Hi guys, i am really new on this type of technology, i have managed to create a VectorStore index with trained data using the OpenAI API. I am really interested on getting to know how can i create larger VectorStores indexes. The reason is i have now a lot of files and when i try to train the model, i get a OpenAI token limit error. So i was wondering how can i merge/load different VectorStores, or how can i load a lot more of files.
This i how i am loading the files (Failing code due to token limit):
def construct_index(directory_path):
num_outputs = 1024
llm_predictor = LLMPredictor(
llm=OpenAI(
temperature=0.1, model_name="text-davinci-003", max_tokens=num_outputs
)
)
service_context = ServiceContext.from_defaults(llm_predictor=llm_predictor)
docs = SimpleDirectoryReader(directory_path).load_data()
index = GPTVectorStoreIndex(nodes=docs, service_context=service_context)
index.storage_context.persist(persist_dir="index")
return index
Thanks in advance for the help π