sparse vectors name unknown about langchain

[wulifu2hao]

I am able to reproduce your issue. However changing "Qdrant.from_texts(" in your step 1 To "QdrantVectorStore.from_texts" fix the issue for me

import os
from langchain_huggingface import HuggingFaceEmbeddings
from langchain_qdrant import FastEmbedSparse, RetrievalMode, QdrantVectorStore

embeddings = HuggingFaceEmbeddings(model_name='OrdalieTech/Solon-embeddings-large-0.1')

sparse_embeddings = FastEmbedSparse(model_name="Qdrant/bm25")

texts = ["the capital of france is paris", "the capital of germany is berlin", "the capital of italy is rome"]
vectordb = QdrantVectorStore.from_texts(
    # vectordb = Qdrant.from_texts(
    texts=texts,
    embedding=embeddings,
    sparse_embedding=sparse_embeddings,
    sparse_vector_name="sparse-vector",
    path=os.path.join(os.getcwd(), 'manuscrits_biblissima_vectordb'),
    collection_name="manuscrits_biblissima",
    retrieval_mode=RetrievalMode.HYBRID,
)
print(vectordb)
        
qdrant = QdrantVectorStore.from_existing_collection(
    collection_name="manuscrits_biblissima",
    path=os.path.join(os.getcwd(), 'manuscrits_biblissima_vectordb'),
    retrieval_mode=RetrievalMode.HYBRID,
    embedding=embeddings, 
    sparse_embedding=sparse_embeddings,
    sparse_vector_name="sparse-vector"
    )
res = qdrant.search("where is the capital of france",search_type="similarity", k=1)
print(res)

[EtienneFerrandi]

yes, it works for me also when I change Qdrant.from_texts by QdrantVectorStore.from_texts.
Thanks !