git: f6f34943182e - main - databases/py-redisvl: Add port: Python client library and CLI for using Redis as a vector database

From: Hiroki Tagato <tagattie_at_FreeBSD.org>
Date: Wed, 15 Oct 2025 07:36:23 UTC
The branch main has been updated by tagattie:

URL: https://cgit.FreeBSD.org/ports/commit/?id=f6f34943182e2f4f31c3cb789319c392a53e2027

commit f6f34943182e2f4f31c3cb789319c392a53e2027
Author:     Hiroki Tagato <tagattie@FreeBSD.org>
AuthorDate: 2025-10-15 07:34:47 +0000
Commit:     Hiroki Tagato <tagattie@FreeBSD.org>
CommitDate: 2025-10-15 07:36:09 +0000

    databases/py-redisvl: Add port: Python client library and CLI for using Redis as a vector database
    
    Redis Vector Library (RedisVL) is the production-ready Python client
    for AI applications built on Redis. Lightning-fast vector search meets
    enterprise-grade reliability.
    
    Built for Modern AI Workloads:
    - RAG Pipelines -> Real-time retrieval with hybrid search capabilities
    - AI Agents -> Short term & long term memory and semantic routing for
      intent-based decisions
    - Recommendation Systems -> Fast retrieval and reranking
    
    WWW: https://github.com/redis/redis-vl-python
---
 databases/Makefile             |  1 +
 databases/py-redisvl/Makefile  | 38 ++++++++++++++++++++++++++++++++++++++
 databases/py-redisvl/distinfo  |  3 +++
 databases/py-redisvl/pkg-descr |  9 +++++++++
 4 files changed, 51 insertions(+)

diff --git a/databases/Makefile b/databases/Makefile
index 5ac70381f6ed..9e2eaa683ef9 100644
--- a/databases/Makefile
+++ b/databases/Makefile
@@ -841,6 +841,7 @@
     SUBDIR += py-redis
     SUBDIR += py-redis2
     SUBDIR += py-redis5
+    SUBDIR += py-redisvl
     SUBDIR += py-rrdtool
     SUBDIR += py-schemachange
     SUBDIR += py-sispy
diff --git a/databases/py-redisvl/Makefile b/databases/py-redisvl/Makefile
new file mode 100644
index 000000000000..8dc2d6eda00a
--- /dev/null
+++ b/databases/py-redisvl/Makefile
@@ -0,0 +1,38 @@
+PORTNAME=	redisvl
+DISTVERSION=	0.9.1
+CATEGORIES=	databases python
+MASTER_SITES=	PYPI
+PKGNAMEPREFIX=	${PYTHON_PKGNAMEPREFIX}
+
+MAINTAINER=	tagattie@FreeBSD.org
+COMMENT=	Python client library and CLI for using Redis as a vector database
+WWW=		https://github.com/redis/redis-vl-python
+
+LICENSE=	MIT
+LICENSE_FILE=	${WRKSRC}/LICENSE
+
+BUILD_DEPENDS=	${PYTHON_PKGNAMEPREFIX}hatchling>0:devel/py-hatchling@${PY_FLAVOR}
+RUN_DEPENDS=	${PYNUMPY} \
+		${PYTHON_PKGNAMEPREFIX}pyyaml>=5.4<7.0:devel/py-pyyaml@${PY_FLAVOR} \
+		${PYTHON_PKGNAMEPREFIX}redis>=5.0<7.0:databases/py-redis@${PY_FLAVOR} \
+		${PYTHON_PKGNAMEPREFIX}pydantic2>=2<3:devel/py-pydantic2@${PY_FLAVOR} \
+		${PYTHON_PKGNAMEPREFIX}tenacity>=8.2.2:devel/py-tenacity@${PY_FLAVOR} \
+		${PYTHON_PKGNAMEPREFIX}ml-dtypes>=0.4.0<1.0.0:math/py-ml-dtypes@${PY_FLAVOR} \
+		${PYTHON_PKGNAMEPREFIX}python-ulid>=3.0.0:textproc/py-python-ulid@${PY_FLAVOR} \
+		${PYTHON_PKGNAMEPREFIX}jsonpath-ng>=1.5.0:devel/py-jsonpath-ng@${PY_FLAVOR}
+
+USES=		python
+
+USE_PYTHON=	autoplist concurrent pep517
+
+NO_ARCH=	yes
+
+PORTDOCS=	CONTRIBUTING.md README.md
+
+OPTIONS_DEFINE=	DOCS
+
+do-install-DOCS-on:
+	@${MKDIR} ${STAGEDIR}${DOCSDIR}
+	${INSTALL_MAN} ${PORTDOCS:S|^|${WRKSRC}/|} ${STAGEDIR}${DOCSDIR}
+
+.include <bsd.port.mk>
diff --git a/databases/py-redisvl/distinfo b/databases/py-redisvl/distinfo
new file mode 100644
index 000000000000..b92a628c3925
--- /dev/null
+++ b/databases/py-redisvl/distinfo
@@ -0,0 +1,3 @@
+TIMESTAMP = 1760507103
+SHA256 (redisvl-0.9.1.tar.gz) = a735ecf3238e804800b54a513b85a8cf4300fe6d111fb055bd75528f77dd5419
+SIZE (redisvl-0.9.1.tar.gz) = 606980
diff --git a/databases/py-redisvl/pkg-descr b/databases/py-redisvl/pkg-descr
new file mode 100644
index 000000000000..e06569dd1329
--- /dev/null
+++ b/databases/py-redisvl/pkg-descr
@@ -0,0 +1,9 @@
+Redis Vector Library (RedisVL) is the production-ready Python client
+for AI applications built on Redis. Lightning-fast vector search meets
+enterprise-grade reliability.
+
+Built for Modern AI Workloads:
+- RAG Pipelines -> Real-time retrieval with hybrid search capabilities
+- AI Agents -> Short term & long term memory and semantic routing for
+  intent-based decisions
+- Recommendation Systems -> Fast retrieval and reranking