diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml new file mode 100644 index 0000000..9de890e --- /dev/null +++ b/.github/workflows/ci.yml @@ -0,0 +1,73 @@ +name: CI + +on: + push: + branches: [ main ] + pull_request: + branches: [ main ] + +jobs: + test: + runs-on: ubuntu-latest + strategy: + fail-fast: false + matrix: + python-version: ["3.11", "3.12"] + + steps: + - uses: actions/checkout@v4 + + - name: Set up Python ${{ matrix.python-version }} + uses: actions/setup-python@v5 + with: + python-version: ${{ matrix.python-version }} + + - name: Install dependencies + run: | + python -m pip install --upgrade pip + pip install -e ".[dev]" + pip install pytest-cov + + - name: Run linting and type checking + run: | + chmod +x ./lint.sh + ./lint.sh + + - name: Test with pytest + run: | + pytest --cov=pydantic_prompt --cov-report=xml + + - name: Upload coverage to Codecov + uses: codecov/codecov-action@v3 + with: + file: ./coverage.xml + fail_ci_if_error: false + + publish: + needs: test + if: startsWith(github.ref, 'refs/tags/') + runs-on: ubuntu-latest + + steps: + - uses: actions/checkout@v4 + + - name: Set up Python + uses: actions/setup-python@v5 + with: + python-version: "3.10" + + - name: Install build dependencies + run: | + python -m pip install --upgrade pip + pip install build twine + + - name: Build and check package + run: | + python -m build + twine check dist/* + + - name: Publish to PyPI + if: github.event_name == 'push' && startsWith(github.ref, 'refs/tags') + uses: pypa/gh-action-pypi-publish@release/v1 + with: + password: ${{ secrets.PYPI_API_TOKEN }} \ No newline at end of file diff --git a/.python-version b/.python-version new file mode 100644 index 0000000..e4fba21 --- /dev/null +++ b/.python-version @@ -0,0 +1 @@ +3.12 diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000..bd38b7a --- /dev/null +++ b/LICENSE @@ -0,0 +1,21 @@ +MIT License + +Copyright (c) 2025 MLDSAI Inc., Richard Abrich, and contributors. + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. \ No newline at end of file diff --git a/README.md b/README.md index a4b9b10..bc18a09 100644 --- a/README.md +++ b/README.md @@ -1,2 +1,385 @@ # PydanticPrompt -A simple library to document Pydantic models for structured LLM outputs using standard Python docstrings. + +[![PyPI version](https://img.shields.io/pypi/v/pydantic-prompt.svg)](https://pypi.org/project/pydantic-prompt/) +[![Python Versions](https://img.shields.io/pypi/pyversions/pydantic-prompt.svg)](https://pypi.org/project/pydantic-prompt/) +[![Build Status](https://github.com/OpenAdaptAI/PydanticPrompt/actions/workflows/ci.yml/badge.svg)](https://github.com/OpenAdaptAI/PydanticPrompt/actions) +[![codecov](https://codecov.io/gh/OpenAdaptAI/PydanticPrompt/branch/main/graph/badge.svg)](https://codecov.io/gh/OpenAdaptAI/PydanticPrompt) +[![License](https://img.shields.io/github/license/OpenAdaptAI/PydanticPrompt.svg)](https://github.com/OpenAdaptAI/PydanticPrompt/blob/main/LICENSE) +[![Code style: ruff](https://img.shields.io/badge/code%20style-ruff-000000.svg)](https://github.com/astral-sh/ruff) + +A simple library to document [Pydantic](https://docs.pydantic.dev/) models for structured LLM outputs using standard Python docstrings. + +## Installation + +```bash +pip install pydantic-prompt +``` + +## Requirements + +- Python 3.11 or higher +- Pydantic 2.0 or higher + +## Features + +- Document Pydantic model fields using standard Python docstrings +- Format field documentation for LLM prompts with a single method call +- Automatic type inference and display +- Optional validation rule documentation +- Warnings for undocumented fields +- Seamlessly embeds documentation in your prompts + +## Usage + +### Basic Example + +```python +from pydantic import BaseModel, Field +from typing import Optional +from pydantic_prompt import prompt_schema + +@prompt_schema +class Person(BaseModel): + name: str + """The person's full name""" + + age: int = Field(ge=0) + """Age in years""" + + email: Optional[str] = None + """Contact email address if available""" + +# Use in LLM prompt +prompt = f""" +Please extract a Person object from this text according to the schema below: + +{Person.format_for_llm()} + +Input: Jane Smith, 28, works at Acme Corp. +""" +``` + +### Output + +The `format_for_llm()` method produces output like: + +``` +Person: +- name (str): The person's full name +- age (int): Age in years +- email (str, optional): Contact email address if available +``` + +### Working with Nested Models + +```python +from pydantic import BaseModel +from pydantic_prompt import prompt_schema +from typing import list + +@prompt_schema +class Address(BaseModel): + street: str + """Street name and number""" + + city: str + """City name""" + + postal_code: str + """Postal or ZIP code""" + +@prompt_schema +class Contact(BaseModel): + name: str + """Full name of the contact""" + + addresses: list[Address] = [] + """List of addresses associated with this contact""" + +# The format_for_llm method will nicely format nested structures too +print(Contact.format_for_llm()) +``` + +### Including Validation Rules + +You can include validation rules in the output: + +```python +Person.format_for_llm(include_validation=True) +``` + +Output: + +``` +Person: +- name (str): The person's full name +- age (int): Age in years [Constraints: ge: 0] +- email (str, optional): Contact email address if available +``` + +### Warnings for Undocumented Fields + +By default, PydanticPrompt warns you when fields don't have docstrings: + +```python +@prompt_schema +class PartiallyDocumented(BaseModel): + name: str + """This field has a docstring""" + + age: int + # Missing docstring will generate a warning +``` + +Output: +``` +UserWarning: Field 'age' in PartiallyDocumented has no docstring. Add a docstring for better LLM prompts. +``` + +To disable these warnings: + +```python +@prompt_schema(warn_undocumented=False) +class SilentModel(BaseModel): + name: str + # No warning for missing docstring +``` + +## Real-World Example + +```python +from pydantic import BaseModel, Field +from pydantic_prompt import prompt_schema +from typing import list + +@prompt_schema +class ProductReview(BaseModel): + product_name: str + """The exact name of the product being reviewed""" + + rating: int = Field(ge=1, le=5) + """Rating from 1 to 5 stars, where 5 is best""" + + pros: list[str] + """List of positive aspects mentioned about the product""" + + cons: list[str] + """List of negative aspects mentioned about the product""" + + summary: str + """A brief one-sentence summary of the overall review""" + +# In your LLM prompt +prompt = f""" +Extract a structured product review from the following text. +Return the data according to this schema: + +{ProductReview.format_for_llm(include_validation=True)} + +Review text: +I recently purchased the UltraBook Pro X1 and I've been using it for about two weeks. +The screen is absolutely gorgeous and the battery lasts all day which is fantastic. +However, the keyboard feels a bit mushy and it runs hot when doing anything intensive. +Overall, a solid laptop with a few minor issues that don't detract from the experience. +""" +``` + +## How It Works + +PydanticPrompt uses Python's introspection capabilities to: + +1. Capture docstrings defined after field declarations +2. Extract type information from type hints +3. Identify optional fields +4. Format everything in a clear, LLM-friendly format + +The library is designed to be lightweight and focused on a single task: making it easy to document your data models for LLMs in a way that both developers and AI can understand. + +## Why Use PydanticPrompt? + +- **Consistency**: Document your models once, use everywhere +- **DRY Principle**: No need to duplicate field descriptions between code and prompts +- **Developer-Friendly**: Uses standard Python docstrings +- **LLM-Friendly**: Produces clear, structured documentation that LLMs can easily understand +- **Maintainability**: When your models change, your prompt documentation automatically updates + +## Development + +### Setting up the development environment + +Clone the repository: + +```bash +git clone https://github.com/OpenAdaptAI/PydanticPrompt.git +cd PydanticPrompt +``` + +Create and activate a virtual environment with `uv`: + +```bash +# Create a virtual environment +uv venv + +# Activate the virtual environment +source .venv/bin/activate # On Unix/macOS +# or +.venv\Scripts\activate # On Windows +``` + +Install the package in development mode: + +```bash +# Install the package +uv pip install -e . +``` + +Install development dependencies: + +```bash +# Install dev dependencies +uv pip install -e ".[dev]" +``` + +### Note about hardlinking warning + +If you see a warning about hardlinking when installing: + +``` +warning: Failed to hardlink files; falling back to full copy. This may lead to degraded performance. +``` + +This is normal when the cache and target directories are on different filesystems. You can suppress this warning with: + +```bash +export UV_LINK_MODE=copy +``` + +### Running tests + +Make sure your virtual environment is activated, then run: + +```bash +# Run all tests +pytest + +# Run with verbose output +pytest -v + +# Run with coverage information +pytest --cov=pydantic_prompt +``` + +### Code formatting and linting + +You can run all formatting and linting checks with: + +```bash +# Run all linting and formatting +./lint.sh +``` + +Or run individual commands: + +```bash +# Format code +ruff format . + +# Check code +ruff check . + +# Auto-fix issues +ruff check --fix . + +# Type check +mypy pydantic_prompt +``` + +## License + +MIT +``` + +# Updated PR Description + +``` +# Initial Implementation of PydanticPrompt Library + +This PR introduces PydanticPrompt, a lightweight Python library for documenting Pydantic models for LLM interactions using standard Python docstrings. + +## Overview + +PydanticPrompt allows developers to document their Pydantic models with standard Python docstrings and then easily format that documentation for inclusion in LLM prompts, providing a clean, consistent way to describe expected outputs for large language models. + +## Key Features + +- **Simple decorator interface** (`@prompt_schema`) +- **Uses standard Python docstrings** for field documentation +- **Automatic type inference** including generics and nested models +- **Optional validation rule display** +- **Warnings for undocumented fields** +- **Seamless integration** with existing Pydantic models + +## Implementation Details + +- Core functionality built around field inspection and docstring extraction +- Uses Pydantic's JSON schema for validation rule discovery +- Modern type annotations with mypy validation +- Automated CI setup with GitHub Actions +- Comprehensive linting with Ruff + +## Example Usage + +```python +from pydantic import BaseModel, Field +from pydantic_prompt import prompt_schema + +@prompt_schema +class UserProfile(BaseModel): + name: str + """The full name of the user""" + + age: int = Field(ge=0) + """User's age in years - must be a positive integer""" + + email: str = Field(pattern=r"[^@]+@[^@]+\.[^@]+") + """Valid email address that will be used for communication""" + +# In an LLM prompt +prompt = f""" +Extract a UserProfile from this text according to this schema: + +{UserProfile.format_for_llm(include_validation=True)} + +Text: John Doe is 32 years old, contact him at john.doe@example.com +""" +``` + +## Test Results + +All tests are passing: + +``` +====================================================================== test session starts ====================================================================== +platform linux -- Python 3.12.1, pytest-8.3.5, pluggy-1.5.0 -- /workspaces/PydanticPrompt/.venv/bin/python +cachedir: .pytest_cache +rootdir: /workspaces/PydanticPrompt +configfile: pyproject.toml +testpaths: tests +collected 4 items + +tests/test_pydantic_prompt.py::test_basic_docstring_extraction PASSED [ 25%] +tests/test_pydantic_prompt.py::test_optional_fields PASSED [ 50%] +tests/test_pydantic_prompt.py::test_validation_rules PASSED [ 75%] +tests/test_pydantic_prompt.py::test_nested_models PASSED [100%] + +======================================================================= 4 passed in 0.13s ======================================================================= +``` + +## Changes Made + +- Created core implementation with docstring extraction +- Added comprehensive type hints with mypy validation +- Set up CI with GitHub Actions for automated testing +- Added linting script for consistent code style +- Implemented warnings for undocumented fields +- Created detailed documentation and examples \ No newline at end of file diff --git a/lint.sh b/lint.sh new file mode 100755 index 0000000..4cae960 --- /dev/null +++ b/lint.sh @@ -0,0 +1,20 @@ +#!/bin/bash +set -e + +# Format code +echo "Formatting code with ruff..." +ruff format . + +# Fix auto-fixable issues (including unsafe fixes for typing upgrades) +echo "Fixing issues with ruff..." +ruff check --fix --unsafe-fixes . + +# Run the linter to show any remaining issues +echo "Running final check..." +ruff check . + +# Type checking +echo "Type-checking with mypy..." +mypy pydantic_prompt + +echo "All checks completed!" \ No newline at end of file diff --git a/pydantic_prompt/__init__.py b/pydantic_prompt/__init__.py new file mode 100644 index 0000000..793253e --- /dev/null +++ b/pydantic_prompt/__init__.py @@ -0,0 +1,4 @@ +from pydantic_prompt.core import prompt_schema + +__all__ = ["prompt_schema"] +__version__ = "0.1.0" \ No newline at end of file diff --git a/pydantic_prompt/core.py b/pydantic_prompt/core.py new file mode 100644 index 0000000..ceddb18 --- /dev/null +++ b/pydantic_prompt/core.py @@ -0,0 +1,220 @@ +import inspect +import warnings +from typing import TypeVar, Union, get_args, get_origin, Callable, Any, Optional, cast + +from pydantic import BaseModel + +T = TypeVar('T', bound=BaseModel) + + +def prompt_schema(cls: type[T], *, warn_undocumented: bool = True) -> type[T]: + """ + Decorator to add LLM documentation methods to a Pydantic model. + + Args: + cls: The Pydantic model class to decorate + warn_undocumented: Whether to emit warnings for fields without docstrings + + Returns: + The decorated class with format_for_llm method + """ + + def format_for_llm_impl(cls_param: type[T], include_validation: bool = False) -> str: + """Format this model's fields and docstrings for LLM prompts.""" + lines = [f"{cls_param.__name__}:"] + + # Get JSON schema to extract validation info if needed + json_schema = cls_param.model_json_schema() if include_validation else {} + properties = json_schema.get("properties", {}) + + # Iterate through each field + for name, field_info in cls_param.model_fields.items(): + # Get the field's type + field_type = _get_field_type_name(field_info) + + # Get docstring for the field + docstring = _extract_field_docstring(cls_param, name) + + # Warn if field is not documented + if warn_undocumented and not docstring: + warnings.warn( + f"Field '{name}' in {cls_param.__name__} has no docstring. " + "Add a docstring for better LLM prompts.", + UserWarning, + stacklevel=2 + ) + + # Determine if field is optional + is_optional = not field_info.is_required() + optional_str = ", optional" if is_optional else "" + + # Format the field line + field_line = f"- {name} ({field_type}{optional_str}): {docstring}" + + # Add validation info if requested + if include_validation and name in properties: + field_schema = properties[name] + + constraints = [] + # Common validation keywords + for key in ["minLength", "maxLength", "minimum", "maximum", "pattern"]: + if key in field_schema: + # Convert camelCase to snake_case for display + display_key = "".join( + ["_" + c.lower() if c.isupper() else c for c in key] + ).lstrip("_") + # Special case mappings + if display_key == "minimum": + display_key = "ge" + elif display_key == "maximum": + display_key = "le" + elif display_key == "min_length": + display_key = "min_length" + elif display_key == "max_length": + display_key = "max_length" + + constraints.append(f"{display_key}: {field_schema[key]}") + + if constraints: + field_line += f" [Constraints: {', '.join(constraints)}]" + + lines.append(field_line) + + return "\n".join(lines) + + # Add the format_for_llm method to the class using the classmethod decorator + setattr(cls, "format_for_llm", classmethod(format_for_llm_impl)) # type: ignore + + return cls + + +def _extract_field_docstring(cls: type, field_name: str) -> str: + """Extract docstring for a field from class source code.""" + try: + source = inspect.getsource(cls) + + # Look for field definition + patterns = [ + f"{field_name}:", + f"{field_name} :", + f"{field_name} =" + ] + + field_pos = -1 + for pattern in patterns: + pos = source.find(pattern) + if pos != -1: + field_pos = pos + break + + if field_pos == -1: + return "" + + # Look for triple-quoted docstring + for quote in ['"""', "'''"]: + doc_start = source.find(quote, field_pos) + if doc_start != -1: + doc_end = source.find(quote, doc_start + 3) + if doc_end != -1: + return source[doc_start + 3:doc_end].strip() + + except Exception: + pass + + return "" + + +def _get_field_type_name(field_info: Any) -> str: + """Get a user-friendly type name from a field.""" + annotation = field_info.annotation + + # Handle Optional types + if get_origin(annotation) is Union and type(None) in get_args(annotation): + args = get_args(annotation) + for arg in args: + if arg is not type(None): + # Remove Optional wrapper, we handle optionality separately + annotation = arg + break + + # Handle basic types + if isinstance(annotation, type): + return annotation.__name__ + + # Handle parameterized generics + origin = get_origin(annotation) + if origin is not None: + args = get_args(annotation) + + # Handle list types + if origin is list or str(origin).endswith("list"): + arg_type = args[0] + inner_type = "" + + # Get the name of the inner type more reliably + if isinstance(arg_type, type): + inner_type = arg_type.__name__ + elif hasattr(arg_type, "_name") and arg_type._name: + inner_type = arg_type._name + else: + # Fall back to string representation with cleanup + inner_type = str(arg_type).replace("typing.", "").strip("'<>") + + # Extract class name from ForwardRef if needed + if "ForwardRef" in inner_type: + import re + match = re.search(r"ForwardRef\('([^']+)'\)", inner_type) + if match: + inner_type = match.group(1) + + return f"list[{inner_type}]" + + # Handle dict types + if origin is dict or str(origin).endswith("dict"): + key_type = args[0] + val_type = args[1] + + # Get key type name + if isinstance(key_type, type): + key_name = key_type.__name__ + else: + key_name = str(key_type).replace("typing.", "") + + # Get value type name + if isinstance(val_type, type): + val_name = val_type.__name__ + else: + val_name = str(val_type).replace("typing.", "") + + return f"dict[{key_name}, {val_name}]" + + # Handle other generic types + origin_name = origin.__name__ if hasattr(origin, "__name__") else str(origin) + origin_name = origin_name.lower() # Convert List to list, etc. + + arg_strs = [] + for arg in args: + if isinstance(arg, type): + arg_strs.append(arg.__name__) + else: + arg_str = str(arg).replace("typing.", "") + if "ForwardRef" in arg_str: + import re + match = re.search(r"ForwardRef\('([^']+)'\)", arg_str) + if match: + arg_str = match.group(1) + arg_strs.append(arg_str) + + return f"{origin_name}[{', '.join(arg_strs)}]" + + # For any other types + type_str = str(annotation).replace("typing.", "") + + # Clean up ForwardRef representation + if "ForwardRef" in type_str: + import re + match = re.search(r"ForwardRef\('([^']+)'\)", type_str) + if match: + return match.group(1) + + return type_str \ No newline at end of file diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 0000000..b116289 --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,80 @@ +[build-system] +requires = ["hatchling"] +build-backend = "hatchling.build" + +[project] +name = "pydantic-prompt" +version = "0.1.0" +description = "Document Pydantic models for structured LLM outputs using Python docstrings" +readme = "README.md" +authors = [ + {name = "Richard Abrich", email = "richard@openadapt.ai"} +] +license = {text = "MIT"} +classifiers = [ + "Programming Language :: Python :: 3", + "Programming Language :: Python :: 3.11", + "Programming Language :: Python :: 3.12", + "License :: OSI Approved :: MIT License", + "Operating System :: OS Independent", + "Development Status :: 4 - Beta", + "Intended Audience :: Developers", + "Topic :: Software Development :: Libraries :: Python Modules", +] +dependencies = [ + "pydantic>=2.0.0", +] +requires-python = ">=3.11" + +[project.optional-dependencies] +dev = [ + "pytest", + "mypy", + "ruff", +] + +[project.urls] +"Homepage" = "https://github.com/OpenAdaptAI/PydanticPrompt" +"Bug Tracker" = "https://github.com/OpenAdaptAI/PydanticPrompt/issues" + +[tool.pytest.ini_options] +testpaths = ["tests"] + +[tool.mypy] +python_version = "3.9" +warn_return_any = true +warn_unused_configs = true +disallow_untyped_defs = true +disallow_incomplete_defs = true + +[tool.ruff] +line-length = 88 +target-version = "py39" + +[tool.ruff.lint] +select = [ + "E", # pycodestyle errors + "F", # pyflakes + "I", # isort + "B", # flake8-bugbear + "C4", # flake8-comprehensions + "RET", # flake8-return + "SIM", # flake8-simplify + "N", # pep8-naming + "UP", # pyupgrade +] +ignore = [] + +[tool.ruff.lint.isort] +known-first-party = ["pydantic_prompt"] + +[tool.ruff.format] +quote-style = "double" +indent-style = "space" +skip-magic-trailing-comma = false +line-ending = "auto" + +[dependency-groups] +dev = [ + "pytest-cov>=6.0.0", +] diff --git a/tests/test_pydantic_prompt.py b/tests/test_pydantic_prompt.py new file mode 100644 index 0000000..a95f2c2 --- /dev/null +++ b/tests/test_pydantic_prompt.py @@ -0,0 +1,79 @@ +from typing import Optional + +from pydantic import BaseModel, Field +from pydantic_prompt import prompt_schema + + +def test_basic_docstring_extraction(): + @prompt_schema + class BasicModel(BaseModel): + name: str + """The user's name""" + + age: int + """Age in years""" + + output = BasicModel.format_for_llm() + assert "name (str): The user's name" in output + assert "age (int): Age in years" in output + + +def test_optional_fields(): + @prompt_schema + class OptionalFieldsModel(BaseModel): + required: str + """Required field""" + + optional: Optional[str] = None + """Optional field""" + + output = OptionalFieldsModel.format_for_llm() + assert "required (str):" in output + assert "optional (str, optional):" in output + + +def test_validation_rules(): + @prompt_schema + class ValidationModel(BaseModel): + name: str = Field(min_length=2, max_length=50) + """User name""" + + age: int = Field(ge=0, le=120) + """Age in years""" + + # Without validation + basic_output = ValidationModel.format_for_llm() + assert "Constraints" not in basic_output + + # With validation + validation_output = ValidationModel.format_for_llm(include_validation=True) + assert "Constraints: min_length: 2, max_length: 50" in validation_output + assert "Constraints: ge: 0, le: 120" in validation_output + + +def test_nested_models(): + @prompt_schema + class Address(BaseModel): + street: str + """Street address""" + + city: str + """City name""" + + @prompt_schema + class Person(BaseModel): + name: str + """Person's name""" + + addresses: list[Address] = [] + """List of addresses""" + + output = Person.format_for_llm() + assert "name (str): Person's name" in output + + # More flexible assertion that checks for the important parts + assert "addresses (list[Address], optional): List of addresses" in output or ( + "addresses (list[" in output and + "Address" in output and + "optional): List of addresses" in output + ) \ No newline at end of file diff --git a/uv.lock b/uv.lock new file mode 100644 index 0000000..180f91b --- /dev/null +++ b/uv.lock @@ -0,0 +1,431 @@ +version = 1 +revision = 1 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