Supported Semantic Kernel languages

Article
09/09/2024

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.

Available SDK packages

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.OpenAI`	The connector for OpenAI
`Microsoft.SemanticKernel.Connectors.HuggingFace`	The connector for Hugging Face models
`Microsoft.SemanticKernel.Connectors.Google`	The connector for Google models (e.g., Gemini)
`Microsoft.SemanticKernel.Connectors.MistralAI`	The connector for Mistral AI models
`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

There are other packages available (e.g., the memory connectors), but they are still experimental and are not yet recommended for production use.

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
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
OpenAI	✅	✅	✅
Azure OpenAI	✅	✅	✅
Other endpoints that suppoprt OpenAI APIs	✅	✅	✅	Includes Ollama, LLM Studio, Azure Model-as-a-service, etc.
Hugging Face Inference API	🔄	❌	❌	Coming soon to Python, not all scenarios are covered for .NET

Memory Connectors (Experimental)

Important

All of the existing memory connectors are currently experimental and will be replaced by Vector Store connectors. These will provide more functionality via an updated abstraction layer.

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

Vector Store Connectors (Experimental)