LangTrace - Trace Attributes
Project description
LangTrace - Trace Attributes
This repository hosts the JSON schema definitions and the generated model code for both Python and TypeScript. It's designed to streamline the development process across different programming languages, ensuring consistency in data structure and validation logic. The repository includes tools for automatically generating model code from JSON schema definitions, simplifying the task of keeping model implementations synchronized with schema changes.
Repository Structure
/
├── schemas/ # JSON schema definitions
│ └── openai_span_attributes.json
├── scripts/ # Shell scripts for model generation
│ └── generate_python.sh
├── generated/ # Generated model code
│ ├── python/ # Python models
│ └── typescript/ # TypeScript interfaces
├── package.json
├── requirements.txt
├── README.md
└── .gitignore
Prerequisites
Before you begin, make sure you have the following installed on your system:
- Node.js and npm
- Python and pip
ts-node
for running TypeScript scripts directly (install globally vianpm install -g ts-node
)datamodel-code-generator
for Python model generation (install viapip install datamodel-code-generator
)
Generating Models
Python Models
To generate Python models from a JSON schema, use the generate_python.sh
script located in the scripts
directory. This script takes the path to a JSON schema file as an argument and generates a Python model in the generated/python
directory.
./scripts/generate_python.sh schemas/openai_span_attributes.json
TypeScript Interfaces
To generate TypeScript interfaces from a JSON schema, use the schema_to_interface.ts
script located in the src/models
directory. This script also takes the path to a JSON schema file as an argument and generates a TypeScript interface in the generated/typescript
directory.
ts-node src/models/schema_to_interface.ts schemas/openai_span_attributes.json
To include instructions for building and uploading your Python package to PyPI, as well as how to automate this process using GitHub Actions, you can update your README.md
file with the following sections:
Building and Uploading Your Package to PyPI
This guide provides instructions on how to manually build your Python package and upload it to the Python Package Index (PyPI), as well as how to automate this process using GitHub Actions.
Manual Upload to PyPI
To manually upload your package to PyPI, follow these steps:
Prerequisites
Ensure you have the latest versions of setuptools
, wheel
, and twine
installed:
pip install --upgrade setuptools wheel twine
Building Your Package
Navigate to your project root (where setup.py
is located) and run:
python setup.py sdist bdist_wheel
This command generates distribution archives in the dist/
directory.
Uploading Your Package
To upload your package to PyPI, use twine
:
twine upload dist/*
You'll be prompted for your PyPI username and password. For token-based authentication, your username is __token__
, and your password is the PyPI token.
Generating a PyPI Token
- Log in to your PyPI account.
- Navigate to Account Settings > API tokens > Add API token.
- Follow the prompts to generate a new token.
- Use this token with
twine
for uploading your package.
Contributing
Contributions are welcome! If you'd like to add a new schema or improve the existing model generation process, please follow these steps:
- Fork the repository.
- Create a new branch for your feature or fix.
- Make your changes.
- Test your changes to ensure the generated models are correct.
- Submit a pull request with a clear description of your changes.
License
This project is licensed under the MIT License. See the LICENSE file for more details.
This README provides a comprehensive overview of the repository, including its purpose, structure, prerequisites for generating models, and guidelines for contributing. Adjust any paths, installation commands, or other details as necessary to fit your project's specific setup and requirements.
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