diff --git a/.github/workflows/docs_test.yml b/.github/workflows/docs_test.yml new file mode 100644 index 00000000..5f236cba --- /dev/null +++ b/.github/workflows/docs_test.yml @@ -0,0 +1,96 @@ +name: Documentation Code Testing + +on: + push: + branches: + - main + paths: + - docs/** + - .github/workflows/docs_test.yml + pull_request: + paths: + - docs/** + - .github/workflows/docs_test.yml + + # Allows you to run this workflow manually from the Actions tab + workflow_dispatch: + +env: + # 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: + test-python: + name: Test doc python code + runs-on: ${{ matrix.os }} + strategy: + matrix: + python-minor-version: [ "11" ] + os: ["ubuntu-22.04"] + steps: + - name: Checkout + uses: actions/checkout@v3 + - name: Set up Python + uses: actions/setup-python@v4 + with: + python-version: 3.${{ matrix.python-minor-version }} + cache: "pip" + cache-dependency-path: "docs/test/requirements.txt" + - name: Build Python + working-directory: docs/test + run: + python -m pip install -r requirements.txt + - name: Create test files + run: | + cd docs/test + python md_testing.py + - name: Test + run: | + cd docs/test/python + for d in *; do cd "$d"; echo "$d".py; python "$d".py; cd ..; done + test-node: + name: Test doc nodejs code + runs-on: ${{ matrix.os }} + strategy: + matrix: + node-version: [ "18" ] + os: ["ubuntu-22.04"] + steps: + - name: Checkout + uses: actions/checkout@v3 + with: + fetch-depth: 0 + lfs: true + - name: Set up Node + uses: actions/setup-node@v3 + with: + node-version: ${{ matrix.node-version }} + cache: 'npm' + cache-dependency-path: docs/test/package-lock.json + - name: Install dependecies needed for ubuntu + if: ${{ matrix.os == 'ubuntu-22.04' }} + run: | + sudo apt install -y protobuf-compiler libssl-dev + - name: Install node dependencies + run: | + cd docs/test + npm cache clean --force + npm ci + - name: Rust cache + uses: swatinem/rust-cache@v2 + - name: Install LanceDB + run: | + cd docs/test/node_modules/vectordb + npm ci + npm run build + npm run tsc + - name: Create test files + run: | + cd docs/test + node md_testing.js + - name: Test + run: | + cd docs/test/node + for d in *; do cd "$d"; echo "$d".js; node "$d".js; cd ..; done diff --git a/README.md b/README.md index 7e83a54c..268f3041 100644 --- a/README.md +++ b/README.md @@ -65,7 +65,7 @@ pip install lancedb ```python import lancedb -uri = "/tmp/lancedb" +uri = "data/sample-lancedb" db = lancedb.connect(uri) table = db.create_table("my_table", data=[{"vector": [3.1, 4.1], "item": "foo", "price": 10.0}, diff --git a/docs/src/ann_indexes.md b/docs/src/ann_indexes.md index 621f3f28..497d37ce 100644 --- a/docs/src/ann_indexes.md +++ b/docs/src/ann_indexes.md @@ -23,7 +23,7 @@ In the future we will look to automatically create and configure the ANN index. # Create 10,000 sample vectors data = [{"vector": row, "item": f"item {i}"} - for i, row in enumerate(np.random.random((10_000, 768)).astype('float32'))] + for i, row in enumerate(np.random.random((10_000, 1536)).astype('float32'))] # Add the vectors to a table tbl = db.create_table("my_vectors", data=data) @@ -41,8 +41,8 @@ In the future we will look to automatically create and configure the ANN index. for (let i = 0; i < 10_000; i++) { data.push({vector: Array(1536).fill(i), id: `${i}`, content: "", longId: `${i}`},) } - const table = await db.createTable('vectors', data) - await table.create_index({ type: 'ivf_pq', column: 'vector', num_partitions: 256, num_sub_vectors: 96 }) + const table = await db.createTable('my_vectors', data) + await table.createIndex({ type: 'ivf_pq', column: 'vector', num_partitions: 256, num_sub_vectors: 96 }) ``` Since `create_index` has a training step, it can take a few minutes to finish for large tables. You can control the index @@ -73,12 +73,13 @@ There are a couple of parameters that can be used to fine-tune the search: === "Python" ```python - tbl.search(np.random.random((768))) \ + tbl.search(np.random.random((1536))) \ .limit(2) \ .nprobes(20) \ .refine_factor(10) \ .to_df() - + ``` + ``` vector item score 0 [0.44949695, 0.8444449, 0.06281311, 0.23338133... item 1141 103.575333 1 [0.48587373, 0.269207, 0.15095535, 0.65531915,... item 3953 108.393867 @@ -86,8 +87,8 @@ There are a couple of parameters that can be used to fine-tune the search: === "Javascript" ```javascript - const results = await table - .search(Array(768).fill(1.2)) + const results_1 = await table + .search(Array(1536).fill(1.2)) .limit(2) .nprobes(20) .refineFactor(10) @@ -104,14 +105,14 @@ You can further filter the elements returned by a search using a where clause. === "Python" ```python - tbl.search(np.random.random((768))).where("item != 'item 1141'").to_df() + tbl.search(np.random.random((1536))).where("item != 'item 1141'").to_df() ``` === "Javascript" ```javascript - const results = await table + const results_2 = await table .search(Array(1536).fill(1.2)) - .where("item != 'item 1141'") + .where("id != '1141'") .execute() ``` @@ -121,7 +122,9 @@ You can select the columns returned by the query using a select clause. === "Python" ```python - tbl.search(np.random.random((768))).select(["vector"]).to_df() + tbl.search(np.random.random((1536))).select(["vector"]).to_df() + ``` + ``` vector score 0 [0.30928212, 0.022668175, 0.1756372, 0.4911822... 93.971092 1 [0.2525465, 0.01723831, 0.261568, 0.002007689,... 95.173485 @@ -130,7 +133,7 @@ You can select the columns returned by the query using a select clause. === "Javascript" ```javascript - const results = await table + const results_3 = await table .search(Array(1536).fill(1.2)) .select(["id"]) .execute() diff --git a/docs/src/basic.md b/docs/src/basic.md index 21638fb8..e6ee76f3 100644 --- a/docs/src/basic.md +++ b/docs/src/basic.md @@ -23,7 +23,7 @@ We'll cover the basics of using LanceDB on your local machine in this section. === "Python" ```python import lancedb - uri = "~/.lancedb" + uri = "data/sample-lancedb" db = lancedb.connect(uri) ``` @@ -35,7 +35,7 @@ We'll cover the basics of using LanceDB on your local machine in this section. ```javascript const lancedb = require("vectordb"); - const uri = "~./lancedb"; + const uri = "data/sample-lancedb"; const db = await lancedb.connect(uri); ``` @@ -102,7 +102,7 @@ Once created, you can open a table using the following code: If you forget the name of your table, you can always get a listing of all table names: ```javascript - console.log(db.tableNames()); + console.log(await db.tableNames()); ``` ## How to add data to a table @@ -118,7 +118,7 @@ After a table has been created, you can always add more data to it using === "Javascript" ```javascript - await tbl.add([vector: [1.3, 1.4], item: "fizz", price: 100.0}, + await tbl.add([{vector: [1.3, 1.4], item: "fizz", price: 100.0}, {vector: [9.5, 56.2], item: "buzz", price: 200.0}]) ``` diff --git a/docs/src/embedding.md b/docs/src/embedding.md index 50f1362e..61118404 100644 --- a/docs/src/embedding.md +++ b/docs/src/embedding.md @@ -98,7 +98,7 @@ You can also use an external API like OpenAI to generate embeddings embededings for your data. ```javascript - const db = await lancedb.connect("/tmp/lancedb"); + const db = await lancedb.connect("data/sample-lancedb"); const data = [ { text: 'pepperoni' }, { text: 'pineapple' } diff --git a/docs/src/fts.md b/docs/src/fts.md index 1f8a1d55..58dea5d7 100644 --- a/docs/src/fts.md +++ b/docs/src/fts.md @@ -18,6 +18,20 @@ Assume: 1. `table` is a LanceDB Table 2. `text` is the name of the Table column that we want to index +For example, + +```python +import lancedb + +uri = "data/sample-lancedb" +db = lancedb.connect(uri) + +table = db.create_table("my_table", + data=[{"vector": [3.1, 4.1], "text": "Frodo was a happy puppy"}, + {"vector": [5.9, 26.5], "text": "There are several kittens playing"}]) + +``` + To create the index: ```python diff --git a/docs/src/index.md b/docs/src/index.md index 8cfe491e..d5209e9d 100644 --- a/docs/src/index.md +++ b/docs/src/index.md @@ -28,7 +28,7 @@ LanceDB's core is written in Rust 🦀 and is built using '); -const table = await db.openTable('my_table'); -const query = await table.search([0.1, 0.3]).limit(20).execute(); +const db = await lancedb.connect('data/sample-lancedb'); +const table = await db.createTable("my_table", + [{ id: 1, vector: [0.1, 1.0], item: "foo", price: 10.0 }, + { id: 2, vector: [3.9, 0.5], item: "bar", price: 20.0 }]) +const results = await table.search([0.1, 0.3]).limit(20).execute(); console.log(results); ``` diff --git a/docs/src/search.md b/docs/src/search.md index db9a59ae..9414cdcb 100644 --- a/docs/src/search.md +++ b/docs/src/search.md @@ -17,7 +17,7 @@ Currently, we support the following metrics: | Metric | Description | | ----------- | ------------------------------------ | | `L2` | [Euclidean / L2 distance](https://en.wikipedia.org/wiki/Euclidean_distance) | -| `Cosine` | [Cosine Similarity](https://en.wikipedia.org/wiki/Cosine_similarity)| + ## Search @@ -28,16 +28,44 @@ Currently, we support the following metrics: If there is no [vector index is created](ann_indexes.md), LanceDB will just brute-force scan the vector column and compute the distance. + + === "Python" + ```python import lancedb + import numpy as np + db = lancedb.connect("data/sample-lancedb") tbl = db.open_table("my_vectors") - df = tbl.search(np.random.random((768))) - .limit(10) + df = tbl.search(np.random.random((1536))) \ + .limit(10) \ .to_df() ``` @@ -47,38 +75,41 @@ the vector column and compute the distance. const vectordb = require('vectordb') const db = await vectordb.connect('data/sample-lancedb') - tbl = db.open_table("my_vectors") + const tbl = await db.openTable("my_vectors") - const results = await tbl.search(Array(768)) + const results_1 = await tbl.search(Array(1536).fill(1.2)) .limit(20) .execute() ``` + + + + + - ```javascript - const vectordb = require('vectordb') - const db = await vectordb.connect('data/sample-lancedb') - - tbl = db.open_table("my_vectors") - - const results = await tbl.search(Array(768)) - .metric("cosine") + ### Search with Vector Index. diff --git a/docs/src/sql.md b/docs/src/sql.md index 7d39f6d4..ef1b9b52 100644 --- a/docs/src/sql.md +++ b/docs/src/sql.md @@ -15,11 +15,35 @@ Currently, Lance supports a growing list of expressions. * ``regexp_match(column, pattern)`` For example, the following filter string is acceptable: + + === "Python" ```python - tbl.search([100, 102]) + tbl.search([100, 102]) \ .where("""( (label IN [10, 20]) AND diff --git a/docs/test/md_testing.js b/docs/test/md_testing.js new file mode 100644 index 00000000..6e9c3cc4 --- /dev/null +++ b/docs/test/md_testing.js @@ -0,0 +1,51 @@ +const glob = require("glob"); +const fs = require("fs"); +const path = require("path"); + +const excludedFiles = [ + "../src/fts.md", + "../src/embedding.md", + "../src/examples/serverless_lancedb_with_s3_and_lambda.md", + "../src/examples/serverless_qa_bot_with_modal_and_langchain.md", + "../src/examples/youtube_transcript_bot_with_nodejs.md", +]; +const nodePrefix = "javascript"; +const nodeFile = ".js"; +const nodeFolder = "node"; +const globString = "../src/**/*.md"; +const asyncPrefix = "(async () => {\n"; +const asyncSuffix = "})();"; + +function* yieldLines(lines, prefix, suffix) { + let inCodeBlock = false; + for (const line of lines) { + if (line.trim().startsWith(prefix + nodePrefix)) { + inCodeBlock = true; + } else if (inCodeBlock && line.trim().startsWith(suffix)) { + inCodeBlock = false; + yield "\n"; + } else if (inCodeBlock) { + yield line; + } + } +} + +const files = glob.sync(globString, { recursive: true }); + +for (const file of files.filter((file) => !excludedFiles.includes(file))) { + const lines = []; + const data = fs.readFileSync(file, "utf-8"); + const fileLines = data.split("\n"); + + for (const line of yieldLines(fileLines, "```", "```")) { + lines.push(line); + } + + if (lines.length > 0) { + const fileName = path.basename(file, ".md"); + const outPath = path.join(nodeFolder, fileName, `${fileName}${nodeFile}`); + console.log(outPath) + fs.mkdirSync(path.dirname(outPath), { recursive: true }); + fs.writeFileSync(outPath, asyncPrefix + "\n" + lines.join("\n") + asyncSuffix); + } +} \ No newline at end of file diff --git a/docs/test/md_testing.py b/docs/test/md_testing.py new file mode 100644 index 00000000..0a566a6e --- /dev/null +++ b/docs/test/md_testing.py @@ -0,0 +1,41 @@ +import glob +from typing import Iterator +from pathlib import Path + +excluded_files = [ + "../src/fts.md", + "../src/embedding.md", + "../src/examples/serverless_lancedb_with_s3_and_lambda.md", + "../src/examples/serverless_qa_bot_with_modal_and_langchain.md", + "../src/examples/youtube_transcript_bot_with_nodejs.md" +] + +python_prefix = "py" +python_file = ".py" +python_folder = "python" +glob_string = "../src/**/*.md" + +def yield_lines(lines: Iterator[str], prefix: str, suffix: str): + in_code_block = False + # Python code has strict indentation + strip_length = 0 + for line in lines: + if line.strip().startswith(prefix + python_prefix): + in_code_block = True + strip_length = len(line) - len(line.lstrip()) + elif in_code_block and line.strip().startswith(suffix): + in_code_block = False + yield "\n" + elif in_code_block: + yield line[strip_length:] + +for file in filter(lambda file: file not in excluded_files, glob.glob(glob_string, recursive=True)): + with open(file, "r") as f: + lines = list(yield_lines(iter(f), "```", "```")) + + if len(lines) > 0: + out_path = Path(python_folder) / Path(file).name.strip(".md") / (Path(file).name.strip(".md") + python_file) + print(out_path) + out_path.parent.mkdir(exist_ok=True, parents=True) + with open(out_path, "w") as out: + out.writelines(lines) diff 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