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prob_jsonformer/example.ipynb
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wassname fb12583b58 add example and fix
2024-05-10 18:05:54 +08:00

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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"# autoreload your package\n",
"%load_ext autoreload\n",
"%autoreload 2"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/media/wassname/SGIronWolf/projects5/2024/prob_jsonformer/.venv/lib/python3.9/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"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Loading model and tokenizer...\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/media/wassname/SGIronWolf/projects5/2024/prob_jsonformer/.venv/lib/python3.9/site-packages/huggingface_hub/file_download.py:1132: FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.\n",
" warnings.warn(\n",
"/media/wassname/SGIronWolf/projects5/2024/prob_jsonformer/.venv/lib/python3.9/site-packages/huggingface_hub/file_download.py:1132: FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.\n",
" warnings.warn(\n",
"Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Loaded model and tokenizer\n"
]
}
],
"source": [
"from transformers import AutoModelForCausalLM, AutoTokenizer\n",
"import torch\n",
"\n",
"print(\"Loading model and tokenizer...\")\n",
"model_name = \"databricks/dolly-v2-3b\"\n",
"model = AutoModelForCausalLM.from_pretrained(\n",
" model_name,\n",
" use_cache=True,\n",
" torch_dtype=torch.float16,\n",
" attn_implementation='eager',\n",
").to(\"cuda:0\")\n",
"tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=True, use_cache=True)\n",
"print(\"Loaded model and tokenizer\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Continue"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Generating...\n",
"{\n",
" store: {\n",
" name: \u001b[32m\"Mike's Ski Shop\"\u001b[0m,\n",
" location: \u001b[32m\"Somewhere\"\u001b[0m,\n",
" choice_probs: [\n",
" {\n",
" prob: \u001b[32m0.01739501953125\u001b[0m,\n",
" choice: \u001b[32m\"pretend\"\u001b[0m\n",
" },\n",
" {\n",
" prob: \u001b[32m0.002094268798828125\u001b[0m,\n",
" choice: \u001b[32m\"snowboard\"\u001b[0m\n",
" },\n",
" {\n",
" prob: \u001b[32m0.0007467269897460938\u001b[0m,\n",
" choice: \u001b[32m\"walk\"\u001b[0m\n",
" },\n",
" {\n",
" prob: \u001b[32m0.97998046875\u001b[0m,\n",
" choice: \u001b[32m\"ski\"\u001b[0m\n",
" }\n",
" ],\n",
" inventory: [\n",
" {\n",
" productId: \u001b[32m\"1\"\u001b[0m,\n",
" name: \u001b[32m\"Snowboard X-15\"\u001b[0m,\n",
" description: \u001b[32m\"Snowboard for all levels\"\u001b[0m,\n",
" category: \u001b[32m\"Snowboards\"\u001b[0m,\n",
" price: \u001b[32m20.0375\u001b[0m,\n",
" inStock: \u001b[32mTrue\u001b[0m,\n",
" rating: \u001b[32m5.0\u001b[0m,\n",
" images: [\n",
" \u001b[32m\"https://s3.amazonaws.com/mikesskisport/images/Snow\"\u001b[0m\n",
" ]\n",
" }\n",
" ]\n",
" }\n",
"}\n"
]
}
],
"source": [
"from prob_jsonformer.format import highlight_values\n",
"from prob_jsonformer.main import Jsonformer\n",
"\n",
"ecomm = {\n",
" \"type\": \"object\",\n",
" \"properties\": {\n",
" \"store\": {\n",
" \"type\": \"object\",\n",
" \"properties\": {\n",
" \"name\": {\"type\": \"string\"},\n",
" \"location\": {\"type\": \"string\"},\n",
" \"choice_probs\": {\"type\": \"choice_probs\", \"enum\": [\"ski\", \"snowboard\", \"walk\", \"pretend\"]},\n",
" \"inventory\": {\n",
" \"type\": \"array\",\n",
" \"items\": {\n",
" \"type\": \"object\",\n",
" \"properties\": {\n",
" \"productId\": {\"type\": \"string\"},\n",
" \"name\": {\"type\": \"string\"},\n",
" \"description\": {\"type\": \"string\"},\n",
" \"category\": {\"type\": \"string\"},\n",
" \"price\": {\"type\": \"number\"},\n",
" \"inStock\": {\"type\": \"boolean\"},\n",
" \"rating\": {\"type\": \"number\"},\n",
" \"images\": {\"type\": \"array\", \"items\": {\"type\": \"string\"}},\n",
" },\n",
" },\n",
" },\n",
" },\n",
" }\n",
" },\n",
"}\n",
"\n",
"\n",
"builder = Jsonformer(\n",
" model=model,\n",
" tokenizer=tokenizer,\n",
" json_schema=ecomm,\n",
" prompt=\"write a description about mike's ski shop which sells premium skis and snowboards\",\n",
" max_string_token_length=20,\n",
")\n",
"\n",
"print(\"Generating...\")\n",
"output = builder()\n",
"\n",
"highlight_values(output)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Generating...\n",
"{\n",
" make: \u001b[32m\"Mazda\"\u001b[0m,\n",
" model: [\n",
" {\n",
" prob: \u001b[32m0.8154296875\u001b[0m,\n",
" choice: \u001b[32m\"Kea\"\u001b[0m\n",
" },\n",
" {\n",
" prob: \u001b[32m0.184814453125\u001b[0m,\n",
" choice: \u001b[32m\"Mazda\"\u001b[0m\n",
" }\n",
" ],\n",
" new: [\n",
" {\n",
" prob: \u001b[32m0.90185546875\u001b[0m,\n",
" choice: \u001b[32m\"true\"\u001b[0m\n",
" },\n",
" {\n",
" prob: \u001b[32m0.09808349609375\u001b[0m,\n",
" choice: \u001b[32m\"false\"\u001b[0m\n",
" }\n",
" ],\n",
" rating: [\n",
" {\n",
" prob: \u001b[32m0.221435546875\u001b[0m,\n",
" choice: \u001b[32m\"1\"\u001b[0m\n",
" },\n",
" {\n",
" prob: \u001b[32m0.394775390625\u001b[0m,\n",
" choice: \u001b[32m\"2\"\u001b[0m\n",
" },\n",
" {\n",
" prob: \u001b[32m0.382568359375\u001b[0m,\n",
" choice: \u001b[32m\"3\"\u001b[0m\n",
" },\n",
" {\n",
" prob: \u001b[32m0.0013370513916015625\u001b[0m,\n",
" choice: \u001b[32m\"4\"\u001b[0m\n",
" }\n",
" ],\n",
" year: \u001b[32m2016.0\u001b[0m,\n",
" colors_available: [\n",
" \u001b[32m\"red\"\u001b[0m\n",
" ]\n",
"}\n"
]
}
],
"source": [
"car = {\n",
" \"type\": \"object\",\n",
" \"properties\": {\n",
" \"make\": {\"type\": \"string\"},\n",
" \"model\": {\"type\": \"choice_probs\", \"enum\": [\"Mazda\", \"Kea\"]},\n",
" \"new\": {\"type\": \"choice_probs\", \"enum\": [\"true\", \"false\"]},\n",
" \"rating\": {\"type\": \"choice_probs\", \"enum\": [\"1\", \"2\", \"3\", \"4\"]},\n",
" \"year\": {\"type\": \"number\"},\n",
" \"colors_available\": {\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)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Generating...\n",
"{\n",
" car: {\n",
" make: \u001b[32m\"Rolls Royce\"\u001b[0m,\n",
" model: \u001b[32m\"Phantom\"\u001b[0m,\n",
" year: \u001b[32m2014.0\u001b[0m,\n",
" colors: [\n",
" {\n",
" prob: \u001b[32m0.001560211181640625\u001b[0m,\n",
" choice: \u001b[32m\"white\"\u001b[0m\n",
" },\n",
" {\n",
" prob: \u001b[32m0.833984375\u001b[0m,\n",
" choice: \u001b[32m\"red\"\u001b[0m\n",
" },\n",
" {\n",
" prob: \u001b[32m0.0865478515625\u001b[0m,\n",
" choice: \u001b[32m\"black\"\u001b[0m\n",
" },\n",
" {\n",
" prob: \u001b[32m0.048553466796875\u001b[0m,\n",
" choice: \u001b[32m\"blue\"\u001b[0m\n",
" },\n",
" {\n",
" prob: \u001b[32m0.0294342041015625\u001b[0m,\n",
" choice: \u001b[32m\"green\"\u001b[0m\n",
" }\n",
" ],\n",
" as_new: [\n",
" {\n",
" prob: \u001b[32m0.96533203125\u001b[0m,\n",
" choice: \u001b[32m\"true\"\u001b[0m\n",
" },\n",
" {\n",
" prob: \u001b[32m0.03460693359375\u001b[0m,\n",
" choice: \u001b[32m\"false\"\u001b[0m\n",
" }\n",
" ],\n",
" rating: [\n",
" {\n",
" prob: \u001b[32m0.05462646484375\u001b[0m,\n",
" choice: \u001b[32m\"1\"\u001b[0m\n",
" },\n",
" {\n",
" prob: \u001b[32m0.233642578125\u001b[0m,\n",
" choice: \u001b[32m\"2\"\u001b[0m\n",
" },\n",
" {\n",
" prob: \u001b[32m0.2093505859375\u001b[0m,\n",
" choice: \u001b[32m\"3\"\u001b[0m\n",
" },\n",
" {\n",
" prob: \u001b[32m0.50244140625\u001b[0m,\n",
" choice: \u001b[32m\"4\"\u001b[0m\n",
" }\n",
" ],\n",
" features: {\n",
" audio: {\n",
" brand: \u001b[32m\"Mercedes-Benz\"\u001b[0m,\n",
" speakers: \u001b[32m2.09999\u001b[0m,\n",
" hasBluetooth: \u001b[32mTrue\u001b[0m\n",
" },\n",
" safety: {\n",
" airbags: \u001b[32m2.09999\u001b[0m,\n",
" parkingSensors: \u001b[32mTrue\u001b[0m,\n",
" laneAssist: \u001b[32mTrue\u001b[0m\n",
" },\n",
" performance: {\n",
" engine: \u001b[32m\"Mercedes-Benz 6.2 L\"\u001b[0m,\n",
" horsepower: \u001b[32m423.09999\u001b[0m,\n",
" topSpeed: \u001b[32m220.09999\u001b[0m\n",
" }\n",
" }\n",
" },\n",
" owner: {\n",
" firstName: \u001b[32m\"John\"\u001b[0m,\n",
" lastName: \u001b[32m\"Doe\"\u001b[0m,\n",
" age: \u001b[32m40.09999\u001b[0m\n",
" }\n",
"}\n"
]
}
],
"source": [
"complex_car = {\n",
" \"type\": \"object\",\n",
" \"properties\": {\n",
" \"car\": {\n",
" \"type\": \"object\",\n",
" \"properties\": {\n",
" \"make\": {\"type\": \"string\"},\n",
" \"model\": {\"type\": \"string\"},\n",
" \"year\": {\"type\": \"number\"},\n",
" \"colors\": {\"type\": \"choice_probs\", \"enum\": [\"red\", \"green\", \"blue\", \"black\", \"white\"]},\n",
" \"as_new\": {\"type\": \"choice_probs\", \"enum\": [\"true\", \"false\"]},\n",
" \"rating\": {\"type\": \"choice_probs\", \"enum\": [\"1\", \"2\", \"3\", \"4\"]},\n",
" \"features\": {\n",
" \"type\": \"object\",\n",
" \"properties\": {\n",
" \"audio\": {\n",
" \"type\": \"object\",\n",
" \"properties\": {\n",
" \"brand\": {\"type\": \"string\"},\n",
" \"speakers\": {\"type\": \"number\"},\n",
" \"hasBluetooth\": {\"type\": \"boolean\"},\n",
" },\n",
" },\n",
" \"safety\": {\n",
" \"type\": \"object\",\n",
" \"properties\": {\n",
" \"airbags\": {\"type\": \"number\"},\n",
" \"parkingSensors\": {\"type\": \"boolean\"},\n",
" \"laneAssist\": {\"type\": \"boolean\"},\n",
" },\n",
" },\n",
" \"performance\": {\n",
" \"type\": \"object\",\n",
" \"properties\": {\n",
" \"engine\": {\"type\": \"string\"},\n",
" \"horsepower\": {\"type\": \"number\"},\n",
" \"topSpeed\": {\"type\": \"number\"},\n",
" },\n",
" },\n",
" },\n",
" },\n",
" },\n",
" },\n",
" \"owner\": {\n",
" \"type\": \"object\",\n",
" \"properties\": {\n",
" \"firstName\": {\"type\": \"string\"},\n",
" \"lastName\": {\"type\": \"string\"},\n",
" \"age\": {\"type\": \"number\"},\n",
" },\n",
" },\n",
" },\n",
"}\n",
"builder = Jsonformer(\n",
" model=model,\n",
" tokenizer=tokenizer,\n",
" json_schema=complex_car,\n",
" prompt=\"generate an example Rolls Royce Phantom\",\n",
")\n",
"\n",
"print(\"Generating...\")\n",
"output = builder()\n",
"\n",
"highlight_values(output)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": ".venv",
"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": "3.9.16"
},
"orig_nbformat": 4
},
"nbformat": 4,
"nbformat_minor": 2
}
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