171 lines
4.0 KiB
Plaintext
171 lines
4.0 KiB
Plaintext
{
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"cells": [
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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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"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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"Installing hub:\u001b[35m/\u001b[0m\u001b[35m/guardrails/\u001b[0m\u001b[95mtwo_words...\u001b[0m\n",
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"✅Successfully installed guardrails/two_words version \u001b[1;36m0.0\u001b[0m.\u001b[1;36m0\u001b[0m!\n",
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"\n",
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"\n"
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]
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}
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],
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"source": [
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"! guardrails hub install hub://guardrails/two_words --quiet"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Input Validation\n",
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"\n",
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"Guardrails supports validating inputs (messages) with string validators."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"In XML, specify the validators on the `messages` tag, as such:"
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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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"is_executing": true
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},
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"outputs": [],
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"source": [
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"from guardrails import Guard\n",
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"\n",
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"rail_spec = \"\"\"\n",
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"<rail version=\"0.1\">\n",
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"<messages\n",
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" validators=\"hub://guardrails/two_words\"\n",
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" on-fail-two-words=\"exception\"\n",
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">\n",
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"<message role=\"user\">\n",
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"This is not two words\n",
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"</message>\n",
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"</messages>\n",
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"\n",
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"<output type=\"string\">\n",
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"</output>\n",
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"</rail>\n",
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"\"\"\"\n",
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"\n",
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"guard = Guard.for_rail_string(rail_spec)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"When `fix` is specified as the on-fail handler, the prompt will automatically be amended before calling the LLM.\n",
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"\n",
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"In any other case (for example, `exception`), a `ValidationError` will be returned in the outcome."
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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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"is_executing": true
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},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"/Users/calebcourier/Projects/guardrails/docs/.venv/lib/python3.10/site-packages/guardrails/validator_service/__init__.py:75: UserWarning: Could not obtain an event loop. Falling back to synchronous validation.\n",
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" warnings.warn(\n"
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]
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}
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],
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"source": [
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"from guardrails.errors import ValidationError\n",
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"\n",
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"# Add your OPENAI_API_KEY as an environment variable if it's not already set\n",
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"# import os\n",
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"# os.environ[\"OPENAI_API_KEY\"] = \"YOUR_API_KEY\"\n",
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"\n",
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"try:\n",
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" guard(model=\"gpt-4o\")\n",
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"except ValidationError as e:\n",
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" print(e)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"When using pydantic to initialize a `Guard`, input validators can be specified by composition, as such:"
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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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"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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"Validation failed for field with errors: Value must be exactly two words\n"
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]
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}
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],
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"source": [
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"from guardrails.hub import TwoWords\n",
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"from pydantic import BaseModel\n",
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"\n",
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"\n",
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"class Pet(BaseModel):\n",
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" name: str\n",
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" age: int\n",
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"\n",
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"\n",
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"guard = Guard.for_pydantic(Pet)\n",
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"guard.use(TwoWords(on_fail=\"exception\"), on=\"messages\")\n",
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"\n",
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"try:\n",
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" guard(\n",
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" model=\"gpt-4o\",\n",
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" messages=[{\"role\": \"user\", \"content\": \"This is not two words\"}],\n",
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" )\n",
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"except ValidationError as e:\n",
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" print(e)"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": ".venv (3.10.16)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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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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"version": "3.10.16"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 1
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}
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