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>

docs/source/providers/index.md

@@ -2,7 +2,7 @@
 
 The goal of Llama Stack is to build an ecosystem where users can easily swap out different implementations for the same API. Examples for these include:
 - LLM inference providers (e.g., Fireworks, Together, AWS Bedrock, Groq, Cerebras, SambaNova, vLLM, etc.),
-- Vector databases (e.g., ChromaDB, Weaviate, Qdrant, FAISS, PGVector, etc.),
+- Vector databases (e.g., ChromaDB, Weaviate, Qdrant, Milvus, FAISS, PGVector, etc.),
 - Safety providers (e.g., Meta's Llama Guard, AWS Bedrock Guardrails, etc.)
 
 Providers come in two flavors:
@@ -55,5 +55,6 @@ vector_io/sqlite-vec
 vector_io/chromadb
 vector_io/pgvector
 vector_io/qdrant
+vector_io/milvus
 vector_io/weaviate
 ```