": [
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        "We need to register the two functions as actions like so:"
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      ]
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    },
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    {
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      "cell_type": "code",
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      "execution_count": 46,
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      "metadata": {
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        "id": "B8jjXe3MfVmU"
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      },
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      "outputs": [],
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      "source": [
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        "rails.register_action(action=location_api, name=\"location_api\")\n",
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        "rails.register_action(action=weather_api, name=\"weather_api\")"
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      ]
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    },
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    {
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      "attachments": {},
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      "cell_type": "markdown",
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      "metadata": {
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        "id": "CNQ3Si4ufVmU"
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      },
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      "source": [
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        "Let's try our guardrails..."
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      ]
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    },
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    {
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      "cell_type": "code",
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      "execution_count": 47,
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      "metadata": {
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        "colab": {
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          "base_uri": "https://localhost:8080/",
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          "height": 36
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        },
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        "id": "wMiR0TfWfVmU",
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        "outputId": "b7634af8-6c2c-405d-a5ae-cbc16460f856"
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      },
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      "outputs": [
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        {
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          "data": {
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            "application/vnd.google.colaboratory.intrinsic+json": {
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              "type": "string"
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            },
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            "text/plain": [
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              "'Hi there! How can I be of assistance?'"
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            ]
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          },
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          "execution_count": 47,
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          "metadata": {},
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          "output_type": "execute_result"
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        }
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      ],
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      "source": [
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        "await rails.generate_async(prompt=\"hello\")"
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      ]
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    },
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    {
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      "attachments": {},
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      "cell_type": "markdown",
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      "metadata": {
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        "id": "yRVLJc3yfVmV"
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      },
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      "source": [
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        "Now we can try again:"
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      ]
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    },
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    {
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      "cell_type": "code",
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      "execution_count": 48,
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      "metadata": {
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        "colab": {
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          "base_uri": "https://localhost:8080/",
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          "height": 53
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        },
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        "id": "bgRfARA2fVmV",
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        "outputId": "0e5c00ae-7aa3-4e18-b647-2e62fc0d1c22"
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      },
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      "outputs": [
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        {
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          "data": {
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            "application/vnd.google.colaboratory.intrinsic+json": {
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              "type": "string"
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            },
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            "text/plain": [
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              "'The current weather in Washington, DC is 27.8 degrees, with a wind speed of 13.7 mph and a wind direction of 275.0 degrees. It is currently daytime.'"
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            ]
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          },
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          "execution_count": 48,
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          "metadata": {},
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          "output_type": "execute_result"
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        }
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      ],
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      "source": [
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        "await rails.generate_async(prompt=\"how is the weather?\")"
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      ]
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    },
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    {
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      "cell_type": "code",
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      "execution_count": 49,
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      "metadata": {
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        "colab": {
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          "base_uri": "https://localhost:8080/",
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          "height": 53
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        },
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        "id": "fXK1TfuMGo8A",
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        "outputId": "9088d716-10aa-4a20-e8e9-26e2461826a8"
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      },
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      "outputs": [
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        {
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          "data": {
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            "application/vnd.google.colaboratory.intrinsic+json": {
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              "type": "string"
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            },
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            "text/plain": [
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              "'It is currently 27.8 degrees outside with a windspeed of 13.7 and a wind direction of 275.0 degrees. Based on this, it is recommended that you wear a sweatshirt today.'"
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            ]
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          },
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          "execution_count": 49,
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          "metadata": {},
346
          "output_type": "execute_result"
347
        }
348
      ],
349
      "source": [
350
        "await rails.generate_async(prompt=\"do I need a sweatshirt today?\")"
351
      ]
352
    },
353
    {
354
      "attachments": {},
355
      "cell_type": "markdown",
356
      "metadata": {
357
        "id": "bn4w59GbfVmV"
358
      },
359
      "source": [
360
        "Great, we can see our weather checking Guardrails are working!"
361
      ]
362
    }
363
  ],
364
  "metadata": {
365
    "colab": {
366
      "provenance": []
367
    },
368
    "kernelspec": {
369
      "display_name": "redacre",
370
      "language": "python",
371
      "name": "python3"
372
    },
373
    "language_info": {
374
      "codemirror_mode": {
375
        "name": "ipython",
376
        "version": 3
377
      },
378
      "file_extension": ".py",
379
      "mimetype": "text/x-python",
380
      "name": "python",
381
      "nbconvert_exporter": "python",
382
      "pygments_lexer": "ipython3",
383
      "version": "3.11.3"
384
    },
385
    "orig_nbformat": 4
386
  },
387
  "nbformat": 4,
388
  "nbformat_minor": 0
389
}
390