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[Bug]: Unable to load and create vector data base by using langchain module hugging face embedding
What happened?
from langchaincommunity.embeddings import HuggingFaceEmbeddings embeddings = HuggingFaceEmbeddings(modelname="BAAI/bge-large-en-v1.5") vectorstore_2 = Chroma( collection_name="full_document", embedding_function=embeddings,persist_directory="./multi_vector_retriver_new" )
ValueError: Expected EmbeddingFunction.__call to have the following signature: odict_keys(['self', 'input']), got odict_keys(['args', 'kwargs']) Please see https://docs.trychroma.com/embeddings for details of the EmbeddingFunction interface. Please note the recent change to the EmbeddingFunction interface: https://docs.trychroma.com/migration#migration-to-0416---november-7-2023
Hi team, i was able get response in morning but from 12 oclock i am getting this error , can anyone please help me
Versions
langchainhub==0.1.15 chromadb==0.4.24
Relevant log output
ValueError: Expected EmbeddingFunction.__call to have the following signature: odict_keys(['self', 'input']), got odict_keys(['args', 'kwargs'])
Please see https://docs.trychroma.com/embeddings for details of the EmbeddingFunction interface.
Please note the recent change to the EmbeddingFunction interface: https://docs.trychroma.com/migration#migration-to-0416---november-7-2023
This should be fixed in our next release this coming monday - we now wrap the EF langchain gives us.
This PR needs to land - https://github.com/chroma-core/chroma/pull/1880
@srnsrn120, can you test your use case with the latest main branch and let us know if the new LC wrapper works for you?