Schemaformer is a Python library that leverages the power of Hugging Face Transformers to generate text that follows a specified JSON schema. With Schemaformer, you can easily create coherent and structured text based on a well-defined schema, ensuring consistency and adherence to predefined rules. Importantly it ensures deterministically that the output either is valid for the schema or exausted the max tokens and is a valid prefix for the schema.

Utilizes state-of-the-art transformer models from the Hugging Face library Validates generated text against a user-defined JSON schema Customizable generation parameters for fine-tuning the output

from transformers import AutoModelForCausalLM, AutoTokenizer
from schemaformer.schemaformer import Schemaformer

modelname = "databricks/dolly-v2-3b"
model = AutoModelForCausalLM.from_pretrained(modelname, use_cache=True)
tokenizer = AutoTokenizer.from_pretrained(modelname, use_fast=True, use_cache=True)
schemaformer = Schemaformer(model, tokenizer)

Define your JSON schema and generate text based on the schema:

schema = {
    "type": "object",
    "properties": {
        "name": {"type": "string"},
        "age": {"type": "integer"},
        "city": {"type": "string"}
    },
    "required": ["name", "age", "city"]
}
prompt = "I am Alex I am 24 years old and I live in Pittsburgh"
generated_text = schemaformer(prompt, schema)

print(generated_text)
# {'name': 'Alex', 'age': 24, 'city': 'Pittsburgh'}

You can also use the pattern functionality to constrain the output e.g.:

{
    "type": "object",
    "properties": {
        "name": {"type": "string", "pattern": "A..x.n.er"},
        "age": {"type": "integer"},
        "city": {"type": "string"}
    },
    "required": ["name", "age", "city"]
}
prompt = "I am Alex I am 24 years old and I live in Pittsburgh"
generated_text = schemaformer(prompt, schema)

print(generated_text)
# {"name":"Alexander","age":24,"city":"Pittsburgh"}

Please note that Schemaformer is a work in progress. While the core functionality is in place, much is broken owing to the hastly implemented valid pre-fix checking. We appreciate your understanding and welcome any feedback, contributions, or bug reports to help us improve the library.

There are several areas where Schemaformer can be improved:

Caching portions of the string that have already been validated: As Schemaformer processes the input string, it can benefit from caching portions of the string that have already been validated. This will help avoid redundant checks and speed up the validation process.

More efficiently checking tokens per character: Schemaformer currently checks tokens for each character in the input string. Optimizing the token checking process to better handle large input strings can improve the performance of the application.

Improving support for more JSON Schema features: While Schemaformer currently supports a limited set of JSON Schema features, expanding its support for additional features would make it more versatile and useful in various applications. This may include handling more complex schema structures, supporting additional validation keywords, and implementing features like conditional validation.

Speeding up + paralellizing the valid pre-fix checking.

• Data types (string, number, integer, boolean, array, object, null)
• Pattern (string)
• Enum
• Format (date-time, email, hostname, IPv4, IPv6, URI)
• Required properties
• Min and max length (string and array)
• Unique items (array) [Not proper sorting implementation but works for basic data]
• AllOf, AnyOf, OneOf, and Not

• Conditional schema application
• Dependencies
• MultipleOf (number and integer)
• Default values
• Schema references (JSON pointers and URIs)
• Minimum and maximum values (number and integer)

Schemaformer allows you to customize the generation process by modifying parameters such as the temperature, max tokens, and more:

generated_text = schemaformer.generate_text(
    prompt,
    schema,
    temperature=0.8,
    max_tokens=100
)

We welcome contributions to Schemaformer! If you'd like to help improve the library or report any issues, please feel free to open a pull request or submit an issue on the GitHub repository.

Schemaformer is released under the MIT License. See LICENSE for more information.