Skip to content

Latest commit

 

History

History
116 lines (90 loc) · 8.47 KB

README.md

File metadata and controls

116 lines (90 loc) · 8.47 KB

Note

This project is currently under active development and has not been officially released to the public yet. If you're interested in staying up-to-date with the latest progress and being notified when the project is ready for use, please show your support by starring ⭐️ this repository. By starring the repo, you'll be among the first to know about any updates, releases, or important announcements. Thank you for your interest and patience!

 

sec-ai

Essentials ➔       Documentation Status Licence Project Type: Federation Experimental
Health ➔              GitHub Workflow Status: ci.yml GitHub Workflow Status: cd.yml Last Commit
Quality ➔             Code Style: Black Ruff
Distribution ➔    PyPI version PyPI - Python Version PyPI downloads
Community ➔     Discord X (formerly Twitter) Follow GitHub stars

A comprehensive open-source toolkit for AI-powered analysis and interpretation of SEC EDGAR filings, providing valuable insights for investors, fintech developers, and researchers.


Overview

sec-ai is an open-source project designed to provide a comprehensive toolset for analyzing and interpreting data from SEC filings. Utilizing advanced AI technologies, this project aims to serve a wide range of users, from individual investors to researchers and regulatory bodies.

The project leverages alphanome-ai/sec-parser for its data extraction needs, an essential component that simplifies the parsing of SEC EDGAR HTML documents into a structured and analyzable format.

Disclaimer

Warning This project, sec-ai, is an independent, open-source initiative and has no affiliation, endorsement, or verification by the United States Securities and Exchange Commission (SEC). It utilizes public APIs and data provided by the SEC solely for research, informational, and educational objectives. This tool is not intended for financial advisement or as a substitute for professional investment advice or compliance with securities regulations. The creators and maintainers make no warranties, expressed or implied, about the accuracy, completeness, or reliability of the data and analyses presented. Use this software at your own risk. For accurate and comprehensive financial analysis, consult with qualified financial professionals and comply with all relevant legal requirements. The project maintainers and contributors are not liable for any financial or legal consequences arising from the use of this tool.

Getting Started

To get started, first install the sec-ai package:

pip install sec-ai

Next, please visit the Demo and explore the corresponding source code to understand how to utilize the package effectively.

Best Practices

How to Import Modules In Your Code

To ensure your code remains functional even when we change the internal structure of sec-ai, it's recommended to avoid deep imports. Here is an example of a deep import:

from sec_ai.something_package.internal_utils.core import SomeInternalClass

Here are the suggested ways to import modules from sec-ai:

Root Import (prefix)

  • import sec_ai as sp. This imports the main package as sp. You can then access its functionalities using sp. prefix.

Root Import (direct)

  • from sec_ai import SomeClass: This allows you to directly use SomeClass without any prefix.

Submodule Import (prefix)

  • import sec_ai.something_package**: This imports the something_package submodule, and you can access its classes and functions using something_package. prefix.

Submodule Import (direct)

  • from sec_ai.something_package import SomeClass: This imports a specific class SomeClass from the something_package submodule.

Note The main package sec_ai contains only the most common functionalities. For specialized tasks, please use submodule or submodule-level imports.

Contributing

For information about setting up the development environment, coding standards, and contribution workflows, please refer to our CONTRIBUTING.md guide.

License

This project is licensed under the MIT License - see the LICENSE file for details.