Nat TaylorBlog, AI, Product Management & Tinkering

Test Drive: llama-index

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Today I’m test driving llama-index, “a data framework for your LLM application.” My task will be to summarize my recent Google location history. I’m just going to do the boring quickstart with barely any modification.

from llama_index.core import VectorStoreIndex, SimpleDirectoryReader

documents = SimpleDirectoryReader("data").load_data()
index = VectorStoreIndex.from_documents(documents)
query_engine = index.as_query_engine()
response = query_engine.query("What places have I spent time recently?")
print(response)

The result was the following, which is true but pretty meaningless

You have recently spent time at “Messina Site and Utility Corp.” in Marblehead, MA and at locations along a walking route with waypoints including ChIJtbU17bsU44kR6pLuGMFRJ4k, ChIJc1v_77sU44kRqSUfpZPkufc, ChIJY8KHV7kU44kRMFeDo84Hiio, and ChIJcQCpSLkU44kRU3N0beAOx6E.

Behind the scenes it created embeddings of chunks of my documents, retrieved the relevant docs and queried the LLM.

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