config.py

import os
from flask import Flask, render_template, request, jsonify
from gpt_index import SimpleDirectoryReader, GPTListIndex, readers, GPTSimpleVectorIndex, LLMPredictor, PromptHelper, ServiceContext
from langchain import OpenAI
import asttokens, ast
from IPython.display import Markdown, display
import openai

class Config(object):
    DEBUG = True
    TESTING = False

class DevelopmentConfig(Config):
    SECRET_KEY = "this-is-a-super-secret-key"
    OPENAI_KEY = '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'
os.environ["OPENAI_API_KEY"] = DevelopmentConfig.OPENAI_KEY
config = {
    'development': DevelopmentConfig,
    'testing': DevelopmentConfig,
    'production': DevelopmentConfig
}

def construct_index(directory_path):
    # set maximum input size
    max_input_size = 4096 
    # set number of output tokens
    num_outputs = 2000
    # set maximum chunk overlap
    max_chunk_overlap = 20
    # set chunk size limit
    chunk_size_limit = 600 

    # define prompt helper
    prompt_helper = PromptHelper(max_input_size, num_outputs, max_chunk_overlap, chunk_size_limit=chunk_size_limit)

    # define LLM
    llm_predictor = LLMPredictor(llm=OpenAI(temperature=0.5, model_name="text-davinci-003", max_tokens=num_outputs))
 
    documents = SimpleDirectoryReader(directory_path).load_data()
    
    service_context = ServiceContext.from_defaults(llm_predictor=llm_predictor, prompt_helper=prompt_helper)
    index = GPTSimpleVectorIndex.from_documents(documents, service_context=service_context)

    index.save_to_disk('static/vector_index/index.json')

    return index

construct_index("static/data")