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Python SDK : Add native vector database connectors and retrieval patterns #1188
Description
Currently, the Agent Framework lacks built-in support for vector databases, which are essential for RAG patterns in production agent systems.
Proposed Enhancement:
Add first-class connectors for popular vector databases:
Azure AI Search (given Azure ecosystem focus)
Pinecone
Weaviate
Qdrant
Chroma
PostgreSQL with pgvector
Include built-in retrieval patterns:
Semantic search tools for agents
Hybrid search (vector + keyword)
Re-ranking capabilities
Metadata filtering
Reacted by Luis Mañez and mabelbracketslab
Reacted by Daniel Cazzulino and mabelbracketslab
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markwallace-microsoft commentedon Oct 6, 2025
The Semantic Kernel already contains first-class connectors for popular vector databases (see https://learn.microsoft.com/en-us/semantic-kernel/concepts/vector-store-connectors/out-of-the-box-connectors/?pivots=programming-language-python)
These connectors are general purpose and can be used with Agent Framework.
I'll keep this issue option so cover creating samples and dociumentation.
[-]Python SDK : Add native vector database connectors and retrieval patterns[/-][+].NET: Python SDK : Add native vector database connectors and retrieval patterns[/+]luismanez commentedon Oct 6, 2025
But are there plans to move SK Vector DB connectors into Agent Framework? I think is a bit confusing if we mix both things. Announcement said:
[-].NET: Python SDK : Add native vector database connectors and retrieval patterns[/-][+]Python SDK : Add native vector database connectors and retrieval patterns[/+]12 remaining items
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markwallace-microsoft commentedon Mar 20, 2026
Pujarini Mohapatra (@biswapm), friendly reminder — this issue is waiting on your response. Please share any updates when you get a chance. (This is an automated message.)