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# Description This PR makes it possible to use named vectors from Qdrant in Langchain. That was requested multiple times, as people want to reuse externally created collections in Langchain. It doesn't change anything for the existing applications. The changes were covered with some integration tests and included in the docs. ## Example ```python Qdrant.from_documents( docs, embeddings, location=":memory:", collection_name="my_documents", vector_name="custom_vector", ) ``` ### Issue: #2594 Tagging @rlancemartin & @eyurtsev. I'd appreciate your review. |
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.. | ||
agent | ||
cache | ||
callbacks | ||
chains | ||
chat_models | ||
document_loaders | ||
embeddings | ||
examples | ||
llms | ||
memory | ||
prompts | ||
retrievers | ||
utilities | ||
vectorstores | ||
__init__.py | ||
.env.example | ||
conftest.py | ||
test_document_transformers.py | ||
test_kuzu.py | ||
test_nebulagraph.py | ||
test_nlp_text_splitters.py | ||
test_pdf_pagesplitter.py | ||
test_schema.py | ||
test_text_splitter.py |