examples

02-colang-actions.ipynb
5531 строка · 199.1 Кб
Перенос по словам
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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/02-colang-actions.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/02-colang-actions.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": 1,
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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": "af2f695d-f574-4ba6-8461-71e898025f75"
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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[31m8.5 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[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m58.3/58.3 kB\u001b[0m \u001b[31m4.6 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[31m2.7 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[31m120.2 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[31m61.0 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": 2,
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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\"] = os.environ.get(\"OPENAI_API_KEY\") or \"YOUR_API_KEY\""
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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\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": 3,
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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 politics\n",
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        "    \"what are your political beliefs?\"\n",
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        "    \"thoughts on the president?\"\n",
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        "    \"left wing\"\n",
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        "    \"right wing\"\n",
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        "\n",
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        "define bot answer politics\n",
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        "    \"I'm a shopping assistant, I don't like to talk of politics.\"\n",
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        "\n",
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        "define flow politics\n",
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        "    user ask politics\n",
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        "    bot answer politics\n",
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        "    bot offer help\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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        "    $answer = execute response(inputs=$last_user_message)\n",
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        "    bot $answer\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": "83ZFNkebfVmT"
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      },
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      "source": [
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        "Here we have our typical guardrail for any politcal talk. Anything else will get captured by the _catch all_ statement of `user ...` — triggering the final flow.\n",
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        "\n",
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        "Within that final flow we execute the `response` function and pass the `last_user_message` via the `inputs` parameter. By itself, this won't do anything, we need to tell Guardrails what this action/function is. Let's begin by initializing our rails."
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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": 4,
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      "metadata": {
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        "colab": {
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          "base_uri": "https://localhost:8080/",
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          "height": 465,
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          "referenced_widgets": [
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        "id": "GGEaBLR9fVmU",
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        "outputId": "427c7b67-aa58-4560-e43e-90235833d4ba"
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      "outputs": [
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        {
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        {
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          "data": {
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              "model_id": "db7abc4130574ed18e77042ce7567788",
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            ]
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        },
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        {
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          "data": {
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              "model_id": "f0ad3047e139434283098ea2680d4c23",
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              "version_major": 2,
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              "version_minor": 0
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            },
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            ]
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          },
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        },
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        {
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          "data": {
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              "model_id": "31b3b06d337f4a4393f7e810a7981397",
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          },
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          "metadata": {},
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          "output_type": "display_data"
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        }
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      ],
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      "source": [
529
        "from nemoguardrails import LLMRails, RailsConfig\n",
530
        "\n",
531
        "# initialize rails config\n",
532
        "config = RailsConfig.from_content(\n",
533
        "    colang_content=colang_content,\n",
534
        "    yaml_content=yaml_content\n",
535
        ")\n",
536
        "# create rails\n",
537
        "rails = LLMRails(config)"
538
      ]
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    },
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    {
541
      "attachments": {},
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      "cell_type": "markdown",
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      "metadata": {
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        "id": "CNQ3Si4ufVmU"
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      },
546
      "source": [
547
        "Let's try our guardrails..."
548
      ]
549
    },
550
    {
551
      "cell_type": "code",
552
      "execution_count": 5,
553
      "metadata": {
554
        "colab": {
555
          "base_uri": "https://localhost:8080/",
556
          "height": 36
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        },
558
        "id": "wMiR0TfWfVmU",
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        "outputId": "a7bf4530-5531-416f-88f9-3aec19e62af4"
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      },
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      "outputs": [
562
        {
563
          "data": {
564
            "application/vnd.google.colaboratory.intrinsic+json": {
565
              "type": "string"
566
            },
567
            "text/plain": [
568
              "\"Action 'response' not found.\""
569
            ]
570
          },
571
          "execution_count": 5,
572
          "metadata": {},
573
          "output_type": "execute_result"
574
        }
575
      ],
576
      "source": [
577
        "await rails.generate_async(prompt=\"hello\")"
578
      ]
579
    },
580
    {
581
      "attachments": {},
582
      "cell_type": "markdown",
583
      "metadata": {
584
        "id": "6gvMEBMWfVmU"
585
      },
586
      "source": [
587
        "The `response` action couldn't be found. That makes sense we haven't defined anything yet, so let's initialize a function to act as our `response` action."
588
      ]
589
    },
590
    {
591
      "cell_type": "code",
592
      "execution_count": 13,
593
      "metadata": {
594
        "id": "g50VIeJbfVmU"
595
      },
596
      "outputs": [],
597
      "source": [
598
        "async def func(inputs: str):\n",
599
        "    return \"hello you are an orange\""
600
      ]
601
    },
602
    {
603
      "attachments": {},
604
      "cell_type": "markdown",
605
      "metadata": {
606
        "id": "UAmotuvRfVmU"
607
      },
608
      "source": [
609
        "This won't do anything other than tell us we're oranges, but that's fine for this example. Guardrails still doesn't know that this is the correct action to use though:"
610
      ]
611
    },
612
    {
613
      "cell_type": "code",
614
      "execution_count": 7,
615
      "metadata": {
616
        "colab": {
617
          "base_uri": "https://localhost:8080/",
618
          "height": 36
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        },
620
        "id": "zqOhtmgofVmU",
621
        "outputId": "69a6e4ab-8ae3-4668-9e2e-bf346b534a36"
622
      },
623
      "outputs": [
624
        {
625
          "data": {
626
            "application/vnd.google.colaboratory.intrinsic+json": {
627
              "type": "string"
628
            },
629
            "text/plain": [
630
              "\"Action 'response' not found.\""
631
            ]
632
          },
633
          "execution_count": 7,
634
          "metadata": {},
635
          "output_type": "execute_result"
636
        }
637
      ],
638
      "source": [
639
        "await rails.generate_async(prompt=\"hello\")"
640
      ]
641
    },
642
    {
643
      "attachments": {},
644
      "cell_type": "markdown",
645
      "metadata": {
646
        "id": "Dkzl4ZU7fVmU"
647
      },
648
      "source": [
649
        "That's because we need to register the action like so:"
650
      ]
651
    },
652
    {
653
      "cell_type": "code",
654
      "execution_count": 14,
655
      "metadata": {
656
        "id": "B8jjXe3MfVmU"
657
      },
658
      "outputs": [],
659
      "source": [
660
        "rails.register_action(action=func, name=\"response\")"
661
      ]
662
    },
663
    {
664
      "attachments": {},
665
      "cell_type": "markdown",
666
      "metadata": {
667
        "id": "yRVLJc3yfVmV"
668
      },
669
      "source": [
670
        "Now we can try again:"
671
      ]
672
    },
673
    {
674
      "cell_type": "code",
675
      "execution_count": 15,
676
      "metadata": {
677
        "colab": {
678
          "base_uri": "https://localhost:8080/",
679
          "height": 36
680
        },
681
        "id": "bgRfARA2fVmV",
682
        "outputId": "6aaf45e4-8edf-434b-ea7c-11f9adaefcc8"
683
      },
684
      "outputs": [
685
        {
686
          "data": {
687
            "application/vnd.google.colaboratory.intrinsic+json": {
688
              "type": "string"
689
            },
690
            "text/plain": [
691
              "'hello you are an orange'"
692
            ]
693
          },
694
          "execution_count": 15,
695
          "metadata": {},
696
          "output_type": "execute_result"
697
        }
698
      ],
699
      "source": [
700
        "await rails.generate_async(prompt=\"hello\")"
701
      ]
702
    },
703
    {
704
      "attachments": {},
705
      "cell_type": "markdown",
706
      "metadata": {
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        "id": "bn4w59GbfVmV"
708
      },
709
      "source": [
710
        "Perfect, that's the essentials behind using actions in Guardrails. One thing to note here is that we used `async def` to define our action function. If using async Guardrails we do need this otherwise we'll raise a async/await error in Python."
711
      ]
712
    }
713
  ],
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    "colab": {
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      "provenance": []
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      "language": "python",
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    },
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      "codemirror_mode": {
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        "name": "ipython",
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        "version": 3
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      },
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      "file_extension": ".py",
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      "mimetype": "text/x-python",
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      "name": "python",
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      "nbconvert_exporter": "python",
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      "pygments_lexer": "ipython3",
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    },
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examples

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