Semantic Kernel

Overview

Semantic Kernel is a lightweight, open-source development kit that empowers developers to build AI agents and integrate the latest AI models into C#, Python, or Java codebases. It provides a model-agnostic framework for building, orchestrating, and deploying AI agents and multi-agent systems.

Features

• Multi-Agent Orchestration: Build, manage, and scale complex agent workflows with multiple orchestration patterns including Sequential (pipeline) and Concurrent (parallel) execution
• Unified Interface: All orchestration patterns share a unified interface for construction and invocation, making it easy to switch between patterns
• Model Agnostic: Works with OpenAI, Azure OpenAI, Anthropic, Google, and other LLM providers
• Function Calling: Combines prompts with existing APIs to perform actions by describing existing code to AI models
• Memory Management: Built-in support for conversation history and context management
• Cross-Platform: Available for C#, Python, and Java with consistent API design

How It Works

Semantic Kernel acts as middleware that translates model requests to function calls and passes results back to the model. By describing your existing code to AI models, they can be called to address user requests through a structured orchestration layer.

Use Cases

• Building intelligent assistants with specialized skills
• Creating multi-agent systems where agents collaborate on complex tasks
• Integrating LLM capabilities into existing enterprise applications
• Developing context-aware chatbots with memory

Pricing

Free and open-source under the MIT license.