Bump version: 0.1.5 → 0.1.6

Closes #181

.bumpversion.cfg

@@ -0,0 +1,12 @@
+[bumpversion]
+current_version = 0.1.6
+commit = True
+message = Bump version: {current_version} → {new_version}
+tag = True
+tag_name = v{new_version}
+
+[bumpversion:file:node/package.json]
+
+[bumpversion:file:rust/ffi/node/Cargo.toml]
+
+[bumpversion:file:rust/vectordb/Cargo.toml]

.github/workflows/cargo-publish.yml

@@ -0,0 +1,29 @@
+name: Cargo Publish
+
+on:
+  release:
+    types: [ published ]
+
+env:
+  # This env var is used by Swatinem/rust-cache@v2 for the cache
+  # key, so we set it to make sure it is always consistent.
+  CARGO_TERM_COLOR: always
+
+jobs:
+  build:
+    runs-on: ubuntu-22.04
+    timeout-minutes: 30
+    # Only runs on tags that matches the make-release action
+    if: startsWith(github.ref, 'refs/tags/v')
+    steps:
+      - uses: actions/checkout@v3
+      - uses: Swatinem/rust-cache@v2
+        with:
+          workspaces: rust
+      - name: Install dependencies
+        run: |
+          sudo apt update
+          sudo apt install -y protobuf-compiler libssl-dev
+      - name: Publish the package
+        run: |
+          cargo publish -p vectordb --all-features --token ${{ secrets.CARGO_REGISTRY_TOKEN }}

.github/workflows/make-release-commit.yml

@@ -0,0 +1,55 @@
+name: Create release commit
+
+on:
+  workflow_dispatch:
+    inputs:
+      dry_run:
+        description: 'Dry run (create the local commit/tags but do not push it)'
+        required: true
+        default: "false"
+        type: choice
+        options:
+          - "true"
+          - "false"
+      part:
+        description: 'What kind of release is this?'
+        required: true
+        default: 'patch'
+        type: choice
+        options:
+          - patch
+          - minor
+          - major
+
+jobs:
+  bump-version:
+    runs-on: ubuntu-latest
+    steps:
+    - name: Check out main
+      uses: actions/checkout@v3
+      with:
+        ref: main
+        persist-credentials: false
+        fetch-depth: 0
+        lfs: true
+    - name: Set git configs for bumpversion
+      shell: bash
+      run: |
+        git config user.name 'Lance Release'
+        git config user.email 'lance-dev@lancedb.com'
+    - name: Set up Python 3.10
+      uses: actions/setup-python@v4
+      with:
+        python-version: "3.10"
+    - name: Bump version, create tag and commit
+      run: |
+        pip install bump2version
+        bumpversion --verbose ${{ inputs.part }}
+    - name: Push new version and tag
+      if: ${{ inputs.dry_run }} == "false"
+      uses: ad-m/github-push-action@master
+      with:
+        github_token: ${{ secrets.LANCEDB_RELEASE_TOKEN }}
+        branch: main
+        tags: true
+

.github/workflows/pypi-publish.yml

@@ -3,12 +3,12 @@ name: PyPI Publish
 on:
   release:
     types: [ published ]
-    tags:
-      - 'python-v*' # Push events that matches the python-make-release action
 
 jobs:
   publish:
     runs-on: ubuntu-latest
+    # Only runs on tags that matches the python-make-release action
+    if: startsWith(github.ref, 'refs/tags/python-v')
     defaults:
       run:
         shell: bash

.github/workflows/rust.yml

@@ -0,0 +1,67 @@
+name: Rust
+
+on:
+  push:
+    branches:
+      - main
+  pull_request:
+    paths:
+      - rust/**
+      - .github/workflows/rust.yml
+
+env:
+  # This env var is used by Swatinem/rust-cache@v2 for the cache
+  # key, so we set it to make sure it is always consistent.
+  CARGO_TERM_COLOR: always
+  # Disable full debug symbol generation to speed up CI build and keep memory down
+  # "1" means line tables only, which is useful for panic tracebacks.
+  RUSTFLAGS: "-C debuginfo=1"
+  RUST_BACKTRACE: "1"
+
+jobs:
+  linux:
+    timeout-minutes: 30
+    runs-on: ubuntu-22.04
+    defaults:
+      run:
+        shell: bash
+        working-directory: rust
+    steps:
+    - uses: actions/checkout@v3
+      with:
+          fetch-depth: 0
+          lfs: true
+    - uses: Swatinem/rust-cache@v2
+      with:
+          workspaces: rust
+    - name: Install dependencies
+      run: |
+          sudo apt update
+          sudo apt install -y protobuf-compiler libssl-dev
+    - name: Build
+      run: cargo build --all-features
+    - name: Run tests
+      run: cargo test --all-features
+  macos:
+    runs-on: macos-12
+    timeout-minutes: 30
+    defaults:
+      run:
+        shell: bash
+        working-directory: rust
+    steps:
+      - uses: actions/checkout@v3
+        with:
+            fetch-depth: 0
+            lfs: true
+      - name: CPU features
+        run: sysctl -a | grep cpu
+      - uses: Swatinem/rust-cache@v2
+        with:
+          workspaces: rust
+      - name: Install dependencies
+        run: brew install protobuf
+      - name: Build
+        run: cargo build --all-features
+      - name: Run tests
+        run: cargo test --all-features

Cargo.lock

@@ -190,6 +190,7 @@ dependencies = [
  "arrow-data",
  "arrow-schema",
  "flatbuffers",
+ "zstd",
 ]
 
 [[package]]
@@ -654,6 +655,12 @@ version = "3.12.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "9b1ce199063694f33ffb7dd4e0ee620741495c32833cde5aa08f02a0bf96f0c8"
 
+[[package]]
+name = "bytemuck"
+version = "1.13.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "17febce684fd15d89027105661fec94afb475cb995fbc59d2865198446ba2eea"
+
 [[package]]
 name = "byteorder"
 version = "1.4.3"
@@ -1646,9 +1653,9 @@ dependencies = [
 
 [[package]]
 name = "lance"
-version = "0.4.17"
+version = "0.4.21"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "86dda8185bd1ffae7b910c1f68035af23be9b717c52e9cc4de176cd30b47f772"
+checksum = "3d6c2e7bcfc71c7167ec70cd06c6d55c644a148f6580218c5a0b66e13ac5b5cc"
 dependencies = [
  "accelerate-src",
  "arrow",
@@ -1657,7 +1664,9 @@ dependencies = [
  "arrow-buffer",
  "arrow-cast",
  "arrow-data",
+ "arrow-ipc",
  "arrow-ord",
+ "arrow-row",
  "arrow-schema",
  "arrow-select",
  "async-recursion",
@@ -1668,6 +1677,7 @@ dependencies = [
  "bytes",
  "cblas",
  "chrono",
+ "dashmap",
  "datafusion",
  "futures",
  "lapack",
@@ -1684,6 +1694,7 @@ dependencies = [
  "prost-types",
  "rand",
  "reqwest",
+ "roaring",
  "shellexpand",
  "snafu",
  "sqlparser-lance",
@@ -2598,6 +2609,12 @@ dependencies = [
  "winreg",
 ]
 
+[[package]]
+name = "retain_mut"
+version = "0.1.7"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "8c31b5c4033f8fdde8700e4657be2c497e7288f01515be52168c631e2e4d4086"
+
 [[package]]
 name = "ring"
 version = "0.16.20"
@@ -2613,6 +2630,17 @@ dependencies = [
  "winapi",
 ]
 
+[[package]]
+name = "roaring"
+version = "0.10.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "ef0fb5e826a8bde011ecae6a8539dd333884335c57ff0f003fbe27c25bbe8f71"
+dependencies = [
+ "bytemuck",
+ "byteorder",
+ "retain_mut",
+]
+
 [[package]]
 name = "rustc_version"
 version = "0.4.0"

docs/src/ann_indexes.md

@@ -67,7 +67,7 @@ There are a couple of parameters that can be used to fine-tune the search:
   e.g., for 1M vectors divided up into 256 partitions, nprobes should be set to ~20-40.<br/>
   Note: nprobes is only applicable if an ANN index is present. If specified on a table without an ANN index, it is ignored.
 - **refine_factor** (default: None): Refine the results by reading extra elements and re-ranking them in memory.<br/>
-  A higher number makes search more accurate but also slower. If you find the recall is less than idea, try refine_factor=10 to start.<br/>
+  A higher number makes search more accurate but also slower. If you find the recall is less than ideal, try refine_factor=10 to start.<br/>
   e.g., for 1M vectors divided into 256 partitions, if you're looking for top 20, then refine_factor=200 reranks the whole partition.<br/>
   Note: refine_factor is only applicable if an ANN index is present. If specified on a table without an ANN index, it is ignored.
 

docs/src/index.md

@@ -14,7 +14,7 @@ The key features of LanceDB include:
 
 * Zero-copy, automatic versioning, manage versions of your data without needing extra infrastructure.
 
-* Ecosystem integrations with [LangChain 🦜️🔗](https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/lanecdb.html), [LlamaIndex 🦙](https://gpt-index.readthedocs.io/en/latest/examples/vector_stores/LanceDBIndexDemo.html), Apache-Arrow, Pandas, Polars, DuckDB and more on the way.
+* Ecosystem integrations with [LangChain 🦜️🔗](https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/lancedb.html), [LlamaIndex 🦙](https://gpt-index.readthedocs.io/en/latest/examples/vector_stores/LanceDBIndexDemo.html), Apache-Arrow, Pandas, Polars, DuckDB and more on the way.
 
 LanceDB's core is written in Rust 🦀 and is built using <a href="https://github.com/lancedb/lance">Lance</a>, an open-source columnar format designed for performant ML workloads.
 

node/package.json

@@ -1,6 +1,6 @@
 {
   "name": "vectordb",
-  "version": "0.1.5",
+  "version": "0.1.6",
   "description": " Serverless, low-latency vector database for AI applications",
   "main": "dist/index.js",
   "types": "dist/index.d.ts",

node/src/index.ts

@@ -293,6 +293,8 @@ export class Query<T = number[]> {
     return this
   }
 
+  where = this.filter
+
   /** Return only the specified columns.
    *
    * @param value Only select the specified columns. If not specified, all columns will be returned.

node/src/test/test.ts

@@ -64,13 +64,20 @@ describe('LanceDB client', function () {
       assert.equal(results[0].id, 1)
     })
 
-    it('uses a filter', async function () {
+    it('uses a filter / where clause', async function () {
+      // eslint-disable-next-line @typescript-eslint/explicit-function-return-type
+      const assertResults = (results: Array<Record<string, unknown>>) => {
+        assert.equal(results.length, 1)
+        assert.equal(results[0].id, 2)
+      }
+
       const uri = await createTestDB()
       const con = await lancedb.connect(uri)
       const table = await con.openTable('vectors')
-      const results = await table.search([0.1, 0.1]).filter('id == 2').execute()
+      let results = await table.search([0.1, 0.1]).filter('id == 2').execute()
-      assert.equal(results.length, 1)
+      assertResults(results)
-      assert.equal(results[0].id, 2)
+      results = await table.search([0.1, 0.1]).where('id == 2').execute()
+      assertResults(results)
     })
 
     it('select only a subset of columns', async function () {

python/lancedb/context.py

@@ -42,34 +42,38 @@ def contextualize(raw_df: pd.DataFrame) -> Contextualizer:
     paragraphs, messages, etc.
 
     >>> contextualize(data).window(3).stride(1).text_col('token').to_df()
-                  token  document_id
+                    token  document_id
-    0   The quick brown            1
+    0     The quick brown            1
-    1   quick brown fox            1
+    1     quick brown fox            1
-    2  brown fox jumped            1
+    2    brown fox jumped            1
-    3   fox jumped over            1
+    3     fox jumped over            1
-    4   jumped over the            1
+    4     jumped over the            1
-    5     over the lazy            1
+    5       over the lazy            1
-    6      the lazy dog            1
+    6        the lazy dog            1
-    7        lazy dog I            1
+    7          lazy dog I            1
-    8        dog I love            1
+    8          dog I love            1
-    >>> contextualize(data).window(7).stride(1).text_col('token').to_df()
+    9   I love sandwiches            2
+    10    love sandwiches            2
+    >>> contextualize(data).window(7).stride(1).min_window_size(7).text_col('token').to_df()
                                       token  document_id
     0   The quick brown fox jumped over the            1
     1  quick brown fox jumped over the lazy            1
     2    brown fox jumped over the lazy dog            1
     3        fox jumped over the lazy dog I            1
     4       jumped over the lazy dog I love            1
-
+    5   over the lazy dog I love sandwiches            1
 
     ``stride`` determines how many rows to skip between each window start. This can
     be used to reduce the total number of windows generated.
 
     >>> contextualize(data).window(4).stride(2).text_col('token').to_df()
-                       token  document_id
+                        token  document_id
-    0    The quick brown fox            1
+    0     The quick brown fox            1
-    2  brown fox jumped over            1
+    2   brown fox jumped over            1
-    4   jumped over the lazy            1
+    4    jumped over the lazy            1
-    6         the lazy dog I            1
+    6          the lazy dog I            1
+    8   dog I love sandwiches            1
+    10        love sandwiches            2
 
     ``groupby`` determines how to group the rows. For example, we would like to have
     context windows that don't cross document boundaries. In this case, we can
@@ -80,6 +84,25 @@ def contextualize(raw_df: pd.DataFrame) -> Contextualizer:
     0    The quick brown fox            1
     2  brown fox jumped over            1
     4   jumped over the lazy            1
+    6           the lazy dog            1
+    9      I love sandwiches            2
+
+    ``min_window_size`` determines the minimum size of the  context windows that are generated
+    This can be used to trim the last few context windows which have size less than
+    ``min_window_size``. By default context windows of size 1 are skipped.
+
+    >>> contextualize(data).window(6).stride(3).text_col('token').groupby('document_id').to_df()
+                                 token  document_id
+    0  The quick brown fox jumped over            1
+    3     fox jumped over the lazy dog            1
+    6                     the lazy dog            1
+    9                I love sandwiches            2
+
+    >>> contextualize(data).window(6).stride(3).min_window_size(4).text_col('token').groupby('document_id').to_df()
+                                 token  document_id
+    0  The quick brown fox jumped over            1
+    3     fox jumped over the lazy dog            1
+
     """
     return Contextualizer(raw_df)
 
@@ -92,6 +115,7 @@ class Contextualizer:
         self._groupby = None
         self._stride = None
         self._window = None
+        self._min_window_size = 2
         self._raw_df = raw_df
 
     def window(self, window: int) -> Contextualizer:
@@ -139,6 +163,17 @@ class Contextualizer:
         self._text_col = text_col
         return self
 
+    def min_window_size(self, min_window_size: int) -> Contextualizer:
+        """Set the (optional) min_window_size size for the context window.
+
+        Parameters
+        ----------
+        min_window_size: int
+            The min_window_size.
+        """
+        self._min_window_size = min_window_size
+        return self
+
     def to_df(self) -> pd.DataFrame:
         """Create the context windows and return a DataFrame."""
 
@@ -159,12 +194,19 @@ class Contextualizer:
 
         def process_group(grp):
             # For each group, create the text rolling window
+            # with values of size >= min_window_size
             text = grp[self._text_col].values
-            contexts = grp.iloc[: -self._window : self._stride, :].copy()
+            contexts = grp.iloc[:: self._stride, :].copy()
-            contexts[self._text_col] = [
+            windows = [
-                " ".join(text[start_i : start_i + self._window])
+                " ".join(text[start_i : min(start_i + self._window, len(grp))])
-                for start_i in range(0, len(grp) - self._window, self._stride)
+                for start_i in range(0, len(grp), self._stride)
+                if start_i + self._window <= len(grp)
+                or len(grp) - start_i >= self._min_window_size
             ]
+            # if last few rows dropped
+            if len(windows) < len(contexts):
+                contexts = contexts.iloc[: len(windows)]
+            contexts[self._text_col] = windows
             return contexts
 
         if self._groupby is None:

python/tests/test_context.py

@@ -0,0 +1,77 @@
+#  Copyright 2023 LanceDB Developers
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+
+import pandas as pd
+import pytest
+
+from lancedb.context import contextualize
+
+
+@pytest.fixture
+def raw_df() -> pd.DataFrame:
+    return pd.DataFrame(
+        {
+            "token": [
+                "The",
+                "quick",
+                "brown",
+                "fox",
+                "jumped",
+                "over",
+                "the",
+                "lazy",
+                "dog",
+                "I",
+                "love",
+                "sandwiches",
+            ],
+            "document_id": [1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2],
+        }
+    )
+
+
+def test_contextualizer(raw_df: pd.DataFrame):
+    result = (
+        contextualize(raw_df)
+        .window(6)
+        .stride(3)
+        .text_col("token")
+        .groupby("document_id")
+        .to_df()["token"]
+        .to_list()
+    )
+
+    assert result == [
+        "The quick brown fox jumped over",
+        "fox jumped over the lazy dog",
+        "the lazy dog",
+        "I love sandwiches",
+    ]
+
+
+def test_contextualizer_with_threshold(raw_df: pd.DataFrame):
+    result = (
+        contextualize(raw_df)
+        .window(6)
+        .stride(3)
+        .text_col("token")
+        .groupby("document_id")
+        .min_window_size(4)
+        .to_df()["token"]
+        .to_list()
+    )
+
+    assert result == [
+        "The quick brown fox jumped over",
+        "fox jumped over the lazy dog",
+    ]

rust/ffi/node/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "vectordb-node"
-version = "0.1.0"
+version = "0.1.6"
 description = "Serverless, low-latency vector database for AI applications"
 license = "Apache-2.0"
 edition = "2018"

rust/ffi/node/src/index/vector.rs

@@ -97,6 +97,7 @@ fn get_index_params_builder(
                 let ivf_params = IvfBuildParams {
                     num_partitions: np,
                     max_iters,
+                    centroids: None,
                 };
                 index_builder.ivf_params(ivf_params)
             });

rust/vectordb/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "vectordb"
-version = "0.0.1"
+version = "0.1.6"
 edition = "2021"
 description = "Serverless, low-latency vector database for AI applications"
 license = "Apache-2.0"
@@ -14,7 +14,7 @@ arrow-data = "37.0"
 arrow-schema = "37.0"
 object_store = "0.5.6"
 snafu = "0.7.4"
-lance = "0.4.17"
+lance = "0.4.21"
 tokio = { version = "1.23", features = ["rt-multi-thread"] }
 
 [dev-dependencies]

rust/vectordb/src/database.rs

@@ -42,7 +42,7 @@ impl Database {
     ///
     /// * A [Database] object.
     pub async fn connect(uri: &str) -> Result<Database> {
-        let object_store = ObjectStore::new(uri).await?;
+        let (object_store, _) = ObjectStore::from_uri(uri).await?;
         if object_store.is_local() {
             Self::try_create_dir(uri).context(CreateDirSnafu { path: uri })?;
         }
@@ -69,7 +69,7 @@ impl Database {
     pub async fn table_names(&self) -> Result<Vec<String>> {
         let f = self
             .object_store
-            .read_dir("/")
+            .read_dir(self.uri.as_str())
             .await?
             .iter()
             .map(|fname| Path::new(fname))

rust/vectordb/src/index/vector.rs

@@ -20,6 +20,8 @@ pub trait VectorIndexBuilder {
     fn get_column(&self) -> Option<String>;
     fn get_index_name(&self) -> Option<String>;
     fn build(&self) -> VectorIndexParams;
+
+    fn get_replace(&self) -> bool;
 }
 
 pub struct IvfPQIndexBuilder {
@@ -28,6 +30,7 @@ pub struct IvfPQIndexBuilder {
     metric_type: Option<MetricType>,
     ivf_params: Option<IvfBuildParams>,
     pq_params: Option<PQBuildParams>,
+    replace: bool,
 }
 
 impl IvfPQIndexBuilder {
@@ -38,6 +41,7 @@ impl IvfPQIndexBuilder {
             metric_type: None,
             ivf_params: None,
             pq_params: None,
+            replace: true,
         }
     }
 }
@@ -67,6 +71,11 @@ impl IvfPQIndexBuilder {
         self.pq_params = Some(pq_params);
         self
     }
+
+    pub fn replace(&mut self, replace: bool) -> &mut IvfPQIndexBuilder {
+        self.replace = replace;
+        self
+    }
 }
 
 impl VectorIndexBuilder for IvfPQIndexBuilder {
@@ -84,6 +93,10 @@ impl VectorIndexBuilder for IvfPQIndexBuilder {
 
         VectorIndexParams::with_ivf_pq_params(pq_params.metric_type, ivf_params, pq_params)
     }
+
+    fn get_replace(&self) -> bool {
+        self.replace
+    }
 }
 
 #[cfg(test)]

rust/vectordb/src/query.rs

@@ -177,7 +177,7 @@ mod tests {
     #[tokio::test]
     async fn test_setters_getters() {
         let mut batches: Box<dyn RecordBatchReader> = Box::new(make_test_batches());
-        let ds = Dataset::write(&mut batches, ":memory:", None)
+        let ds = Dataset::write(&mut batches, "memory://foo", None)
             .await
             .unwrap();
 
@@ -206,7 +206,7 @@ mod tests {
     #[tokio::test]
     async fn test_execute() {
         let mut batches: Box<dyn RecordBatchReader> = Box::new(make_test_batches());
-        let ds = Dataset::write(&mut batches, ":memory:", None)
+        let ds = Dataset::write(&mut batches, "memory://foo", None)
             .await
             .unwrap();
 

rust/vectordb/src/table.rs

@@ -130,6 +130,7 @@ impl Table {
                 IndexType::Vector,
                 index_builder.get_index_name(),
                 &index_builder.build(),
+                index_builder.get_replace(),
             )
             .await?;
         self.dataset = Arc::new(dataset);
@@ -233,7 +234,7 @@ mod tests {
         let uri = tmp_dir.path().to_str().unwrap();
 
         let batches: Box<dyn RecordBatchReader> = Box::new(make_test_batches());
-        let schema = batches.schema().clone();
+        let _ = batches.schema().clone();
         Table::create(&uri, "test", batches).await.unwrap();
 
         let batches: Box<dyn RecordBatchReader> = Box::new(make_test_batches());