AttributeError: 'NVIDIAEmbeddings' object has no attribute 'truncate'

[gnanaprakash-ravi]

Hi,
I am working on 5_mins_rag_no_gpu.
Facing this error: AttributeError: 'NVIDIAEmbeddings' object has no attribute 'truncate'
on this version: langchain-nvidia-ai-endpoints==0.1.2

Detailed error:

File "C:\Users\inrgna00\OneDrive - Ingram Micro\From Downloads\RAG\mistral.py", line 183, in <module>
    docs = retriever.get_relevant_documents(user_input)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\inrgna00\AppData\Local\miniconda3\envs\rag\Lib\site-packages\langchain_core\_api\deprecation.py", line 148, in warning_emitting_wrapper
    return wrapped(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\inrgna00\AppData\Local\miniconda3\envs\rag\Lib\site-packages\langchain_core\retrievers.py", line 323, in get_relevant_documents
    raise e
  File "C:\Users\inrgna00\AppData\Local\miniconda3\envs\rag\Lib\site-packages\langchain_core\retrievers.py", line 316, in get_relevant_documents
    result = self._get_relevant_documents(
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\inrgna00\AppData\Local\miniconda3\envs\rag\Lib\site-packages\langchain_core\vectorstores.py", line 696, in _get_relevant_documents
    docs = self.vectorstore.similarity_search(query, **self.search_kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\inrgna00\AppData\Local\miniconda3\envs\rag\Lib\site-packages\langchain_community\vectorstores\faiss.py", line 530, in similarity_search
    docs_and_scores = self.similarity_search_with_score(
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\inrgna00\AppData\Local\miniconda3\envs\rag\Lib\site-packages\langchain_community\vectorstores\faiss.py", line 402, in similarity_search_with_score
    embedding = self._embed_query(query)
                ^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\inrgna00\AppData\Local\miniconda3\envs\rag\Lib\site-packages\langchain_community\vectorstores\faiss.py", line 154, in _embed_query
    return self.embedding_function.embed_query(text)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\inrgna00\AppData\Local\miniconda3\envs\rag\Lib\site-packages\langchain_nvidia_ai_endpoints\embeddings.py", line 156, in embed_query
    return self._embed([text], model_type=self.model_type or "query")[0]
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\inrgna00\AppData\Local\miniconda3\envs\rag\Lib\site-packages\langchain_nvidia_ai_endpoints\embeddings.py", line 139, in _embed
    if self.truncate:
       ^^^^^^^^^^^^^
AttributeError: 'NVIDIAEmbeddings' object has no attribute 'truncate'

I have tried the version: langchain-nvidia-ai-endpoints==0.0.19
I had this error:

File "C:\Users\inrgna00\AppData\Local\miniconda3\envs\rag\Lib\site-packages\langchain_core\retrievers.py", line 316, in get_relevant_documents
    result = self._get_relevant_documents(
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\inrgna00\AppData\Local\miniconda3\envs\rag\Lib\site-packages\langchain_core\vectorstores.py", line 696, in _get_relevant_documents
    docs = self.vectorstore.similarity_search(query, **self.search_kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\inrgna00\AppData\Local\miniconda3\envs\rag\Lib\site-packages\langchain_community\vectorstores\faiss.py", line 530, in similarity_search
    docs_and_scores = self.similarity_search_with_score(
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\inrgna00\AppData\Local\miniconda3\envs\rag\Lib\site-packages\langchain_community\vectorstores\faiss.py", line 402, in similarity_search_with_score
    embedding = self._embed_query(query)
                ^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\inrgna00\AppData\Local\miniconda3\envs\rag\Lib\site-packages\langchain_community\vectorstores\faiss.py", line 154, in _embed_query
    return self.embedding_function.embed_query(text)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\inrgna00\AppData\Local\miniconda3\envs\rag\Lib\site-packages\langchain_nvidia_ai_endpoints\embeddings.py", line 125, in embed_query
    return self._embed([text], model_type=self.model_type or "query")[0]
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\inrgna00\AppData\Local\miniconda3\envs\rag\Lib\site-packages\langchain_nvidia_ai_endpoints\embeddings.py", line 102, in _embed
    "model": self.get_binding_model() or self.model,
             ^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\inrgna00\AppData\Local\miniconda3\envs\rag\Lib\site-packages\langchain_core\_api\deprecation.py", line 148, in warning_emitting_wrapper
    return wrapped(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\inrgna00\AppData\Local\miniconda3\envs\rag\Lib\site-packages\langchain_nvidia_ai_endpoints\_common.py", line 690, in get_binding_model
    matches = [model for model in self.available_models if model.id == self.model]
                                  ^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\inrgna00\AppData\Local\miniconda3\envs\rag\Lib\site-packages\langchain_nvidia_ai_endpoints\_common.py", line 620, in available_models
    if self.curr_mode == "nim" or not self.is_hosted:
       ^^^^^^^^^^^^^^
AttributeError: 'NVIDIAEmbeddings' object has no attribute 'curr_mode'

[gnanaprakash-ravi]

I have tried with .invoke method from the retriever as well.

File "C:\Users\inrgna00\OneDrive - Ingram Micro\From Downloads\RAG\1mistral.py", line 143, in <module>
    docs = retriever.invoke(user_input)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\inrgna00\AppData\Local\miniconda3\envs\rag\Lib\site-packages\langchain_core\retrievers.py", line 194, in invoke
    return self.get_relevant_documents(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\inrgna00\AppData\Local\miniconda3\envs\rag\Lib\site-packages\langchain_core\_api\deprecation.py", line 148, in warning_emitting_wrapper
    return wrapped(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\inrgna00\AppData\Local\miniconda3\envs\rag\Lib\site-packages\langchain_core\retrievers.py", line 323, in get_relevant_documents
    raise e
  File "C:\Users\inrgna00\AppData\Local\miniconda3\envs\rag\Lib\site-packages\langchain_core\retrievers.py", line 316, in get_relevant_documents
    result = self._get_relevant_documents(
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\inrgna00\AppData\Local\miniconda3\envs\rag\Lib\site-packages\langchain_core\vectorstores.py", line 696, in _get_relevant_documents
    docs = self.vectorstore.similarity_search(query, **self.search_kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\inrgna00\AppData\Local\miniconda3\envs\rag\Lib\site-packages\langchain_community\vectorstores\faiss.py", line 530, in similarity_search
    docs_and_scores = self.similarity_search_with_score(
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\inrgna00\AppData\Local\miniconda3\envs\rag\Lib\site-packages\langchain_community\vectorstores\faiss.py", line 402, in similarity_search_with_score
    embedding = self._embed_query(query)
                ^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\inrgna00\AppData\Local\miniconda3\envs\rag\Lib\site-packages\langchain_community\vectorstores\faiss.py", line 154, in _embed_query
    return self.embedding_function.embed_query(text)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\inrgna00\AppData\Local\miniconda3\envs\rag\Lib\site-packages\langchain_nvidia_ai_endpoints\embeddings.py", line 156, in embed_query
    return self._embed([text], model_type=self.model_type or "query")[0]
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\inrgna00\AppData\Local\miniconda3\envs\rag\Lib\site-packages\langchain_nvidia_ai_endpoints\embeddings.py", line 139, in _embed
    if self.truncate:
       ^^^^^^^^^^^^^
AttributeError: 'NVIDIAEmbeddings' object has no attribute 'truncate'

[mattf]

@gnanaprakash-ravi does your code work with v0.2.1?