landing_page/qdrant-landing/content/documentation/integrations/cohere.md

title, weight

title	weight
Cohere	700

Cohere

Qdrant is compatible with Cohere co.embed API and its 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.