Geneva - Multimodal Data Lake for AI
Project description
Geneva - Multimodal Data Platform
Geneva is a petabyte-scale multimodal feature engineering and data management platform built on LanceDB.
What lives in this repo
src/- Geneva client library and core runtimesrc/tests/- unit test suitessrc/integ_tests/- integration test suitessrc/stress_tests/- stress and load testsdocs/- mkdocs configuration and API docs (source for autogenerated public facing api documentation page)e2e/- end-to-end test suites and UDF manifestsnotebook/- quickstart notebooks (TODO replace with link to colab demo notebook)internal_docs/- internal design and operational notestools/- helper scripts for local clusters and cleanup
User facing documentation should be submitted here.
Quickstart (local development)
uv sync --all-groups --all-extras --locked
import geneva
import pyarrow as pa
@geneva.udf(data_type=pa.int32())
def double(x: int) -> int:
return x * 2
conn = geneva.connect("./db")
table = conn.create_table("numbers", [{"x": i} for i in range(10)])
table.add_columns({"doubled": double})
with conn.local_ray_context():
table.backfill("doubled")
result = table.search().select(["doubled"]).to_arrow()
Development
See Development for details.
Configuration
Geneva supports specifying configuration in a few different ways. Refer to CONFIGURATION.md for more details.
Project details
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