AI/참고/guardrails-main/docs/examples/input_validation.ipynb

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      "Installing hub:\u001b[35m/\u001b[0m\u001b[35m/guardrails/\u001b[0m\u001b[95mtwo_words...\u001b[0m\n",
      "✅Successfully installed guardrails/two_words version \u001b[1;36m0.0\u001b[0m.\u001b[1;36m0\u001b[0m!\n",
      "\n",
      "\n"
     ]
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   ],
   "source": [
    "! guardrails hub install hub://guardrails/two_words --quiet"
   ]
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   "source": [
    "## Input Validation\n",
    "\n",
    "Guardrails supports validating inputs (messages) with string validators."
   ]
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In XML, specify the validators on the `messages` tag, as such:"
   ]
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   "source": [
    "from guardrails import Guard\n",
    "\n",
    "rail_spec = \"\"\"\n",
    "<rail version=\"0.1\">\n",
    "<messages\n",
    "    validators=\"hub://guardrails/two_words\"\n",
    "    on-fail-two-words=\"exception\"\n",
    ">\n",
    "<message role=\"user\">\n",
    "This is not two words\n",
    "</message>\n",
    "</messages>\n",
    "\n",
    "<output type=\"string\">\n",
    "</output>\n",
    "</rail>\n",
    "\"\"\"\n",
    "\n",
    "guard = Guard.for_rail_string(rail_spec)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When `fix` is specified as the on-fail handler, the prompt will automatically be amended before calling the LLM.\n",
    "\n",
    "In any other case (for example, `exception`), a `ValidationError` will be returned in the outcome."
   ]
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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",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "from guardrails.errors import ValidationError\n",
    "\n",
    "# Add your OPENAI_API_KEY as an environment variable if it's not already set\n",
    "# import os\n",
    "# os.environ[\"OPENAI_API_KEY\"] = \"YOUR_API_KEY\"\n",
    "\n",
    "try:\n",
    "    guard(model=\"gpt-4o\")\n",
    "except ValidationError as e:\n",
    "    print(e)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When using pydantic to initialize a `Guard`, input validators can be specified by composition, as such:"
   ]
  },
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   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Validation failed for field with errors: Value must be exactly two words\n"
     ]
    }
   ],
   "source": [
    "from guardrails.hub import TwoWords\n",
    "from pydantic import BaseModel\n",
    "\n",
    "\n",
    "class Pet(BaseModel):\n",
    "    name: str\n",
    "    age: int\n",
    "\n",
    "\n",
    "guard = Guard.for_pydantic(Pet)\n",
    "guard.use(TwoWords(on_fail=\"exception\"), on=\"messages\")\n",
    "\n",
    "try:\n",
    "    guard(\n",
    "        model=\"gpt-4o\",\n",
    "        messages=[{\"role\": \"user\", \"content\": \"This is not two words\"}],\n",
    "    )\n",
    "except ValidationError as e:\n",
    "    print(e)"
   ]
  }
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