Callback error in Llama Index RAG pipeline integration for Node post processors

[nashugame]

Describe the bug
Hi, I have followed the tutorial for Llama Index RAG implementation for llm-guard (ref: https://llm-guard.com/tutorials/notebooks/llama_index_rag/). I am getting callback error (NoneType object has no attribute "callback manager"). I am using latest Llama Index package where I have passed callback manager at vector index creation rather than service context (which is getting depreciated in future).
To Reproduce
Steps to reproduce the behavior:

1. All steps are same except I am not initializing service context and passing callback manager instead I am passing it at vector index creation stage.
   
2. Here self._llamaindex_settings contains initialized callback_manager.
   
3. Rest part of code I have kept the same, created the LLMGuardNodePostProcessor as per tutorial and fed it to query engine.
   For ref:

import logging
from typing import List, Optional
 
from llama_index.core.bridge.pydantic import Field
from llama_index.core.postprocessor.types import BaseNodePostprocessor
from llama_index.core.schema import MetadataMode, NodeWithScore, QueryBundle
from llama_index.core.callbacks import CallbackManager, LlamaDebugHandler
llama_debug = LlamaDebugHandler(print_trace_on_end=True)
 
 
 
class LLMGuardNodePostProcessor(BaseNodePostprocessor):
   
    scanners: List = Field(description="Scanner objects")
    fail_fast: bool = Field(
        description="If True, the postprocessor will stop after the first scanner failure.",
    )
    skip_scanners: List[str] = Field(
        description="List of scanner names to skip when failed e.g. Anonymize.",
    )
 
    def __init__(
        self,
        scanners: List,
        fail_fast: bool = True,
        skip_scanners: List[str] = None,
    ) -> None:
        if skip_scanners is None:
            skip_scanners = []
 
        try:
            import llm_guard  # noqa: F401
        except ImportError:
            raise ImportError(
                "Cannot import llm_guard package, please install it: ",
                "pip install llm-guard",
            )
 
        super().__init__(
            scanners=scanners,
            fail_fast=fail_fast,
            skip_scanners=skip_scanners,
        )
 
    @classmethod
    def class_name(cls) -> str:
        return "LLMGuardNodePostProcessor"
 
    def _postprocess_nodes(
        self,
        nodes: List[NodeWithScore],
        query_bundle: Optional[QueryBundle] = None,
    ) -> List[NodeWithScore]:
        from llm_guard import scan_prompt
 
        safe_nodes = []
        for node_with_score in nodes:
            node = node_with_score.node
 
            sanitized_text, results_valid, results_score = scan_prompt(
                self.scanners,
                node.get_content(metadata_mode=MetadataMode.LLM),
                self.fail_fast,
            )
 
            for scanner_name in self.skip_scanners:
                results_valid[scanner_name] = True
 
            if any(not result for result in results_valid.values()):
                logger.warning(f"Node `{node.node_id}` is not valid, scores: {results_score}")
 
                continue
 
            node.set_content(sanitized_text)
            safe_nodes.append(NodeWithScore(node=node, score=node_with_score.score))
 
        return safe_nodes

For query engine:

      query_engine = self.documents.index.as_query_engine(
        similarity_top_k= similarity_top_k,
        response_synthesizer= response_synthesizer,
        llm=llamaindex_settings['llm'],
        node_postprocessors=[llm_guard_postprocessor]
      )

Screen Shot of Error Message

Can you pls help with issue pointed above.

[asofter]

Hey @nashugame , I updated the notebook and removed the usage of ServiceContext.