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import os
# Uncomment to specify your OpenAI API key here (local testing only, not in production!), or add corresponding environment variable (recommended)
# os.environ['OPENAI_API_KEY']= ""
from llama_index import LLMPredictor, PromptHelper, SimpleDirectoryReader, ServiceContext
from langchain.llms.openai import OpenAI
from llama_index import StorageContext, load_index_from_storage
base_path = os.environ.get('OPENAI_API_BASE', 'http://localhost:8080/v1')
# This example uses text-davinci-003 by default; feel free to change if desired
llm_predictor = LLMPredictor(llm=OpenAI(temperature=0, model_name="gpt-3.5-turbo", openai_api_base=base_path))
# Configure prompt parameters and initialise helper
max_input_size = 512
num_output = 256
max_chunk_overlap = 20
prompt_helper = PromptHelper(max_input_size, num_output, max_chunk_overlap)
# Load documents from the 'data' directory
service_context = ServiceContext.from_defaults(llm_predictor=llm_predictor, prompt_helper=prompt_helper)
# rebuild storage context
storage_context = StorageContext.from_defaults(persist_dir='./storage')
# load index
index = load_index_from_storage(storage_context, service_context=service_context, )
documents = SimpleDirectoryReader('data').load_data()
index.refresh(documents)
index.storage_context.persist(persist_dir="./storage") |