Some unofficial extensions to Kernel Memory to do some advanced RAG
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Updated
May 27, 2024 - C#
Some unofficial extensions to Kernel Memory to do some advanced RAG
A sample showing how vector comparison can be used to detect plagiarismm using a simple in-memory vector store.
Lightweight In-memory Vector Database to embed in any .NET Applications
RAG implementation using Microsoft Semantic Kernel and .NET
A service for automating document ingestion for Semantic Kernel's KernelMemory service
ChatGPT-like Application using RAG pattern that allows to ask question to my own documents - I Used Semantic Kernel to integrate a LLM (OpenAI) using C# to orchestrate AI pluggins (Azure Cognitive Services). For the document embeddings I used Qdrant for the vector database and Pdfpig to extract the content from the pdfs
This example shows how a multitenant service can distribute requests evenly among multiple Azure OpenAI Service instances and manage tokens per minute (TPM) for multiple tenants.
Implements a framework to build Generative AI applications.
SQL Server as a vector database, SQL Server Extenstion for RAG
A lightweight implementation of Kernel Memory as a Service
Semantic search in Unity!
SQL Server connector for Semantic Kernel plugin and Kernel Memory
Index and query any data using LLM and natural language, tracking sources and showing citations.
The AI Agent Framework in .NET
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