Use LlamaIndex and GPT-3 to query customer insights

query_customer_feedback.py

import os
import logging
import sys
import textwrap

from llama_index import (
    GPTKeywordTableIndex,
    SimpleDirectoryReader,
    LLMPredictor,
)
from langchain import OpenAI


if __name__ == "__main__":
    logging.basicConfig(stream=sys.stdout, level=logging.CRITICAL)
    logging.getLogger().addHandler(logging.StreamHandler(stream=sys.stdout))

    if not os.path.exists("index.json"):
        documents = SimpleDirectoryReader("docs").load_data()
        llm_predictor = LLMPredictor(
            llm=OpenAI(temperature=0,
                       model_name="text-davinci-003",
                       max_tokens=2048)
        )
        index = GPTKeywordTableIndex(documents, llm_predictor=llm_predictor)
        index.save_to_disk("index.json")
    else:
        index = GPTKeywordTableIndex.load_from_disk("index.json")

    while True:
        try:
            prompt = input("What should I figure out? ")
            response = index.query(prompt)
            response = str(response).strip()
            if not response:
                continue
            for line in textwrap.wrap(response, width=75):
                print(line)
            print("-----")
        except KeyboardInterrupt:
            break