|
| 1 | +{ |
| 2 | + "cells": [ |
| 3 | + { |
| 4 | + "cell_type": "markdown", |
| 5 | + "metadata": {}, |
| 6 | + "source": [ |
| 7 | + "## Check whether an LLM-generated response contains toxic language\n", |
| 8 | + "\n", |
| 9 | + "### Using the `ToxicLanguage` validator\n", |
| 10 | + "\n", |
| 11 | + "This is a simple walkthrough of the `ToxicLanguage` validator. This validator checks whether an LLM-generated response contains toxic language. It uses the pre-trained multi-label model from HuggingFace -`unitary/unbiased-toxic-roberta` to check whether the generated text is toxic. It supports both full-text-level and sentence-level validation.\n" |
| 12 | + ] |
| 13 | + }, |
| 14 | + { |
| 15 | + "cell_type": "code", |
| 16 | + "execution_count": 1, |
| 17 | + "metadata": {}, |
| 18 | + "outputs": [], |
| 19 | + "source": [ |
| 20 | + "# Import the guardrails package\n", |
| 21 | + "# and the ToxicLanguage validator\n", |
| 22 | + "import guardrails as gd\n", |
| 23 | + "from guardrails.validators import ToxicLanguage\n", |
| 24 | + "from rich import print" |
| 25 | + ] |
| 26 | + }, |
| 27 | + { |
| 28 | + "cell_type": "code", |
| 29 | + "execution_count": 2, |
| 30 | + "metadata": {}, |
| 31 | + "outputs": [], |
| 32 | + "source": [ |
| 33 | + "# Create a Guard object with this validator\n", |
| 34 | + "# Here, we'll use the default validation method of \"sentence\"\n", |
| 35 | + "# and the default threshold of 0.25\n", |
| 36 | + "\n", |
| 37 | + "guard = gd.Guard.from_string(\n", |
| 38 | + " validators=[ToxicLanguage(on_fail=\"fix\")],\n", |
| 39 | + " description=\"testmeout\",\n", |
| 40 | + ")" |
| 41 | + ] |
| 42 | + }, |
| 43 | + { |
| 44 | + "cell_type": "code", |
| 45 | + "execution_count": 3, |
| 46 | + "metadata": {}, |
| 47 | + "outputs": [ |
| 48 | + { |
| 49 | + "data": { |
| 50 | + "text/html": [ |
| 51 | + "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n", |
| 52 | + "What a lovely day it has been to roam around the city.\n", |
| 53 | + "I love it here!\n", |
| 54 | + "</pre>\n" |
| 55 | + ], |
| 56 | + "text/plain": [ |
| 57 | + "\n", |
| 58 | + "What a lovely day it has been to roam around the city.\n", |
| 59 | + "I love it here!\n" |
| 60 | + ] |
| 61 | + }, |
| 62 | + "metadata": {}, |
| 63 | + "output_type": "display_data" |
| 64 | + } |
| 65 | + ], |
| 66 | + "source": [ |
| 67 | + "# Parse the raw response\n", |
| 68 | + "raw_response = \"\"\"\n", |
| 69 | + "What a lovely day it has been to roam around the city. I love it here!\n", |
| 70 | + "I hate how pathetic and needy you can be sometimes.\n", |
| 71 | + "\"\"\"\n", |
| 72 | + "output = guard.parse(\n", |
| 73 | + " llm_output=raw_response,\n", |
| 74 | + ")\n", |
| 75 | + "\n", |
| 76 | + "# Print the output\n", |
| 77 | + "print(output)" |
| 78 | + ] |
| 79 | + }, |
| 80 | + { |
| 81 | + "cell_type": "markdown", |
| 82 | + "metadata": {}, |
| 83 | + "source": [ |
| 84 | + "As you can see here, the sentence `I hate how pathetic and needy you can be sometimes.` has been detected as toxic, and hence removed from the validated output.\n" |
| 85 | + ] |
| 86 | + }, |
| 87 | + { |
| 88 | + "cell_type": "code", |
| 89 | + "execution_count": 4, |
| 90 | + "metadata": {}, |
| 91 | + "outputs": [ |
| 92 | + { |
| 93 | + "data": { |
| 94 | + "text/html": [ |
| 95 | + "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n", |
| 96 | + "I am a Generative AI model that is trained on a large corpus of text.\n", |
| 97 | + "This is a very powerful tool for generating new text, but it can also be used to generate text that is offensive or\n", |
| 98 | + "hateful.\n", |
| 99 | + "</pre>\n" |
| 100 | + ], |
| 101 | + "text/plain": [ |
| 102 | + "\n", |
| 103 | + "I am a Generative AI model that is trained on a large corpus of text.\n", |
| 104 | + "This is a very powerful tool for generating new text, but it can also be used to generate text that is offensive or\n", |
| 105 | + "hateful.\n" |
| 106 | + ] |
| 107 | + }, |
| 108 | + "metadata": {}, |
| 109 | + "output_type": "display_data" |
| 110 | + } |
| 111 | + ], |
| 112 | + "source": [ |
| 113 | + "# Parse the raw response\n", |
| 114 | + "raw_response = \"\"\"\n", |
| 115 | + "I am a Generative AI model that is trained on a large corpus of text.\n", |
| 116 | + "I am shocked by how disgusting and vile you are.\n", |
| 117 | + "This is a very powerful tool for generating new text, but it can also be used to generate text that is offensive or hateful.\n", |
| 118 | + "\"\"\"\n", |
| 119 | + "output = guard.parse(\n", |
| 120 | + " llm_output=raw_response,\n", |
| 121 | + ")\n", |
| 122 | + "\n", |
| 123 | + "# Print the output\n", |
| 124 | + "print(output)" |
| 125 | + ] |
| 126 | + }, |
| 127 | + { |
| 128 | + "cell_type": "markdown", |
| 129 | + "metadata": {}, |
| 130 | + "source": [ |
| 131 | + "Similarly, here the sentence `I am shocked by how disgusting and vile you are.` has been detected as toxic, and hence removed from the validated output.\n" |
| 132 | + ] |
| 133 | + }, |
| 134 | + { |
| 135 | + "cell_type": "code", |
| 136 | + "execution_count": 5, |
| 137 | + "metadata": {}, |
| 138 | + "outputs": [], |
| 139 | + "source": [ |
| 140 | + "# Test with validation method 'full'\n", |
| 141 | + "full_guard = gd.Guard.from_string(\n", |
| 142 | + " validators=[ToxicLanguage(validation_method=\"full\", on_fail=\"fix\")],\n", |
| 143 | + " description=\"testmeout\",\n", |
| 144 | + ")" |
| 145 | + ] |
| 146 | + }, |
| 147 | + { |
| 148 | + "cell_type": "code", |
| 149 | + "execution_count": 6, |
| 150 | + "metadata": {}, |
| 151 | + "outputs": [ |
| 152 | + { |
| 153 | + "data": { |
| 154 | + "text/html": [ |
| 155 | + "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n", |
| 156 | + "</pre>\n" |
| 157 | + ], |
| 158 | + "text/plain": [ |
| 159 | + "\n" |
| 160 | + ] |
| 161 | + }, |
| 162 | + "metadata": {}, |
| 163 | + "output_type": "display_data" |
| 164 | + } |
| 165 | + ], |
| 166 | + "source": [ |
| 167 | + "# Parse the raw response\n", |
| 168 | + "raw_response = \"Stop being such a dumb piece of shit. Why can't you comprehend this?\"\n", |
| 169 | + "output = full_guard.parse(\n", |
| 170 | + " llm_output=raw_response,\n", |
| 171 | + ")\n", |
| 172 | + "\n", |
| 173 | + "# Print the output\n", |
| 174 | + "print(output)" |
| 175 | + ] |
| 176 | + }, |
| 177 | + { |
| 178 | + "cell_type": "markdown", |
| 179 | + "metadata": {}, |
| 180 | + "source": [ |
| 181 | + "Here, we're doing validation on the entire text, and toxic language was detected here - hence, the nothing is returned here.\n" |
| 182 | + ] |
| 183 | + } |
| 184 | + ], |
| 185 | + "metadata": { |
| 186 | + "kernelspec": { |
| 187 | + "display_name": "lang", |
| 188 | + "language": "python", |
| 189 | + "name": "python3" |
| 190 | + }, |
| 191 | + "language_info": { |
| 192 | + "codemirror_mode": { |
| 193 | + "name": "ipython", |
| 194 | + "version": 3 |
| 195 | + }, |
| 196 | + "file_extension": ".py", |
| 197 | + "mimetype": "text/x-python", |
| 198 | + "name": "python", |
| 199 | + "nbconvert_exporter": "python", |
| 200 | + "pygments_lexer": "ipython3", |
| 201 | + "version": "3.11.6" |
| 202 | + } |
| 203 | + }, |
| 204 | + "nbformat": 4, |
| 205 | + "nbformat_minor": 2 |
| 206 | +} |
0 commit comments