From 0fd8a50bd78d7cfd5df6ed84f7fdcb2c67338747 Mon Sep 17 00:00:00 2001 From: Will Jones Date: Wed, 13 Nov 2024 11:10:56 -0800 Subject: [PATCH] ci(node): run examples in CI (#1796) This is done as setup for a PR that will fix the OpenAI dependency issue. * [x] FTS examples * [x] Setup mock openai * [x] Ran `npm audit fix` * [x] sentences embeddings test * [x] Double check formatting of docs examples --- .github/workflows/nodejs.yml | 16 + ci/mock_openai.py | 57 + docs/src/ann_indexes.md | 10 +- docs/src/basic.md | 24 +- .../embeddings/custom_embedding_function.md | 6 +- docs/src/embeddings/embedding_functions.md | 6 +- docs/src/embeddings/index.md | 14 +- docs/src/guides/tables.md | 12 +- docs/src/search.md | 6 +- docs/src/sql.md | 6 +- nodejs/biome.json | 3 +- nodejs/examples/ann_indexes.test.ts | 57 + nodejs/examples/ann_indexes.ts | 49 - nodejs/examples/basic.test.ts | 175 + nodejs/examples/basic.ts | 162 - .../custom_embedding_function.test.ts | 76 + nodejs/examples/custom_embedding_function.ts | 64 - nodejs/examples/embedding.test.ts | 96 + nodejs/examples/embedding.ts | 83 - nodejs/examples/filtering.test.ts | 42 + nodejs/examples/filtering.ts | 34 - nodejs/examples/full_text_search.test.ts | 45 + nodejs/examples/full_text_search.ts | 52 - nodejs/examples/jest.config.cjs | 6 + nodejs/examples/jsconfig.json | 27 - nodejs/examples/package-lock.json | 5009 +++++++++++++++-- nodejs/examples/package.json | 29 +- nodejs/examples/search.test.ts | 42 + nodejs/examples/search.ts | 38 - nodejs/examples/sentence-transformers.js | 50 - nodejs/examples/sentence-transformers.test.ts | 59 + nodejs/examples/tsconfig.json | 17 + nodejs/examples/util.ts | 16 + nodejs/jest.config.js | 1 + nodejs/lancedb/embedding/transformers.ts | 16 +- nodejs/lancedb/query.ts | 5 + nodejs/package-lock.json | 1432 +++-- nodejs/package.json | 2 +- nodejs/tsconfig.json | 2 +- 39 files changed, 6141 insertions(+), 1705 deletions(-) create mode 100644 ci/mock_openai.py create mode 100644 nodejs/examples/ann_indexes.test.ts delete mode 100644 nodejs/examples/ann_indexes.ts create mode 100644 nodejs/examples/basic.test.ts delete mode 100644 nodejs/examples/basic.ts create mode 100644 nodejs/examples/custom_embedding_function.test.ts delete mode 100644 nodejs/examples/custom_embedding_function.ts create mode 100644 nodejs/examples/embedding.test.ts delete mode 100644 nodejs/examples/embedding.ts create mode 100644 nodejs/examples/filtering.test.ts delete mode 100644 nodejs/examples/filtering.ts create mode 100644 nodejs/examples/full_text_search.test.ts delete mode 100644 nodejs/examples/full_text_search.ts create mode 100644 nodejs/examples/jest.config.cjs delete mode 100644 nodejs/examples/jsconfig.json create mode 100644 nodejs/examples/search.test.ts delete mode 100644 nodejs/examples/search.ts delete mode 100644 nodejs/examples/sentence-transformers.js create mode 100644 nodejs/examples/sentence-transformers.test.ts create mode 100644 nodejs/examples/tsconfig.json create mode 100644 nodejs/examples/util.ts diff --git a/.github/workflows/nodejs.yml b/.github/workflows/nodejs.yml index 80f654ad..cbbef821 100644 --- a/.github/workflows/nodejs.yml +++ b/.github/workflows/nodejs.yml @@ -53,6 +53,9 @@ jobs: cargo clippy --all --all-features -- -D warnings npm ci npm run lint-ci + - name: Lint examples + working-directory: nodejs/examples + run: npm ci && npm run lint-ci linux: name: Linux (NodeJS ${{ matrix.node-version }}) timeout-minutes: 30 @@ -91,6 +94,19 @@ jobs: env: S3_TEST: "1" run: npm run test + - name: Setup examples + working-directory: nodejs/examples + run: npm ci + - name: Test examples + working-directory: ./ + env: + OPENAI_API_KEY: test + OPENAI_BASE_URL: http://0.0.0.0:8000 + run: | + python ci/mock_openai.py & + ss -ltnp | grep :8000 + cd nodejs/examples + npm test macos: timeout-minutes: 30 runs-on: "macos-14" diff --git a/ci/mock_openai.py b/ci/mock_openai.py new file mode 100644 index 00000000..da3cb6c4 --- /dev/null +++ b/ci/mock_openai.py @@ -0,0 +1,57 @@ +# SPDX-License-Identifier: Apache-2.0 +# SPDX-FileCopyrightText: Copyright The LanceDB Authors +"""A zero-dependency mock OpenAI embeddings API endpoint for testing purposes.""" +import argparse +import json +import http.server + + +class MockOpenAIRequestHandler(http.server.BaseHTTPRequestHandler): + def do_POST(self): + content_length = int(self.headers["Content-Length"]) + post_data = self.rfile.read(content_length) + post_data = json.loads(post_data.decode("utf-8")) + # See: https://platform.openai.com/docs/api-reference/embeddings/create + + if isinstance(post_data["input"], str): + num_inputs = 1 + else: + num_inputs = len(post_data["input"]) + + model = post_data.get("model", "text-embedding-ada-002") + + data = [] + for i in range(num_inputs): + data.append({ + "object": "embedding", + "embedding": [0.1] * 1536, + "index": i, + }) + + response = { + "object": "list", + "data": data, + "model": model, + "usage": { + "prompt_tokens": 0, + "total_tokens": 0, + } + } + + self.send_response(200) + self.send_header("Content-type", "application/json") + self.end_headers() + self.wfile.write(json.dumps(response).encode("utf-8")) + + +if __name__ == "__main__": + parser = argparse.ArgumentParser(description="Mock OpenAI embeddings API endpoint") + parser.add_argument("--port", type=int, default=8000, help="Port to listen on") + args = parser.parse_args() + port = args.port + + print(f"server started on port {port}. Press Ctrl-C to stop.") + print(f"To use, set OPENAI_BASE_URL=http://localhost:{port} in your environment.") + + with http.server.HTTPServer(("0.0.0.0", port), MockOpenAIRequestHandler) as server: + server.serve_forever() diff --git a/docs/src/ann_indexes.md b/docs/src/ann_indexes.md index 95ae6e90..5b3bac30 100644 --- a/docs/src/ann_indexes.md +++ b/docs/src/ann_indexes.md @@ -45,9 +45,9 @@ Lance supports `IVF_PQ` index type by default. Creating indexes is done via the [lancedb.Table.createIndex](../js/classes/Table.md/#createIndex) method. ```typescript - --8<--- "nodejs/examples/ann_indexes.ts:import" + --8<--- "nodejs/examples/ann_indexes.test.ts:import" - --8<-- "nodejs/examples/ann_indexes.ts:ingest" + --8<-- "nodejs/examples/ann_indexes.test.ts:ingest" ``` === "vectordb (deprecated)" @@ -171,7 +171,7 @@ There are a couple of parameters that can be used to fine-tune the search: === "@lancedb/lancedb" ```typescript - --8<-- "nodejs/examples/ann_indexes.ts:search1" + --8<-- "nodejs/examples/ann_indexes.test.ts:search1" ``` === "vectordb (deprecated)" @@ -205,7 +205,7 @@ You can further filter the elements returned by a search using a where clause. === "@lancedb/lancedb" ```typescript - --8<-- "nodejs/examples/ann_indexes.ts:search2" + --8<-- "nodejs/examples/ann_indexes.test.ts:search2" ``` === "vectordb (deprecated)" @@ -237,7 +237,7 @@ You can select the columns returned by the query using a select clause. === "@lancedb/lancedb" ```typescript - --8<-- "nodejs/examples/ann_indexes.ts:search3" + --8<-- "nodejs/examples/ann_indexes.test.ts:search3" ``` === "vectordb (deprecated)" diff --git a/docs/src/basic.md b/docs/src/basic.md index 23084871..8e4a7402 100644 --- a/docs/src/basic.md +++ b/docs/src/basic.md @@ -157,7 +157,7 @@ recommend switching to stable releases. import * as lancedb from "@lancedb/lancedb"; import * as arrow from "apache-arrow"; - --8<-- "nodejs/examples/basic.ts:connect" + --8<-- "nodejs/examples/basic.test.ts:connect" ``` === "vectordb (deprecated)" @@ -212,7 +212,7 @@ table. === "@lancedb/lancedb" ```typescript - --8<-- "nodejs/examples/basic.ts:create_table" + --8<-- "nodejs/examples/basic.test.ts:create_table" ``` === "vectordb (deprecated)" @@ -268,7 +268,7 @@ similar to a `CREATE TABLE` statement in SQL. === "@lancedb/lancedb" ```typescript - --8<-- "nodejs/examples/basic.ts:create_empty_table" + --8<-- "nodejs/examples/basic.test.ts:create_empty_table" ``` === "vectordb (deprecated)" @@ -298,7 +298,7 @@ Once created, you can open a table as follows: === "@lancedb/lancedb" ```typescript - --8<-- "nodejs/examples/basic.ts:open_table" + --8<-- "nodejs/examples/basic.test.ts:open_table" ``` === "vectordb (deprecated)" @@ -327,7 +327,7 @@ If you forget the name of your table, you can always get a listing of all table === "@lancedb/lancedb" ```typescript - --8<-- "nodejs/examples/basic.ts:table_names" + --8<-- "nodejs/examples/basic.test.ts:table_names" ``` === "vectordb (deprecated)" @@ -357,7 +357,7 @@ After a table has been created, you can always add more data to it as follows: === "@lancedb/lancedb" ```typescript - --8<-- "nodejs/examples/basic.ts:add_data" + --8<-- "nodejs/examples/basic.test.ts:add_data" ``` === "vectordb (deprecated)" @@ -389,7 +389,7 @@ Once you've embedded the query, you can find its nearest neighbors as follows: === "@lancedb/lancedb" ```typescript - --8<-- "nodejs/examples/basic.ts:vector_search" + --8<-- "nodejs/examples/basic.test.ts:vector_search" ``` === "vectordb (deprecated)" @@ -429,7 +429,7 @@ LanceDB allows you to create an ANN index on a table as follows: === "@lancedb/lancedb" ```typescript - --8<-- "nodejs/examples/basic.ts:create_index" + --8<-- "nodejs/examples/basic.test.ts:create_index" ``` === "vectordb (deprecated)" @@ -469,7 +469,7 @@ This can delete any number of rows that match the filter. === "@lancedb/lancedb" ```typescript - --8<-- "nodejs/examples/basic.ts:delete_rows" + --8<-- "nodejs/examples/basic.test.ts:delete_rows" ``` === "vectordb (deprecated)" @@ -527,7 +527,7 @@ Use the `drop_table()` method on the database to remove a table. === "@lancedb/lancedb" ```typescript - --8<-- "nodejs/examples/basic.ts:drop_table" + --8<-- "nodejs/examples/basic.test.ts:drop_table" ``` === "vectordb (deprecated)" @@ -561,8 +561,8 @@ You can use the embedding API when working with embedding models. It automatical === "@lancedb/lancedb" ```typescript - --8<-- "nodejs/examples/embedding.ts:imports" - --8<-- "nodejs/examples/embedding.ts:openai_embeddings" + --8<-- "nodejs/examples/embedding.test.ts:imports" + --8<-- "nodejs/examples/embedding.test.ts:openai_embeddings" ``` === "Rust" diff --git a/docs/src/embeddings/custom_embedding_function.md b/docs/src/embeddings/custom_embedding_function.md index 4dbd19a1..619c5437 100644 --- a/docs/src/embeddings/custom_embedding_function.md +++ b/docs/src/embeddings/custom_embedding_function.md @@ -47,9 +47,9 @@ Let's implement `SentenceTransformerEmbeddings` class. All you need to do is imp === "TypeScript" ```ts - --8<--- "nodejs/examples/custom_embedding_function.ts:imports" + --8<--- "nodejs/examples/custom_embedding_function.test.ts:imports" - --8<--- "nodejs/examples/custom_embedding_function.ts:embedding_impl" + --8<--- "nodejs/examples/custom_embedding_function.test.ts:embedding_impl" ``` @@ -78,7 +78,7 @@ Now you can use this embedding function to create your table schema and that's i === "TypeScript" ```ts - --8<--- "nodejs/examples/custom_embedding_function.ts:call_custom_function" + --8<--- "nodejs/examples/custom_embedding_function.test.ts:call_custom_function" ``` !!! note diff --git a/docs/src/embeddings/embedding_functions.md b/docs/src/embeddings/embedding_functions.md index 1cfa6157..de9d29e7 100644 --- a/docs/src/embeddings/embedding_functions.md +++ b/docs/src/embeddings/embedding_functions.md @@ -94,8 +94,8 @@ the embeddings at all: === "@lancedb/lancedb" ```ts - --8<-- "nodejs/examples/embedding.ts:imports" - --8<-- "nodejs/examples/embedding.ts:embedding_function" + --8<-- "nodejs/examples/embedding.test.ts:imports" + --8<-- "nodejs/examples/embedding.test.ts:embedding_function" ``` === "vectordb (deprecated)" @@ -150,7 +150,7 @@ need to worry about it when you query the table: .toArray() ``` - === "vectordb (deprecated) + === "vectordb (deprecated)" ```ts const results = await table diff --git a/docs/src/embeddings/index.md b/docs/src/embeddings/index.md index 6420aa8f..28185491 100644 --- a/docs/src/embeddings/index.md +++ b/docs/src/embeddings/index.md @@ -51,8 +51,8 @@ LanceDB registers the OpenAI embeddings function in the registry as `openai`. Yo === "TypeScript" ```typescript - --8<--- "nodejs/examples/embedding.ts:imports" - --8<--- "nodejs/examples/embedding.ts:openai_embeddings" + --8<--- "nodejs/examples/embedding.test.ts:imports" + --8<--- "nodejs/examples/embedding.test.ts:openai_embeddings" ``` === "Rust" @@ -121,12 +121,10 @@ class Words(LanceModel): vector: Vector(func.ndims()) = func.VectorField() table = db.create_table("words", schema=Words) -table.add( - [ - {"text": "hello world"}, - {"text": "goodbye world"} - ] - ) +table.add([ + {"text": "hello world"}, + {"text": "goodbye world"} +]) query = "greetings" actual = table.search(query).limit(1).to_pydantic(Words)[0] diff --git a/docs/src/guides/tables.md b/docs/src/guides/tables.md index 9de2ba94..97b12b83 100644 --- a/docs/src/guides/tables.md +++ b/docs/src/guides/tables.md @@ -85,13 +85,13 @@ Initialize a LanceDB connection and create a table ```ts - --8<-- "nodejs/examples/basic.ts:create_table" + --8<-- "nodejs/examples/basic.test.ts:create_table" ``` This will infer the schema from the provided data. If you want to explicitly provide a schema, you can use `apache-arrow` to declare a schema ```ts - --8<-- "nodejs/examples/basic.ts:create_table_with_schema" + --8<-- "nodejs/examples/basic.test.ts:create_table_with_schema" ``` !!! info "Note" @@ -100,14 +100,14 @@ Initialize a LanceDB connection and create a table passed in will NOT be appended to the table in that case. ```ts - --8<-- "nodejs/examples/basic.ts:create_table_exists_ok" + --8<-- "nodejs/examples/basic.test.ts:create_table_exists_ok" ``` Sometimes you want to make sure that you start fresh. If you want to overwrite the table, you can pass in mode: "overwrite" to the createTable function. ```ts - --8<-- "nodejs/examples/basic.ts:create_table_overwrite" + --8<-- "nodejs/examples/basic.test.ts:create_table_overwrite" ``` === "vectordb (deprecated)" @@ -227,7 +227,7 @@ LanceDB supports float16 data type! === "@lancedb/lancedb" ```typescript - --8<-- "nodejs/examples/basic.ts:create_f16_table" + --8<-- "nodejs/examples/basic.test.ts:create_f16_table" ``` === "vectordb (deprecated)" @@ -455,7 +455,7 @@ You can create an empty table for scenarios where you want to add data to the ta === "@lancedb/lancedb" ```typescript - --8<-- "nodejs/examples/basic.ts:create_empty_table" + --8<-- "nodejs/examples/basic.test.ts:create_empty_table" ``` === "vectordb (deprecated)" diff --git a/docs/src/search.md b/docs/src/search.md index 62f46a63..f207a942 100644 --- a/docs/src/search.md +++ b/docs/src/search.md @@ -58,9 +58,9 @@ db.create_table("my_vectors", data=data) === "@lancedb/lancedb" ```ts - --8<-- "nodejs/examples/search.ts:import" + --8<-- "nodejs/examples/search.test.ts:import" - --8<-- "nodejs/examples/search.ts:search1" + --8<-- "nodejs/examples/search.test.ts:search1" ``` @@ -89,7 +89,7 @@ By default, `l2` will be used as metric type. You can specify the metric type as === "@lancedb/lancedb" ```ts - --8<-- "nodejs/examples/search.ts:search2" + --8<-- "nodejs/examples/search.test.ts:search2" ``` === "vectordb (deprecated)" diff --git a/docs/src/sql.md b/docs/src/sql.md index b1d10d97..118553c2 100644 --- a/docs/src/sql.md +++ b/docs/src/sql.md @@ -49,7 +49,7 @@ const tbl = await db.createTable('myVectors', data) === "@lancedb/lancedb" ```ts - --8<-- "nodejs/examples/filtering.ts:search" + --8<-- "nodejs/examples/filtering.test.ts:search" ``` === "vectordb (deprecated)" @@ -91,7 +91,7 @@ For example, the following filter string is acceptable: === "@lancedb/lancedb" ```ts - --8<-- "nodejs/examples/filtering.ts:vec_search" + --8<-- "nodejs/examples/filtering.test.ts:vec_search" ``` === "vectordb (deprecated)" @@ -169,7 +169,7 @@ You can also filter your data without search. === "@lancedb/lancedb" ```ts - --8<-- "nodejs/examples/filtering.ts:sql_search" + --8<-- "nodejs/examples/filtering.test.ts:sql_search" ``` === "vectordb (deprecated)" diff --git a/nodejs/biome.json b/nodejs/biome.json index 584976b9..29ca74fa 100644 --- a/nodejs/biome.json +++ b/nodejs/biome.json @@ -9,7 +9,8 @@ "**/native.js", "**/native.d.ts", "**/npm/**/*", - "**/.vscode/**" + "**/.vscode/**", + "./examples/*" ] }, "formatter": { diff --git a/nodejs/examples/ann_indexes.test.ts b/nodejs/examples/ann_indexes.test.ts new file mode 100644 index 00000000..cfed5f38 --- /dev/null +++ b/nodejs/examples/ann_indexes.test.ts @@ -0,0 +1,57 @@ +// SPDX-License-Identifier: Apache-2.0 +// SPDX-FileCopyrightText: Copyright The LanceDB Authors +import { expect, test } from "@jest/globals"; +// --8<-- [start:import] +import * as lancedb from "@lancedb/lancedb"; +import { VectorQuery } from "@lancedb/lancedb"; +// --8<-- [end:import] +import { withTempDirectory } from "./util.ts"; + +test("ann index examples", async () => { + await withTempDirectory(async (databaseDir) => { + // --8<-- [start:ingest] + const db = await lancedb.connect(databaseDir); + + const data = Array.from({ length: 5_000 }, (_, i) => ({ + vector: Array(128).fill(i), + id: `${i}`, + content: "", + longId: `${i}`, + })); + + const table = await db.createTable("my_vectors", data, { + mode: "overwrite", + }); + await table.createIndex("vector", { + config: lancedb.Index.ivfPq({ + numPartitions: 10, + numSubVectors: 16, + }), + }); + // --8<-- [end:ingest] + + // --8<-- [start:search1] + const search = table.search(Array(128).fill(1.2)).limit(2) as VectorQuery; + const results1 = await search.nprobes(20).refineFactor(10).toArray(); + // --8<-- [end:search1] + expect(results1.length).toBe(2); + + // --8<-- [start:search2] + const results2 = await table + .search(Array(128).fill(1.2)) + .where("id != '1141'") + .limit(2) + .toArray(); + // --8<-- [end:search2] + expect(results2.length).toBe(2); + + // --8<-- [start:search3] + const results3 = await table + .search(Array(128).fill(1.2)) + .select(["id"]) + .limit(2) + .toArray(); + // --8<-- [end:search3] + expect(results3.length).toBe(2); + }); +}, 100_000); diff --git a/nodejs/examples/ann_indexes.ts b/nodejs/examples/ann_indexes.ts deleted file mode 100644 index 0c14da4a..00000000 --- a/nodejs/examples/ann_indexes.ts +++ /dev/null @@ -1,49 +0,0 @@ -// --8<-- [start:import] -import * as lancedb from "@lancedb/lancedb"; -// --8<-- [end:import] - -// --8<-- [start:ingest] -const db = await lancedb.connect("/tmp/lancedb/"); - -const data = Array.from({ length: 10_000 }, (_, i) => ({ - vector: Array(1536).fill(i), - id: `${i}`, - content: "", - longId: `${i}`, -})); - -const table = await db.createTable("my_vectors", data, { mode: "overwrite" }); -await table.createIndex("vector", { - config: lancedb.Index.ivfPq({ - numPartitions: 16, - numSubVectors: 48, - }), -}); -// --8<-- [end:ingest] - -// --8<-- [start:search1] -const _results1 = await table - .search(Array(1536).fill(1.2)) - .limit(2) - .nprobes(20) - .refineFactor(10) - .toArray(); -// --8<-- [end:search1] - -// --8<-- [start:search2] -const _results2 = await table - .search(Array(1536).fill(1.2)) - .where("id != '1141'") - .limit(2) - .toArray(); -// --8<-- [end:search2] - -// --8<-- [start:search3] -const _results3 = await table - .search(Array(1536).fill(1.2)) - .select(["id"]) - .limit(2) - .toArray(); -// --8<-- [end:search3] - -console.log("Ann indexes: done"); diff --git a/nodejs/examples/basic.test.ts b/nodejs/examples/basic.test.ts new file mode 100644 index 00000000..829b446e --- /dev/null +++ b/nodejs/examples/basic.test.ts @@ -0,0 +1,175 @@ +// SPDX-License-Identifier: Apache-2.0 +// SPDX-FileCopyrightText: Copyright The LanceDB Authors +import { expect, test } from "@jest/globals"; +// --8<-- [start:imports] +import * as lancedb from "@lancedb/lancedb"; +import * as arrow from "apache-arrow"; +import { + Field, + FixedSizeList, + Float16, + Int32, + Schema, + Utf8, +} from "apache-arrow"; +// --8<-- [end:imports] +import { withTempDirectory } from "./util.ts"; + +test("basic table examples", async () => { + await withTempDirectory(async (databaseDir) => { + // --8<-- [start:connect] + const db = await lancedb.connect(databaseDir); + // --8<-- [end:connect] + { + // --8<-- [start:create_table] + const _tbl = await db.createTable( + "myTable", + [ + { vector: [3.1, 4.1], item: "foo", price: 10.0 }, + { vector: [5.9, 26.5], item: "bar", price: 20.0 }, + ], + { mode: "overwrite" }, + ); + // --8<-- [end:create_table] + + const data = [ + { vector: [3.1, 4.1], item: "foo", price: 10.0 }, + { vector: [5.9, 26.5], item: "bar", price: 20.0 }, + ]; + + { + // --8<-- [start:create_table_exists_ok] + const tbl = await db.createTable("myTable", data, { + existOk: true, + }); + // --8<-- [end:create_table_exists_ok] + expect(await tbl.countRows()).toBe(2); + } + { + // --8<-- [start:create_table_overwrite] + const tbl = await db.createTable("myTable", data, { + mode: "overwrite", + }); + // --8<-- [end:create_table_overwrite] + expect(await tbl.countRows()).toBe(2); + } + } + + await db.dropTable("myTable"); + + { + // --8<-- [start:create_table_with_schema] + const schema = new arrow.Schema([ + new arrow.Field( + "vector", + new arrow.FixedSizeList( + 2, + new arrow.Field("item", new arrow.Float32(), true), + ), + ), + new arrow.Field("item", new arrow.Utf8(), true), + new arrow.Field("price", new arrow.Float32(), true), + ]); + const data = [ + { vector: [3.1, 4.1], item: "foo", price: 10.0 }, + { vector: [5.9, 26.5], item: "bar", price: 20.0 }, + ]; + const tbl = await db.createTable("myTable", data, { + schema, + }); + // --8<-- [end:create_table_with_schema] + expect(await tbl.countRows()).toBe(2); + } + + { + // --8<-- [start:create_empty_table] + + const schema = new arrow.Schema([ + new arrow.Field("id", new arrow.Int32()), + new arrow.Field("name", new arrow.Utf8()), + ]); + + const emptyTbl = await db.createEmptyTable("empty_table", schema); + // --8<-- [end:create_empty_table] + expect(await emptyTbl.countRows()).toBe(0); + } + { + // --8<-- [start:open_table] + const _tbl = await db.openTable("myTable"); + // --8<-- [end:open_table] + } + + { + // --8<-- [start:table_names] + const tableNames = await db.tableNames(); + // --8<-- [end:table_names] + expect(tableNames).toEqual(["empty_table", "myTable"]); + } + + const tbl = await db.openTable("myTable"); + { + // --8<-- [start:add_data] + const data = [ + { vector: [1.3, 1.4], item: "fizz", price: 100.0 }, + { vector: [9.5, 56.2], item: "buzz", price: 200.0 }, + ]; + await tbl.add(data); + // --8<-- [end:add_data] + } + { + // --8<-- [start:vector_search] + const res = await tbl.search([100, 100]).limit(2).toArray(); + // --8<-- [end:vector_search] + expect(res.length).toBe(2); + } + { + const data = Array.from({ length: 1000 }) + .fill(null) + .map(() => ({ + vector: [Math.random(), Math.random()], + item: "autogen", + price: Math.round(Math.random() * 100), + })); + + await tbl.add(data); + } + + // --8<-- [start:create_index] + await tbl.createIndex("vector"); + // --8<-- [end:create_index] + + // --8<-- [start:delete_rows] + await tbl.delete('item = "fizz"'); + // --8<-- [end:delete_rows] + + // --8<-- [start:drop_table] + await db.dropTable("myTable"); + // --8<-- [end:drop_table] + await db.dropTable("empty_table"); + + { + // --8<-- [start:create_f16_table] + const db = await lancedb.connect(databaseDir); + const dim = 16; + const total = 10; + const f16Schema = new Schema([ + new Field("id", new Int32()), + new Field( + "vector", + new FixedSizeList(dim, new Field("item", new Float16(), true)), + false, + ), + ]); + const data = lancedb.makeArrowTable( + Array.from(Array(total), (_, i) => ({ + id: i, + vector: Array.from(Array(dim), Math.random), + })), + { schema: f16Schema }, + ); + const _table = await db.createTable("f16_tbl", data); + // --8<-- [end:create_f16_table] + await db.dropTable("f16_tbl"); + } + }); +}); diff --git a/nodejs/examples/basic.ts b/nodejs/examples/basic.ts deleted file mode 100644 index 3d8cdfea..00000000 --- a/nodejs/examples/basic.ts +++ /dev/null @@ -1,162 +0,0 @@ -// --8<-- [start:imports] -import * as lancedb from "@lancedb/lancedb"; -import * as arrow from "apache-arrow"; -import { - Field, - FixedSizeList, - Float16, - Int32, - Schema, - Utf8, -} from "apache-arrow"; - -// --8<-- [end:imports] - -// --8<-- [start:connect] -const uri = "/tmp/lancedb/"; -const db = await lancedb.connect(uri); -// --8<-- [end:connect] -{ - // --8<-- [start:create_table] - const tbl = await db.createTable( - "myTable", - [ - { vector: [3.1, 4.1], item: "foo", price: 10.0 }, - { vector: [5.9, 26.5], item: "bar", price: 20.0 }, - ], - { mode: "overwrite" }, - ); - // --8<-- [end:create_table] - - const data = [ - { vector: [3.1, 4.1], item: "foo", price: 10.0 }, - { vector: [5.9, 26.5], item: "bar", price: 20.0 }, - ]; - - { - // --8<-- [start:create_table_exists_ok] - const tbl = await db.createTable("myTable", data, { - existsOk: true, - }); - // --8<-- [end:create_table_exists_ok] - } - { - // --8<-- [start:create_table_overwrite] - const _tbl = await db.createTable("myTable", data, { - mode: "overwrite", - }); - // --8<-- [end:create_table_overwrite] - } -} - -{ - // --8<-- [start:create_table_with_schema] - const schema = new arrow.Schema([ - new arrow.Field( - "vector", - new arrow.FixedSizeList( - 2, - new arrow.Field("item", new arrow.Float32(), true), - ), - ), - new arrow.Field("item", new arrow.Utf8(), true), - new arrow.Field("price", new arrow.Float32(), true), - ]); - const data = [ - { vector: [3.1, 4.1], item: "foo", price: 10.0 }, - { vector: [5.9, 26.5], item: "bar", price: 20.0 }, - ]; - const _tbl = await db.createTable("myTable", data, { - schema, - }); - // --8<-- [end:create_table_with_schema] -} - -{ - // --8<-- [start:create_empty_table] - - const schema = new arrow.Schema([ - new arrow.Field("id", new arrow.Int32()), - new arrow.Field("name", new arrow.Utf8()), - ]); - - const empty_tbl = await db.createEmptyTable("empty_table", schema); - // --8<-- [end:create_empty_table] -} -{ - // --8<-- [start:open_table] - const _tbl = await db.openTable("myTable"); - // --8<-- [end:open_table] -} - -{ - // --8<-- [start:table_names] - const tableNames = await db.tableNames(); - console.log(tableNames); - // --8<-- [end:table_names] -} - -const tbl = await db.openTable("myTable"); -{ - // --8<-- [start:add_data] - const data = [ - { vector: [1.3, 1.4], item: "fizz", price: 100.0 }, - { vector: [9.5, 56.2], item: "buzz", price: 200.0 }, - ]; - await tbl.add(data); - // --8<-- [end:add_data] -} -{ - // --8<-- [start:vector_search] - const _res = tbl.search([100, 100]).limit(2).toArray(); - // --8<-- [end:vector_search] -} -{ - const data = Array.from({ length: 1000 }) - .fill(null) - .map(() => ({ - vector: [Math.random(), Math.random()], - item: "autogen", - price: Math.round(Math.random() * 100), - })); - - await tbl.add(data); -} - -// --8<-- [start:create_index] -await tbl.createIndex("vector"); -// --8<-- [end:create_index] - -// --8<-- [start:delete_rows] -await tbl.delete('item = "fizz"'); -// --8<-- [end:delete_rows] - -// --8<-- [start:drop_table] -await db.dropTable("myTable"); -// --8<-- [end:drop_table] -await db.dropTable("empty_table"); - -{ - // --8<-- [start:create_f16_table] - const db = await lancedb.connect("/tmp/lancedb"); - const dim = 16; - const total = 10; - const f16Schema = new Schema([ - new Field("id", new Int32()), - new Field( - "vector", - new FixedSizeList(dim, new Field("item", new Float16(), true)), - false, - ), - ]); - const data = lancedb.makeArrowTable( - Array.from(Array(total), (_, i) => ({ - id: i, - vector: Array.from(Array(dim), Math.random), - })), - { schema: f16Schema }, - ); - const _table = await db.createTable("f16_tbl", data); - // --8<-- [end:create_f16_table] - await db.dropTable("f16_tbl"); -} diff --git a/nodejs/examples/custom_embedding_function.test.ts b/nodejs/examples/custom_embedding_function.test.ts new file mode 100644 index 00000000..5ec42c99 --- /dev/null +++ b/nodejs/examples/custom_embedding_function.test.ts @@ -0,0 +1,76 @@ +import { FeatureExtractionPipeline, pipeline } from "@huggingface/transformers"; +// SPDX-License-Identifier: Apache-2.0 +// SPDX-FileCopyrightText: Copyright The LanceDB Authors +import { expect, test } from "@jest/globals"; +// --8<-- [start:imports] +import * as lancedb from "@lancedb/lancedb"; +import { + LanceSchema, + TextEmbeddingFunction, + getRegistry, + register, +} from "@lancedb/lancedb/embedding"; +// --8<-- [end:imports] +import { withTempDirectory } from "./util.ts"; + +// --8<-- [start:embedding_impl] +@register("sentence-transformers") +class SentenceTransformersEmbeddings extends TextEmbeddingFunction { + name = "Xenova/all-miniLM-L6-v2"; + #ndims!: number; + extractor!: FeatureExtractionPipeline; + + async init() { + this.extractor = await pipeline("feature-extraction", this.name, { + dtype: "fp32", + }); + this.#ndims = await this.generateEmbeddings(["hello"]).then( + (e) => e[0].length, + ); + } + + ndims() { + return this.#ndims; + } + + toJSON() { + return { + name: this.name, + }; + } + async generateEmbeddings(texts: string[]) { + const output = await this.extractor(texts, { + pooling: "mean", + normalize: true, + }); + return output.tolist(); + } +} +// -8<-- [end:embedding_impl] + +test("Registry examples", async () => { + await withTempDirectory(async (databaseDir) => { + // --8<-- [start:call_custom_function] + const registry = getRegistry(); + + const sentenceTransformer = await registry + .get("sentence-transformers")! + .create(); + + const schema = LanceSchema({ + vector: sentenceTransformer.vectorField(), + text: sentenceTransformer.sourceField(), + }); + + const db = await lancedb.connect(databaseDir); + const table = await db.createEmptyTable("table", schema, { + mode: "overwrite", + }); + + await table.add([{ text: "hello" }, { text: "world" }]); + + const results = await table.search("greeting").limit(1).toArray(); + // -8<-- [end:call_custom_function] + expect(results.length).toBe(1); + }); +}, 100_000); diff --git a/nodejs/examples/custom_embedding_function.ts b/nodejs/examples/custom_embedding_function.ts deleted file mode 100644 index 5307cd6d..00000000 --- a/nodejs/examples/custom_embedding_function.ts +++ /dev/null @@ -1,64 +0,0 @@ -// --8<-- [start:imports] -import * as lancedb from "@lancedb/lancedb"; -import { - LanceSchema, - TextEmbeddingFunction, - getRegistry, - register, -} from "@lancedb/lancedb/embedding"; -import { pipeline } from "@xenova/transformers"; -// --8<-- [end:imports] - -// --8<-- [start:embedding_impl] -@register("sentence-transformers") -class SentenceTransformersEmbeddings extends TextEmbeddingFunction { - name = "Xenova/all-miniLM-L6-v2"; - #ndims!: number; - extractor: any; - - async init() { - this.extractor = await pipeline("feature-extraction", this.name); - this.#ndims = await this.generateEmbeddings(["hello"]).then( - (e) => e[0].length, - ); - } - - ndims() { - return this.#ndims; - } - - toJSON() { - return { - name: this.name, - }; - } - async generateEmbeddings(texts: string[]) { - const output = await this.extractor(texts, { - pooling: "mean", - normalize: true, - }); - return output.tolist(); - } -} -// -8<-- [end:embedding_impl] - -// --8<-- [start:call_custom_function] -const registry = getRegistry(); - -const sentenceTransformer = await registry - .get("sentence-transformers")! - .create(); - -const schema = LanceSchema({ - vector: sentenceTransformer.vectorField(), - text: sentenceTransformer.sourceField(), -}); - -const db = await lancedb.connect("/tmp/db"); -const table = await db.createEmptyTable("table", schema, { mode: "overwrite" }); - -await table.add([{ text: "hello" }, { text: "world" }]); - -const results = await table.search("greeting").limit(1).toArray(); -console.log(results[0].text); -// -8<-- [end:call_custom_function] diff --git a/nodejs/examples/embedding.test.ts b/nodejs/examples/embedding.test.ts new file mode 100644 index 00000000..2dc79c69 --- /dev/null +++ b/nodejs/examples/embedding.test.ts @@ -0,0 +1,96 @@ +// SPDX-License-Identifier: Apache-2.0 +// SPDX-FileCopyrightText: Copyright The LanceDB Authors +import { expect, test } from "@jest/globals"; +// --8<-- [start:imports] +import * as lancedb from "@lancedb/lancedb"; +import "@lancedb/lancedb/embedding/openai"; +import { LanceSchema, getRegistry, register } from "@lancedb/lancedb/embedding"; +import { EmbeddingFunction } from "@lancedb/lancedb/embedding"; +import { type Float, Float32, Utf8 } from "apache-arrow"; +// --8<-- [end:imports] +import { withTempDirectory } from "./util.ts"; + +const openAiTest = process.env.OPENAI_API_KEY == null ? test.skip : test; + +openAiTest("openai embeddings", async () => { + await withTempDirectory(async (databaseDir) => { + // --8<-- [start:openai_embeddings] + const db = await lancedb.connect(databaseDir); + const func = getRegistry() + .get("openai") + ?.create({ model: "text-embedding-ada-002" }) as EmbeddingFunction; + + const wordsSchema = LanceSchema({ + text: func.sourceField(new Utf8()), + vector: func.vectorField(), + }); + const tbl = await db.createEmptyTable("words", wordsSchema, { + mode: "overwrite", + }); + await tbl.add([{ text: "hello world" }, { text: "goodbye world" }]); + + const query = "greetings"; + const actual = (await tbl.search(query).limit(1).toArray())[0]; + // --8<-- [end:openai_embeddings] + expect(actual).toHaveProperty("text"); + }); +}); + +test("custom embedding function", async () => { + await withTempDirectory(async (databaseDir) => { + // --8<-- [start:embedding_function] + const db = await lancedb.connect(databaseDir); + + @register("my_embedding") + class MyEmbeddingFunction extends EmbeddingFunction { + toJSON(): object { + return {}; + } + ndims() { + return 3; + } + embeddingDataType(): Float { + return new Float32(); + } + async computeQueryEmbeddings(_data: string) { + // This is a placeholder for a real embedding function + return [1, 2, 3]; + } + async computeSourceEmbeddings(data: string[]) { + // This is a placeholder for a real embedding function + return Array.from({ length: data.length }).fill([ + 1, 2, 3, + ]) as number[][]; + } + } + + const func = new MyEmbeddingFunction(); + + const data = [{ text: "pepperoni" }, { text: "pineapple" }]; + + // Option 1: manually specify the embedding function + const table = await db.createTable("vectors", data, { + embeddingFunction: { + function: func, + sourceColumn: "text", + vectorColumn: "vector", + }, + mode: "overwrite", + }); + + // Option 2: provide the embedding function through a schema + + const schema = LanceSchema({ + text: func.sourceField(new Utf8()), + vector: func.vectorField(), + }); + + const table2 = await db.createTable("vectors2", data, { + schema, + mode: "overwrite", + }); + // --8<-- [end:embedding_function] + expect(await table.countRows()).toBe(2); + expect(await table2.countRows()).toBe(2); + }); +}); diff --git a/nodejs/examples/embedding.ts b/nodejs/examples/embedding.ts deleted file mode 100644 index dbf7a6e6..00000000 --- a/nodejs/examples/embedding.ts +++ /dev/null @@ -1,83 +0,0 @@ -// --8<-- [start:imports] -import * as lancedb from "@lancedb/lancedb"; -import { LanceSchema, getRegistry, register } from "@lancedb/lancedb/embedding"; -import { EmbeddingFunction } from "@lancedb/lancedb/embedding"; -import { type Float, Float32, Utf8 } from "apache-arrow"; -// --8<-- [end:imports] - -{ - // --8<-- [start:openai_embeddings] - - const db = await lancedb.connect("/tmp/db"); - const func = getRegistry() - .get("openai") - ?.create({ model: "text-embedding-ada-002" }) as EmbeddingFunction; - - const wordsSchema = LanceSchema({ - text: func.sourceField(new Utf8()), - vector: func.vectorField(), - }); - const tbl = await db.createEmptyTable("words", wordsSchema, { - mode: "overwrite", - }); - await tbl.add([{ text: "hello world" }, { text: "goodbye world" }]); - - const query = "greetings"; - const actual = (await (await tbl.search(query)).limit(1).toArray())[0]; - - // --8<-- [end:openai_embeddings] - console.log("result = ", actual.text); -} - -{ - // --8<-- [start:embedding_function] - const db = await lancedb.connect("/tmp/db"); - - @register("my_embedding") - class MyEmbeddingFunction extends EmbeddingFunction { - toJSON(): object { - return {}; - } - ndims() { - return 3; - } - embeddingDataType(): Float { - return new Float32(); - } - async computeQueryEmbeddings(_data: string) { - // This is a placeholder for a real embedding function - return [1, 2, 3]; - } - async computeSourceEmbeddings(data: string[]) { - // This is a placeholder for a real embedding function - return Array.from({ length: data.length }).fill([1, 2, 3]) as number[][]; - } - } - - const func = new MyEmbeddingFunction(); - - const data = [{ text: "pepperoni" }, { text: "pineapple" }]; - - // Option 1: manually specify the embedding function - const table = await db.createTable("vectors", data, { - embeddingFunction: { - function: func, - sourceColumn: "text", - vectorColumn: "vector", - }, - mode: "overwrite", - }); - - // Option 2: provide the embedding function through a schema - - const schema = LanceSchema({ - text: func.sourceField(new Utf8()), - vector: func.vectorField(), - }); - - const table2 = await db.createTable("vectors2", data, { - schema, - mode: "overwrite", - }); - // --8<-- [end:embedding_function] -} diff --git a/nodejs/examples/filtering.test.ts b/nodejs/examples/filtering.test.ts new file mode 100644 index 00000000..1c35d512 --- /dev/null +++ b/nodejs/examples/filtering.test.ts @@ -0,0 +1,42 @@ +// SPDX-License-Identifier: Apache-2.0 +// SPDX-FileCopyrightText: Copyright The LanceDB Authors +import { expect, test } from "@jest/globals"; +import * as lancedb from "@lancedb/lancedb"; +import { withTempDirectory } from "./util.ts"; + +test("filtering examples", async () => { + await withTempDirectory(async (databaseDir) => { + const db = await lancedb.connect(databaseDir); + + const data = Array.from({ length: 10_000 }, (_, i) => ({ + vector: Array(1536).fill(i), + id: i, + item: `item ${i}`, + strId: `${i}`, + })); + + const tbl = await db.createTable("myVectors", data, { mode: "overwrite" }); + + // --8<-- [start:search] + const _result = await tbl + .search(Array(1536).fill(0.5)) + .limit(1) + .where("id = 10") + .toArray(); + // --8<-- [end:search] + + // --8<-- [start:vec_search] + const result = await ( + tbl.search(Array(1536).fill(0)) as lancedb.VectorQuery + ) + .where("(item IN ('item 0', 'item 2')) AND (id > 10)") + .postfilter() + .toArray(); + // --8<-- [end:vec_search] + expect(result.length).toBe(0); + + // --8<-- [start:sql_search] + await tbl.query().where("id = 10").limit(10).toArray(); + // --8<-- [end:sql_search] + }); +}); diff --git a/nodejs/examples/filtering.ts b/nodejs/examples/filtering.ts deleted file mode 100644 index a999581b..00000000 --- a/nodejs/examples/filtering.ts +++ /dev/null @@ -1,34 +0,0 @@ -import * as lancedb from "@lancedb/lancedb"; - -const db = await lancedb.connect("data/sample-lancedb"); - -const data = Array.from({ length: 10_000 }, (_, i) => ({ - vector: Array(1536).fill(i), - id: i, - item: `item ${i}`, - strId: `${i}`, -})); - -const tbl = await db.createTable("myVectors", data, { mode: "overwrite" }); - -// --8<-- [start:search] -const _result = await tbl - .search(Array(1536).fill(0.5)) - .limit(1) - .where("id = 10") - .toArray(); -// --8<-- [end:search] - -// --8<-- [start:vec_search] -await tbl - .search(Array(1536).fill(0)) - .where("(item IN ('item 0', 'item 2')) AND (id > 10)") - .postfilter() - .toArray(); -// --8<-- [end:vec_search] - -// --8<-- [start:sql_search] -await tbl.query().where("id = 10").limit(10).toArray(); -// --8<-- [end:sql_search] - -console.log("SQL search: done"); diff --git a/nodejs/examples/full_text_search.test.ts b/nodejs/examples/full_text_search.test.ts new file mode 100644 index 00000000..44587f22 --- /dev/null +++ b/nodejs/examples/full_text_search.test.ts @@ -0,0 +1,45 @@ +// SPDX-License-Identifier: Apache-2.0 +// SPDX-FileCopyrightText: Copyright The LanceDB Authors +import { expect, test } from "@jest/globals"; +import * as lancedb from "@lancedb/lancedb"; +import { withTempDirectory } from "./util.ts"; + +test("full text search", async () => { + await withTempDirectory(async (databaseDir) => { + const db = await lancedb.connect(databaseDir); + + const words = [ + "apple", + "banana", + "cherry", + "date", + "elderberry", + "fig", + "grape", + ]; + + const data = Array.from({ length: 10_000 }, (_, i) => ({ + vector: Array(1536).fill(i), + id: i, + item: `item ${i}`, + strId: `${i}`, + doc: words[i % words.length], + })); + + const tbl = await db.createTable("myVectors", data, { mode: "overwrite" }); + + await tbl.createIndex("doc", { + config: lancedb.Index.fts(), + }); + + // --8<-- [start:full_text_search] + const result = await tbl + .query() + .nearestToText("apple") + .select(["id", "doc"]) + .limit(10) + .toArray(); + expect(result.length).toBe(10); + // --8<-- [end:full_text_search] + }); +}); diff --git a/nodejs/examples/full_text_search.ts b/nodejs/examples/full_text_search.ts deleted file mode 100644 index 0fcc10a7..00000000 --- a/nodejs/examples/full_text_search.ts +++ /dev/null @@ -1,52 +0,0 @@ -// Copyright 2024 Lance 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 * as lancedb from "@lancedb/lancedb"; - -const db = await lancedb.connect("data/sample-lancedb"); - -const words = [ - "apple", - "banana", - "cherry", - "date", - "elderberry", - "fig", - "grape", -]; - -const data = Array.from({ length: 10_000 }, (_, i) => ({ - vector: Array(1536).fill(i), - id: i, - item: `item ${i}`, - strId: `${i}`, - doc: words[i % words.length], -})); - -const tbl = await db.createTable("myVectors", data, { mode: "overwrite" }); - -await tbl.createIndex("doc", { - config: lancedb.Index.fts(), -}); - -// --8<-- [start:full_text_search] -let result = await tbl - .search("apple") - .select(["id", "doc"]) - .limit(10) - .toArray(); -console.log(result); -// --8<-- [end:full_text_search] - -console.log("SQL search: done"); diff --git a/nodejs/examples/jest.config.cjs b/nodejs/examples/jest.config.cjs new file mode 100644 index 00000000..db83d639 --- /dev/null +++ b/nodejs/examples/jest.config.cjs @@ -0,0 +1,6 @@ +/** @type {import('ts-jest').JestConfigWithTsJest} */ +module.exports = { + preset: "ts-jest", + testEnvironment: "node", + testPathIgnorePatterns: ["./dist"], +}; diff --git a/nodejs/examples/jsconfig.json b/nodejs/examples/jsconfig.json deleted file mode 100644 index 238655f2..00000000 --- a/nodejs/examples/jsconfig.json +++ /dev/null @@ -1,27 +0,0 @@ -{ - "compilerOptions": { - // Enable latest features - "lib": ["ESNext", "DOM"], - "target": "ESNext", - "module": "ESNext", - "moduleDetection": "force", - "jsx": "react-jsx", - "allowJs": true, - - // Bundler mode - "moduleResolution": "bundler", - "allowImportingTsExtensions": true, - "verbatimModuleSyntax": true, - "noEmit": true, - - // Best practices - "strict": true, - "skipLibCheck": true, - "noFallthroughCasesInSwitch": true, - - // Some stricter flags (disabled by default) - "noUnusedLocals": false, - "noUnusedParameters": false, - "noPropertyAccessFromIndexSignature": false - } -} diff --git a/nodejs/examples/package-lock.json b/nodejs/examples/package-lock.json index 3ff4d029..f12e5f50 100644 --- a/nodejs/examples/package-lock.json +++ b/nodejs/examples/package-lock.json @@ -9,20 +9,23 @@ "version": "1.0.0", "license": "Apache-2.0", "dependencies": { - "@lancedb/lancedb": "file:../", - "@xenova/transformers": "^2.17.2", - "tsc": "^2.0.4" + "@huggingface/transformers": "^3.0.2", + "@lancedb/lancedb": "file:../dist", + "openai": "^4.29.2", + "sharp": "^0.33.5" }, "devDependencies": { + "@biomejs/biome": "^1.7.3", + "@jest/globals": "^29.7.0", + "jest": "^29.7.0", + "jest-environment-node-single-context": "^29.4.0", + "ts-jest": "^29.2.5", "typescript": "^5.5.4" - }, - "peerDependencies": { - "typescript": "^5.0.0" } }, "..": { "name": "@lancedb/lancedb", - "version": "0.8.0", + "version": "0.12.0", "cpu": [ "x64", "arm64" @@ -34,7 +37,6 @@ "win32" ], "dependencies": { - "axios": "^1.7.2", "reflect-metadata": "^0.2.2" }, "devDependencies": { @@ -46,6 +48,7 @@ "@napi-rs/cli": "^2.18.3", "@types/axios": "^0.14.0", "@types/jest": "^29.1.2", + "@types/node": "^22.7.4", "@types/tmp": 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test specified\" && exit 1" + "//1": "--experimental-vm-modules is needed to run jest with sentence-transformers", + "//2": "--testEnvironment is needed to run jest with sentence-transformers", + "//3": "See: https://github.com/huggingface/transformers.js/issues/57", + "test": "node --experimental-vm-modules node_modules/.bin/jest --testEnvironment jest-environment-node-single-context --verbose", + "lint": "biome check *.ts && biome format *.ts", + "lint-ci": "biome ci .", + "lint-fix": "biome check --write *.ts && npm run format", + "format": "biome format --write *.ts" }, "author": "Lance Devs", "license": "Apache-2.0", "dependencies": { - "@lancedb/lancedb": "file:../", - "@xenova/transformers": "^2.17.2" + "@huggingface/transformers": "^3.0.2", + "@lancedb/lancedb": "file:../dist", + "openai": "^4.29.2", + "sharp": "^0.33.5" }, "devDependencies": { + "@biomejs/biome": "^1.7.3", + "@jest/globals": "^29.7.0", + "jest": "^29.7.0", + "jest-environment-node-single-context": "^29.4.0", + "ts-jest": "^29.2.5", "typescript": "^5.5.4" - }, - "compilerOptions": { - "target": "ESNext", - "module": "ESNext", - "moduleResolution": "Node", - "strict": true, - "esModuleInterop": true, - "skipLibCheck": true, - "forceConsistentCasingInFileNames": true } } diff --git a/nodejs/examples/search.test.ts b/nodejs/examples/search.test.ts new file mode 100644 index 00000000..ccca9b78 --- /dev/null +++ b/nodejs/examples/search.test.ts @@ -0,0 +1,42 @@ +// SPDX-License-Identifier: Apache-2.0 +// SPDX-FileCopyrightText: Copyright The LanceDB Authors +import { expect, test } from "@jest/globals"; +// --8<-- [start:import] +import * as lancedb from "@lancedb/lancedb"; +// --8<-- [end:import] +import { withTempDirectory } from "./util.ts"; + +test("full text search", async () => { + await withTempDirectory(async (databaseDir) => { + { + const db = await lancedb.connect(databaseDir); + + const data = Array.from({ length: 10_000 }, (_, i) => ({ + vector: Array(128).fill(i), + id: `${i}`, + content: "", + longId: `${i}`, + })); + + await db.createTable("my_vectors", data); + } + + // --8<-- [start:search1] + const db = await lancedb.connect(databaseDir); + const tbl = await db.openTable("my_vectors"); + + const results1 = await tbl.search(Array(128).fill(1.2)).limit(10).toArray(); + // --8<-- [end:search1] + expect(results1.length).toBe(10); + + // --8<-- [start:search2] + const results2 = await ( + tbl.search(Array(128).fill(1.2)) as lancedb.VectorQuery + ) + .distanceType("cosine") + .limit(10) + .toArray(); + // --8<-- [end:search2] + expect(results2.length).toBe(10); + }); +}); diff --git a/nodejs/examples/search.ts b/nodejs/examples/search.ts deleted file mode 100644 index 80d64795..00000000 --- a/nodejs/examples/search.ts +++ /dev/null @@ -1,38 +0,0 @@ -// --8<-- [end:import] -import * as fs from "node:fs"; -// --8<-- [start:import] -import * as lancedb from "@lancedb/lancedb"; - -async function setup() { - fs.rmSync("data/sample-lancedb", { recursive: true, force: true }); - const db = await lancedb.connect("data/sample-lancedb"); - - const data = Array.from({ length: 10_000 }, (_, i) => ({ - vector: Array(1536).fill(i), - id: `${i}`, - content: "", - longId: `${i}`, - })); - - await db.createTable("my_vectors", data); -} - -await setup(); - -// --8<-- [start:search1] -const db = await lancedb.connect("data/sample-lancedb"); -const tbl = await db.openTable("my_vectors"); - -const _results1 = await tbl.search(Array(1536).fill(1.2)).limit(10).toArray(); -// --8<-- [end:search1] - -// --8<-- [start:search2] -const _results2 = await tbl - .search(Array(1536).fill(1.2)) - .distanceType("cosine") - .limit(10) - .toArray(); -console.log(_results2); -// --8<-- [end:search2] - -console.log("search: done"); diff --git a/nodejs/examples/sentence-transformers.js b/nodejs/examples/sentence-transformers.js deleted file mode 100644 index 245c4f3f..00000000 --- a/nodejs/examples/sentence-transformers.js +++ /dev/null @@ -1,50 +0,0 @@ -import * as lancedb from "@lancedb/lancedb"; - -import { LanceSchema, getRegistry } from "@lancedb/lancedb/embedding"; -import { Utf8 } from "apache-arrow"; - -const db = await lancedb.connect("/tmp/db"); -const func = await getRegistry().get("huggingface").create(); - -const facts = [ - "Albert Einstein was a theoretical physicist.", - "The capital of France is Paris.", - "The Great Wall of China is one of the Seven Wonders of the World.", - "Python is a popular programming language.", - "Mount Everest is the highest mountain in the world.", - "Leonardo da Vinci painted the Mona Lisa.", - "Shakespeare wrote Hamlet.", - "The human body has 206 bones.", - "The speed of light is approximately 299,792 kilometers per second.", - "Water boils at 100 degrees Celsius.", - "The Earth orbits the Sun.", - "The Pyramids of Giza are located in Egypt.", - "Coffee is one of the most popular beverages in the world.", - "Tokyo is the capital city of Japan.", - "Photosynthesis is the process by which plants make their food.", - "The Pacific Ocean is the largest ocean on Earth.", - "Mozart was a prolific composer of classical music.", - "The Internet is a global network of computers.", - "Basketball is a sport played with a ball and a hoop.", - "The first computer virus was created in 1983.", - "Artificial neural networks are inspired by the human brain.", - "Deep learning is a subset of machine learning.", - "IBM's Watson won Jeopardy! in 2011.", - "The first computer programmer was Ada Lovelace.", - "The first chatbot was ELIZA, created in the 1960s.", -].map((text) => ({ text })); - -const factsSchema = LanceSchema({ - text: func.sourceField(new Utf8()), - vector: func.vectorField(), -}); - -const tbl = await db.createTable("facts", facts, { - mode: "overwrite", - schema: factsSchema, -}); - -const query = "How many bones are in the human body?"; -const actual = await tbl.search(query).limit(1).toArray(); - -console.log("Answer: ", actual[0]["text"]); diff --git a/nodejs/examples/sentence-transformers.test.ts b/nodejs/examples/sentence-transformers.test.ts new file mode 100644 index 00000000..561419a3 --- /dev/null +++ b/nodejs/examples/sentence-transformers.test.ts @@ -0,0 +1,59 @@ +// SPDX-License-Identifier: Apache-2.0 +// SPDX-FileCopyrightText: Copyright The LanceDB Authors +import { expect, test } from "@jest/globals"; +import { withTempDirectory } from "./util.ts"; + +import * as lancedb from "@lancedb/lancedb"; +import "@lancedb/lancedb/embedding/transformers"; +import { LanceSchema, getRegistry } from "@lancedb/lancedb/embedding"; +import { Utf8 } from "apache-arrow"; + +test("full text search", async () => { + await withTempDirectory(async (databaseDir) => { + const db = await lancedb.connect(databaseDir); + const func = await getRegistry().get("huggingface").create(); + + const facts = [ + "Albert Einstein was a theoretical physicist.", + "The capital of France is Paris.", + "The Great Wall of China is one of the Seven Wonders of the World.", + "Python is a popular programming language.", + "Mount Everest is the highest mountain in the world.", + "Leonardo da Vinci painted the Mona Lisa.", + "Shakespeare wrote Hamlet.", + "The human body has 206 bones.", + "The speed of light is approximately 299,792 kilometers per second.", + "Water boils at 100 degrees Celsius.", + "The Earth orbits the Sun.", + "The Pyramids of Giza are located in Egypt.", + "Coffee is one of the most popular beverages in the world.", + "Tokyo is the capital city of Japan.", + "Photosynthesis is the process by which plants make their food.", + "The Pacific Ocean is the largest ocean on Earth.", + "Mozart was a prolific composer of classical music.", + "The Internet is a global network of computers.", + "Basketball is a sport played with a ball and a hoop.", + "The first computer virus was created in 1983.", + "Artificial neural networks are inspired by the human brain.", + "Deep learning is a subset of machine learning.", + "IBM's Watson won Jeopardy! in 2011.", + "The first computer programmer was Ada Lovelace.", + "The first chatbot was ELIZA, created in the 1960s.", + ].map((text) => ({ text })); + + const factsSchema = LanceSchema({ + text: func.sourceField(new Utf8()), + vector: func.vectorField(), + }); + + const tbl = await db.createTable("facts", facts, { + mode: "overwrite", + schema: factsSchema, + }); + + const query = "How many bones are in the human body?"; + const actual = await tbl.search(query).limit(1).toArray(); + + expect(actual[0]["text"]).toBe("The human body has 206 bones."); + }); +}); diff --git a/nodejs/examples/tsconfig.json b/nodejs/examples/tsconfig.json new file mode 100644 index 00000000..49a04ac1 --- /dev/null +++ b/nodejs/examples/tsconfig.json @@ -0,0 +1,17 @@ +{ + "include": ["*.test.ts"], + "compilerOptions": { + "target": "es2022", + "module": "NodeNext", + "declaration": true, + "outDir": "./dist", + "strict": true, + "allowJs": true, + "resolveJsonModule": true, + "emitDecoratorMetadata": true, + "experimentalDecorators": true, + "moduleResolution": "NodeNext", + "allowImportingTsExtensions": true, + "emitDeclarationOnly": true + } +} diff --git a/nodejs/examples/util.ts b/nodejs/examples/util.ts new file mode 100644 index 00000000..4a65bfb8 --- /dev/null +++ b/nodejs/examples/util.ts @@ -0,0 +1,16 @@ +// SPDX-License-Identifier: Apache-2.0 +// SPDX-FileCopyrightText: Copyright The LanceDB Authors +import * as fs from "fs"; +import { tmpdir } from "os"; +import * as path from "path"; + +export async function withTempDirectory( + fn: (tempDir: string) => Promise, +) { + const tmpDirPath = fs.mkdtempSync(path.join(tmpdir(), "temp-dir-")); + try { + await fn(tmpDirPath); + } finally { + fs.rmSync(tmpDirPath, { recursive: true }); + } +} diff --git a/nodejs/jest.config.js b/nodejs/jest.config.js index c5b6a40a..dc99083a 100644 --- a/nodejs/jest.config.js +++ b/nodejs/jest.config.js @@ -4,4 +4,5 @@ module.exports = { testEnvironment: "node", moduleDirectories: ["node_modules", "./dist"], moduleFileExtensions: ["js", "ts"], + modulePathIgnorePatterns: ["/examples/"], }; diff --git a/nodejs/lancedb/embedding/transformers.ts b/nodejs/lancedb/embedding/transformers.ts index 2c692d38..4b9af1e1 100644 --- a/nodejs/lancedb/embedding/transformers.ts +++ b/nodejs/lancedb/embedding/transformers.ts @@ -47,8 +47,8 @@ export class TransformersEmbeddingFunction extends EmbeddingFunction< string, Partial > { - #model?: import("@xenova/transformers").PreTrainedModel; - #tokenizer?: import("@xenova/transformers").PreTrainedTokenizer; + #model?: import("@huggingface/transformers").PreTrainedModel; + #tokenizer?: import("@huggingface/transformers").PreTrainedTokenizer; #modelName: XenovaTransformerOptions["model"]; #initialized = false; #tokenizerOptions: XenovaTransformerOptions["tokenizerOptions"]; @@ -92,18 +92,19 @@ export class TransformersEmbeddingFunction extends EmbeddingFunction< try { // SAFETY: // since typescript transpiles `import` to `require`, we need to do this in an unsafe way - // We can't use `require` because `@xenova/transformers` is an ESM module + // We can't use `require` because `@huggingface/transformers` is an ESM module // and we can't use `import` directly because typescript will transpile it to `require`. // and we want to remain compatible with both ESM and CJS modules // so we use `eval` to bypass typescript for this specific import. - transformers = await eval('import("@xenova/transformers")'); + transformers = await eval('import("@huggingface/transformers")'); } catch (e) { - throw new Error(`error loading @xenova/transformers\nReason: ${e}`); + throw new Error(`error loading @huggingface/transformers\nReason: ${e}`); } try { this.#model = await transformers.AutoModel.from_pretrained( this.#modelName, + { dtype: "fp32" }, ); } catch (e) { throw new Error( @@ -128,7 +129,8 @@ export class TransformersEmbeddingFunction extends EmbeddingFunction< } else { const config = this.#model!.config; - const ndims = config["hidden_size"]; + // biome-ignore lint/style/useNamingConvention: we don't control this name. + const ndims = (config as unknown as { hidden_size: number }).hidden_size; if (!ndims) { throw new Error( "hidden_size not found in model config, you may need to manually specify the embedding dimensions. ", @@ -183,7 +185,7 @@ export class TransformersEmbeddingFunction extends EmbeddingFunction< } const tensorDiv = ( - src: import("@xenova/transformers").Tensor, + src: import("@huggingface/transformers").Tensor, divBy: number, ) => { for (let i = 0; i < src.data.length; ++i) { diff --git a/nodejs/lancedb/query.ts b/nodejs/lancedb/query.ts index 32d58e05..9a1ab8bf 100644 --- a/nodejs/lancedb/query.ts +++ b/nodejs/lancedb/query.ts @@ -571,4 +571,9 @@ export class Query extends QueryBase { return new VectorQuery(vectorQuery); } } + + nearestToText(query: string, columns?: string[]): Query { + this.doCall((inner) => inner.fullTextSearch(query, columns)); + return this; + } } diff --git a/nodejs/package-lock.json b/nodejs/package-lock.json index f56ad672..c76e7390 100644 --- a/nodejs/package-lock.json +++ b/nodejs/package-lock.json @@ -1,12 +1,12 @@ { "name": "@lancedb/lancedb", - "version": "0.12.0", + "version": "0.13.0-beta.1", "lockfileVersion": 3, "requires": true, "packages": { "": { 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a/nodejs/tsconfig.json +++ b/nodejs/tsconfig.json @@ -12,7 +12,7 @@ "experimentalDecorators": true, "moduleResolution": "Node" }, - "exclude": ["./dist/*"], + "exclude": ["./dist/*", "./examples/*"], "typedocOptions": { "entryPoints": ["lancedb/index.ts"], "out": "../docs/src/javascript/",