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feat: Added docling and pytorch as add on #5089

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Feb 27, 2025
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6 changes: 6 additions & 0 deletions Makefile
Original file line number Diff line number Diff line change
Expand Up @@ -527,6 +527,12 @@ build-feast-operator-docker:

# Dev images

build-feature-server-dev-minimal:
docker buildx build \
-t feastdev/feature-server:dev \
-f sdk/python/feast/infra/feature_servers/multicloud/Dockerfile \
--load sdk/python/feast/infra/feature_servers/multicloud

Comment on lines +530 to +535
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this is just a release build... its not a dev image build

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we'll need to remove this

build-feature-server-dev:
docker buildx build \
-t feastdev/feature-server:dev \
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2 changes: 1 addition & 1 deletion docs/getting-started/architecture/push-vs-pull-model.md
Original file line number Diff line number Diff line change
Expand Up @@ -25,4 +25,4 @@ Implicit in the Push model are decisions about _how_ and _when_ to push feature

From a developer's perspective, there are three ways to push feature values to the online store with different tradeoffs.

They are discussed further in the [Write Patterns](getting-started/architecture/write-patterns.md) section.
They are discussed further in the [Write Patterns](write-patterns.md) section.
2 changes: 1 addition & 1 deletion docs/getting-started/architecture/write-patterns.md
Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
# Writing Data to Feast

Feast uses a [Push Model](getting-started/architecture/push-vs-pull-model.md) to push features to the online store.
Feast uses a [Push Model](push-vs-pull-model.md) to push features to the online store.

This has two important consequences: (1) communication patterns between the Data Producer (i.e., the client) and Feast (i.e,. the server) and (2) feature computation and
_feature value_ write patterns to Feast's online store.
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2 changes: 1 addition & 1 deletion infra/feast-operator/Makefile
Original file line number Diff line number Diff line change
Expand Up @@ -162,7 +162,7 @@ docker-build: ## Build docker image with the manager.
## Build feast docker image.
.PHONY: feast-ci-dev-docker-img
feast-ci-dev-docker-img:
cd ./../.. && make build-feature-server-dev
cd ./../.. && make build-feature-server-dev-minimal
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@franciscojavierarceo Since we do not have larger runner to run kind + feast with all dependencies, either we need self-hosted runners or we need to use image with minimal dependencies installed in CI.
Currently moving from multicloud/Dockerfile.dev to multicloud/Dockerfile works in CI to run operator e2e test.

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My concern is that we miss potential breaks by using this minimal image. That's the risk here, right?

Cc @lokeshrangineni @tchughesiv @redhatHameed

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We will be using this image just for operator e2e test, feast functionality will be tested via integration and unit tests with all dependencies installed.
@tchughesiv or someone more familiar with operator work can confirm if it's a big risk in operator testing or better way to handle this.

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this change needs to be reverted

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@tchughesiv tchughesiv Mar 3, 2025

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@ntkathole @franciscojavierarceo this must remain make build-feature-server-dev



.PHONY: docker-push
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5 changes: 4 additions & 1 deletion pyproject.toml
Original file line number Diff line number Diff line change
Expand Up @@ -57,6 +57,7 @@ azure = [
cassandra = ["cassandra-driver>=3.24.0,<4"]
couchbase = ["couchbase==4.3.2"]
delta = ["deltalake"]
docling = ["docling>=2.23.0"]
duckdb = ["ibis-framework[duckdb]>=9.0.0,<10"]
elasticsearch = ["elasticsearch>=8.13.0"]
faiss = ["faiss-cpu>=1.7.0,<2"]
Expand Down Expand Up @@ -94,6 +95,7 @@ opentelemetry = ["prometheus_client", "psutil"]
spark = ["pyspark>=3.0.0,<4"]
trino = ["trino>=0.305.0,<0.400.0", "regex"]
postgres = ["psycopg[binary,pool]>=3.0.0,<4"]
pytorch = ["torch>=2.2.2", "torchvision>=0.17.2"]
qdrant = ["qdrant-client>=1.12.0"]
redis = [
"redis>=4.2.2,<5",
Expand Down Expand Up @@ -148,8 +150,9 @@ ci = [
"types-setuptools",
"types-tabulate",
"virtualenv<20.24.2",
"feast[aws, azure, cassandra, couchbase, delta, duckdb, elasticsearch, faiss, gcp, ge, go, grpcio, hazelcast, hbase, ibis, ikv, k8s, milvus, mssql, mysql, opentelemetry, spark, trino, postgres, qdrant, redis, singlestore, snowflake, sqlite_vec]"
"feast[aws, azure, cassandra, couchbase, delta, docling, duckdb, elasticsearch, faiss, gcp, ge, go, grpcio, hazelcast, hbase, ibis, ikv, k8s, milvus, mssql, mysql, opentelemetry, spark, trino, postgres, pytorch, qdrant, redis, singlestore, snowflake, sqlite_vec]"
]
nlp = ["feast[docling, milvus, pytorch]"]
dev = ["feast[ci]"]
docs = ["feast[ci]"]

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