impact-index 1.1.0

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Impact Index for Information Retrieval

A Python/Rust library for efficient sparse retrieval from neural information retrieval systems. Built on Rust with PyO3 bindings for high performance.

Unlike traditional IR libraries, impact-index specifically targets neural IR models with floating-point impact scores (no quantization assumed) and does not implement frequency-based algorithms.

Features

• Index construction with checkpointing for crash recovery
• WAND and MaxScore search algorithms for top-k retrieval
• Block-based compression with Elias-Fano doc IDs and quantized impacts
• Posting list splitting by quantile for term impact decomposition
• BMP (Block-Max Pruning) for fast approximate search (SIGIR 2024)
• Document store with zstd compression and key-based retrieval
• Async support for non-blocking search and document retrieval

Installation

pip install maturin
maturin develop --release

Quick Example

import numpy as np
import impact_index

# Build an index
builder = impact_index.IndexBuilder("/path/to/index")
builder.add(0, np.array([1, 5, 10], dtype=np.uintp),
            np.array([0.5, 1.2, 0.8], dtype=np.float32))
index = builder.build(in_memory=True)

# Search
results = index.search_wand({5: 1.0, 10: 0.5}, top_k=10)
for doc in results:
    print(f"Document {doc.docid}: {doc.score}")

Documentation

Full documentation including guides on compression, BMP search, and the document store is available at:

https://experimaestro-ir-rust.readthedocs.io/en/latest/index.html