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## Description Currently, the Qdrant integration relies on exceptions raised by [`get_collection` ](https://qdrant.tech/documentation/concepts/collections/#collection-info) to check if a collection exists. Using [`collection_exists`](https://qdrant.tech/documentation/concepts/collections/#check-collection-existence) is recommended to avoid missing any unhandled exceptions. This PR addresses this. ## Testing All integration and unit tests pass. No user-facing changes. |
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| .. | ||
| langchain_qdrant | ||
| scripts | ||
| tests | ||
| .gitignore | ||
| LICENSE | ||
| Makefile | ||
| poetry.lock | ||
| pyproject.toml | ||
| README.md | ||
langchain-qdrant
This package contains the LangChain integration with Qdrant.
Installation
pip install -U langchain-qdrant
Usage
The Qdrant class exposes the connection to the Qdrant vector store.
from langchain_qdrant import Qdrant
embeddings = ... # use a LangChain Embeddings class
vectorstore = Qdrant.from_existing_collection(
embeddings=embeddings,
collection_name="<COLLECTION_NAME>",
url="http://localhost:6333",
)