[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-9728":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":11,"languages":10,"totalLinesOfCode":10,"stars":12,"forks":13,"watchers":14,"openIssues":15,"contributorsCount":16,"subscribersCount":16,"size":16,"stars1d":17,"stars7d":18,"stars30d":19,"stars90d":16,"forks30d":16,"starsTrendScore":20,"compositeScore":21,"rankGlobal":10,"rankLanguage":10,"license":22,"archived":23,"fork":23,"defaultBranch":24,"hasWiki":23,"hasPages":23,"topics":25,"createdAt":10,"pushedAt":10,"updatedAt":31,"readmeContent":32,"aiSummary":33,"trendingCount":16,"starSnapshotCount":16,"syncStatus":34,"lastSyncTime":35,"discoverSource":36},9728,"semantic-kernel","microsoft\u002Fsemantic-kernel","microsoft","Integrate cutting-edge LLM technology quickly and easily into your apps","https:\u002F\u002Faka.ms\u002Fsemantic-kernel",null,"C#",28105,4642,292,143,0,14,51,215,54,45,"MIT License",false,"main",[26,27,28,29,30],"ai","artificial-intelligence","llm","openai","sdk","2026-06-12 02:02:11","# Semantic Kernel\n\n> [!IMPORTANT]\n> Semantic Kernel is now [Microsoft Agent Framework](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fagent-framework)! Microsoft Agent Framework (MAF) is the enterprise‑ready successor to Semantic Kernel. Microsoft Agent Framework is now available at version 1.0 as a production-ready release: stable APIs, and a commitment to long-term support. Whether you're building a single assistant or orchestrating a fleet of specialized agents, Microsoft Agent Framework 1.0 gives you enterprise-grade multi-agent orchestration, multi-provider model support, and cross-runtime interoperability via A2A and MCP.\n>\n> Learn more about Semantic Kernel and Agent Framework here: [Semantic Kernel and Microsoft Agent Framework on the Agent Framework blog](https:\u002F\u002Fdevblogs.microsoft.com\u002Fagent-framework\u002Fsemantic-kernel-and-microsoft-agent-framework\u002F), and try out the [Semantic Kernel migration guide](https:\u002F\u002Flearn.microsoft.com\u002Fen-us\u002Fagent-framework\u002Fmigration-guide\u002Ffrom-semantic-kernel).\n\n**Build intelligent AI agents and multi-agent systems with this enterprise-ready orchestration framework**\n\n[![License: MIT](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Flicense\u002Fmicrosoft\u002Fsemantic-kernel)](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fsemantic-kernel\u002Fblob\u002Fmain\u002FLICENSE)\n[![Python package](https:\u002F\u002Fimg.shields.io\u002Fpypi\u002Fv\u002Fsemantic-kernel)](https:\u002F\u002Fpypi.org\u002Fproject\u002Fsemantic-kernel\u002F)\n[![Nuget package](https:\u002F\u002Fimg.shields.io\u002Fnuget\u002Fvpre\u002FMicrosoft.SemanticKernel)](https:\u002F\u002Fwww.nuget.org\u002Fpackages\u002FMicrosoft.SemanticKernel\u002F)\n[![Discord](https:\u002F\u002Fimg.shields.io\u002Fdiscord\u002F1063152441819942922?label=Discord&logo=discord&logoColor=white&color=d82679)](https:\u002F\u002Faka.ms\u002FSKDiscord)\n\n## What is Semantic Kernel?\n\nSemantic Kernel is a model-agnostic SDK that empowers developers to build, orchestrate, and deploy AI agents and multi-agent systems. Whether you're building a simple chatbot or a complex multi-agent workflow, Semantic Kernel provides the tools you need with enterprise-grade reliability and flexibility.\n\n## System Requirements\n\n- **Python**: 3.10+\n- **.NET**: .NET 10.0+ \n- **Java**: JDK 17+\n- **OS Support**: Windows, macOS, Linux\n\n## Key Features\n\n- **Model Flexibility**: Connect to any LLM with built-in support for [OpenAI](https:\u002F\u002Fplatform.openai.com\u002Fdocs\u002Fintroduction), [Azure OpenAI](https:\u002F\u002Fazure.microsoft.com\u002Fen-us\u002Fproducts\u002Fai-services\u002Fopenai-service), [Hugging Face](https:\u002F\u002Fhuggingface.co\u002F), [NVidia](https:\u002F\u002Fwww.nvidia.com\u002Fen-us\u002Fai-data-science\u002Fproducts\u002Fnim-microservices\u002F) and more\n- **Agent Framework**: Build modular AI agents with access to tools\u002Fplugins, memory, and planning capabilities\n- **Multi-Agent Systems**: Orchestrate complex workflows with collaborating specialist agents\n- **Plugin Ecosystem**: Extend with native code functions, prompt templates, OpenAPI specs, or Model Context Protocol (MCP)\n- **Vector DB Support**: Seamless integration with [Azure AI Search](https:\u002F\u002Flearn.microsoft.com\u002Fen-us\u002Fazure\u002Fsearch\u002Fsearch-what-is-azure-search), [Elasticsearch](https:\u002F\u002Fwww.elastic.co\u002F), [Chroma](https:\u002F\u002Fdocs.trychroma.com\u002Fdocs\u002Foverview\u002Fgetting-started), and more\n- **Multimodal Support**: Process text, vision, and audio inputs\n- **Local Deployment**: Run with [Ollama](https:\u002F\u002Follama.com\u002F), [LMStudio](https:\u002F\u002Flmstudio.ai\u002F), or [ONNX](https:\u002F\u002Fonnx.ai\u002F)\n- **Process Framework**: Model complex business processes with a structured workflow approach\n- **Enterprise Ready**: Built for observability, security, and stable APIs\n\n## Installation\n\nFirst, set the environment variable for your AI Services:\n\n**Azure OpenAI:**\n```bash\nexport AZURE_OPENAI_API_KEY=AAA....\n```\n\n**or OpenAI directly:**\n```bash\nexport OPENAI_API_KEY=sk-...\n```\n\n### Python\n\n```bash\npip install semantic-kernel\n```\n\n### .NET\n\n```bash\ndotnet add package Microsoft.SemanticKernel\ndotnet add package Microsoft.SemanticKernel.Agents.Core\n```\n\n### Java\n\nSee [semantic-kernel-java build](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fsemantic-kernel-java\u002Fblob\u002Fmain\u002FBUILD.md) for instructions.\n\n## Quickstart\n\n### Basic Agent - Python\n\nCreate a simple assistant that responds to user prompts:\n\n```python\nimport asyncio\nfrom semantic_kernel.agents import ChatCompletionAgent\nfrom semantic_kernel.connectors.ai.open_ai import AzureChatCompletion\n\nasync def main():\n    # Initialize a chat agent with basic instructions\n    agent = ChatCompletionAgent(\n        service=AzureChatCompletion(),\n        name=\"SK-Assistant\",\n        instructions=\"You are a helpful assistant.\",\n    )\n\n    # Get a response to a user message\n    response = await agent.get_response(messages=\"Write a haiku about Semantic Kernel.\")\n    print(response.content)\n\nasyncio.run(main()) \n\n# Output:\n# Language's essence,\n# Semantic threads intertwine,\n# Meaning's core revealed.\n```\n\n### Basic Agent - .NET\n\n```csharp\nusing Microsoft.SemanticKernel;\nusing Microsoft.SemanticKernel.Agents;\n\nvar builder = Kernel.CreateBuilder();\nbuilder.AddAzureOpenAIChatCompletion(\n                Environment.GetEnvironmentVariable(\"AZURE_OPENAI_DEPLOYMENT\"),\n                Environment.GetEnvironmentVariable(\"AZURE_OPENAI_ENDPOINT\"),\n                Environment.GetEnvironmentVariable(\"AZURE_OPENAI_API_KEY\")\n                );\nvar kernel = builder.Build();\n\nChatCompletionAgent agent =\n    new()\n    {\n        Name = \"SK-Agent\",\n        Instructions = \"You are a helpful assistant.\",\n        Kernel = kernel,\n    };\n\nawait foreach (AgentResponseItem\u003CChatMessageContent> response \n    in agent.InvokeAsync(\"Write a haiku about Semantic Kernel.\"))\n{\n    Console.WriteLine(response.Message);\n}\n\n\u002F\u002F Output:\n\u002F\u002F Language's essence,\n\u002F\u002F Semantic threads intertwine,\n\u002F\u002F Meaning's core revealed.\n```\n\n### Agent with Plugins - Python\n\nEnhance your agent with custom tools (plugins) and structured output:\n\n```python\nimport asyncio\nfrom typing import Annotated\nfrom pydantic import BaseModel\nfrom semantic_kernel.agents import ChatCompletionAgent\nfrom semantic_kernel.connectors.ai.open_ai import AzureChatCompletion, OpenAIChatPromptExecutionSettings\nfrom semantic_kernel.functions import kernel_function, KernelArguments\n\nclass MenuPlugin:\n    @kernel_function(description=\"Provides a list of specials from the menu.\")\n    def get_specials(self) -> Annotated[str, \"Returns the specials from the menu.\"]:\n        return \"\"\"\n        Special Soup: Clam Chowder\n        Special Salad: Cobb Salad\n        Special Drink: Chai Tea\n        \"\"\"\n\n    @kernel_function(description=\"Provides the price of the requested menu item.\")\n    def get_item_price(\n        self, menu_item: Annotated[str, \"The name of the menu item.\"]\n    ) -> Annotated[str, \"Returns the price of the menu item.\"]:\n        return \"$9.99\"\n\nclass MenuItem(BaseModel):\n    price: float\n    name: str\n\nasync def main():\n    # Configure structured output format\n    settings = OpenAIChatPromptExecutionSettings()\n    settings.response_format = MenuItem\n\n    # Create agent with plugin and settings\n    agent = ChatCompletionAgent(\n        service=AzureChatCompletion(),\n        name=\"SK-Assistant\",\n        instructions=\"You are a helpful assistant.\",\n        plugins=[MenuPlugin()],\n        arguments=KernelArguments(settings)\n    )\n\n    response = await agent.get_response(messages=\"What is the price of the soup special?\")\n    print(response.content)\n\n    # Output:\n    # The price of the Clam Chowder, which is the soup special, is $9.99.\n\nasyncio.run(main()) \n```\n\n### Agent with Plugin - .NET\n\n```csharp\nusing System.ComponentModel;\nusing Microsoft.SemanticKernel;\nusing Microsoft.SemanticKernel.Agents;\nusing Microsoft.SemanticKernel.ChatCompletion;\n\nvar builder = Kernel.CreateBuilder();\nbuilder.AddAzureOpenAIChatCompletion(\n                Environment.GetEnvironmentVariable(\"AZURE_OPENAI_DEPLOYMENT\"),\n                Environment.GetEnvironmentVariable(\"AZURE_OPENAI_ENDPOINT\"),\n                Environment.GetEnvironmentVariable(\"AZURE_OPENAI_API_KEY\")\n                );\nvar kernel = builder.Build();\n\nkernel.Plugins.Add(KernelPluginFactory.CreateFromType\u003CMenuPlugin>());\n\nChatCompletionAgent agent =\n    new()\n    {\n        Name = \"SK-Assistant\",\n        Instructions = \"You are a helpful assistant.\",\n        Kernel = kernel,\n        Arguments = new KernelArguments(new PromptExecutionSettings() { FunctionChoiceBehavior = FunctionChoiceBehavior.Auto() })\n\n    };\n\nawait foreach (AgentResponseItem\u003CChatMessageContent> response \n    in agent.InvokeAsync(\"What is the price of the soup special?\"))\n{\n    Console.WriteLine(response.Message);\n}\n\nsealed class MenuPlugin\n{\n    [KernelFunction, Description(\"Provides a list of specials from the menu.\")]\n    public string GetSpecials() =>\n        \"\"\"\n        Special Soup: Clam Chowder\n        Special Salad: Cobb Salad\n        Special Drink: Chai Tea\n        \"\"\";\n\n    [KernelFunction, Description(\"Provides the price of the requested menu item.\")]\n    public string GetItemPrice(\n        [Description(\"The name of the menu item.\")]\n        string menuItem) =>\n        \"$9.99\";\n}\n```\n\n### Multi-Agent System - Python\n\nBuild a system of specialized agents that can collaborate:\n\n```python\nimport asyncio\nfrom semantic_kernel.agents import ChatCompletionAgent, ChatHistoryAgentThread\nfrom semantic_kernel.connectors.ai.open_ai import AzureChatCompletion, OpenAIChatCompletion\n\nbilling_agent = ChatCompletionAgent(\n    service=AzureChatCompletion(), \n    name=\"BillingAgent\", \n    instructions=\"You handle billing issues like charges, payment methods, cycles, fees, discrepancies, and payment failures.\"\n)\n\nrefund_agent = ChatCompletionAgent(\n    service=AzureChatCompletion(),\n    name=\"RefundAgent\",\n    instructions=\"Assist users with refund inquiries, including eligibility, policies, processing, and status updates.\",\n)\n\ntriage_agent = ChatCompletionAgent(\n    service=OpenAIChatCompletion(),\n    name=\"TriageAgent\",\n    instructions=\"Evaluate user requests and forward them to BillingAgent or RefundAgent for targeted assistance.\"\n    \" Provide the full answer to the user containing any information from the agents\",\n    plugins=[billing_agent, refund_agent],\n)\n\nthread: ChatHistoryAgentThread = None\n\nasync def main() -> None:\n    print(\"Welcome to the chat bot!\\n  Type 'exit' to exit.\\n  Try to get some billing or refund help.\")\n    while True:\n        user_input = input(\"User:> \")\n\n        if user_input.lower().strip() == \"exit\":\n            print(\"\\n\\nExiting chat...\")\n            return False\n\n        response = await triage_agent.get_response(\n            messages=user_input,\n            thread=thread,\n        )\n\n        if response:\n            print(f\"Agent :> {response}\")\n\n# Agent :> I understand that you were charged twice for your subscription last month, and I'm here to assist you with resolving this issue. Here’s what we need to do next:\n\n# 1. **Billing Inquiry**:\n#    - Please provide the email address or account number associated with your subscription, the date(s) of the charges, and the amount charged. This will allow the billing team to investigate the discrepancy in the charges.\n\n# 2. **Refund Process**:\n#    - For the refund, please confirm your subscription type and the email address associated with your account.\n#    - Provide the dates and transaction IDs for the charges you believe were duplicated.\n\n# Once we have these details, we will be able to:\n\n# - Check your billing history for any discrepancies.\n# - Confirm any duplicate charges.\n# - Initiate a refund for the duplicate payment if it qualifies. The refund process usually takes 5-10 business days after approval.\n\n# Please provide the necessary details so we can proceed with resolving this issue for you.\n\n\nif __name__ == \"__main__\":\n    asyncio.run(main())\n```\n\n\n\n## Where to Go Next\n\n1. 📖 Try our [Getting Started Guide](https:\u002F\u002Flearn.microsoft.com\u002Fen-us\u002Fsemantic-kernel\u002Fget-started\u002Fquick-start-guide) or learn about [Building Agents](https:\u002F\u002Flearn.microsoft.com\u002Fen-us\u002Fsemantic-kernel\u002Fframeworks\u002Fagent\u002F)\n2. 🔌 Explore over 100 [Detailed Samples](https:\u002F\u002Flearn.microsoft.com\u002Fen-us\u002Fsemantic-kernel\u002Fget-started\u002Fdetailed-samples)\n3. 💡 Learn about core Semantic Kernel [Concepts](https:\u002F\u002Flearn.microsoft.com\u002Fen-us\u002Fsemantic-kernel\u002Fconcepts\u002Fkernel)\n\n### API References\n\n- [C# API reference](https:\u002F\u002Flearn.microsoft.com\u002Fen-us\u002Fdotnet\u002Fapi\u002Fmicrosoft.semantickernel?view=semantic-kernel-dotnet)\n- [Python API reference](https:\u002F\u002Flearn.microsoft.com\u002Fen-us\u002Fpython\u002Fapi\u002Fsemantic-kernel\u002Fsemantic_kernel?view=semantic-kernel-python)\n\n## Troubleshooting\n\n### Common Issues\n\n- **Authentication Errors**: Check that your API key environment variables are correctly set\n- **Model Availability**: Verify your Azure OpenAI deployment or OpenAI model access\n\n### Getting Help\n\n- Check our [GitHub issues](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fsemantic-kernel\u002Fissues) for known problems\n- Search the [Discord community](https:\u002F\u002Faka.ms\u002FSKDiscord) for solutions\n- Include your SDK version and full error messages when asking for help\n\n\n## Join the community\n\nWe welcome your contributions and suggestions to the SK community! One of the easiest ways to participate is to engage in discussions in the GitHub repository. Bug reports and fixes are welcome!\n\nFor new features, components, or extensions, please open an issue and discuss with us before sending a PR. This is to avoid rejection as we might be taking the core in a different direction, but also to consider the impact on the larger ecosystem.\n\nTo learn more and get started:\n\n- Read the [documentation](https:\u002F\u002Faka.ms\u002Fsk\u002Flearn)\n- Learn how to [contribute](https:\u002F\u002Flearn.microsoft.com\u002Fen-us\u002Fsemantic-kernel\u002Fsupport\u002Fcontributing) to the project\n- Ask questions in the [GitHub discussions](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fsemantic-kernel\u002Fdiscussions)\n- Ask questions in the [Discord community](https:\u002F\u002Faka.ms\u002FSKDiscord)\n\n- Attend [regular office hours and SK community events](COMMUNITY.md)\n- Follow the team on our [blog](https:\u002F\u002Faka.ms\u002Fsk\u002Fblog)\n\n## Contributor Wall of Fame\n\n[![semantic-kernel contributors](https:\u002F\u002Fcontrib.rocks\u002Fimage?repo=microsoft\u002Fsemantic-kernel)](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fsemantic-kernel\u002Fgraphs\u002Fcontributors)\n\n## Code of Conduct\n\nThis project has adopted the\n[Microsoft Open Source Code of Conduct](https:\u002F\u002Fopensource.microsoft.com\u002Fcodeofconduct\u002F).\nFor more information, see the\n[Code of Conduct FAQ](https:\u002F\u002Fopensource.microsoft.com\u002Fcodeofconduct\u002Ffaq\u002F)\nor contact [opencode@microsoft.com](mailto:opencode@microsoft.com)\nwith any additional questions or comments.\n\n## License\n\nCopyright (c) Microsoft Corporation. All rights reserved.\n\nLicensed under the [MIT](LICENSE) license.\n","Semantic Kernel 是一个旨在帮助企业快速轻松地将尖端大语言模型技术集成到应用程序中的软件开发工具包。它支持多种语言模型，包括OpenAI、Azure OpenAI和Hugging Face等，并提供构建模块化AI代理的能力，这些代理可以访问工具\u002F插件、记忆以及规划功能。此外，该框架还支持多代理系统的协同工作，适用于需要创建智能助手或协调多个专业代理的应用场景。通过其丰富的插件生态系统和向量数据库支持，开发者能够扩展应用的功能性和灵活性，从而满足从简单聊天机器人到复杂多代理工作流的各种需求。",2,"2026-06-11 03:24:28","top_topic"]