A comprehensive open-source toolkit for AI-powered analysis and interpretation of SEC EDGAR filings, providing valuable insights for investors, fintech developers, and researchers.
Project description
sec-ai
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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
- Become part of our Discord community
- Report bugs in Issues
- Stay updated and contribute to our project's direction in Announcements and Roadmap
- Learn How to Contribute
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
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 tosec-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 aboutsec-parser
and the upcoming sec-ai feature as we are, we warmly invite you to get involved!
- Join our Discussions and connect with us on Discord.
- Please review our Contribution Guide for sec-parser.
- Explore the current Issues or propose new enhancements to thesec-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
How to Import Modules In Your Code
To ensure your code remains functional even when we update sec-ai
, it's recommended to avoid complex imports. Don't use intricate import statements that go deep into the package, like this:
from sec_ai.some_package.internal_utils import SomeInternalClass
Here are the suggested ways to import modules from sec-ai
:
Basic Import
- Standard Way: Use
import sec_ai as sai
This imports the main package assai
. You can then access its functionalities usingsai.
prefix.
Specific Import
- Package-Level Import: Use
from sec_ai import SomeClass
This allows you to directly useSomeClass
without any prefix.
Submodule Import
- Submodule: Use
from sec_ai import some_package
This imports thesome_package
submodule, and you can access its classes and functions usingsome_package.
prefix.
More Specific Submodule Import
- Submodule-Level: Use
from sec_ai.some_package import SomeClass
This imports a specific classSomeClass
from thesome_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.
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