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Jina Reranker

This re-ranker uses the Jina API to rerank the search results. You can use this re-ranker by passing JinaReranker() to the rerank() method. Note that you'll either need to set the JINA_API_KEY environment variable or pass the api_key argument to use this re-ranker.

Note

Supported Query Types: Hybrid, Vector, FTS

import os
import lancedb
from lancedb.embeddings import get_registry
from lancedb.pydantic import LanceModel, Vector
from lancedb.rerankers import JinaReranker

os.environ['JINA_API_KEY'] = "jina_*"


embedder = get_registry().get("jina").create()
db = lancedb.connect("~/.lancedb")

class Schema(LanceModel):
    text: str = embedder.SourceField()
    vector: Vector(embedder.ndims()) = embedder.VectorField()

data = [
    {"text": "hello world"},
    {"text": "goodbye world"}
    ]
tbl = db.create_table("test", schema=Schema, mode="overwrite")
tbl.add(data)
reranker = JinaReranker(api_key="key")

# Run vector search with a reranker
result = tbl.search("hello").rerank(reranker=reranker).to_list() 

# Run FTS search with a reranker
result = tbl.search("hello", query_type="fts").rerank(reranker=reranker).to_list()

# Run hybrid search with a reranker
tbl.create_fts_index("text", replace=True)
result = tbl.search("hello", query_type="hybrid").rerank(reranker=reranker).to_list()

Accepted Arguments

Argument Type Default Description
model_name str "jina-reranker-v2-base-multilingual" The name of the reranker model to use. You can find the list of available models in https://jina.ai/reranker/
column str "text" The name of the column to use as input to the cross encoder model.
top_n str None The number of results to return. If None, will return all results.
api_key str None The API key for the Jina API. If not provided, the JINA_API_KEY environment variable is used.
return_score str "relevance" Options are "relevance" or "all". The type of score to return. If "relevance", will return only the `_relevance_score. If "all" is supported, will return relevance score along with the vector and/or fts scores depending on query type

Supported Scores for each query type

You can specify the type of scores you want the reranker to return. The following are the supported scores for each query type:

return_score Status Description
relevance ✅ Supported Returns only have the _relevance_score column
all ❌ Not Supported Returns have vector(_distance) and FTS(score) along with Hybrid Search score(_relevance_score)
return_score Status Description
relevance ✅ Supported Returns only have the _relevance_score column
all ✅ Supported Returns have vector(_distance) along with Hybrid Search score(_relevance_score)
return_score Status Description
relevance ✅ Supported Returns only have the _relevance_score column
all ✅ Supported Returns have FTS(score) along with Hybrid Search score(_relevance_score)