sec-ai 0.7.0

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

 

sec-ai

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

See Demo | Read Docs | Join Discussions | Report Bugs

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.

• Explore the Demo
• Read the Documentation
• Join the Discussions to get help, propose ideas, or chat with the community
• Report bugs in Issues
• Stay updated and contribute to our project's direction in Announcements and Roadmap
• Learn How to Contribute

Getting Started

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

pip install sec-ai

Warning We're thrilled to inform you that the sec-parser project is the final prerequisite for launching our eagerly anticipated feature, sec-ai. We're diligently working to ensure that it meets all the necessary standards and functionalities.

Stay Informed: For detailed information and updates specific to sec-parser and to be the first to know when sec-ai is launched, please follow our Announcements page.

Contribute to sec-parser: If you're as excited about sec-parser and the upcoming sec-ai feature as we are, we warmly invite you to get involved!

- Please visit our Contribution Guide for sec-parser.
- Explore current Issues or propose new enhancements to sec-parser.

Our targeted launch for sec-ai is approaching, and we're grateful for your continued anticipation and interest, which are invaluable to our endeavors.

Best Practices

Importing modules

1. Standard: import sec_ai as sai
2. Package-Level: from sec_ai import SomeClass
3. Submodule: from sec_ai import sub_module
4. Submodule-Level: from sec_ai.sub_module import SomeClass

Note The root-level package sec_ai contains only the most common symbols. For more specialized functionalities, you should use submodule or submodule-level imports.

Warning To allow us to maintain backward compatibility with your code during internal structure refactoring for sec-ai, avoid deep or chained imports such as sec_ai.sub_module.internal_utils import SomeInternalClass.

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.