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Milvus is the open-source, cloud-native vector database that scales to billions of vectors. It's the open-source version of Zilliz. It supports:
Visit the Github to learn more.
You can deploy and manage Milvus using Docker Compose, Helm, K8's Operator, or Ansible. Follow the instructions here to get started.
Environment Variables:
Name | Required | Description |
---|---|---|
DATASTORE |
Yes | Datastore name, set to milvus |
BEARER_TOKEN |
Yes | Your bearer token |
OPENAI_API_KEY |
Yes | Your OpenAI API key |
MILVUS_COLLECTION |
Optional | Milvus collection name, defaults to a random UUID |
MILVUS_HOST |
Optional | Milvus host IP, defaults to localhost |
MILVUS_PORT |
Optional | Milvus port, defaults to 19530 |
MILVUS_USER |
Optional | Milvus username if RBAC is enabled, defaults to None |
MILVUS_PASSWORD |
Optional | Milvus password if required, defaults to None |
MILVUS_INDEX_PARAMS |
Optional | Custom index options for the collection, defaults to {"metric_type": "IP", "index_type": "HNSW", "params": {"M": 8, "efConstruction": 64}} |
MILVUS_SEARCH_PARAMS |
Optional | Custom search options for the collection, defaults to {"metric_type": "IP", "params": {"ef": 10}} |
MILVUS_CONSISTENCY_LEVEL |
Optional | Data consistency level for the collection, defaults to Bounded |
A suite of integration tests is available to verify the Milvus integration. To run the tests, run the milvus docker compose found in the examples folder.
Then, launch the test suite with this command:
pytest ./tests/datastore/providers/milvus/test_milvus_datastore.py
Press p or to see the previous file or, n or to see the next file
Are you sure you want to delete this access key?
Are you sure you want to delete this access key?
Are you sure you want to delete this access key?
Are you sure you want to delete this access key?