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https://github.com/lancedb/lancedb.git
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ci: fix broken CI checks (#2585)
This commit is contained in:
4
.github/workflows/nodejs.yml
vendored
4
.github/workflows/nodejs.yml
vendored
@@ -79,7 +79,7 @@ jobs:
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with:
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node-version: ${{ matrix.node-version }}
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cache: 'npm'
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cache-dependency-path: node/package-lock.json
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cache-dependency-path: nodejs/package-lock.json
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- uses: Swatinem/rust-cache@v2
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- name: Install dependencies
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run: |
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@@ -137,7 +137,7 @@ jobs:
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with:
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node-version: 20
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cache: 'npm'
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cache-dependency-path: node/package-lock.json
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cache-dependency-path: nodejs/package-lock.json
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- uses: Swatinem/rust-cache@v2
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- name: Install dependencies
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run: |
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@@ -12,7 +12,7 @@ test("ann index examples", async () => {
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// --8<-- [start:ingest]
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const db = await lancedb.connect(databaseDir);
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const data = Array.from({ length: 5_000 }, (_, i) => ({
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const data = Array.from({ length: 1_000 }, (_, i) => ({
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vector: Array(128).fill(i),
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id: `${i}`,
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content: "",
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@@ -24,8 +24,8 @@ test("ann index examples", async () => {
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});
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await table.createIndex("vector", {
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config: lancedb.Index.ivfPq({
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numPartitions: 10,
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numSubVectors: 16,
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numPartitions: 30,
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numSubVectors: 8,
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}),
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});
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// --8<-- [end:ingest]
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@@ -910,7 +910,7 @@ class LanceQueryBuilder(ABC):
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ProjectionExec: expr=[vector@0 as vector, _distance@2 as _distance]
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GlobalLimitExec: skip=0, fetch=10
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FilterExec: _distance@2 IS NOT NULL
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SortExec: TopK(fetch=10), expr=[_distance@2 ASC NULLS LAST], preserve_partitioning=[false]
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SortExec: TopK(fetch=10), expr=[_distance@2 ASC NULLS LAST, _rowid@1 ASC NULLS LAST], preserve_partitioning=[false]
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KNNVectorDistance: metric=l2
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LanceRead: uri=..., projection=[vector], ...
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@@ -2041,11 +2041,11 @@ class LanceHybridQueryBuilder(LanceQueryBuilder):
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>>> plan = table.search(query).explain_plan(True)
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>>> print(plan) # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
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ProjectionExec: expr=[vector@0 as vector, _distance@2 as _distance]
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GlobalLimitExec: skip=0, fetch=10
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FilterExec: _distance@2 IS NOT NULL
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SortExec: TopK(fetch=10), expr=[_distance@2 ASC NULLS LAST], preserve_partitioning=[false]
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KNNVectorDistance: metric=l2
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LanceRead: uri=..., projection=[vector], ...
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GlobalLimitExec: skip=0, fetch=10
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FilterExec: _distance@2 IS NOT NULL
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SortExec: TopK(fetch=10), expr=[_distance@2 ASC NULLS LAST, _rowid@1 ASC NULLS LAST], preserve_partitioning=[false]
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KNNVectorDistance: metric=l2
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LanceRead: uri=..., projection=[vector], ...
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Parameters
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----------
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@@ -2429,7 +2429,7 @@ class AsyncQueryBase(object):
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ProjectionExec: expr=[vector@0 as vector, _distance@2 as _distance]
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GlobalLimitExec: skip=0, fetch=10
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FilterExec: _distance@2 IS NOT NULL
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SortExec: TopK(fetch=10), expr=[_distance@2 ASC NULLS LAST], preserve_partitioning=[false]
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SortExec: TopK(fetch=10), expr=[_distance@2 ASC NULLS LAST, _rowid@1 ASC NULLS LAST], preserve_partitioning=[false]
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KNNVectorDistance: metric=l2
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LanceRead: uri=..., projection=[vector], ...
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@@ -3054,7 +3054,7 @@ class AsyncHybridQuery(AsyncQueryBase, AsyncVectorQueryBase):
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CoalesceBatchesExec: target_batch_size=1024
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GlobalLimitExec: skip=0, fetch=10
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FilterExec: _distance@2 IS NOT NULL
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SortExec: TopK(fetch=10), expr=[_distance@2 ASC NULLS LAST], preserve_partitioning=[false]
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SortExec: TopK(fetch=10), expr=[_distance@2 ASC NULLS LAST, _rowid@1 ASC NULLS LAST], preserve_partitioning=[false]
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KNNVectorDistance: metric=l2
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LanceRead: uri=..., projection=[vector], ...
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<BLANKLINE>
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@@ -290,7 +290,7 @@ def test_add_struct(mem_db: DBConnection):
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}
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)
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data = [{"s_list": [{"b": 1, "a": 2}, {"b": 4}]}]
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table = mem_db.create_table("test", schema=schema)
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table = mem_db.create_table("test2", schema=schema)
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table.add(data)
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