制作阅读器

我们展示了如何通过将GPT索引响应发送到场景webhook，使LlamaIndex与您的Make.com工作流程相适配。

如果您在 Colab 上打开这个笔记本，您可能需要安装 LlamaIndex 🦙。

%pip install llama-index-readers-make-com

!pip install llama-index

import logging
import sys

logging.basicConfig(stream=sys.stdout, level=logging.INFO)
logging.getLogger().addHandler(logging.StreamHandler(stream=sys.stdout))

from llama_index.core import VectorStoreIndex, SimpleDirectoryReader
from llama_index.readers.make_com import MakeWrapper

下载数据

!mkdir -p 'data/paul_graham/'
!wget 'https://raw.githubusercontent.com/run-llama/llama_index/main/docs/examples/data/paul_graham/paul_graham_essay.txt' -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 Make.com webhook
wrapper = MakeWrapper()
wrapper.pass_response_to_webhook("<webhook_url>", response, query_str)