Skip to main content

sie-haystack

SIE integration for Haystack.

Installation

pip install sie-haystack

Imports

Preferred import paths follow Haystack's namespace convention:

from haystack_integrations.components.embedders.sie import (
    SIEDocumentEmbedder,
    SIETextEmbedder,
)
from haystack_integrations.components.rankers.sie import SIERanker
from haystack_integrations.components.extractors.sie import SIEExtractor

The legacy flat imports remain supported for compatibility:

from sie_haystack import SIEDocumentEmbedder, SIEExtractor, SIERanker, SIETextEmbedder

Usage

from haystack import Document
from haystack_integrations.components.embedders.sie import SIEDocumentEmbedder, SIETextEmbedder
from haystack_integrations.components.rankers.sie import SIERanker

# Embed a query
text_embedder = SIETextEmbedder(base_url="http://localhost:8080", model="BAAI/bge-m3")
result = text_embedder.run(text="What is machine learning?")
query_embedding = result["embedding"]

# Embed documents
doc_embedder = SIEDocumentEmbedder(base_url="http://localhost:8080", model="BAAI/bge-m3")
docs = [Document(content="Python is a programming language.")]
result = doc_embedder.run(documents=docs)
embedded_docs = result["documents"]

# Rerank documents
ranker = SIERanker(
    base_url="http://localhost:8080",
    model="jinaai/jina-reranker-v2-base-multilingual"
)
result = ranker.run(query="What is Python?", documents=embedded_docs, top_k=3)
ranked_docs = result["documents"]

Relation models such as GLiREL classify relations between supplied entity spans. Extract those spans first, then pass them through the relation extractor's entities input:

from haystack_integrations.components.extractors.sie import SIEExtractor

text = "Tim Cook is the CEO of Apple Inc."
entity_extractor = SIEExtractor(
    model="urchade/gliner_multi-v2.1",
    labels=["person", "organization"],
)
relation_extractor = SIEExtractor(
    model="jackboyla/glirel-large-v0",
    labels=["ceo_of"],
)

entities = entity_extractor.run(text=text)["entities"]
result = relation_extractor.run(text=text, entities=entities)

Metadata

Release files for sie-haystack 0.10.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for sie-haystack 0.10.1
File Size Uploaded Provenance Actions
sie_haystack-0.10.1.tar.gz 20.3 kB With provenance Details for sie_haystack-0.10.1.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for sie-haystack 0.10.1
File Interpreter ABI Platform Actions
sie_haystack-0.10.1-py3-none-any.whl Python 3 none any Details for sie_haystack-0.10.1-py3-none-any.whl

Total release size: 32.0 kB

Release files / sie_haystack-0.10.1.tar.gz

Download URL sie_haystack-0.10.1.tar.gz
Size 20.3 kB
Tags Source
SHA-256 checksum
How to use checksums
731d4587887831eccefa760def73c41ec3f5b4c8d7afce99e9bb1a9f768c43f8
BLAKE2b-256 checksum
How to use checksums
9a2086db20e7b0543e207c3249d440814550ff7995bf0c26bc0d43ccadb6de4d
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Oct 13, 2026.

Transparency log

Release files / sie_haystack-0.10.1-py3-none-any.whl

Download URL sie_haystack-0.10.1-py3-none-any.whl
Size 11.7 kB
Tags Python 3
SHA-256 checksum
How to use checksums
3caeb4959daa46310c1c2f8bdbc02ccec1a221b10b6e8c164cfd2d2f75a38d1d
BLAKE2b-256 checksum
How to use checksums
416ed652cb5af7a6e3bfa631b8544e611e0cad95424f89f7896b8c3a585db479
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Oct 13, 2026.

Transparency log

Security for sie-haystack 0.10.1

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

Full provenance

All 2 files in this release have been uploaded with provenance metadata.

Select from 2 files

Attestation for sie_haystack-0.10.1.tar.gz

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Oct 13, 2026.

Transparency log

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Release history Release notifications | RSS feed

This release

0.10.1 This release

2 release files Full provenance

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page