Purpose of project :
The purpose of this project is to create a collaborative framework that acts as the central, global standard for sharing high-quality, reusable AI prompts. The ultimate goal is to democratize AI development, empowering users worldwide to build and customize powerful tools, which in turn accelerates innovation and global knowledge sharing.
Purpose of framework :
The framework aims to provide access to complete blueprints for effective AI assistants. This includes sharing the generative AI model, prompts, configurations, and source documents used to build them. It focuses on defining how prompts can be shared and stored, rather than on how the prompts themselves are created.
Rationale:
While tools like Ansible playbooks or Docker Compose files have standardized schemas, no similar schema exists for AI prompts. Establishing a standardized format for AI prompts would make sharing, version-controlling, and collaboration significantly easier. The Prompt Sharing Framework focuses on defining a schema for prompts—what a prompt should or could look like when shared.
What problem are we trying to solve :
The problem this project is trying to solve is that there is currently no similar standard notation available in the open-source community for sharing these AI prompts and blueprints.
Our Goals For AI Development :
To democratize AI by establishing a trusted, high-quality standard that accelerates innovation and empowers users worldwide to build powerful, custom tools.
For Contributors :
Contributors will gain invaluable experience, learn from their peers, and build a public portfolio of their expertise, which enhances their skills and professional reputation. In return, the project's engagement model is built on active collaboration, and we "absolutely expect and encourage contributions" to co-develop this new standard with the community. We are specifically seeking crucial feedback from contributors to influence the framework’s direction based on their real-world needs. We are also inviting the community to collaborate on the active development, testing, and documentation to build the final, high-quality framework.
- Reference Materials:
To keep this README concise, please refer to the following files for detailed specifications and examples
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field_dictionary.txt: Definitions of all keys, parameters, and data types used in this project.
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YAML_example.txt: A standard configuration template showing the expected YAML structure.
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JSON_example1.txt: Sample data payload for [Use Case A ].
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JSON_example2.txt: Sample data payload for [Use Case B ].