Neo4jVector initialising vectorstore problem with params

[rmccorkl]

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Example Code

1) Have the following code in common file 

dotenv_path = Path(__file__).resolve().parents[2] / '.env'
print(f"Loading environment variables from: {dotenv_path}")# Setup the Neo4j connection (replace with actual connection details)

def get_env_variable(var_name):
    """Get an environment variable. Exit with an error message if it's not set."""
    try:
        return os.environ[var_name]
    except KeyError:
        print(f"Environment variable {var_name} is not set. Please set it in the .env file.")
        sys.exit(1)

# graph_conn = Neo4jGraph(uri="bolt://localhost:7687", user="neo4j", pwd="password")
url = get_env_variable("2NEO4J_SCFMAC4_URI")
username = get_env_variable("2NEO4J_USERNAME")
password = get_env_variable("2NEO4J_PASSWORD")
graph = Neo4jGraph(url=url, username=username, password=password)
TOP_K = get_env_variable("TOP_K")
database = "neo4j"
embedding_node_property = "embedding"

# Create a Neo4jVector instance
embeddings = OpenAIEmbeddings(api_key=os.environ["OPENAI_API_KEY"]) 
vectorstore = Neo4jVector(
        embedding=embeddings,
        url=url,
        username=username,
        password=password,
        database=database,
        embedding_node_property=embedding_node_property
    )


2) In the file I utilise the objects 

from src.common.CommonArtifacts import (
    Node, Relationship, 
    debug_print, 
    graph, TOP_K, 
    create_properties_from_row,
    CYPHER_GENERATION_PROMPT,
    vectorstore,
    embeddings,
    load_schema_data,
)

.....

 vector_index=None 
    if os.getenv("VECTOR_INDEX_ENABLED") == "true":
        try:
            vector_index = vectorstore.from_existing_graph(
                embedding=embeddings,
                search_type='hybrid',
                index_name='vector',
                node_label="DomainNode",
                text_node_properties=df.loc[:, 'SCFDomain':'SCFIdentifier'].columns.tolist(),
                embedding_node_property="embedding",
            )
            print(f"Vector Index: {vector_index}")
        except Exception as e:
            print(f"Error occurred: {e}")

Description

@dosubot

I have what seems a scoping issue which I can't fathom I get the following error

Error occurred: Did not find url, please add an environment variable NEO4J_URIwhich contains it, or passurl as a named parameter

I've actual set and pass the url explicitly in the common file to initialise Neo4jVector, hence though I understand the error I don't understand why the url is not being picked up in the calling file using the vectorstore.from_existing_graph

System Info

langchain==0.2.5
langchain-community==0.2.5
langchain-core==0.2.7
langchain-experimental==0.0.61
langchain-google-vertexai==1.0.5
langchain-openai==0.1.8
langchain-pinecone==0.1.1
langchain-text-splitters==0.2.1

[dosubot[bot]]

The error you're encountering suggests that the url parameter is not being picked up correctly when calling vectorstore.from_existing_graph. This could be due to how the url is being passed or retrieved in the Neo4jVector class.

Here are a few steps to troubleshoot and resolve this issue:

1. Ensure Environment Variables are Loaded:
   Make sure that the environment variables are loaded correctly before initializing the Neo4jVector instance. You can use the python-dotenv package to load the environment variables from your .env file.

   from dotenv import load_dotenv
   import os
   
   load_dotenv()  # Load environment variables from .env file

2. Check get_from_dict_or_env Function:
   The url parameter is processed using the get_from_dict_or_env function. Ensure that this function is correctly retrieving the url value from the provided dictionary or environment variables.

   def get_from_dict_or_env(
       data: Dict[str, Any],
       key: Union[str, List[str]],
       env_key: str,
       default: Optional[str] = None,
   ) -> str:
       if isinstance(key, (list, tuple)):
           for k in key:
               if k in data and data[k]:
                   return data[k]
   
       if isinstance(key, str):
           if key in data and data[key]:
               return data[key]
   
       if isinstance(key, (list, tuple)):
           key_for_err = key[0]
       else:
           key_for_err = key
   
       return get_from_env(key_for_err, env_key, default=default)

3. Explicitly Pass the url Parameter:
   When calling vectorstore.from_existing_graph, ensure that the url parameter is explicitly passed and correctly set.

   vector_index = vectorstore.from_existing_graph(
       embedding=embeddings,
       search_type='hybrid',
       index_name='vector',
       node_label="DomainNode",
       text_node_properties=df.loc[:, 'SCFDomain':'SCFIdentifier'].columns.tolist(),
       embedding_node_property="embedding",
       url=url,  # Explicitly pass the url parameter
   )

4. Verify Initialization:
   Ensure that the Neo4jVector instance is initialized correctly with the url parameter.

   vectorstore = Neo4jVector(
       embedding=embeddings,
       url=url,
       username=username,
       password=password,
       database=database,
       embedding_node_property=embedding_node_property
   )

By following these steps, you should be able to resolve the issue of the url parameter not being picked up correctly. If the problem persists, double-check the environment variable names and ensure there are no typos or mismatches.

For more details on how the url parameter is handled, you can refer to the implementation of the Neo4jVector class and the get_from_dict_or_env function ^[1][2].

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