ReRanker for hybrid retrieval.
For end-to-end text query service, check qtext.
-
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
You can start all the service with the following command:
docker compose -f serving/compose.yaml up -dpip install rerankerIf you need the cross-encoder model service, you can start the server with the following command:
docker compose -f serving/compose.yaml up -d encoderIf you need the semantic highlight service, you can start the server with the following command:
docker compose -f serving/compose.yaml up -d colbertfrom 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),
),
]
)
