wehub-resource-sync
138 lines
7.6 KiB
Markdown
138 lines
7.6 KiB
Markdown
# Get Started with Semantic Kernel ⚡
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> [!IMPORTANT]
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> Semantic Kernel is now [Microsoft Agent Framework](https://github.com/microsoft/agent-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.
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>
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> Learn more about Semantic Kernel and Agent Framework here: [Semantic Kernel and Microsoft Agent Framework on the Agent Framework blog](https://devblogs.microsoft.com/agent-framework/semantic-kernel-and-microsoft-agent-framework/), and try out the [Semantic Kernel migration guide](https://learn.microsoft.com/en-us/agent-framework/migration-guide/from-semantic-kernel).
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## OpenAI / Azure OpenAI API keys
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To run the LLM prompts and semantic functions in the examples below, make sure
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you have an
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- [Azure OpenAI Service Key](https://learn.microsoft.com/azure/cognitive-services/openai/quickstart?pivots=rest-api) or
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- [OpenAI API Key](https://platform.openai.com).
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## Nuget package
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Here is a quick example of how to use Semantic Kernel from a C# console app.
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First, let's create a new project, targeting .NET 6 or newer, and add the
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`Microsoft.SemanticKernel` nuget package to your project from the command prompt
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in Visual Studio:
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dotnet add package Microsoft.SemanticKernel
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# Running prompts with input parameters
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Copy and paste the following code into your project, with your Azure OpenAI key in hand:
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```csharp
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using Microsoft.SemanticKernel;
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using Microsoft.SemanticKernel.Connectors.OpenAI;
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var builder = Kernel.CreateBuilder();
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builder.AddAzureOpenAIChatCompletion(
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"gpt-35-turbo", // Azure OpenAI Deployment Name
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"https://contoso.openai.azure.com/", // Azure OpenAI Endpoint
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"...your Azure OpenAI Key..."); // Azure OpenAI Key
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// Alternative using OpenAI
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//builder.AddOpenAIChatCompletion(
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// "gpt-3.5-turbo", // OpenAI Model name
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// "...your OpenAI API Key..."); // OpenAI API Key
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var kernel = builder.Build();
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var prompt = @"{{$input}}
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One line TLDR with the fewest words.";
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var summarize = kernel.CreateFunctionFromPrompt(prompt, executionSettings: new OpenAIPromptExecutionSettings { MaxTokens = 100 });
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string text1 = @"
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1st Law of Thermodynamics - Energy cannot be created or destroyed.
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2nd Law of Thermodynamics - For a spontaneous process, the entropy of the universe increases.
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3rd Law of Thermodynamics - A perfect crystal at zero Kelvin has zero entropy.";
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string text2 = @"
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1. An object at rest remains at rest, and an object in motion remains in motion at constant speed and in a straight line unless acted on by an unbalanced force.
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2. The acceleration of an object depends on the mass of the object and the amount of force applied.
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3. Whenever one object exerts a force on another object, the second object exerts an equal and opposite on the first.";
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Console.WriteLine(await kernel.InvokeAsync(summarize, new() { ["input"] = text1 }));
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Console.WriteLine(await kernel.InvokeAsync(summarize, new() { ["input"] = text2 }));
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// Output:
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// Energy conserved, entropy increases, zero entropy at 0K.
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// Objects move in response to forces.
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```
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# Semantic Kernel Notebooks
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The repository contains also a few C# Jupyter notebooks that demonstrates
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how to get started with the Semantic Kernel.
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See [here](./notebooks/README.md) for the full list, with
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requirements and setup instructions.
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1. [Getting started](./notebooks/00-getting-started.ipynb)
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2. [Loading and configuring Semantic Kernel](./notebooks/01-basic-loading-the-kernel.ipynb)
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3. [Running AI prompts from file](./notebooks/02-running-prompts-from-file.ipynb)
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4. [Creating Semantic Functions at runtime (i.e. inline functions)](./notebooks/03-semantic-function-inline.ipynb)
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5. [Using Kernel Arguments to Build a Chat Experience](./notebooks/04-kernel-arguments-chat.ipynb)
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6. [Introduction to the Function Calling](./notebooks/05-using-function-calling.ipynb)
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7. [Vector Stores and Embeddings](./notebooks/06-vector-stores-and-embeddings.ipynb)
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8. [Creating images with DALL-E 3](./notebooks/07-DALL-E-3.ipynb)
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9. [Chatting with ChatGPT and Images](./notebooks/08-chatGPT-with-DALL-E-3.ipynb)
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10. [BingSearch using Kernel](./notebooks/09-RAG-with-BingSearch.ipynb)
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# Semantic Kernel Samples
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The repository also contains the following code samples:
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| Type | Description |
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| -------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------- |
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| [`GettingStarted`](./samples/GettingStarted/README.md) | Take this step by step tutorial to get started with the Semantic Kernel and get introduced to the key concepts. |
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| [`GettingStartedWithAgents`](./samples/GettingStartedWithAgents/README.md) | Take this step by step tutorial to get started with the Semantic Kernel Agents and get introduced to the key concepts. |
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| [`Concepts`](./samples/Concepts/README.md) | This section contains focussed samples which illustrate all of the concepts included in the Semantic Kernel. |
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| [`Demos`](./samples/Demos/README.md) | Look here to find a sample which demonstrates how to use many of Semantic Kernel features. |
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| [`LearnResources`](./samples/LearnResources/README.md) | Code snippets that are related to online documentation sources like Microsoft Learn, DevBlogs and others |
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# Nuget packages
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Semantic Kernel provides a set of nuget packages to allow extending the core with
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more features, such as connectors to services and plugins to perform specific actions.
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Unless you need to optimize which packages to include in your app, you will usually
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start by installing this meta-package first:
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- **Microsoft.SemanticKernel**
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This meta package includes core packages and OpenAI connectors, allowing to run
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most samples and build apps with OpenAI and Azure OpenAI.
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Packages included in **Microsoft.SemanticKernel**:
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1. **Microsoft.SemanticKernel.Abstractions**: contains common interfaces and classes
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used by the core and other SK components.
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1. **Microsoft.SemanticKernel.Core**: contains the core logic of SK, such as prompt
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engineering, semantic memory and semantic functions definition and orchestration.
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1. **Microsoft.SemanticKernel.Connectors.OpenAI**: connectors to OpenAI and Azure
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OpenAI, allowing to run semantic functions, chats, text to image with GPT3,
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GPT3.5, GPT4, DALL-E3.
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Other SK packages available at nuget.org:
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1. **Microsoft.SemanticKernel.Connectors.Qdrant**: Qdrant connector for
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plugins and semantic memory.
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2. **Microsoft.SemanticKernel.Connectors.Sqlite**: SQLite connector for
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plugins and semantic memory
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3. **Microsoft.SemanticKernel.Plugins.Document**: Document Plugin: Word processing,
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OpenXML, etc.
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4. **Microsoft.SemanticKernel.Plugins.MsGraph**: Microsoft Graph Plugin: access your
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tenant data, schedule meetings, send emails, etc.
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5. **Microsoft.SemanticKernel.Plugins.OpenApi**: OpenAPI Plugin.
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6. **Microsoft.SemanticKernel.Plugins.Web**: Web Plugin: search the web, download
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files, etc.
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