This is a GPT aggregator of KNOWLEDGE files for the Broadcasting Industry.
Broadcast-GPT aims to build a comprehensive database of broadcast-related documentation to enhance custom GPT models with a diverse range of knowledge files. This repository serves as a hub for collecting user manuals, service manuals, API documentation, data sheets, schematics, diagrams, hardware documentation, software documentation, instructional videos, educational content, standards papers, white papers, GitHub repositories, patents, and more.
- Extensive Knowledge Base: Aggregates various forms of documentation to create a rich source of information for GPT models.
- Multi-Format Support: Users can upload content in various formats including PDF, TXT, DOC, JPG, PNG, GIF, and URLs to YouTube videos.
- Simple Data Collection: A straightforward form located at http://aggregator.ramiroslab.com allows for easy submission of documents and links.
- Visit the Aggregator: Go to https://forms.gle/xAyK5wnkym638FBeA to start contributing documentation.
- Document URL: Submit your files URL in the supported formats (PDF, TXT, DOC, JPG, PNG, GIF). Ensure they are related to broadcast technology and can enrich the GPT's knowledge. If not, indicate on the designated field.
- Contribute Links: Share URLs to relevant YouTube videos or other educational content that can provide valuable insights into broadcast technologies.
We welcome contributions from the community! If you have documentation or links to share, please submit them through our form. For larger contributions or suggestions, please open an issue or pull request in this repository.
- Ensure all submitted content is relevant and beneficial to the Broadcast-GPT project.
- Respect copyright and intellectual property rights. Only submit content you are legally allowed to share.
For any questions or assistance, please reach out to [email protected] .
A special thanks to everyone who has contributed to building this valuable resource!