prob_jsonformer/example.ipynb

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     "text": [
      "/home/ubuntu/jsonllm/.venv/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
      "  from .autonotebook import tqdm as notebook_tqdm\n"
     ]
    },
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading model and tokenizer...\n",
      "Loaded model and tokenizer\n"
     ]
    }
   ],
   "source": [
    "from transformers import AutoModelForCausalLM, AutoTokenizer\n",
    "\n",
    "print(\"Loading model and tokenizer...\")\n",
    "model_name = \"databricks/dolly-v2-12b\"\n",
    "model = AutoModelForCausalLM.from_pretrained(model_name, use_cache=True)\n",
    "tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=True, use_cache=True)\n",
    "print(\"Loaded model and tokenizer\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generating...\n",
      "{\n",
      "  temperature: \u001b[32m2.2225\u001b[0m,\n",
      "  humidity: \u001b[32m1.0\u001b[0m,\n",
      "  wind_speed: {\n",
      "    value: \u001b[32m0.0\u001b[0m,\n",
      "    unit: \u001b[32m\"value\"\u001b[0m\n",
      "  }\n",
      "}\n"
     ]
    }
   ],
   "source": [
    "from jsonformer.format import highlight_values\n",
    "from jsonformer.main import Jsonformer\n",
    "\n",
    "weather_schema = {\n",
    "    \"type\": \"object\",\n",
    "    \"properties\": {\n",
    "        \"temperature\": {\"type\": \"number\"},\n",
    "        \"humidity\": {\n",
    "            \"type\": \"number\",\n",
    "        },\n",
    "        \"wind_speed\": {\n",
    "            \"type\": \"object\",\n",
    "            \"properties\": {\n",
    "                \"value\": {\"type\": \"number\"},\n",
    "                \"unit\": {\"type\": \"string\"},\n",
    "            },\n",
    "        },\n",
    "    },\n",
    "}\n",
    "\n",
    "builder = Jsonformer(\n",
    "    model=model,\n",
    "    tokenizer=tokenizer,\n",
    "    json_schema=weather_schema,\n",
    "    prompt=\"generate the weather\",\n",
    ")\n",
    "\n",
    "print(\"Generating...\")\n",
    "output = builder()\n",
    "\n",
    "highlight_values(output)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generating...\n",
      "{\n",
      "  make: \u001b[32m\"Ford\"\u001b[0m,\n",
      "  model: \u001b[32m\"Mustang\"\u001b[0m,\n",
      "  year: \u001b[32m10.0\u001b[0m,\n",
      "  colors: [\n",
      "    \u001b[32m\"red\"\u001b[0m,\n",
      "    \u001b[32m\"white\"\u001b[0m,\n",
      "    \u001b[32m\"blue\"\u001b[0m,\n",
      "    \u001b[32m\"black\"\u001b[0m,\n",
      "    \u001b[32m\"yellow\"\u001b[0m,\n",
      "    \u001b[32m\"orange\"\u001b[0m,\n",
      "    \u001b[32m\"green\"\u001b[0m,\n",
      "    \u001b[32m\"pink\"\u001b[0m,\n",
      "    \u001b[32m\"purple\"\u001b[0m,\n",
      "    \u001b[32m\"violet\"\u001b[0m\n",
      "  ]\n",
      "}\n"
     ]
    }
   ],
   "source": [
    "car = {\n",
    "    \"type\": \"object\",\n",
    "    \"properties\": {\n",
    "        \"make\": {\"type\": \"string\"},\n",
    "        \"model\": {\"type\": \"string\"},\n",
    "        \"year\": {\"type\": \"number\"},\n",
    "        \"colors\": {\n",
    "            \"type\": \"array\",\n",
    "            \"items\": {\"type\": \"string\"},\n",
    "        }\n",
    "    },\n",
    "}\n",
    "\n",
    "builder = Jsonformer(\n",
    "    model=model,\n",
    "    tokenizer=tokenizer,\n",
    "    json_schema=car,\n",
    "    prompt=\"generate an example car\",\n",
    ")\n",
    "\n",
    "print(\"Generating...\")\n",
    "output = builder()\n",
    "\n",
    "highlight_values(output)\n"
   ]
  }
 ],
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