alicloud-ai-search-milvus

name	alicloud-ai-search-milvus
description	Use AliCloud Milvus (serverless) with PyMilvus to create collections, insert vectors, and run filtered similarity search. Optimized for Claude Code/Codex vector retrieval flows.

Category: provider

AliCloud Milvus (Serverless) via PyMilvus

This skill uses standard PyMilvus APIs to connect to AliCloud Milvus and run vector search.

Prerequisites

• Install SDK (recommended in a venv to avoid PEP 668 limits):

python3 -m venv .venv
. .venv/bin/activate
python -m pip install --upgrade pymilvus

• Provide connection via environment variables:
  • MILVUS_URI (e.g. http://<host>:19530)
  • MILVUS_TOKEN (<username>:<password>)
  • MILVUS_DB (default: default)

Quickstart (Python)

import os
from pymilvus import MilvusClient

client = MilvusClient(
    uri=os.getenv("MILVUS_URI"),
    token=os.getenv("MILVUS_TOKEN"),
    db_name=os.getenv("MILVUS_DB", "default"),
)

# 1) Create a collection
client.create_collection(
    collection_name="docs",
    dimension=768,
)

# 2) Insert data
items = [
    {"id": 1, "vector": [0.01] * , : , : },
    {: , : [] * , : , : },
]
client.insert(collection_name=, data=items)


query_vectors = [[] * ]
res = client.search(
    collection_name=,
    data=query_vectors,
    limit=,
    =,
    output_fields=[, ],
)
(res)