Open In Colab

Make Reader#

We show how LlamaIndex can fit with your workflow by sending the GPT Index response to a scenario webhook.

If you’re opening this Notebook on colab, you will probably need to install LlamaIndex 🦙.

%pip install llama-index-readers-make-com
!pip install llama-index
import logging
import sys

logging.basicConfig(stream=sys.stdout, level=logging.INFO)
from llama_index.core import VectorStoreIndex, SimpleDirectoryReader
from llama_index.readers.make_com import MakeWrapper

Download Data

!mkdir -p 'data/paul_graham/'
!wget '' -O 'data/paul_graham/paul_graham_essay.txt'
documents = SimpleDirectoryReader("./data/paul_graham/").load_data()
index = VectorStoreIndex.from_documents(documents=documents)
# set Logging to DEBUG for more detailed outputs
# query index
query_str = "What did the author do growing up?"
query_engine = index.as_query_engine()
response = query_engine.query(query_str)
# Send response to webhook
wrapper = MakeWrapper()
wrapper.pass_response_to_webhook("<webhook_url>", response, query_str)