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Supported Semantic Kernel languages

  • Article

Semantic Kernel plans on providing support to the following languages:

  • C#
  • Python
  • Java

While the overall architecture of the kernel is consistent across all languages, we made sure the SDK for each language follows common paradigms and styles in each language to make it feel native and easy to use.

C# packages

In C#, there are several packages to help ensure that you only need to import the functionality that you need for your project. The following table shows the available packages in C#.

Package name Description
Microsoft.SemanticKernel The main package that includes everything to get started
Microsoft.SemanticKernel.Core The core package that provides implementations for Microsoft.SemanticKernel.Abstractions
Microsoft.SemanticKernel.Abstractions The base abstractions for Semantic Kernel
Microsoft.SemanticKernel.Connectors.Amazon The AI connector for Amazon AI
Microsoft.SemanticKernel.Connectors.AzureAIInference The AI connector for Azure AI Inference
Microsoft.SemanticKernel.Connectors.AzureOpenAI The AI connector for Azure OpenAI
Microsoft.SemanticKernel.Connectors.Google The AI connector for Google models (e.g., Gemini)
Microsoft.SemanticKernel.Connectors.HuggingFace The AI connector for Hugging Face models
Microsoft.SemanticKernel.Connectors.MistralAI The AI connector for Mistral AI models
Microsoft.SemanticKernel.Connectors.Ollama The AI connector for Ollama
Microsoft.SemanticKernel.Connectors.Onnx The AI connector for Onnx
Microsoft.SemanticKernel.Connectors.OpenAI The AI connector for OpenAI
Microsoft.SemanticKernel.Connectors.AzureAISearch The vector store connector for AzureAISearch
Microsoft.SemanticKernel.Connectors.AzureCosmosDBMongoDB The vector store connector for AzureCosmosDBMongoDB
Microsoft.SemanticKernel.Connectors.AzureCosmosDBNoSQL The vector store connector for AzureAISearch
Microsoft.SemanticKernel.Connectors.MongoDB The vector store connector for MongoDB
Microsoft.SemanticKernel.Connectors.Pinecone The vector store connector for Pinecone
Microsoft.SemanticKernel.Connectors.Qdrant The vector store connector for Qdrant
Microsoft.SemanticKernel.Connectors.Redis The vector store connector for Redis
Microsoft.SemanticKernel.Connectors.Sqlite The vector store connector for Sqlite
Microsoft.SemanticKernel.Connectors.Weaviate The vector store connector for Weaviate
Microsoft.SemanticKernel.Plugins.OpenApi (Experimental) Enables loading plugins from OpenAPI specifications
Microsoft.SemanticKernel.PromptTemplates.Handlebars Enables the use of Handlebars templates for prompts
Microsoft.SemanticKernel.Yaml Provides support for serializing prompts using YAML files
Microsoft.SemanticKernel.Prompty Provides support for serializing prompts using Prompty files
Microsoft.SemanticKernel.Agents.Abstractions Provides abstractions for creating agents
Microsoft.SemanticKernel.Agents.OpenAI Provides support for Assistant API agents

To install any of these packages, you can use the following command:

dotnet add package <package-name>

Python packages

In Python, there's a single package that includes everything you need to get started with Semantic Kernel. To install the package, you can use the following command:

pip install semantic-kernel

On PyPI under Provides-Extra the additional extras you can install are also listed and when used that will install the packages needed for using SK with that specific connector or service, you can install those with the square bracket syntax for instance:

pip install semantic-kernel[azure]

This will install Semantic Kernel, as well as specific tested versions of: azure-ai-inference, azure-search-documents, azure-core, azure-identity, azure-cosmos and msgraph-sdk (and any dependencies of those packages). Similarly the extra hugging_face will install transformers and sentence-transformers.

Java packages

For Java, Semantic Kernel has the following packages; all are under the group Id com.microsoft.semantic-kernel, and can be imported from maven.

    <dependency>
        <groupId>com.microsoft.semantic-kernel</groupId>
        <artifactId>semantickernel-api</artifactId>
    </dependency>

A BOM is provided that can be used to define the versions of all Semantic Kernel packages.

    <dependencyManagement>
        <dependencies>
            <dependency>
                <groupId>com.microsoft.semantic-kernel</groupId>
                <artifactId>semantickernel-bom</artifactId>
                <version>${semantickernel.version}</version>
                <scope>import</scope>
                <type>pom</type>
            </dependency>
        </dependencies>
    </dependencyManagement>
  • semantickernel-bom – A Maven project BOM that can be used to define the versions of all Semantic Kernel packages.
  • semantickernel-api – Package that defines the core public API for the Semantic Kernel for a Maven project.
  • semantickernel-aiservices-openai –Provides a connector that can be used to interact with the OpenAI API.

Below is an example POM XML for a simple project that uses OpenAI.

<project>
    <dependencyManagement>
        <dependencies>
            <dependency>
                <groupId>com.microsoft.semantic-kernel</groupId>
                <artifactId>semantickernel-bom</artifactId>
                <version>${semantickernel.version}</version>
                <scope>import</scope>
                <type>pom</type>
            </dependency>
        </dependencies>
    </dependencyManagement>
    <dependencies>
        <dependency>
            <groupId>com.microsoft.semantic-kernel</groupId>
            <artifactId>semantickernel-api</artifactId>
        </dependency>
        <dependency>
            <groupId>com.microsoft.semantic-kernel</groupId>
            <artifactId>semantickernel-connectors-ai-openai</artifactId>
        </dependency>
    </dependencies>
</project>

Available features in each SDK

The following tables show which features are available in each language. The 🔄 symbol indicates that the feature is partially implemented, please see the associated note column for more details. The ❌ symbol indicates that the feature is not yet available in that language; if you would like to see a feature implemented in a language, please consider contributing to the project or opening an issue.

Core capabilities

Services C# Python Java Notes
Prompts ✅ ✅ ✅ To see the full list of supported template and serialization formats, refer to the tables below
Native functions and plugins ✅ ✅ ✅
OpenAPI plugins ✅ ✅ ✅ Java has a sample demonstrating how to load OpenAPI plugins
Automatic function calling ✅ ✅ ✅
Open Telemetry logs ✅ ✅ ❌
Hooks and filters ✅ ✅ ✅

Prompt template formats

When authoring prompts, Semantic Kernel provides a variety of template languages that allow you to embed variables and invoke functions. The following table shows which template languages are supported in each language.

Formats C# Python Java Notes
Semantic Kernel template language ✅ ✅ ✅
Handlebars ✅ ✅ ✅
Liquid ✅ ❌ ❌
Jinja2 ❌ ✅ ❌

Prompt serialization formats

Once you've created a prompt, you can serialize it so that it can be stored or shared across teams. The following table shows which serialization formats are supported in each language.

Formats C# Python Java Notes
YAML ✅ ✅ ✅
Prompty ✅ ❌ ❌

AI Services Modalities

Services C# Python Java Notes
Text Generation ✅ ✅ ✅ Example: Text-Davinci-003
Chat Completion ✅ ✅ ✅ Example: GPT4, Chat-GPT
Text Embeddings (Experimental) ✅ ✅ ✅ Example: Text-Embeddings-Ada-002
Text to Image (Experimental) ✅ ✅ ❌ Example: Dall-E
Image to Text (Experimental) ✅ ❌ ❌ Example: Pix2Struct
Text to Audio (Experimental) ✅ ✅ ❌ Example: Text-to-speech
Audio to Text (Experimental) ✅ ✅ ❌ Example: Whisper

AI Service Connectors

Endpoints C# Python Java Notes
Amazon Bedrock ✅ ✅ ❌
Anthropic ✅ ✅ ❌
Azure AI Inference ✅ ✅ ❌
Azure OpenAI ✅ ✅ ✅
Google ✅ ✅ ✅
Hugging Face Inference API ✅ ✅ ❌
Mistral ✅ ✅ ❌
Ollama ✅ ✅ ❌
ONNX ✅ ✅ ❌
OpenAI ✅ ✅ ✅
Other endpoints that suppoprt OpenAI APIs ✅ ✅ ✅ Includes LLM Studio, etc.

Vector Store Connectors (Experimental)

Warning

The Semantic Kernel Vector Store functionality is in preview, and improvements that require breaking changes may still occur in limited circumstances before release.

For the list of out of the box vector store connectors and the language support for each, refer to out of the box connectors.

Memory Store Connectors (Legacy)

Important

Memory Store connectors are legacy and have been replaced by Vector Store connectors. For more information see Legacy Memory Stores.

Memory Connectors C# Python Java Notes
Azure AI Search ✅ ✅ ✅
Chroma ✅ ✅ ❌
DuckDB ✅ ❌ ❌
Milvus ✅ ✅ ❌
Pinecone ✅ ✅ ❌
Postgres ✅ ✅ ❌
Qdrant ✅ ✅ ❌
Redis ✅ ✅ ❌
Sqlite ✅ ❌ 🔄
Weaviate ✅ ✅ ❌