reranker 0.2.2

Argument parsing with structured class.

ReRanker

ReRanker for hybrid retrieval.

For end-to-end text query service, check qtext.

Ranking

• rank(query: str, docs: list[str])
  • cross-encoder model
  • cohere model
  • diversity (Max Marginal Relevance)
• rank(docs: list[Record])
  • time decay with expressions
  • title n-gram with bm25
  • content n-gram with bm25
  • document boost with expressions
  • title embedding with content embedding
  • title keywords with content keywords
  • combination of the above features

Installation

pip install reranker

Usage

If you need the cross-encoder model service, you can start the server with the following command:

docker compose -f serving/compose.yaml up -d encoder

If you need the semantic highlight service, you can start the server with the following command:

docker compose -f serving/compose.yaml up -d colbert

from datetime import datetime, timedelta
from reranker import ReRanker, CrossEncoderClient, TimeDecayRanker


reranker = ReRanker(
    steps=[
        CrossEncoderClient(
            model_name="cross-encoder/ms-marco-MiniLM-L-6-v2",
            addr="http://localhost:8000",
        ),
        TimeDecayRanker(decay_rate=0.5),
    ]
)

reranker.rank(
    query="What is the capital of France?",
    docs=[
        "Paris is the capital of France.",
        "The Eiffel Tower is in Paris.",
        "The Louvre is in Paris.",
    ],
)
reranker.rank(
    query=Record(
        text="What is the capital of France?",
        timestamp=datetime.now(),
    ),
    docs=[
        Record(
            text="Paris is the capital of France.",
            timestamp=datetime.now() - timedelta(days=1),
        ),
        Record(
            text="The Eiffel Tower is in Paris.",
            timestamp=datetime.now() - timedelta(days=2),
        ),
        Record(
            text="The Louvre is in Paris.",
            timestamp=datetime.now() - timedelta(days=3),
        ),
    ]
)