how to do 'Convert to Intents' for the uploaded FAQ in KnowledgeBase in Dialogflow programmatically

Using the Dialogflow python client library, I am able to create KnowledgeBase and upload a document.

I am looking for a way to be able to do 'Convert to Intents' for the uploaded QA pairs. Did not find anything related in the product documentation.

Has anyone tried something like this?

Thanks Deepak

actually no, you can't convert to intents. The Idea of a knowledge base is that you can use it directly to detect intents:

Here is an snnipet of how to use it (also here):

"""Dialogflow API Detect Knowledge Base Intent Python sample with text inputs.
Examples:
  python detect_intent_knowledge.py -h
  python detect_intent_knowledge.py --project-id PROJECT_ID \
  --session-id SESSION_ID --knowledge-base-id KNOWLEDGE_BASE_ID \
  "hello" "how do I reset my password?"
"""

import argparse
import uuid


# [START dialogflow_detect_intent_knowledge]
def detect_intent_knowledge(
    project_id, session_id, language_code, knowledge_base_id, texts
):
    """Returns the result of detect intent with querying Knowledge Connector.
    Args:
    project_id: The GCP project linked with the agent you are going to query.
    session_id: Id of the session, using the same `session_id` between requests
              allows continuation of the conversation.
    language_code: Language of the queries.
    knowledge_base_id: The Knowledge base's id to query against.
    texts: A list of text queries to send.
    """
    from google.cloud import dialogflow_v2beta1 as dialogflow

    session_client = dialogflow.SessionsClient()

    session_path = session_client.session_path(project_id, session_id)
    print("Session path: {}\n".format(session_path))

    for text in texts:
        text_input = dialogflow.TextInput(text=text, language_code=language_code)

        query_input = dialogflow.QueryInput(text=text_input)

        knowledge_base_path = dialogflow.KnowledgeBasesClient.knowledge_base_path(
            project_id, knowledge_base_id
        )

        query_params = dialogflow.QueryParameters(
            knowledge_base_names=[knowledge_base_path]
        )

        request = dialogflow.DetectIntentRequest(
            session=session_path, query_input=query_input, query_params=query_params
        )
        response = session_client.detect_intent(request=request)

        print("=" * 20)
        print("Query text: {}".format(response.query_result.query_text))
        print(
            "Detected intent: {} (confidence: {})\n".format(
                response.query_result.intent.display_name,
                response.query_result.intent_detection_confidence,
            )
        )
        print("Fulfillment text: {}\n".format(response.query_result.fulfillment_text))
        print("Knowledge results:")
        knowledge_answers = response.query_result.knowledge_answers
        for answers in knowledge_answers.answers:
            print(" - Answer: {}".format(answers.answer))
            print(" - Confidence: {}".format(answers.match_confidence))


# [END dialogflow_detect_intent_knowledge]


if __name__ == "__main__":
    parser = argparse.ArgumentParser(
        description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter
    )
    parser.add_argument(
        "--project-id", help="Project/agent id.  Required.", required=True
    )
    parser.add_argument(
        "--session-id",
        help="ID of the DetectIntent session. " "Defaults to a random UUID.",
        default=str(uuid.uuid4()),
    )
    parser.add_argument(
        "--language-code",
        help='Language code of the query. Defaults to "en-US".',
        default="en-US",
    )
    parser.add_argument(
        "--knowledge-base-id",
        help="The id of the Knowledge Base to query against",
        required=True,
    )
    parser.add_argument("texts", nargs="+", type=str, help="Text inputs.")

    args = parser.parse_args()

    detect_intent_knowledge(
        args.project_id,
        args.session_id,
        args.language_code,
        args.knowledge_base_id,
        args.texts,
    )

Check out this Documentation: Knowledge connectors  |  Dialogflow ES  |  Google Cloud