FFAR
Adaptive Retrieval component for Efficient Retrieval
Installation
Install the package via pip:
pip install ff-adaptive
Getting Started
- Create an Index
- Run the following code:
import pyterrier as pt
from pyterrier_adaptive import CorpusGraph
from ff_adaptive import FFAdaptive
if __name__ == "__main__":
corpus_graph = CorpusGraph.from_hf("macavaney/msmarco-passage.corpusgraph.bm25.128")
dataset = pt.get_dataset(f"irds:msmarco-passage/trec-dl-2019/judged")
index = pt.IndexFactory.of("/path/to/your/index") # Replace with index path
bm25 = pt.terrier.Retriever(index, wmodel="BM25")
rerank_model = pt.terrier.Retriever(index, wmodel="BM25") # Replace with a re-ranker of choice
pipeline = bm25 >> FFAdaptive(corpus_graph=corpus_graph, retriever=bm25, k=16) >> rerank_model
result = pipeline.transform(dataset.get_topics())
print(result)
Citation
@inproceedings{rear2025,
title = {Resource Efficient Adaptive Retrieval},
author = {Martijn Smits},
year = {2025},
}
Metadata
Release files for ff-adaptive 0.1.1
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
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| ff_adaptive-0.1.1.tar.gz | 3.2 kB | Without provenance | Details for ff_adaptive-0.1.1.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
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| ff_adaptive-0.1.1-py3-none-any.whl | Python 3 | none | any | Details for ff_adaptive-0.1.1-py3-none-any.whl |
Total release size: 7.3 kB
Release files / ff_adaptive-0.1.1.tar.gz
| Download URL | ff_adaptive-0.1.1.tar.gz |
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| Size | 3.2 kB |
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| Download URL | ff_adaptive-0.1.1-py3-none-any.whl |
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| Size | 4.1 kB |
| Tags | Python 3 |
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