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import os
from dotenv import load_dotenv
from llama_index import (Document, GPTSimpleVectorIndex, LLMPredictor,
ServiceContext)
from data.prepare import data
from .customLLM import CustomLLM, prompt_helper
load_dotenv()
#define our llm
llm_predictor = LLMPredictor(llm=CustomLLM())
service_context = ServiceContext.from_defaults(llm_predictor=llm_predictor, prompt_helper=prompt_helper)
def initialize_index(index_name):
path = f"./vectorStores/{index_name}"
if os.path.exists(path):
return GPTSimpleVectorIndex.load_from_disk(path)
else:
documents = [Document(d) for d in data]
index = GPTSimpleVectorIndex.from_documents(documents, service_context=service_context)
index.save_to_disk(path)
return index |