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Basic full text search capabilities (#62)
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>
This commit is contained in:
@@ -19,6 +19,7 @@ nav:
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- Basics: basic.md
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- Embeddings: embedding.md
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- Indexing: ann_indexes.md
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- Full-text search: fts.md
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- Integrations: integrations.md
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- Python API: python.md
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50
docs/src/fts.md
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50
docs/src/fts.md
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# [EXPERIMENTAL] Full text search
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LanceDB now provides experimental support for full text search.
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This is currently Python only. We plan to push the integration down to Rust in the future
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to make this available for JS as well.
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## Installation
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To use full text search, you must install the fts optional dependencies:
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`pip install lancedb[fts]`
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## Quickstart
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Assume:
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1. `table` is a LanceDB Table
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2. `text` is the name of the Table column that we want to index
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To create the index:
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```python
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table.create_fts_index("text")
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```
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To search:
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```python
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df = table.search("puppy").limit(10).select(["text"]).to_df()
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```
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LanceDB automatically looks for an FTS index if the input is str.
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## Multiple text columns
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If you have multiple columns to index, pass them all as a list to `create_fts_index`:
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```python
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table.create_fts_index(["text1", "text2"])
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```
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Note that the search API call does not change - you can search over all indexed columns at once.
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## Current limitations
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1. Currently we do not yet support incremental writes.
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If you add data after fts index creation, it won't be reflected
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in search results until you do a full reindex.
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2. We currently only support local filesystem paths for the fts index.
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@@ -45,5 +45,6 @@ We will be adding completed demo apps built using LanceDB.
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* [`Basic Operations`](basic.md) - basic functionality of LanceDB.
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* [`Embedding Functions`](embedding.md) - functions for working with embeddings.
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* [`Indexing`](ann_indexes.md) - create vector indexes to speed up queries.
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* [`Full text search`](fts.md) - [EXPERIMENTAL] full-text search API
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* [`Ecosystem Integrations`](integrations.md) - integrating LanceDB with python data tooling ecosystem.
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* [`API Reference`](python.md) - detailed documentation for the LanceDB Python SDK.
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