OpenAI Plugin Standard
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A OpenAI Plugin Standard is a specification that enables AI language models to interact with external applications and APIs in a standardized way (allowing developers to create plugins for multiple AI platforms).
- Context:
- It can provide Standard Interface through API specifications and manifest files.
- It can enable AI Model to perform external actions through HTTP requests.
- It can support cross-platform compatibility through standardized protocols.
- It can facilitate secure interaction through authorization controls and predefined contexts.
- It can ensure documentation visibility through conversation context integration.
- It can maintain platform independence through OpenAPI specifications.
- ...
- It can (often) handle real-time data through external service integration.
- It can (often) manage computation tasks through remote service execution.
- It can (often) process user requests through standardized endpoints.
- ...
- It can range from being a Basic Plugin to being an Advanced Integration, depending on its implementation complexity.
- It can range from being a Single Platform Plugin to being a Cross Platform Plugin, depending on its compatibility scope.
- ...
- Examples:
- ...
- Counter-Examples:
- Proprietary Plugin Systems, which lack standard compliance and cross-platform compatibility.
- Ad-hoc API Integrations, which bypass standardized protocols.
- Custom Integration Solutions, which use non-standard interfaces.
- Anthropic Model Context Protocol (MCP), ...
- See: ChatGPT Plugin, Microsoft Copilot Plugin, Semantic Kernel Plugin, OpenAPI Specification, API Standard, Plugin Architecture.
References
2024-12-12
- Perplexity.ai
- Question: Tell me about the OpenAI Plugin Standard - what is it and how does it work? I'm particularly interested in understanding its core components, how it enables AI models to interact with external services, and what makes it a standard specification. Please include details about the manifest file, API specifications, and how it supports cross-platform compatibility.
- Answer: The OpenAI Plugin Standard is a specification that enables AI models to interact with third-party applications through standardized APIs, establishing a framework for external service integration.
- Core Architecture:
- System Components:
- Standardized manifest file (ai-plugin.json).
- OpenAPI specification defining API endpoints.
- System Components:
- Manifest Structure:
- Key Components:
- Schema version indicating the manifest version.
- Name for human serving as the display name.
- Name for model acting as the namespace identifier.
- Description for human providing user-facing documentation.
- Description for model containing technical specifications.
- Key Components:
- Operation Mechanism:
- AI Model Functions:
- Reads the manifest and specifications.
- Interprets user requests.
- Executes API calls for requested actions.
- Combines API responses with language capabilities.
- AI Model Functions:
- Technical Implementation:
- API Integration:
- Developers expose APIs through standardized manifests.
- OpenAPI specification defines functionality.
- AI model makes API calls based on queries.
- API Integration:
- Cross-Platform Support:
- Development Process:
- Implementation Steps:
- Build API endpoints.
- Create OpenAPI documentation.
- Develop manifest file.
- Complete platform registration.
- Implementation Steps:
- Security Framework:
- Core Architecture:
- Citations:
[1] https://www.qodo.ai/blog/openais-chatgpt-plugins-is-the-new-internet-gateway/ [2] https://azure.github.io/aihub/docs/openai-plugins/ [3] https://apidog.com/articles/chatgpt-plugins-open-api/ [4] https://www.hackwithgpt.com/blog/what-is-the-chatgpt-plugin-manifest/ [5] https://openai.com/index/chatgpt-plugins/ [6] https://www.codingthesmartway.com/mastering-chatgpt-plugins-a-comprehensive-guide-for-developers/ [7] https://www.linkedin.com/pulse/exploring-power-openai-chatgpt-plugins-enhancing-ai-rany [8] https://devblogs.microsoft.com/semantic-kernel/skills-to-plugins-fully-embracing-the-openai-plugin-spec-in-semantic-kernel/