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2023-04-11 23:50:20 +00:00
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qdrant-landing/content/documentation/integrations.md
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@@ -19,7 +19,7 @@ pip install langchain
```
Qdrant acts as a vector index that may store the embeddings with the documents used to generate them. There are various ways
how to us it, but calling `Qdrant.from_texts` is probably the most straightforward way how to get started:
how to use it, but calling `Qdrant.from_texts` is probably the most straightforward way how to get started:
```python
from langchain.vectorstores import Qdrant