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Update qdrant-landing/content/documentation/frameworks/langchain.md

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Co-authored-by: Anush <mail@anush.sh>
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Manas Chopra
2026-07-30 19:48:32 +05:30
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co-authored by Anush
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@@ -128,9 +128,7 @@ query = "What did the president say about Ketanji Brown Jackson"
found_docs = qdrant.similarity_search(query)
```
If you'd rather not depend on an embedding provider's API, [FastEmbed](https://github.com/qdrant/fastembed) also lets you generate dense embeddings
locally. `langchain-community`, which used to ship a `FastEmbedEmbeddings` class, is [being sunset](https://github.com/langchain-ai/langchain-community/issues/674),
so wrap FastEmbed's `TextEmbedding` directly with LangChain's `Embeddings` interface instead:
If you'd rather not depend on an embedding provider's API, [FastEmbed](https://github.com/qdrant/fastembed) also lets you generate dense embeddings locally. You can wrap FastEmbed's `TextEmbedding` into LangChain's `Embeddings` interface:
```py
from typing import List