while two "NestedDict" data set advance False in a custom component, error happen

[liaochf]

from typing import Optional, Union

from langchain.schema import BaseRetriever, Document
from langflow import CustomComponent
from langchain_community.vectorstores import VectorStore, Milvus
from langchain.embeddings.base import Embeddings
from langflow.field_typing import NestedDict,Embeddings,Document

class MilvusVectorStore(CustomComponent):
    display_name: str = "Milvus"
    description: str = "Implementation of Vector Store using Milvus"
    documentation = "https://python.langchain.com/docs/integrations/vectorstores/milvus"
    beta = True
    field_config = {
        "connection_args": {
            "display_name": "Connection Args", 
            "field_type": "NestedDict",
            "required": True,
            "value": {
                "host": "localhost",
                "port": "19530",
                "user": "",
                "password": ""
            }
        },
        "collection_name": {
            "display_name": "Collection Name",
            "field_type": "str",
            "required": False,
        },
        "documents": {
            "display_name": "Documents", 
            "field_type": "Document",
            "is_list": True
        },
        "embedding_function": {
            "display_name": "Embedding",
            "required": True,
            "field_type": "Embeddings"
        },
        "index_params": {
            "display_name": "Index Parameters",
            "required": False,
            "field_type": "NestedDict",
            "advanced": F,
        },
        "search_params": {
            "display_name": "Search Parameters", 
            "field_type": "NestedDict",
            "advanced": True,
        },
        "text_field":{
            "display_name": "Text Field",
            "field_type": "str",
        },
        "vector_field":{
            "display_name": "Vector Field",
            "field_type": "str",
        },
        "code": {"show": False},
    }

    def build(
        self,
        connection_args: NestedDict,
        collection_name: Optional[str] = None,
        index_params: Optional[NestedDict] = None,
        search_params: Optional[NestedDict] = None,
        embedding_function: Optional[Embeddings] = None,
        documents: Optional[Document] = None
    ) -> Union[VectorStore, BaseRetriever]:
        
        if documents is not None and embedding_function is not None:
            try:
                vector_db = Milvus.from_documents(
                    documents=documents,
                    embedding=embedding_function,
                    connection_args=connection_args,
                    collection_name=collection_name,
                    index_params=index_params,
                    search_params=search_params
                )
            except Exception as e:
                raise ValueError(str(e)) from e
        try:
            vector_db = Milvus(
                connection_args=connection_args,
                collection_name=collection_name,
                embedding_function=embedding_function,
                search_params=search_params,
                index_params=index_params
            )
        except Exception as e:
            raise ValueError(str(e)) from e
        
        return vector_db

[liaochf]

[ogabrielluiz]

Hey @liaochf

Thank you for reporting this.

Hey @Cristhianzl could you take a look at this, please? This is a problem in the stable version.