Files
lancedb/docs
Ayush Chaurasia a41f7be88d feat(python): Hybrid search & Reranker API (#824)
based on https://github.com/lancedb/lancedb/pull/713
- The Reranker api can be plugged into vector only or fts only search
but this PR doesn't do that (see example -
https://txt.cohere.com/rerank/)


### Default reranker -- `LinearCombinationReranker(weight=0.7,
fill=1.0)`

```
table.search("hello", query_type="hybrid").rerank(normalize="score").to_pandas()
```
### Available rerankers
LinearCombinationReranker
```
from lancedb.rerankers import LinearCombinationReranker

# Same as default 
table.search("hello", query_type="hybrid").rerank(
                                      normalize="score", 
                                      reranker=LinearCombinationReranker()
                                     ).to_pandas()

# with custom params
reranker = LinearCombinationReranker(weight=0.3, fill=1.0)
table.search("hello", query_type="hybrid").rerank(
                                      normalize="score", 
                                      reranker=reranker
                                     ).to_pandas()
```

Cohere Reranker
```
from lancedb.rerankers import CohereReranker

# default model.. English and multi-lingual supported. See docstring for available custom params
table.search("hello", query_type="hybrid").rerank(
                                      normalize="rank",  # score or rank
                                      reranker=CohereReranker()
                                     ).to_pandas()

```

CrossEncoderReranker

```
from lancedb.rerankers import CrossEncoderReranker

table.search("hello", query_type="hybrid").rerank(
                                      normalize="rank", 
                                      reranker=CrossEncoderReranker()
                                     ).to_pandas()

```

## Using custom Reranker
```
from lancedb.reranker import Reranker

class CustomReranker(Reranker):
    def rerank_hybrid(self, vector_result, fts_result):
           combined_res = self.merge_results(vector_results, fts_results) # or use custom combination logic
           # Custom rerank logic here
           
           return combined_res
```

- [x] Expand testing
- [x] Make sure usage makes sense
- [x] Run simple benchmarks for correctness (Seeing weird result from
cohere reranker in the toy example)
- Support diverse rerankers by default:
- [x] Cross encoding
- [x] Cohere
- [x] Reciprocal Rank Fusion

---------

Co-authored-by: Chang She <759245+changhiskhan@users.noreply.github.com>
Co-authored-by: Prashanth Rao <35005448+prrao87@users.noreply.github.com>
2024-04-05 16:28:56 -07:00
..

LanceDB Documentation

LanceDB docs are deployed to https://lancedb.github.io/lancedb/.

Docs is built and deployed automatically by Github Actions whenever a commit is pushed to the main branch. So it is possible for the docs to show unreleased features.

Building the docs

Setup

  1. Install LanceDB. From LanceDB repo root: pip install -e python
  2. Install dependencies. From LanceDB repo root: pip install -r docs/requirements.txt
  3. Make sure you have node and npm setup
  4. Make sure protobuf and libssl are installed

Building node module and create markdown files

See Javascript docs README

Build docs

From LanceDB repo root:

Run: PYTHONPATH=. mkdocs build -f docs/mkdocs.yml

If successful, you should see a docs/site directory that you can verify locally.

Run local server

You can run a local server to test the docs prior to deployment by navigating to the docs directory and running the following command:

cd docs
mkdocs serve

Run doctest for typescript example

cd lancedb/docs
npm i
npm run build
npm run all