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)
1 maintainer
Metadata
1 maintainer
Release files for sie-haystack 0.9.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| sie_haystack-0.9.0.tar.gz | 20.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| sie_haystack-0.9.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 32.0 kB
Release files / sie_haystack-0.9.0.tar.gz
| Download URL | sie_haystack-0.9.0.tar.gz |
|---|---|
| Size | 20.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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| Download URL | sie_haystack-0.9.0-py3-none-any.whl |
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| Size | 11.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
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