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PII

Node PostProcessor module.

PIINodePostprocessor #

Bases: BaseNodePostprocessor

PII Node processor.

NOTE: this is a beta feature, the API might change.

Parameters:

Name Type Description Default
llm LLM

The local LLM to use for prediction.

 required
Source code in llama-index-core/llama_index/core/postprocessor/pii.py 
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class PIINodePostprocessor(BaseNodePostprocessor):
    """PII Node processor.

    NOTE: this is a beta feature, the API might change.

    Args:
        llm (LLM): The local LLM to use for prediction.

    """

    llm: LLM
    pii_str_tmpl: str = DEFAULT_PII_TMPL
    pii_node_info_key: str = "__pii_node_info__"

    @classmethod
    def class_name(cls) -> str:
        return "PIINodePostprocessor"

    def mask_pii(self, text: str) -> Tuple[str, Dict]:
        """Mask PII in text."""
        pii_prompt = PromptTemplate(self.pii_str_tmpl)
        # TODO: allow customization
        task_str = (
            "Mask out the PII, replace each PII with a tag, and return the text. "
            "Return the mapping in JSON."
        )

        response = self.llm.predict(pii_prompt, context_str=text, query_str=task_str)
        splits = response.split("Output Mapping:")
        text_output = splits[0].strip()
        json_str_output = splits[1].strip()
        json_dict = json.loads(json_str_output)
        return text_output, json_dict

    def _postprocess_nodes(
        self,
        nodes: List[NodeWithScore],
        query_bundle: Optional[QueryBundle] = None,
    ) -> List[NodeWithScore]:
        """Postprocess nodes."""
        # swap out text from nodes, with the original node mappings
        new_nodes = []
        for node_with_score in nodes:
            node = node_with_score.node
            new_text, mapping_info = self.mask_pii(
                node.get_content(metadata_mode=MetadataMode.LLM)
            )
            new_node = deepcopy(node)
            new_node.excluded_embed_metadata_keys.append(self.pii_node_info_key)
            new_node.excluded_llm_metadata_keys.append(self.pii_node_info_key)
            new_node.metadata[self.pii_node_info_key] = mapping_info
            new_node.set_content(new_text)
            new_nodes.append(NodeWithScore(node=new_node, score=node_with_score.score))

        return new_nodes

mask_pii #

mask_pii(text: str) -> Tuple[str, Dict]

Mask PII in text.

Source code in llama-index-core/llama_index/core/postprocessor/pii.py 
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def mask_pii(self, text: str) -> Tuple[str, Dict]:
    """Mask PII in text."""
    pii_prompt = PromptTemplate(self.pii_str_tmpl)
    # TODO: allow customization
    task_str = (
        "Mask out the PII, replace each PII with a tag, and return the text. "
        "Return the mapping in JSON."
    )

    response = self.llm.predict(pii_prompt, context_str=text, query_str=task_str)
    splits = response.split("Output Mapping:")
    text_output = splits[0].strip()
    json_str_output = splits[1].strip()
    json_dict = json.loads(json_str_output)
    return text_output, json_dict

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