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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): | |
if os.path.exists(index_name): | |
return GPTSimpleVectorIndex.load_from_disk(index_name) | |
else: | |
documents = [Document(d) for d in data] | |
index = GPTSimpleVectorIndex.from_documents(documents, service_context=service_context) | |
index.save_to_disk(index_name) | |
return index |