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Kernel Feature Matrix by Language

AI Services

C# Python Notes
TextGeneration Example: Text-Davinci-003
TextEmbeddings Example: Text-Embeddings-Ada-002
ChatCompletion Example: GPT4, Chapt-GPT
Image Generation Example: Dall-E

AI Service Endpoints

C# Python Notes
OpenAI
AzureOpenAI
Hugging Face Coming soon to Python - both native and web endpoint support
Custom Requires the user to define the service schema in their application

Tokenizers

C# Python Notes
GPT2 🔄 Can be manually added to Python via pip install transformers
GPT3
tiktoken 🔄 Coming soon to Python and C#. Can be manually added to Python via pip install tiktoken

Core Skills

C# Python Notes
TextMemorySkill
PlannerSkill 🔄
ConversationSummarySkill
FileIOSkill
HttpSkill
MathSkill
TextSkill
TimeSkill

Connectors and Skill Libraries

C# Python Notes
Qdrant (Memory) Vector optimized
ChromaDb (Memory) 🔄
Milvus (Memory) Vector optimized
Pinecone (Memory) Vector optimized
Weaviate (Memory) Vector optimized
CosmosDB (Memory) CosmosDB is not optimized for vector storage
Sqlite (Memory) Sqlite is not optimized for vector storage
Azure Cognitive Search
MsGraph Contains connectors for OneDrive, Outlook, ToDos, and Organization Hierarchies
Document Skills Currently only supports Word documents
OpenAPI
Web Skills

Design Choices

The overall architecture of the core kernel is consistent across Python and C#, however, the code should follow common paradigms and style of each language.

During the initial development phase, many Python best practices have been ignored in the interest of velocity and feature parity. The project is now going through a refactoring exercise to increase code quality.

To make the Kernel as lightweight as possible, the core pip package should have a minimal set of external dependencies. On the other hand, the SDK should not reinvent mature solutions already available, unless of major concerns.