mirror of
https://github.com/qdrant/landing_page.git
synced 2026-10-06 11:28:31 +02:00
1a40961d62
* initial commit; fixed anchor links on internal docs pages * add back in absolute paths for links in code comments * fix: update linkchecker include filter to match server port 1314 PR #1629 changed the Hugo server to port 1314 but forgot to update the --include filter, which still matched port 1313. This caused all links to be excluded, making the checker a no-op (0 checked, 82277 excluded). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * Fix url rewrite regex so images are not impacted * Fix links from non-documentation pages * Fix broken links * more broken links * more broken links * broken link * Add srcset width descriptor to .lycheeignore * Ignore URLs that contain a % character * Anchor regex so it matches the entire URL --------- Co-authored-by: kanungle <neil.kanungo@gmail.com> Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> Co-authored-by: Abdon Pijpelink <abdon.pijpelink@qdrant.com>
50 lines
2.0 KiB
Markdown
50 lines
2.0 KiB
Markdown
---
|
|
title: Haystack
|
|
aliases:
|
|
- ../integrations/haystack/
|
|
- /documentation/overview/integrations/haystack/
|
|
---
|
|
|
|
# Haystack
|
|
|
|
[Haystack](https://haystack.deepset.ai/) serves as a comprehensive NLP framework, offering a modular methodology for constructing
|
|
cutting-edge generative AI, QA, and semantic knowledge base search systems. A critical element in contemporary NLP systems is an
|
|
efficient database for storing and retrieving extensive text data. Vector databases excel in this role, as they house vector
|
|
representations of text and implement effective methods for swift retrieval. Thus, we are happy to announce the integration
|
|
with Haystack - `QdrantDocumentStore`. This document store is unique, as it is maintained externally by the Qdrant team.
|
|
|
|
The new document store comes as a separate package and can be updated independently of Haystack:
|
|
|
|
```bash
|
|
pip install qdrant-haystack
|
|
```
|
|
|
|
`QdrantDocumentStore` supports [all the configuration properties](/documentation/manage-data/collections/#create-collection) available in
|
|
the Qdrant Python client. If you want to customize the default configuration of the collection used under the hood, you can
|
|
provide that settings when you create an instance of the `QdrantDocumentStore`. For example, if you'd like to enable the
|
|
Scalar Quantization, you'd make that in the following way:
|
|
|
|
```python
|
|
from qdrant_haystack.document_stores import QdrantDocumentStore
|
|
from qdrant_client import models
|
|
|
|
document_store = QdrantDocumentStore(
|
|
":memory:",
|
|
index="Document",
|
|
embedding_dim=512,
|
|
recreate_index=True,
|
|
quantization_config=models.ScalarQuantization(
|
|
scalar=models.ScalarQuantizationConfig(
|
|
type=models.ScalarType.INT8,
|
|
quantile=0.99,
|
|
always_ram=True,
|
|
),
|
|
),
|
|
)
|
|
```
|
|
|
|
## Further Reading
|
|
|
|
- [Haystack Documentation](https://haystack.deepset.ai/integrations/qdrant-document-store)
|
|
- [Source Code](https://github.com/deepset-ai/haystack-core-integrations/tree/main/integrations/qdrant)
|