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3215985d1d
* added a table of content * wide layout for docs, styles for the table of content * fixes for docs layout * wide footer at the docs section * added support for nested docs, added toggling groups of links, delimiters, external links * external link icon * added active state for nested links, styles for the external link icon * styles fix * remove doc sync * update directory structure and doc titles * fix outstanding links * fix more links for merge * Revert "fix more links for merge" This reverts commit 46c9ccaf1b7765f2cda8dc85d625fa6b4e3f5436. * Revert "fix outstanding links" This reverts commit 28e6380b74f1ab74690c8184551f186656d6d4e9. * fix remaining broken links * move how-to tutorials in the different page * split tutorials * fix link * upd github edit link * skip empty index pages --------- Co-authored-by: Andrey Vasnetsov <andrey@vasnetsov.com> Co-authored-by: David Sertic <62056091+davidmyriel@users.noreply.github.com>
1002 B
1002 B
title, weight
| title | weight |
|---|---|
| Cohere | 700 |
Cohere
Qdrant is compatible with Cohere co.embed API and it's official Python SDK that might be installed as any other package:
pip install cohere
The embeddings returned by co.embed API might be used directly in the Qdrant client's calls:
import cohere
import qdrant_client
from qdrant_client.http.models import Batch
cohere_client = cohere.Client("<< your_api_key >>")
qdrant_client = qdrant_client.QdrantClient()
qdrant_client.upsert(
collection_name="MyCollection",
points=Batch(
ids=[1],
vectors=cohere_client.embed(
model="large",
texts=["The best vector database"],
).embeddings,
)
)
If you are interested in seeing an end-to-end project created with co.embed API and Qdrant, please check out the "Question Answering as a Service with Cohere and Qdrant" article.