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* Update notebooks to use pip package
* Add python getting started notebook * Fix notebooks usage of Azure text completion * Fix bug with skills definition * Update READMEs * New release version 0.2.2
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‎.gitignore‎

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venv/
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myvenv/
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ENV/
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# Python dist
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dist/

‎CONTRIBUTING.md‎

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- **DO** follow the standard
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[.NET coding style](https://learn.microsoft.com/dotnet/csharp/fundamentals/coding-style/coding-conventions)
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and [Python code style](https://pypi.org/project/black/)
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- **DO** give priority to the current style of the project or file you're changing
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if it diverges from the general guidelines.
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- **DO** include tests when adding new features. When fixing bugs, start with

‎README.md‎

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# Semantic Kernel
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[![Python package](https://img.shields.io/pypi/v/semantic-kernel)](https://pypi.org/project/semantic-kernel/)
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[![Nuget package](https://img.shields.io/nuget/vpre/Microsoft.SemanticKernel)](https://www.nuget.org/packages/Microsoft.SemanticKernel/)
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[![License: MIT](https://img.shields.io/github/license/microsoft/semantic-kernel)](https://github.com/microsoft/semantic-kernel/blob/main/LICENSE)
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[![dotnet](https://github.com/microsoft/semantic-kernel/actions/workflows/dotnet-ci.yml/badge.svg?branch=main)](https://github.com/microsoft/semantic-kernel/actions/workflows/dotnet-ci.yml)
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[![License: MIT](https://img.shields.io/github/license/microsoft/semantic-kernel)](https://github.com/microsoft/semantic-kernel/blob/main/LICENSE)
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[![Discord](https://img.shields.io/discord/1063152441819942922)](https://aka.ms/SKDiscord)
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> ℹ️ **NOTE**: This project is in early alpha and, just like AI, will evolve quickly.
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> We invite you to join us in developing the Semantic Kernel together!
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> Please contribute by
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> using GitHub [Discussions](https://github.com/microsoft/semantic-kernel/discussions),
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> opening GitHub [Issues](https://github.com/microsoft/semantic-kernel/issues/new/choose),
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> sending us [PRs](https://github.com/microsoft/semantic-kernel/pulls).
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> sending us [PRs](https://github.com/microsoft/semantic-kernel/pulls),
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> joining our [Discord community](https://aka.ms/SKDiscord).
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**Semantic Kernel (SK)** is a lightweight SDK enabling integration of AI Large
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Language Models (LLMs) with conventional programming languages. The SK extensible
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pioneering developers can join us in crafting the future of this landmark moment
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in the history of computing.
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## Samples ⚡
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## Get Started with Semantic Kernel ⚡
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Semantic Kernel is available to explore AI and build apps with C# and Python:
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<div style="display:flex;height:30px;padding:5px 0 5px 10px;">
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<img src="https://user-images.githubusercontent.com/371009/230673036-fad1e8e6-5d48-49b1-a9c1-6f9834e0d165.png" style="margin-right:12px" height="30"/>
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<a href="dotnet/README.md">Using Semantic Kernel in C#</a>.
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</div>
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<div style="display:flex;height:30px;padding:5px 0 5px 10px;">
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<img src="https://user-images.githubusercontent.com/371009/230673733-7a447d30-b48e-46e1-bd84-2b321c90649e.png" style="margin-right:12px" height="30"/>
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<a href="python/README.md">Using Semantic Kernel in Python</a>.
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</div>
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The quickest way to get started with the basics is to get an API key
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(OpenAI or Azure OpenAI)
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and to run one of the C# or Python console applications/scripts:
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For C#:
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1. Create a new console app.
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2. Add the semantic kernel nuget `Microsoft.SemanticKernel`.
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3. Copy the code from [here](dotnet/README.md) into the app `Program.cs` file.
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4. Replace the configuration placeholders for API key and other params with your key and settings.
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5. Run with `F5` or `dotnet run`
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If you would like a quick overview about how Semantic Kernel can integrate with your
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app, start by cloning the repository:
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For Python:
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1. Install the pip package: `python -m pip install semantic-kernel`.
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2. Create a new script e.g. `hello-world.py`.
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3. Store your API key and settings in an `.env` file as described [here](python/README.md).
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4. Copy the code from [here](python/README.md) into the `hello-world.py` script.
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5. Run the python script.
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```shell
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git clone https://github.com/microsoft/semantic-kernel.git
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```
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and try these examples:
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## Samples apps ⚡
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The repository includes some sample applications, with a React frontend and
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a backend web service using Semantic Kernel.
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Follow the links for more information and instructions about running these apps.
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| | |
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| ----------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------- |
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| [Simple chat summary](samples/apps/chat-summary-webapp-react/README.md) | Use ready-to-use skills and get those skills into your app easily. |
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| [Book creator](samples/apps/book-creator-webapp-react/README.md) | Use planner to deconstruct a complex goal and envision using the planner in your app. |
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| [Authentication and APIs](samples/apps/auth-api-webapp-react/README.md) | Use a basic connector pattern to authenticate and connect to an API and imagine integrating external data into your app's LLM AI. |
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| [Github repository Q&A](samples/apps/github-qna-webapp-react/README.md) | Use embeddings and memory to store recent data and allow you to query against it. |
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| [GitHub repository Q&A](samples/apps/github-qna-webapp-react/README.md) | Use embeddings and memory to store recent data and allow you to query against it. |
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| [Copilot Chat Sample App](samples/apps/copilot-chat-app/README.md) | Build your own chat experience based on Semantic Kernel. |
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For a more hands-on overview, you can also run the
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[Getting Started notebook](samples/notebooks/dotnet/Getting-Started-Notebook.ipynb),
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looking into the syntax, creating
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[Semantic Functions](docs/GLOSSARY.md),
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working with Memory, and see how the kernel works.
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**Please note:**
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- You will need an
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[Polyglot extension](https://marketplace.visualstudio.com/items?itemName=ms-dotnettools.dotnet-interactive-vscode)
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to run the notebooks.
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## Get Started with Semantic Kernel ⚡
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Here is a quick example of how to use Semantic Kernel from a C# console app.
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1. Create a new project, targeting .NET 6 or newer, and add the
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`Microsoft.SemanticKernel` nuget package:
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dotnet add package Microsoft.SemanticKernel --prerelease
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## Notebooks ⚡
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See [nuget.org](https://www.nuget.org/packages/Microsoft.SemanticKernel/) for
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the latest version and more instructions.
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2. Copy and paste the following code into your project, with your Azure OpenAI
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key in hand (you can create one
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[here](https://learn.microsoft.com/azure/cognitive-services/openai/quickstart?pivots=rest-api)).
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```csharp
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using Microsoft.SemanticKernel;
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var kernel = Kernel.Builder.Build();
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// For Azure Open AI details please see
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// https://learn.microsoft.com/azure/cognitive-services/openai/quickstart?pivots=rest-api
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kernel.Config.AddAzureOpenAITextCompletionService(
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"davinci-azure", // Alias used by the kernel
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"text-davinci-003", // Azure OpenAI *Deployment ID*
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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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);
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string summarizePrompt = @"{{$input}}
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Give me a TLDR with the fewest words.";
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string jokePrompt = @"{{$input}}
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Write a G rated joke about it, only two lines, with rhyme.";
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var summarize = kernel.CreateSemanticFunction(summarizePrompt);
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var joker = kernel.CreateSemanticFunction(jokePrompt);
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string inputText = @"
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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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var output = await kernel.RunAsync(inputText, summarize, joker);
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Console.WriteLine(output);
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// Output => Entropy is a funny thing,
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// It's always increasing, no matter what we bring!
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```
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For a more hands-on overview, you can also check out the Jupyter C# and Python notebooks, starting
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from here:
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* [Getting Started with C# notebook](samples/notebooks/dotnet/Getting-Started-Notebook.ipynb)
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* [Getting Started with Python notebook](samples/notebooks/python/00-getting-started-notebook.ipynb)
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## Contributing and Community
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- Join the [Discord community](https://aka.ms/SKDiscord)
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- Follow the team on our [blog](https://aka.ms/sk/blog)
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<img src="https://user-images.githubusercontent.com/36091529/225807182-22ad65e9-82c6-4727-bb77-d1c256736045.png" align="left" width="40px"/>
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<b>Python developers:</b> Semantic Kernel is coming to Python soon! Check out the work-in-progress and contribute in the <a href="https://github.com/microsoft/semantic-kernel/tree/python-preview"><b>python-preview</b></a> branch.
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<br clear="left"/>
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## Code of Conduct
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This project has adopted the

‎dotnet/README.md‎

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# Get Started with Semantic Kernel ⚡
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## OpenAI / Azure OpenAI API keys
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Make sure you have an
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[Open AI API Key](https://openai.com/api/) or
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[Azure Open AI service key](https://learn.microsoft.com/azure/cognitive-services/openai/quickstart?pivots=rest-api)
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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:
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dotnet add package Microsoft.SemanticKernel --prerelease
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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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var kernel = Kernel.Builder.Build();
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// Azure OpenAI
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kernel.Config.AddAzureOpenAITextCompletionService(
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"davinci-azure", // Alias used by the kernel
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"text-davinci-003", // 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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);
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// Alternative using OpenAI
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// kernel.Config.AddOpenAITextCompletionService("davinci-openai",
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// "text-davinci-003", // OpenAI Model name
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// "...your OpenAI API Key..." // OpenAI API Key
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// );
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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.CreateSemanticFunction(prompt);
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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 summarize.InvokeAsync(text1));
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Console.WriteLine(await summarize.InvokeAsync(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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# Prompt chaining
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The previous code shows how to invoke individual semantic functions, but you can
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also chain functions (aka prompt chaining) to process the initial input with multiple
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operations.
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The following code for example, translates an initial text to math symbols and
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then generates a summary:
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```csharp
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string translationPrompt = @"{{$input}}
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Translate the text to math.";
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string summarizePrompt = @"{{$input}}
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Give me a TLDR with the fewest words.";
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var translator = kernel.CreateSemanticFunction(translationPrompt);
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var summarize = kernel.CreateSemanticFunction(summarizePrompt);
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string inputText = @"
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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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// Run two prompts in sequence (prompt chaining)
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var output = await kernel.RunAsync(inputText, translator, summarize);
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Console.WriteLine(output);
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// Output: ΔE = 0, ΔSuniv > 0, S = 0 at 0K.
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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](../samples/notebooks/dotnet/README.md) for the full list with setup
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instructions.

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[flake8]
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max-line-length = 88
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extend-ignore = E203

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