{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/2"}],"enrichment":{"capability":"Semantic Kernel is a Python SDK for building AI agents and multi-agent systems that orchestrate language models, plugins, and tools through a unified framework supporting OpenAI, Azure OpenAI, and other LLM providers.","skillfed_tags":["llm-orchestration","multi-agent-systems","async-framework"],"use_cases":["Build a chatbot that invokes custom Python functions or external APIs as tools in response to user queries.","Orchestrate multiple specialized AI agents (writer, reviewer, critic) to iteratively refine content or solve problems collaboratively.","Create a prompt engineering pipeline that templates and invokes LLM calls with variable substitution and structured response parsing.","Integrate retrieval-augmented generation by connecting agents to vector databases for knowledge-grounded question answering.","Deploy multi-provider LLM applications that can switch between OpenAI, Azure OpenAI, or open-source models without code changes."],"what_it_does":"Semantic Kernel is Microsoft's Python SDK for building and orchestrating AI agents powered by large language models. It abstracts away the complexity of connecting to multiple LLM providers (OpenAI, Azure OpenAI, Hugging Face, Mistral, Google AI, ONNX, Ollama, NVIDIA NIM) and provides a unified interface for prompt engineering, function calling, and structured outputs through Pydantic models.\n\nThe framework enables you to compose agents with plugins (Python functions or OpenAPI specs), coordinate multi-agent workflows through orchestration managers, and build structured business processes. It handles async execution natively, integrates with vector databases for retrieval-augmented generation, and supports multimodal inputs (text, vision, audio). The package is actively maintained, recently transitioned to Microsoft Agent Framework as its enterprise successor, and comes with extensive examples for single-agent and multi-agent scenarios.","worth_installing":"Yes. Semantic Kernel is production-stable (Development Status 5), actively maintained, MIT-licensed, and widely used (top 5000 PyPI packages). Install it if you're building AI agents, need multi-provider LLM support, or want a structured framework for prompt orchestration. The 22 runtime dependencies are substantial but standard for async AI workloads; verify your environment can accommodate them. Note that Microsoft now recommends Microsoft Agent Framework as the forward path for new enterprise projects."},"id":"semantic-kernel","links":{"html":"https://skillfed.io/packages/semantic-kernel","md":"https://skillfed.io/packages/semantic-kernel.md","pypi":"https://pypi.org/project/semantic-kernel/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-06","license_spdx":null,"license_treatment":"permissive","name":"semantic-kernel","python_support":"supports_current","summary":"Semantic Kernel Python SDK"},"popularity":{"monthly_downloads":2765519,"position":2897,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"1.44.1"}