[Bug]: KnowledgeGraphQueryEngine occurs error when query

[yanyi74]

Bug Description

ValidationError: 1 validation error for LLMPredictStartEvent
template
none is not an allowed value (type=type_error.none.not_allowed)

Version

0.10.37

Steps to Reproduce

Relevant Logs/Tracbacks

No response

[dosubot]

The ValidationError indicating that none is not an allowed value for template suggests that a None value is being passed where it is not permitted. This issue typically arises in scenarios where the KnowledgeGraphQueryEngine or its methods are expecting certain parameters to be provided, and those parameters are either missing or explicitly set to None.

To address this issue, follow these steps:

1. Verify Constructor Arguments: Ensure the KnowledgeGraphQueryEngine is instantiated with all required arguments, especially storage_context, and that storage_context includes a valid graph_store.

2. Check Method Calls: Make sure that the arguments passed to methods like generate_query are not None, unless allowed by the method's documentation.

3. Optional Parameters: If using optional parameters, confirm they are correctly instantiated or handled when set to None.

4. Debugging: Implement logging within the KnowledgeGraphQueryEngine methods to trace the values of parameters at runtime, helping to pinpoint where a None value might be introduced.

5. Review Code for Dynamic Updates: If your implementation involves dynamically updating prompts or similar features, ensure these updates do not result in None values being passed where they are not expected.

By systematically checking these areas, you should be able to identify and correct the cause of the ValidationError. If the issue persists, creating a minimal reproducible example could further help in isolating and addressing the problem.

Details

Sources

• llama-index-core/llama_index/core/query_engine/knowledge_graph_query_engine.py
• llama-index-legacy/llama_index/legacy/query_engine/knowledge_graph_query_engine.py

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[luisenriqueramos1977]

I have a similar issue, here is the code:

import os
import openai
from llama_index.llms.openai import OpenAI
from llama_index.embeddings.openai import OpenAIEmbedding
from llama_index.core.query_engine import KnowledgeGraphQueryEngine
from llama_index.graph_stores.neo4j import Neo4jGraphStore
from llama_index.core import StorageContext

define LLM

from llama_index.core import Settings

#openai api conneting
os.environ["OPENAI_API_KEY"] = "sk-proj-mykey"
openai.api_key = os.environ["OPENAI_API_KEY"]

#llm=OpenAI(model_name="gpt-3.5-turbo")
#service_context = ServiceContext.from_defaults(llm=llm, chunk_size=256)

llm = OpenAI(temperature=0, model="gpt-3.5-turbo")
Settings.llm = llm
Settings.chunk_size = 512

graph_store = Neo4jGraphStore(username="neo4j",password="mypassword",
url="bolt://localhost:7687",database="neo4j")

storage_context = StorageContext.from_defaults(graph_store=graph_store)

query_engine = KnowledgeGraphQueryEngine(
storage_context=storage_context,
llm=Settings.llm,
verbose=True,
)

response = query_engine.query(
"what is the query?",
)

print(response)