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참고/guardrails-main/docs/examples/constrained_decoding.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
+      "To disable this warning, you can either:\n",
+      "\t- Avoid using `tokenizers` before the fork if possible\n",
+      "\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n"
+     ]
+    }
+   ],
+   "source": [
+    "! pip install ipywidgets \"transformers>=4.38.0,<5.0.0\" \"torch>=2.1.1,<3.0.0\" \"guardrails-jsonformer>=0.13.1,<1.0.0\" -q"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/dtam/dev/guardrails/guardrails/validator_service/__init__.py:85: UserWarning: Could not obtain an event loop. Falling back to synchronous validation.\n",
+      "  warnings.warn(\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{\n",
+      "  \"dogs\": [\n",
+      "    {\n",
+      "      \"name\": \"Max\",\n",
+      "      \"color\": \"red\",\n",
+      "      \"weight_kg\": 20.555\n",
+      "    },\n",
+      "    {\n",
+      "      \"name\": \"Lola\",\n",
+      "      \"color\": \"blue\",\n",
+      "      \"weight_kg\": 15.234\n",
+      "    },\n",
+      "    {\n",
+      "      \"name\": \"Sarah\",\n",
+      "      \"color\": \"green\",\n",
+      "      \"weight_kg\": 10.567\n",
+      "    }\n",
+      "  ]\n",
+      "}\n"
+     ]
+    }
+   ],
+   "source": [
+    "from guardrails import Guard\n",
+    "from pydantic import BaseModel\n",
+    "\n",
+    "# JSONFormer is only compatible with HF Pipelines and HF Models:\n",
+    "from transformers import pipeline\n",
+    "\n",
+    "\n",
+    "class Dog(BaseModel):\n",
+    "    name: str\n",
+    "    color: str\n",
+    "    weight_kg: float\n",
+    "\n",
+    "\n",
+    "class NewFriends(BaseModel):\n",
+    "    dogs: list[Dog]\n",
+    "\n",
+    "\n",
+    "guard = Guard.for_pydantic(NewFriends, output_formatter=\"jsonformer\")\n",
+    "\n",
+    "\n",
+    "tiny_llama_pipeline = pipeline(\"text-generation\", \"TinyLlama/TinyLlama-1.1B-Chat-v1.0\")\n",
+    "\n",
+    "# Inference is straightforward:\n",
+    "response = guard(\n",
+    "    tiny_llama_pipeline,\n",
+    "    messages=[{\"role\": \"user\", \"content\": \"Please enjoy this list of good dogs:\"}],\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# `out` is a dict.  Format it as JSON for readability:\n",
+    "import json\n",
+    "\n",
+    "print(json.dumps(response.validated_output, indent=2))"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "litellm",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}