[](https://colab.research.google.com/github/1rgs/jsonformer/blob/main/Jsonformer_example.ipynb)
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Generating structured JSON from language models is a challenging task. The generated JSON must be syntactically correct, and it must conform to a schema that specifies the structure of the JSON.
Current approaches to this problem are brittle and error-prone. They rely on prompt engineering, fine-tuning, and post-processing, but they still fail to generate syntactically correct JSON in many cases.
Jsonformer is a new approach to this problem. In structured data, many tokens are fixed and predictable. Jsonformer is a wrapper around Hugging Face models that fills in the fixed tokens during the generation process, and only delegates the generation of content tokens to the language model. This makes it more efficient and bulletproof than existing approaches.
This currently supports a subset of JSON Schema. Below is a list of the supported schema types:
from jsonformer import Jsonformer from transformers import AutoModelForCausalLM, AutoTokenizer model = AutoModelForCausalLM.from_pretrained("databricks/dolly-v2-12b") tokenizer = AutoTokenizer.from_pretrained("databricks/dolly-v2-12b") json_schema = { "type": "object", "properties": { "name": {"type": "string"}, "age": {"type": "number"}, "is_student": {"type": "boolean"}, "courses": { "type": "array", "items": {"type": "string"} } } } prompt = "Generate a person's information based on the following schema:" jsonformer = Jsonformer(model, tokenizer, json_schema, prompt) generated_data = jsonformer() print(generated_data)
{"type": "object", "properties": {"car": {"type": "object", "properties": {"make": {"type": "string"}, "model": {"type": "string"}, "year": {"type": "number"}, "colors": {"type": "array", "items": {"type": "string"}}, "features": {"type": "object", "properties": {"audio": {"type": "object", "properties": {"brand": {"type": "string"}, "speakers": {"type": "number"}, "hasBluetooth": {"type": "boolean"}}}, "safety": {"type": "object", "properties": {"airbags": {"type": "number"}, "parkingSensors": {"type": "boolean"}, "laneAssist": {"type": "boolean"}}}, "performance": {"type": "object", "properties": {"engine": {"type": "string"}, "horsepower": {"type": "number"}, "topSpeed": {"type": "number"}}}}}}}, "owner": {"type": "object", "properties": {"firstName": {"type": "string"}, "lastName": {"type": "string"}, "age": {"type": "number"}}}}}
{ car: { make: "audi", model: "model A8", year: 2016.0, colors: [ "blue" ], features: { audio: { brand: "sony", speakers: 2.0, hasBluetooth: True }, safety: { airbags: 2.0, parkingSensors: True, laneAssist: True }, performance: { engine: "4.0", horsepower: 220.0, topSpeed: 220.0 } } }, owner: { firstName: "John", lastName: "Doe", age: 40.0 } }
pip install jsonformer
Poetry is used for dependency management.
poetry install
poetry run python -m jsonformer.example
Jsonformer is released under the MIT License. You are free to use, modify, and distribute this software for any purpose, commercial or non-commercial, as long as the original copyright and license notice are included.