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feat: Added docling and pytorch as add on
Signed-off-by: ntkathole <nikhilkathole2683@gmail.com>
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‎docs/getting-started/architecture/push-vs-pull-model.md‎

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@@ -25,4 +25,4 @@ Implicit in the Push model are decisions about _how_ and _when_ to push feature
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From a developer's perspective, there are three ways to push feature values to the online store with different tradeoffs.
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They are discussed further in the [Write Patterns](getting-started/architecture/write-patterns.md) section.
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They are discussed further in the [Write Patterns](write-patterns.md) section.

‎docs/getting-started/architecture/write-patterns.md‎

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# Writing Data to Feast
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Feast uses a [Push Model](getting-started/architecture/push-vs-pull-model.md) to push features to the online store.
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Feast uses a [Push Model](push-vs-pull-model.md) to push features to the online store.
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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
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_feature value_ write patterns to Feast's online store.

‎pyproject.toml‎

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cassandra = ["cassandra-driver>=3.24.0,<4"]
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couchbase = ["couchbase==4.3.2"]
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delta = ["deltalake"]
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docling = ["docling>=2.23.0"]
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duckdb = ["ibis-framework[duckdb]>=9.0.0,<10"]
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elasticsearch = ["elasticsearch>=8.13.0"]
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faiss = ["faiss-cpu>=1.7.0,<2"]
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spark = ["pyspark>=3.0.0,<4"]
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trino = ["trino>=0.305.0,<0.400.0", "regex"]
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postgres = ["psycopg[binary,pool]>=3.0.0,<4"]
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pytorch = ["torch>=2.2.2", "torchvision>=0.17.2"]
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qdrant = ["qdrant-client>=1.12.0"]
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redis = [
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"redis>=4.2.2,<5",
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"types-setuptools",
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"types-tabulate",
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"virtualenv<20.24.2",
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"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]"
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"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]"
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]
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nlp = ["feast[docling, milvus, pytorch]"]
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dev = ["feast[ci]"]
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docs = ["feast[ci]"]
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