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feat: Qdrant vectorstore support (#4689)
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* feat: Qdrant vectorstore support

Signed-off-by: Anush008 <[email protected]>

* chore: make build-ui again

Signed-off-by: Anush008 <[email protected]>

---------

Signed-off-by: Anush008 <[email protected]>
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8 changes: 8 additions & 0 deletions Makefile
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Expand Up @@ -351,6 +351,14 @@ test-python-universal-singlestore-online:
not test_snowflake" \
sdk/python/tests

test-python-universal-qdrant-online:
PYTHONPATH='.' \
FULL_REPO_CONFIGS_MODULE=sdk.python.feast.infra.online_stores.contrib.qdrant_repo_configuration \
PYTEST_PLUGINS=sdk.python.tests.integration.feature_repos.universal.online_store.qdrant \
python -m pytest -n 8 --integration \
-k "test_retrieve_online_documents" \
sdk/python/tests/integration/online_store/test_universal_online.py

test-python-universal:
python -m pytest -n 8 --integration sdk/python/tests

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22 changes: 19 additions & 3 deletions docs/reference/alpha-vector-database.md
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Expand Up @@ -14,8 +14,9 @@ Below are supported vector databases and implemented features:
| Milvus | [ ] | [ ] |
| Faiss | [ ] | [ ] |
| SQLite | [x] | [ ] |
| Qdrant | [x] | [x] |

Note: SQLite is in limited access and only working on Python 3.10. It will be updated as [sqlite_vec](https://github.com/asg017/sqlite-vec/) progresses.
Note: SQLite is in limited access and only working on Python 3.10. It will be updated as [sqlite_vec](https://github.com/asg017/sqlite-vec/) progresses.

## Example

Expand Down Expand Up @@ -113,9 +114,11 @@ print_online_features(features)
```

### Configuration
We offer two Online Store options for Vector Databases. PGVector and SQLite.

We offer [PGVector](https://github.com/pgvector/pgvector), [SQLite](https://github.com/asg017/sqlite-vec), [Elasticsearch](https://www.elastic.co) and [Qdrant](https://qdrant.tech/) as Online Store options for Vector Databases.

#### Installation with SQLite

If you are using `pyenv` to manage your Python versions, you can install the SQLite extension with the following command:
```bash
PYTHON_CONFIGURE_OPTS="--enable-loadable-sqlite-extensions" \
Expand All @@ -124,6 +127,19 @@ PYTHON_CONFIGURE_OPTS="--enable-loadable-sqlite-extensions" \
pyenv install 3.10.14
```
And you can the Feast install package via:

```bash
pip install feast[sqlite_vec]
```
```

#### Installation with Elasticsearch

```bash
pip install feast[elasticsearch]
```

#### Installation with Qdrant

```bash
pip install feast[qdrant]
```
81 changes: 81 additions & 0 deletions docs/reference/online-stores/qdrant.md
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# Qdrant online store (contrib)

## Description

[Qdrant](http://qdrant.tech) is a vector similarity search engine. It provides a production-ready service with a convenient API to store, search, and manage vectors with additional payload and extended filtering support. It makes it useful for all sorts of neural network or semantic-based matching, faceted search, and other applications.

## Getting started

In order to use this online store, you'll need to run `pip install 'feast[qdrant]'`.

## Example

{% code title="feature_store.yaml" %}

```yaml
project: my_feature_repo
registry: data/registry.db
provider: local
online_store:
type: qdrant
host: localhost
port: 6333
vector_len: 384
write_batch_size: 100
```
{% endcode %}
The full set of configuration options is available in [QdrantOnlineStoreConfig](https://rtd.feast.dev/en/master/#feast.infra.online_stores.contrib.qdrant.QdrantOnlineStoreConfig).
## Functionality Matrix
| | Qdrant |
| :-------------------------------------------------------- | :------- |
| write feature values to the online store | yes |
| read feature values from the online store | yes |
| update infrastructure (e.g. tables) in the online store | yes |
| teardown infrastructure (e.g. tables) in the online store | yes |
| generate a plan of infrastructure changes | no |
| support for on-demand transforms | yes |
| readable by Python SDK | yes |
| readable by Java | no |
| readable by Go | no |
| support for entityless feature views | yes |
| support for concurrent writing to the same key | no |
| support for ttl (time to live) at retrieval | no |
| support for deleting expired data | no |
| collocated by feature view | yes |
| collocated by feature service | no |
| collocated by entity key | no |
To compare this set of functionality against other online stores, please see the full [functionality matrix](overview.md#functionality-matrix).
## Retrieving online document vectors
The Qdrant online store supports retrieving document vectors for a given list of entity keys. The document vectors are returned as a dictionary where the key is the entity key and the value is the document vector. The document vector is a dense vector of floats.
{% code title="python" %}
```python
from feast import FeatureStore

feature_store = FeatureStore(repo_path="feature_store.yaml")

query_vector = [1.0, 2.0, 3.0, 4.0, 5.0]
top_k = 5

# Retrieve the top k closest features to the query vector
# Since Qdrant supports multiple vectors per entry,
# the vector to use can be specified in the repo config.
# Reference: https://qdrant.tech/documentation/concepts/vectors/#named-vectors
feature_values = feature_store.retrieve_online_documents(
feature="my_feature",
query=query_vector,
top_k=top_k
)
```

{% endcode %}

These APIs are subject to change in future versions of Feast to improve performance and usability.
16 changes: 16 additions & 0 deletions sdk/python/docs/source/feast.infra.online_stores.contrib.rst
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Expand Up @@ -40,6 +40,22 @@ feast.infra.online\_stores.contrib.elasticsearch\_repo\_configuration module
:undoc-members:
:show-inheritance:

feast.infra.online\_stores.contrib.qdrant module
-------------------------------------------------------

.. automodule:: feast.infra.online_stores.contrib.qdrant
:members:
:undoc-members:
:show-inheritance:

feast.infra.online\_stores.contrib.qdrant\_repo\_configuration module
----------------------------------------------------------------------------

.. automodule:: feast.infra.online_stores.contrib.qdrant_repo_configuration
:members:
:undoc-members:
:show-inheritance:

feast.infra.online\_stores.contrib.hazelcast\_repo\_configuration module
------------------------------------------------------------------------

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Expand Up @@ -45,6 +45,7 @@
"thrift",
"tpcds",
"tpch",
"qdrant",
}
CONNECTORS_WITHOUT_WITH_STATEMENTS: Set[str] = {
"bigquery",
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