Semantic Kernel
Lightweight open-source SDK for building AI agents and orchestrating AI models with existing code.
About Semantic Kernel
Semantic Kernel is a lightweight, open-source development kit that lets developers build AI agents and integrate AI models into C#, Python, or Java codebases. It acts as middleware that translates AI model requests into function calls against your existing code and passes results back, combining prompts with existing APIs to automate business processes. It offers connectors to AI services, a plugin system based on OpenAPI specifications, planners, and memory abstractions for building enterprise-grade AI solutions.
Commonly Cited Strengths & Limitations
Strengths
- Flexible, modular, and observable
- Enterprise-ready and used by Microsoft and other Fortune 500 companies
- Version 1.0+ support across C#, Python, and Java with commitment to non-breaking changes
- Future-proof design that easily connects to the latest AI models
Common Use Cases
- Building AI-powered chatbots and conversational agents
- Integrating AI into existing enterprise applications
- Creating automated AI function chains for complex tasks
- Developing scalable AI applications incrementally
- Orchestrating multi-step AI workflows
- Automating business processes by combining prompts with existing APIs
Details
- Pricing Model
- Free
- Category
- Developer Tools
Key Features
- Build AI agents that automatically call functions to perform actions
- Middleware translating model requests into function calls and passing results back
- Modular and extensible plugin system for encapsulating functions
- Out-of-the-box connectors for AI services and data sources
- Uses OpenAPI specifications to share extensions with pro or low-code developers
- Kernel as central dependency injection container
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