aws integration tests are flaky because we didn't wait for the services
to become healthy. (we only waited for the localstack service, this PR
adds wait for sub services)
# WARNING: specifying engine is NOT a publicly supported feature in
lancedb yet. THE API WILL CHANGE.
This PR exposes dynamodb based commit to `vectordb` and JS SDK (will do
python in another PR since it's on a different release track)
This PR also added aws integration test using `localstack`
## What?
This PR adds uri parameters to DB connection string. User may specify
`engine` in the connection string to let LanceDB know that the user
wants to use an external store when reading and writing a table. User
may also pass any parameters required by the commitStore in the
connection string, these parameters will be propagated to lance.
e.g.
```
vectordb.connect("s3://my-db-bucket?engine=ddb&ddbTableName=my-commit-table")
```
will automatically convert table path to
```
s3+ddb://my-db-bucket/my_table.lance?&ddbTableName=my-commit-table
```
It's inconvenient to always require data at table creation time.
Here we enable you to create an empty table and add data and set schema
later.
---------
Co-authored-by: Chang She <chang@lancedb.com>
- Creates testing files `md_testing.py` and `md_testing.js` for testing
python and nodejs code in markdown files in the documentation
This listens for HTML tags as well: `<!--[language] code code
code...-->` will create a set-up file to create some mock tables or to
fulfill some assumptions in the documentation.
- Creates a github action workflow that triggers every push/pr to
`docs/**`
- Modifies documentation so tests run (mostly indentation, some small
syntax errors and some missing imports)
A list of excluded files that we need to take a closer look at later on:
```javascript
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",
];
```
Many of them can't be done because we need the OpenAI API key :(.
`fts.md` has some issues with the library, I believe this is still
experimental?
Closes#170
---------
Co-authored-by: Will Jones <willjones127@gmail.com>
* Refactors the Node module to load the shared library from a separate
package. When a user does `npm install vectordb`, the correct optional
dependency is automatically downloaded by npm.
* Add scripts and instructions to build Linux and MacOS node artifacts
locally.
* Add instructions for publishing the npm module and crates.
Co-authored-by: Will Jones <willjones127@gmail.com>
Adds:
* Make `mkdocstrings` aware we are using numpy-style docstrings
* Fixes broken link on `index.md` to Python API docs (and added link to
node ones)
* Added examples to various classes.
* Added doctest to verify examples work.
Changes:
* Refactors the Node module to load the shared library from a separate
package. When a user does `npm install vectordb`, the correct optional
dependency is automatically downloaded by npm.
* Brings Rust and Node versions in alignment at 0.1.2.
* Add scripts and instructions to build Linux and MacOS node artifacts
locally.
* Add instructions for publishing the npm module and crates.
pypi does not allow packages to be uploaded that has a direct reference
for now we'll just ask the user to install tantivy separately
---------
Co-authored-by: Chang She <chang@lancedb.com>
This is v1 of integrating full text search index into LanceDB.
# API
The query API is roughly the same as before, except if the input is text
instead of a vector we assume that its fts search.
## Example
If `table` is a LanceDB LanceTable, then:
Build index: `table.create_fts_index("text")`
Query: `df = table.search("puppy").limit(10).select(["text"]).to_df()`
# Implementation
Here we use the tantivy-py package to build the index. We then use the
row id's as the full-text-search index's doc id then we just do a Take
operation to fetch the rows.
# Limitations
1. don't support incremental row appends yet. New data won't show up in
search
2. local filesystem only
3. requires building tantivy explicitly
---------
Co-authored-by: Chang She <chang@lancedb.com>
