MicrosoftOCTO 

Kernel Memory is a Copilot/Semantic Kernel Plugin and Memory Web Service to index and query any data and documents, using LLM and natural language, tracking sources and showing citations. The package contains... More information

The package contains the the core logic and abstractions of Kernel Memory, not including extensions.

Provide access to OpenAI LLM models in Kernel Memory to generate embeddings and text

Provide access to Azure OpenAI LLM models in Kernel Memory to generate embeddings and text

Azure AI Search connector for Microsoft Kernel Memory, to store and search memory using Azure AI Search vector indexing and semantic features.

Qdrant connector for Microsoft Kernel Memory, to store and search memory using Qdrant vector indexing and Qdrant features.

Add Azure AI Document Intelligence to Kernel Memory to extract content from images and documents.

Azure Queue Storage connector for Microsoft Kernel Memory, to run asynchronous pipelines via Azure Queue Storage queues.

Postgres(with pgvector extension) connector for Microsoft Kernel Memory, to store and search memory using Postgres vector indexing and Postgres features.

Redis connector for Microsoft Kernel Memory, to store and search memory using Redis vector search and other Redis features.

RabbitMQ connector for Microsoft Kernel Memory, to run asynchronous pipelines via RabbitMQ queues.

Provide access to OpenAI LLM models in Kernel Memory to generate text

Azure Blob Storage adapter allowing Kernel Memory to upload documents and maintain their state in Azure Blobs

Kernel Memory Web Client allows to connect to Kernel Memory Web Service to index and query any data and documents, using LLM and natural language, tracking sources and showing citations.

MongoDb Atlas connector for Microsoft Kernel Memory, to store and search memory records with embeddings, and files.

MS SQLServer connector for Microsoft Kernel Memory, to store and search memory using MSSQL.

Elasticsearch connector for Microsoft Kernel Memory, to store and search memory using Elasticsearch vector search and other Elasticsearch features.

Provide access to Anthropic LLM models in Kernel Memory

Kernel Memory Plugin allows to use Kernel Memory Service as a Semantic Kernel plugin, to index and query any data and documents, using LLM and natural language, tracking sources and showing citations.

Provide tokenizers to allow counting content tokens for text and embeddings