kernel-memory
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microsoft
RAG architecture: index and query any data using LLM and natural language, track sources, show citations, asynchronous memory patterns.
Hi, Can I use Azure Search "Hybrid Search + Semantic" Search using Kernel Memory? Or is only vector search possible? Just looking at this article: https://techcommunity.microsoft.com/t5/ai-azure-ai-services-blog/azure-cognitive-search-outperforming-vector-search-with-hybrid/ba-p/3929167 ; it suggests that...
### Context / Scenario I would like to be able to pass parameters to a custom prompt when calling the `AskAsync` method. For example: I want to conditionally instruct the...
### Context / Scenario I hope to add modifications to the sliced document after Import. I have encapsulated the Handle implementation of QA slicing based on step. ### The problem...
### Context / Scenario I want a new feature that lets us use date filters for searching documents. For example, if I search for "documents before 2021 with information on...
I would like to understand if a search found some data on the db vector. If the search didn't return anything, I would like to route the search on a...
### Context / Scenario  I referred to this example and wrote an implementation of OCR. Attempting to scan PDF and PDF containing images did not trigger it. I'm not...
### Context / Scenario Google's Gemini has a `models/embedding-001` [Embedding model](https://ai.google.dev/docs/embeddings_guide) for embedding. Hope Kernel Memory can support it. Is it on the roadmap? ### The problem N/A ### Proposed...
### Context / Scenario I was trying to ingest a large (26MB) PDF file using s Serverless KM instance locally the other day and found that it took really long...
### Context / Scenario I want to try new MongoDb Atlas support from nuget. ### Question I've tried to search for the package for MongoDb ATlas in nuget but I...
### Context / Scenario For the same document and question, when using `text-embedding-3-small` or `text-embedding-3-large` models, similarity returns results with lower relevance than when using `text-embedding-ada-002` model. ### What happened?...
