Document classifier node

Use the document classifier node to classify your documents.

Pre-requisites

Run the following command to enable watsonx Orchestrate Developer Edition to process documents:

BASH

orchestrate server start -e <.env file path> -d

Note: You need to configure a minimum allocation of 20GB RAM to your Docker engine during installation of watsonx Orchestrate Developer edition to support document processing features.

Note: To run the document classifier, you must define the WO_INSTANCE, WO_API_KEY, and AUTHORIZATION_URL credentials in your .env file. For more information on configuring the .env file, see Installing the watsonx Orchestrate Developer Edition.

Configuring document extractor node in agentic workflows

Define document classes. Create a class that defines the document classes to classify. Each document class must follow this structure:

Python

class CustomClasses(BaseModel):
"""
Configuration schema for document classification classes.

Defines the document types/classes that the classifier can identify.
Each class is configured with a DocClassifierClass that specifies the
class name used for categorizing input documents. The classifier uses
an LLM to analyze documents and assign them to one of these classes.

Example custom classes:
    invoice: Configuration for identifying invoice documents
    contract: Configuration for identifying contract documents
    tax_form: Configuration for identifying tax form documents
    bill_of_lading: Configuration for identifying bill of lading documents
"""
invoice: DocClassifierClass = Field(default=DocClassifierClass(class_name="Invoice"))
contract: DocClassifierClass = Field(default=DocClassifierClass(class_name="Contract"))
tax_form: DocClassifierClass = Field(default=DocClassifierClass(class_name="TaxForm"))
bill_of_lading: DocClassifierClass = Field(default=DocClassifierClass(class_name="BillOfLading"))

Configure the document classifier node

Include a call to the docclassifier() method in your agentic workflow to classify the document. This method accepts the following input arguments:

Parameter	Type	Required	Description
name	string	Yes	Unique identifier for the node.
llm	string	Yes	The LLM used for document classification. The default value is `groq/openai/gpt-oss-120b`.
display_name	string	No	Display name for the node.
classes	object	Yes	The document classification classes.
description	string	No	Description of the node.
min_confidence	float	No	Minimum confidence threshold for classification.
input_map	DataMap	No	Define input mappings using a structured collection of Assignment objects.
enable_review	bool	No	Enables or disables the human-in-the-loop feature. Set to `True` to activate it and `False` to deactivate. The default value is `False`.

Note:The min_confidence setting controls the human-in-the-loop feature. This feature only works when you run the Flow from a chat session. If the document is classified with confidence lower than min_confidence, or as Other, the agent opens a review window in the chat. You can then review and confirm the extracted values.

Example use of the docext node in a agentic workflow:

Python

from pydoc import Doc
from pydantic import BaseModel, Field
from ibm_watsonx_orchestrate.flow_builder.flows import (
    Flow, flow, START, END
)
from ibm_watsonx_orchestrate.flow_builder.types import DocClassifierClass, DocumentProcessingCommonInput, DocumentClassificationResponse


class CustomClasses(BaseModel):
    """
    Configuration schema for document classification classes.
    
    Defines the document types/classes that the classifier can identify.
    Each class is configured with a DocClassifierClass that specifies the
    class name used for categorizing input documents. The classifier uses
    an LLM to analyze documents and assign them to one of these classes.
    
    Example custom classes:
        invoice: Configuration for identifying invoice documents
        contract: Configuration for identifying contract documents
        tax_form: Configuration for identifying tax form documents
        bill_of_lading: Configuration for identifying bill of lading documents
    """
    invoice: DocClassifierClass = Field(default=DocClassifierClass(class_name="Invoice"))
    contract: DocClassifierClass = Field(default=DocClassifierClass(class_name="Contract"))
    tax_form: DocClassifierClass = Field(default=DocClassifierClass(class_name="TaxForm"))
    bill_of_lading: DocClassifierClass = Field(default=DocClassifierClass(class_name="BillOfLading"))


@flow(
    name ="custom_flow_docclassifier_example",
    display_name="custom_flow_docclassifier_example",
    description="Classifies documents into custom classes.",
    input_schema=DocumentProcessingCommonInput
)
def build_docclassifier_flow(aflow: Flow = None) -> Flow:
    # aflow.docclassifier returns a DocClassifierNode object.
    # The output schema of a DocClassifierNode is a DocumentClassifierResponse object.

    doc_classifier_node = aflow.docclassifier(
        name="document_classifier_node",
        display_name="document_classifier_node",
        description="Classifies documents into one custom class.",
        llm="groq/openai/gpt-oss-120b",
        classes=CustomClasses(),
    )

    aflow.sequence(START, doc_classifier_node, END)

    return aflow

Release Notes

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Pre-requisites

Configuring document extractor node in agentic workflows

​Pre-requisites

​Configuring document extractor node in agentic workflows

Pre-requisites

Configuring document extractor node in agentic workflows