formkiq_client.IntelligentDocumentProcessingApi

All URIs are relative to http://localhost

Method	HTTP request	Description
add_document_ai_prompt	POST /documents/{documentId}/ai/prompts/{llmPromptEntityName}	Add document AI result from LLM prompt
add_document_metadata_extraction_result	POST /documents/{documentId}/metadataExtractionResults/{llmPromptEntityName}	Add document's metadata extraction result
get_all_document_metadata_extraction_results	GET /documents/{documentId}/metadataExtractionResults	Get all document's metadata extraction results
get_document_ai_prompt_results	GET /documents/{documentId}/ai/prompts/{llmPromptEntityName}	Get document AI results from LLM prompt
get_document_ai_prompts_results	GET /documents/{documentId}/ai/prompts	Get document AI results from LLM prompts
get_document_data_classification	GET /documents/{documentId}/dataClassification	Get document's data classification
get_document_metadata_extraction_results	GET /documents/{documentId}/metadataExtractionResults/{llmPromptEntityName}	Get document's metadata extraction results
set_document_data_classification	PUT /documents/{documentId}/dataClassification	Set document's data classification

add_document_ai_prompt

AddDocumentAiResponse add_document_ai_prompt(document_id, llm_prompt_entity_name, site_id=site_id, artifact_id=artifact_id, add_document_ai_prompt_request=add_document_ai_prompt_request)

Add document AI result from LLM prompt

Run an LLM prompt against a document; available as an Add-On Module

Example

import formkiq_client
from formkiq_client.models.add_document_ai_prompt_request import AddDocumentAiPromptRequest
from formkiq_client.models.add_document_ai_response import AddDocumentAiResponse
from formkiq_client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost
# See configuration.py for a list of all supported configuration parameters.
configuration = formkiq_client.Configuration(
    host = "http://localhost"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Enter a context with an instance of the API client
with formkiq_client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = formkiq_client.IntelligentDocumentProcessingApi(api_client)
    document_id = 'document_id_example' # str | Document Identifier
    llm_prompt_entity_name = 'llm_prompt_entity_name_example' # str | LlmPrompt Entity Name
    site_id = 'site_id_example' # str | Site Identifier (optional)
    artifact_id = 'artifact_id_example' # str | Artifact Document Identifier (optional)
    add_document_ai_prompt_request = formkiq_client.AddDocumentAiPromptRequest() # AddDocumentAiPromptRequest |  (optional)

    try:
        # Add document AI result from LLM prompt
        api_response = api_instance.add_document_ai_prompt(document_id, llm_prompt_entity_name, site_id=site_id, artifact_id=artifact_id, add_document_ai_prompt_request=add_document_ai_prompt_request)
        print("The response of IntelligentDocumentProcessingApi->add_document_ai_prompt:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling IntelligentDocumentProcessingApi->add_document_ai_prompt: %s\n" % e)

Parameters

Name	Type	Description	Notes
document_id	str	Document Identifier
llm_prompt_entity_name	str	LlmPrompt Entity Name
site_id	str	Site Identifier	[optional]
artifact_id	str	Artifact Document Identifier	[optional]
add_document_ai_prompt_request	AddDocumentAiPromptRequest		[optional]

Return type

AddDocumentAiResponse

Authorization

No authorization required

HTTP request headers

Content-Type: application/json
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	200 OK	* Access-Control-Allow-Origin - * Access-Control-Allow-Methods - * Access-Control-Allow-Headers -

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add_document_metadata_extraction_result

AddDocumentMetadataExtractionResponse add_document_metadata_extraction_result(document_id, llm_prompt_entity_name, site_id=site_id, artifact_id=artifact_id)

Add document's metadata extraction result

Create a document Metadatq Extraction Result attributes within a document; available as an Add-On Module. Deprecated. This endpoint is no longer recommended. Please use /documents/{documentId}/ai/prompts/{llmPromptEntityName} instead.

Example

import formkiq_client
from formkiq_client.models.add_document_metadata_extraction_response import AddDocumentMetadataExtractionResponse
from formkiq_client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost
# See configuration.py for a list of all supported configuration parameters.
configuration = formkiq_client.Configuration(
    host = "http://localhost"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Enter a context with an instance of the API client
with formkiq_client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = formkiq_client.IntelligentDocumentProcessingApi(api_client)
    document_id = 'document_id_example' # str | Document Identifier
    llm_prompt_entity_name = 'llm_prompt_entity_name_example' # str | LlmPrompt Entity Name
    site_id = 'site_id_example' # str | Site Identifier (optional)
    artifact_id = 'artifact_id_example' # str | Artifact Document Identifier (optional)

    try:
        # Add document's metadata extraction result
        api_response = api_instance.add_document_metadata_extraction_result(document_id, llm_prompt_entity_name, site_id=site_id, artifact_id=artifact_id)
        print("The response of IntelligentDocumentProcessingApi->add_document_metadata_extraction_result:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling IntelligentDocumentProcessingApi->add_document_metadata_extraction_result: %s\n" % e)

Parameters

Name	Type	Description	Notes
document_id	str	Document Identifier
llm_prompt_entity_name	str	LlmPrompt Entity Name
site_id	str	Site Identifier	[optional]
artifact_id	str	Artifact Document Identifier	[optional]

Return type

AddDocumentMetadataExtractionResponse

Authorization

No authorization required

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	200 OK	* Access-Control-Allow-Origin - * Access-Control-Allow-Methods - * Access-Control-Allow-Headers -

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get_all_document_metadata_extraction_results

GetDocumentMetadataExtractionResponse get_all_document_metadata_extraction_results(document_id, site_id=site_id, artifact_id=artifact_id, limit=limit, next=next)

Get all document's metadata extraction results

Retrieve all document's metadata extraction; available as an Add-On Module. Deprecated. This endpoint is no longer recommended. Please use /documents/{documentId}/ai/prompts/{llmPromptEntityName} instead.

Example

import formkiq_client
from formkiq_client.models.get_document_metadata_extraction_response import GetDocumentMetadataExtractionResponse
from formkiq_client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost
# See configuration.py for a list of all supported configuration parameters.
configuration = formkiq_client.Configuration(
    host = "http://localhost"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Enter a context with an instance of the API client
with formkiq_client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = formkiq_client.IntelligentDocumentProcessingApi(api_client)
    document_id = 'document_id_example' # str | Document Identifier
    site_id = 'site_id_example' # str | Site Identifier (optional)
    artifact_id = 'artifact_id_example' # str | Artifact Document Identifier (optional)
    limit = '10' # str | Limit Results (optional) (default to '10')
    next = 'next_example' # str | Next page of results token (optional)

    try:
        # Get all document's metadata extraction results
        api_response = api_instance.get_all_document_metadata_extraction_results(document_id, site_id=site_id, artifact_id=artifact_id, limit=limit, next=next)
        print("The response of IntelligentDocumentProcessingApi->get_all_document_metadata_extraction_results:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling IntelligentDocumentProcessingApi->get_all_document_metadata_extraction_results: %s\n" % e)

Parameters

Name	Type	Description	Notes
document_id	str	Document Identifier
site_id	str	Site Identifier	[optional]
artifact_id	str	Artifact Document Identifier	[optional]
limit	str	Limit Results	[optional] [default to '10']
next	str	Next page of results token	[optional]

Return type

GetDocumentMetadataExtractionResponse

Authorization

No authorization required

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	200 OK	* Access-Control-Allow-Origin - * Access-Control-Allow-Methods - * Access-Control-Allow-Headers -

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get_document_ai_prompt_results

GetDocumentAiPromptResultsResponse get_document_ai_prompt_results(document_id, llm_prompt_entity_name, site_id=site_id, artifact_id=artifact_id, analysis_category=analysis_category, limit=limit, next=next)

Get document AI results from LLM prompt

Retrieve document AI results from an LLM prompt; available as an Add-On Module

Example

import formkiq_client
from formkiq_client.models.get_document_ai_prompt_results_response import GetDocumentAiPromptResultsResponse
from formkiq_client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost
# See configuration.py for a list of all supported configuration parameters.
configuration = formkiq_client.Configuration(
    host = "http://localhost"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Enter a context with an instance of the API client
with formkiq_client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = formkiq_client.IntelligentDocumentProcessingApi(api_client)
    document_id = 'document_id_example' # str | Document Identifier
    llm_prompt_entity_name = 'llm_prompt_entity_name_example' # str | LlmPrompt Entity Name
    site_id = 'site_id_example' # str | Site Identifier (optional)
    artifact_id = 'artifact_id_example' # str | Artifact Document Identifier (optional)
    analysis_category = 'analysis_category_example' # str | Analysis Category (optional)
    limit = '10' # str | Limit Results (optional) (default to '10')
    next = 'next_example' # str | Next page of results token (optional)

    try:
        # Get document AI results from LLM prompt
        api_response = api_instance.get_document_ai_prompt_results(document_id, llm_prompt_entity_name, site_id=site_id, artifact_id=artifact_id, analysis_category=analysis_category, limit=limit, next=next)
        print("The response of IntelligentDocumentProcessingApi->get_document_ai_prompt_results:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling IntelligentDocumentProcessingApi->get_document_ai_prompt_results: %s\n" % e)

Parameters

Name	Type	Description	Notes
document_id	str	Document Identifier
llm_prompt_entity_name	str	LlmPrompt Entity Name
site_id	str	Site Identifier	[optional]
artifact_id	str	Artifact Document Identifier	[optional]
analysis_category	str	Analysis Category	[optional]
limit	str	Limit Results	[optional] [default to '10']
next	str	Next page of results token	[optional]

Return type

GetDocumentAiPromptResultsResponse

Authorization

No authorization required

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	200 OK	* Access-Control-Allow-Origin - * Access-Control-Allow-Methods - * Access-Control-Allow-Headers -

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get_document_ai_prompts_results

GetDocumentAiPromptsResultsResponse get_document_ai_prompts_results(document_id, site_id=site_id, artifact_id=artifact_id, analysis_category=analysis_category, limit=limit, next=next)

Get document AI results from LLM prompts

Retrieve document AI results from LLM prompts; available as an Add-On Module

Example

import formkiq_client
from formkiq_client.models.get_document_ai_prompts_results_response import GetDocumentAiPromptsResultsResponse
from formkiq_client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost
# See configuration.py for a list of all supported configuration parameters.
configuration = formkiq_client.Configuration(
    host = "http://localhost"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Enter a context with an instance of the API client
with formkiq_client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = formkiq_client.IntelligentDocumentProcessingApi(api_client)
    document_id = 'document_id_example' # str | Document Identifier
    site_id = 'site_id_example' # str | Site Identifier (optional)
    artifact_id = 'artifact_id_example' # str | Artifact Document Identifier (optional)
    analysis_category = 'analysis_category_example' # str | Analysis Category (optional)
    limit = '10' # str | Limit Results (optional) (default to '10')
    next = 'next_example' # str | Next page of results token (optional)

    try:
        # Get document AI results from LLM prompts
        api_response = api_instance.get_document_ai_prompts_results(document_id, site_id=site_id, artifact_id=artifact_id, analysis_category=analysis_category, limit=limit, next=next)
        print("The response of IntelligentDocumentProcessingApi->get_document_ai_prompts_results:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling IntelligentDocumentProcessingApi->get_document_ai_prompts_results: %s\n" % e)

Parameters

Name	Type	Description	Notes
document_id	str	Document Identifier
site_id	str	Site Identifier	[optional]
artifact_id	str	Artifact Document Identifier	[optional]
analysis_category	str	Analysis Category	[optional]
limit	str	Limit Results	[optional] [default to '10']
next	str	Next page of results token	[optional]

Return type

GetDocumentAiPromptsResultsResponse

Authorization

No authorization required

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	200 OK	* Access-Control-Allow-Origin - * Access-Control-Allow-Methods - * Access-Control-Allow-Headers -

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get_document_data_classification

GetDocumentDataClassificationResponse get_document_data_classification(document_id, site_id=site_id, artifact_id=artifact_id, limit=limit, next=next)

Get document's data classification

Retrieve an document's data classification; available as an Add-On Module. Deprecated. This endpoint is no longer recommended. Please use /documents/{documentId}/ai/prompts/{llmPromptEntityName} instead.

Example

import formkiq_client
from formkiq_client.models.get_document_data_classification_response import GetDocumentDataClassificationResponse
from formkiq_client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost
# See configuration.py for a list of all supported configuration parameters.
configuration = formkiq_client.Configuration(
    host = "http://localhost"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Enter a context with an instance of the API client
with formkiq_client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = formkiq_client.IntelligentDocumentProcessingApi(api_client)
    document_id = 'document_id_example' # str | Document Identifier
    site_id = 'site_id_example' # str | Site Identifier (optional)
    artifact_id = 'artifact_id_example' # str | Artifact Document Identifier (optional)
    limit = '10' # str | Limit Results (optional) (default to '10')
    next = 'next_example' # str | Next page of results token (optional)

    try:
        # Get document's data classification
        api_response = api_instance.get_document_data_classification(document_id, site_id=site_id, artifact_id=artifact_id, limit=limit, next=next)
        print("The response of IntelligentDocumentProcessingApi->get_document_data_classification:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling IntelligentDocumentProcessingApi->get_document_data_classification: %s\n" % e)

Parameters

Name	Type	Description	Notes
document_id	str	Document Identifier
site_id	str	Site Identifier	[optional]
artifact_id	str	Artifact Document Identifier	[optional]
limit	str	Limit Results	[optional] [default to '10']
next	str	Next page of results token	[optional]

Return type

GetDocumentDataClassificationResponse

Authorization

No authorization required

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	200 OK	* Access-Control-Allow-Origin - * Access-Control-Allow-Methods - * Access-Control-Allow-Headers -

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get_document_metadata_extraction_results

GetDocumentMetadataExtractionResponse get_document_metadata_extraction_results(document_id, llm_prompt_entity_name, site_id=site_id, artifact_id=artifact_id, limit=limit, next=next)

Get document's metadata extraction results

Retrieve an document's metadata extraction; available as an Add-On Module. Deprecated. This endpoint is no longer recommended. Please use /documents/{documentId}/ai/prompts/{llmPromptEntityName} instead.

Example

import formkiq_client
from formkiq_client.models.get_document_metadata_extraction_response import GetDocumentMetadataExtractionResponse
from formkiq_client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost
# See configuration.py for a list of all supported configuration parameters.
configuration = formkiq_client.Configuration(
    host = "http://localhost"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Enter a context with an instance of the API client
with formkiq_client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = formkiq_client.IntelligentDocumentProcessingApi(api_client)
    document_id = 'document_id_example' # str | Document Identifier
    llm_prompt_entity_name = 'llm_prompt_entity_name_example' # str | LlmPrompt Entity Name
    site_id = 'site_id_example' # str | Site Identifier (optional)
    artifact_id = 'artifact_id_example' # str | Artifact Document Identifier (optional)
    limit = '10' # str | Limit Results (optional) (default to '10')
    next = 'next_example' # str | Next page of results token (optional)

    try:
        # Get document's metadata extraction results
        api_response = api_instance.get_document_metadata_extraction_results(document_id, llm_prompt_entity_name, site_id=site_id, artifact_id=artifact_id, limit=limit, next=next)
        print("The response of IntelligentDocumentProcessingApi->get_document_metadata_extraction_results:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling IntelligentDocumentProcessingApi->get_document_metadata_extraction_results: %s\n" % e)

Parameters

Name	Type	Description	Notes
document_id	str	Document Identifier
llm_prompt_entity_name	str	LlmPrompt Entity Name
site_id	str	Site Identifier	[optional]
artifact_id	str	Artifact Document Identifier	[optional]
limit	str	Limit Results	[optional] [default to '10']
next	str	Next page of results token	[optional]

Return type

GetDocumentMetadataExtractionResponse

Authorization

No authorization required

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	200 OK	* Access-Control-Allow-Origin - * Access-Control-Allow-Methods - * Access-Control-Allow-Headers -

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set_document_data_classification

SetDocumentDataClassificationResponse set_document_data_classification(document_id, site_id=site_id, artifact_id=artifact_id, set_document_data_classification_request=set_document_data_classification_request)

Set document's data classification

Generate Data Classfication attributes within a document; available as an Add-On Module. Deprecated. This endpoint is no longer recommended. Please use /documents/{documentId}/ai/prompts/{llmPromptEntityName} instead.

Example

import formkiq_client
from formkiq_client.models.set_document_data_classification_request import SetDocumentDataClassificationRequest
from formkiq_client.models.set_document_data_classification_response import SetDocumentDataClassificationResponse
from formkiq_client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost
# See configuration.py for a list of all supported configuration parameters.
configuration = formkiq_client.Configuration(
    host = "http://localhost"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Enter a context with an instance of the API client
with formkiq_client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = formkiq_client.IntelligentDocumentProcessingApi(api_client)
    document_id = 'document_id_example' # str | Document Identifier
    site_id = 'site_id_example' # str | Site Identifier (optional)
    artifact_id = 'artifact_id_example' # str | Artifact Document Identifier (optional)
    set_document_data_classification_request = formkiq_client.SetDocumentDataClassificationRequest() # SetDocumentDataClassificationRequest |  (optional)

    try:
        # Set document's data classification
        api_response = api_instance.set_document_data_classification(document_id, site_id=site_id, artifact_id=artifact_id, set_document_data_classification_request=set_document_data_classification_request)
        print("The response of IntelligentDocumentProcessingApi->set_document_data_classification:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling IntelligentDocumentProcessingApi->set_document_data_classification: %s\n" % e)

Parameters

Name	Type	Description	Notes
document_id	str	Document Identifier
site_id	str	Site Identifier	[optional]
artifact_id	str	Artifact Document Identifier	[optional]
set_document_data_classification_request	SetDocumentDataClassificationRequest		[optional]

Return type

SetDocumentDataClassificationResponse

Authorization

No authorization required

HTTP request headers

Content-Type: application/json
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	200 OK	* Access-Control-Allow-Origin - * Access-Control-Allow-Methods - * Access-Control-Allow-Headers -

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formkiq_client.IntelligentDocumentProcessingApi

add_document_ai_prompt

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details

add_document_metadata_extraction_result

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details

get_all_document_metadata_extraction_results

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details

get_document_ai_prompt_results

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details

get_document_ai_prompts_results

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details

get_document_data_classification

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details

get_document_metadata_extraction_results

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details

set_document_data_classification

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details