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franciscojavierarceo merged 2 commits into from
Feb 27, 2025
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feat: Added docling and pytorch as add on #5089

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feat: Added docling and pytorch as add on
ntkathole Feb 25, 2025
adee3e0
Use multicloud/Dockerfile instead of Dockerfile.dev for operator e2e
ntkathole Feb 27, 2025
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feat: Added docling and pytorch as add on 
Signed-off-by: ntkathole <nikhilkathole2683@gmail.com>
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@ntkathole
ntkathole committed Feb 27, 2025
commit 7778335fe8fc52e5fe4248bc7623500857fc7d34
2 changes: 1 addition & 1 deletion docs/getting-started/architecture/push-vs-pull-model.md
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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
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@@ -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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5 changes: 4 additions & 1 deletion pyproject.toml
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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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