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llama-stack/docs/source/providers/vector_io/mivus.md
Ashwin Bharambe 330cc9d09d
feat: add Milvus vectorDB (#1467) 
# What does this PR do?
See https://github.com/meta-llama/llama-stack/pull/1171 which is the
original PR. Author: @zc277584121

feat: add [Milvus](https://milvus.io/) vectorDB

note: I use the MilvusClient to implement it instead of
AsyncMilvusClient, because when I tested AsyncMilvusClient, it would
raise issues about evenloop, which I think AsyncMilvusClient SDK is not
robust enough to be compatible with llama_stack framework.

## Test Plan
have passed the unit test and ene2end test
Here is my end2end test logs, including the client code, client log,
server logs from inline and remote settings

[test_end2end_logs.zip](https://github.com/user-attachments/files/18964391/test_end2end_logs.zip)

---------

Signed-off-by: ChengZi <chen.zhang@zilliz.com>
Co-authored-by: Cheney Zhang <chen.zhang@zilliz.com>
2025-03-06 20:59:31 -08:00

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Milvus

Milvus is an inline and remote vector database provider for Llama Stack. It allows you to store and query vectors directly within a Milvus database. That means you're not limited to storing vectors in memory or in a separate service.

Features

  • Easy to use
  • Fully integrated with Llama Stack

Usage

To use Milvus in your Llama Stack project, follow these steps:

  1. Install the necessary dependencies.
  2. Configure your Llama Stack project to use Milvus.
  3. Start storing and querying vectors.

Installation

You can install Milvus using pymilvus:

pip install pymilvus

Documentation

See the Milvus documentation for more details about Milvus in general.