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