├── .github └── workflows │ └── publish.yaml ├── .gitignore ├── .python-version ├── LICENSE ├── README.md ├── llm_structure.py └── pyproject.toml /.github/workflows/publish.yaml: -------------------------------------------------------------------------------- 1 | name: Publish Python Package 2 | 3 | on: 4 | release: 5 | types: [created] 6 | 7 | permissions: 8 | contents: read 9 | 10 | jobs: 11 | deploy: 12 | runs-on: ubuntu-latest 13 | environment: release 14 | permissions: 15 | id-token: write 16 | steps: 17 | - uses: actions/checkout@v4 18 | - name: Set up Python 19 | uses: actions/setup-python@v5 20 | with: 21 | python-version: "3.10" 22 | cache: pip 23 | cache-dependency-path: pyproject.toml 24 | - name: Install dependencies 25 | run: | 26 | pip install setuptools wheel build 27 | - name: Build 28 | run: | 29 | python -m build 30 | - name: Publish 31 | uses: pypa/gh-action-pypi-publish@release/v1 -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | # Python-generated files 2 | __pycache__/ 3 | *.py[oc] 4 | build/ 5 | dist/ 6 | wheels/ 7 | *.egg-info 8 | 9 | # Virtual environments 10 | .venv 11 | -------------------------------------------------------------------------------- /.python-version: -------------------------------------------------------------------------------- 1 | 3.10 2 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | Apache License 2 | Version 2.0, January 2004 3 | http://www.apache.org/licenses/ 4 | 5 | TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 6 | 7 | 1. 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For usability, users can define their desired schema in YAML. 8 | 9 | ## Features 10 | 11 | - 🔧 Generate structured outputs according to a simple YAML definition 12 | - 🔄 Support for nested objects and references 13 | - 🤖 Uses OpenAI's native structured output API mode 14 | - 🛡️ Built-in validation using Pydantic 15 | 16 | ## Installation 17 | 18 | Assuming you have `llm` installed already, simply run: 19 | 20 | ```bash 21 | llm install -U llm-structure 22 | ``` 23 | 24 | ## Usage 25 | 26 | ### Schema Definition 27 | 28 | Create a YAML file defining your schema. Note the use of `$ref` which allows for lists of objects in this case. This is the same as defining `List[People]`. 29 | 30 | 31 | ```yaml 32 | # people.yaml 33 | 34 | People: 35 | type: array 36 | items: 37 | $ref: "#/Person" 38 | Person: 39 | name: str 40 | age: int 41 | ``` 42 | 43 | Then run the plugin: 44 | ```bash 45 | llm structure "Chase, 53, and 49 year old Mia went to the market." --schema people.yaml -m gpt-4o 46 | ``` 47 | Alternatively, you can use `STDIN` by specifying `-` as the prompt: 48 | 49 | ```bash 50 | echo "Chase, 53, and 49 year old Mia went to the market." | llm structure - --schema people.yaml -m gpt-4o 51 | ``` 52 | 53 | This prints output directly to the console in JSON format: 54 | 55 | ```json 56 | { 57 | "items": [ 58 | { 59 | "name": "Chase", 60 | "age": 53 61 | }, 62 | { 63 | "name": "Mia", 64 | "age": 49 65 | } 66 | ] 67 | } 68 | ``` 69 | 70 | 71 | 72 | ## Supported Models 73 | 74 | Currently supports OpenAI models: 75 | - o1-2024-12-17 and later 76 | - gpt-4o-mini-2024-07-18 and later 77 | - gpt-4o-2024-08-06 and later 78 | 79 | Integration with Gemini (native) and instructor for the balance of models is coming soon. 80 | 81 | ## Requirements 82 | 83 | - Python 3.8+ 84 | - llm 85 | - PyYAML 86 | - Pydantic 87 | -------------------------------------------------------------------------------- /llm_structure.py: -------------------------------------------------------------------------------- 1 | import llm 2 | import click 3 | from typing import Dict, Any, Type, List 4 | import yaml 5 | from pydantic import BaseModel, create_model 6 | import sys 7 | 8 | 9 | def resolve_ref(ref: str, schema_dict: Dict) -> Dict: 10 | """Resolve a $ref reference in the schema.""" 11 | if not ref.startswith("#/"): 12 | raise ValueError(f"Only local references are supported: {ref}") 13 | 14 | path = ref[2:].split("/") 15 | current = schema_dict 16 | for part in path: 17 | if part not in current: 18 | raise ValueError(f"Invalid reference: {ref}") 19 | current = current[part] 20 | return current 21 | 22 | 23 | def create_models_from_schema(schema_dict: Dict) -> Dict[str, Type[BaseModel]]: 24 | """Create all models defined in the schema.""" 25 | models = {} 26 | 27 | def parse_schema_to_pydantic_model( 28 | schema_dict: Dict, model_name: str = None 29 | ) -> Type[BaseModel]: 30 | """Parse a schema into a Pydantic model, supporting nested objects and references.""" 31 | # If it's a reference, resolve it 32 | if isinstance(schema_dict, dict) and "$ref" in schema_dict: 33 | ref_path = schema_dict["$ref"][2:].split("/") 34 | if ref_path[0] in models: 35 | return models[ref_path[0]] 36 | referenced_schema = { 37 | ref_path[0]: resolve_ref(schema_dict["$ref"], root_schema) 38 | } 39 | return parse_schema_to_pydantic_model(referenced_schema) 40 | 41 | if len(schema_dict) == 1 and isinstance(next(iter(schema_dict.values())), dict): 42 | model_name = next(iter(schema_dict.keys())) 43 | fields_dict = next(iter(schema_dict.values())) 44 | 45 | # Handle array type with items 46 | if ( 47 | isinstance(fields_dict, dict) 48 | and fields_dict.get("type") == "array" 49 | and "items" in fields_dict 50 | ): 51 | item_model = parse_schema_to_pydantic_model(fields_dict["items"]) 52 | # Create a wrapper model for arrays to satisfy OpenAI's object requirement 53 | model = create_model(model_name, items=(List[item_model], ...)) 54 | models[model_name] = model 55 | return model 56 | 57 | # Map string type names to actual types 58 | type_mapping = { 59 | "str": str, 60 | "int": int, 61 | "float": float, 62 | "bool": bool, 63 | "list": List, 64 | "dict": Dict, 65 | } 66 | 67 | # Convert fields 68 | fields: Dict[str, Any] = {} 69 | for field_name, field_type in fields_dict.items(): 70 | if isinstance(field_type, dict): 71 | # Nested object 72 | nested_model = parse_schema_to_pydantic_model( 73 | field_type, field_name 74 | ) 75 | fields[field_name] = (nested_model, ...) 76 | elif isinstance(field_type, str): 77 | python_type = type_mapping.get(field_type, Any) 78 | fields[field_name] = (python_type, ...) 79 | 80 | model = create_model(model_name, **fields) 81 | models[model_name] = model 82 | return model 83 | 84 | return create_model(model_name or "DynamicModel", **{}) 85 | 86 | root_schema = schema_dict 87 | # First pass: create all top-level models 88 | for model_name, model_schema in schema_dict.items(): 89 | if model_name not in models: 90 | parse_schema_to_pydantic_model({model_name: model_schema}) 91 | 92 | return models 93 | 94 | 95 | @llm.hookimpl 96 | def register_commands(cli): 97 | """Register the structure command with the CLI.""" 98 | 99 | @cli.command() 100 | @click.argument("prompt", type=click.STRING) 101 | @click.option("--schema", help="JSON schema to parse against", required=True) 102 | @click.option( 103 | "-m", "--model", default="gpt-4o", help="Model to use for structured output" 104 | ) 105 | def structure(prompt: str, schema: str, model: str): 106 | """Generate structured output based on a JSON schema. 107 | 108 | The output will be validated against the provided JSON schema. 109 | The model must support JSON mode/structured output. 110 | """ 111 | 112 | if prompt == "-": 113 | # Read from stdin 114 | prompt = sys.stdin.read() 115 | 116 | try: 117 | # Load schema from file 118 | with open(schema) as f: 119 | schema_dict = yaml.safe_load(f) 120 | 121 | # Create dynamic Pydantic models from schema 122 | models = create_models_from_schema(schema_dict) 123 | 124 | # For array types, we want the container model 125 | model_name = next(iter(schema_dict.keys())) 126 | DynamicModel = models[model_name] 127 | 128 | # Get the model instance 129 | model_instance = llm.get_model(model) 130 | model_id = model_instance.model_id 131 | 132 | # Supported models per: https://platform.openai.com/docs/guides/structured-outputs/examples#supported-schemas 133 | # o1-2024-12-17 and later 134 | # gpt-4o-mini-2024-07-18 and later 135 | # gpt-4o-2024-08-06 and later 136 | # o3-mini 137 | 138 | # TODO: Make supported models detection more robust 139 | # TODO: Add Gemini native support 140 | # TODO: Add instructor for all other models 141 | 142 | if ("o3" in model_id or "o1" in model_id or "gpt-4o" in model_id) and model_id != "gpt-4": 143 | client = model_instance.get_client() 144 | schema = DynamicModel.model_json_schema() 145 | response = client.beta.chat.completions.parse( 146 | model=model_id, 147 | messages=[{"role": "user", "content": prompt}], 148 | response_format=DynamicModel, 149 | ) 150 | result = response.choices[0].message.content 151 | if result: 152 | print(result) 153 | else: 154 | raise click.BadParameter("No response from model") 155 | else: 156 | raise click.BadParameter("Model does not support structured output") 157 | 158 | except Exception as e: 159 | click.echo(f"Error: {str(e)}", err=True) 160 | raise click.Abort() 161 | -------------------------------------------------------------------------------- /pyproject.toml: -------------------------------------------------------------------------------- 1 | [project] 2 | name = "llm-structure" 3 | version = "0.1.0" 4 | description = "An llm plugin to add structured JSON output support to LLMs" 5 | readme = "README.md" 6 | requires-python = ">=3.10" 7 | authors = [{name = "Kevin Madura"}] 8 | license = {text = "Apache-2.0"} 9 | classifiers = [ 10 | "License :: OSI Approved :: Apache Software License", 11 | "Programming Language :: Python :: 3", 12 | "Programming Language :: Python :: 3.10", 13 | "Topic :: Software Development :: Libraries :: Python Modules" 14 | ] 15 | dependencies = [ 16 | "llm>=0.16", 17 | "click>=8.0.0", 18 | "pydantic>=2.0.0", 19 | ] 20 | 21 | [project.urls] 22 | Homepage = "https://github.com/kmad/llm-structure" 23 | Issues = "https://github.com/kmad/llm-structure/issues" 24 | 25 | [project.entry-points.llm] 26 | structure = "llm_structure" 27 | --------------------------------------------------------------------------------