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Use the document field extractor node to extract specific fields from your documents.
This feature is currently in public preview. Functionality and behavior may change in future updates.

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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 field extractor, you must define the WATSONX_SPACE_ID, WATSONX_APIKEY, and WATSONX_PROJECT_ID credentials in your .env file. For more information on configuring the .env file, see Installing the watsonx Orchestrate Developer Edition.

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Configuring document extractor node in agentic workflows

  1. Define the fields to extract. Create a class that defines the fields you want to extract. Each field must follow this structure:
    Python
    field: DocExtConfigField = Field(name="Field name", default=DocExtConfigField(name="Field name", field_name="field_name"))
    Class example:
    Python
    class Fields(BaseModel):
    """
    Configuration schema for document extraction fields.
    
    Defines the fields to be extracted from contract documents, including
    their names, types, and descriptions. Each field is configured with
    a DocExtConfigField that specifies how the document extractor should
    identify and extract the information.
    
    In this example, we define a number of custom fields for a Contract or 
    Agreement document:
        buyer: The purchasing party in the contract
        seller: The selling party in the contract
        agreement_date: The date when the agreement was signed (date type)
        agreement_number: Unique identifier for the contract
        contract_type: Classification of the contract 
    """
    buyer: DocExtConfigField = Field(
        name="Buyer",
        default=DocExtConfigField(
            name="Buyer",
            field_name="buyer"
        )
    )
  2. Configure the document extract node
In your agentic workflow, include a call to the docext() method to extract an field from a document. This method accepts the following input arguments:
ParameterTypeRequiredDescription
namestringYesUnique identifier for the node.
llmstringYesThe LLM used for field extraction. The default value is watsonx/meta-llama/llama-3-2-90b-vision-instruct.
display_namestringNoDisplay name for the node.
fieldsobjectYesThe fields you want to extract.
descriptionstringNoDescription of the node.
input_mapDataMapNoDefine input mappings using a structured collection of Assignment objects.
enable_hwboolNoEnable the handwritten feature by setting this to true.
min_confidencefloatNoThe minimum acceptable confidence for an extracted field value.
review_fieldsList[string]NoThe fields that require user review.
enable_reviewboolNoEnables 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 and review_fields settings control the human-in-the-loop feature. This feature only works when you run the Flow from a chat session. If a field is extracted with confidence lower than min_confidence, and its name appears in review_fields, the agent opens a review window in the chat. You can then review and confirm the extracted values.
The input to a docext node is expected to be of type DocExtInput, from the module ibm_watsonx_orchestrate.flow_builder.types. Example use of the docext node in a agentic workflow:
Python
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 DocExtConfigField, DocumentProcessingCommonInput


class Fields(BaseModel):
    """
    Configuration schema for document extraction fields.
    
    Defines the fields to be extracted from contract documents, including
    their names, types, and descriptions. Each field is configured with
    a DocExtConfigField that specifies how the document extractor should
    identify and extract the information.
    
    In this example, we define a number of custom fields for a Contract or 
    Agreement document:
        buyer: The purchasing party in the contract
        seller: The selling party in the contract
        agreement_date: The date when the agreement was signed (date type)
        agreement_number: Unique identifier for the contract
        contract_type: Classification of the contract 
    """
    buyer: DocExtConfigField = Field(
        name="Buyer",
        default=DocExtConfigField(
            name="Buyer",
            field_name="buyer"
        )
    )
    
    seller: DocExtConfigField = Field(
        name="Seller",
        default=DocExtConfigField(
            name="Seller",
            field_name="seller"
        )
    )
    
    agreement_date: DocExtConfigField = Field(
        name="Agreement date",
        default=DocExtConfigField(
            name="Agreement Date",
            field_name="agreement_date",
            type="date"
        )
    )
    
    agreement_number: DocExtConfigField = Field(
        name="Agreement number",
        default=DocExtConfigField(
            name="Agreement Number",
            field_name="agreement_number",
            description="The identifier of this contract."
        )
    )
    
    contract_type: DocExtConfigField = Field(
        name="Contract type",
        default=DocExtConfigField(
            name="Contract Type",
            field_name="contract_type",
            type="string",
            description="The type of contract between the buyer and the seller."
        )
    )


@flow(
    name ="custom_flow_docext_example",
    display_name="custom_flow_docext_example",
    description="Extraction of custom fields from a document, specified by the user.",
    input_schema=DocumentProcessingCommonInput
)
def build_docext_flow(aflow: Flow = None) -> Flow:
    # aflow.docext returns 2 objects: the document extractor node and the schema of the extracted values.
    # In this example, doc_ext_node is the node and is added to the flow.
    # _ExtractedValues is the output schema of doc_ext_node and can be used as the input schema of nodes downstream in the flow.

    doc_ext_node, _ExtractedValues = aflow.docext(
        name="contract_extractor",
        display_name="Extract fields from a contract",
        description="Extracts fields from an input contract file",
        llm="watsonx/meta-llama/llama-3-2-90b-vision-instruct",
        fields=Fields()
    )

    aflow.sequence(START, doc_ext_node, END)
    return aflow