Llama-index with InterSystems IRIS

Llama-index with support for InterSystems IRIS

Install

pip install llama-iris

Example

import os
from dotenv import load_dotenv
from llama_index import SimpleDirectoryReader, StorageContext, ServiceContext

from llama_index.indices.vector_store import VectorStoreIndex

import openai
from llama_iris import IRISVectorStore
load_dotenv(override=True)
documents = SimpleDirectoryReader("./data/paul_graham").load_data()

print("Document ID:", documents[0].doc_id)
vector_store = IRISVectorStore.from_params(

connection_string=CONNECTION_STRING,

table_name="paul_graham_essay",

embed_dim=1536,  # openai embedding dimension

)
storage_context = StorageContext.from_defaults(vector_store=vector_store)
index = VectorStoreIndex.from_documents(

documents,

storage_context=storage_context,

show_progress=True,

)

query_engine = index.as_query_engine()
response = query_engine.query("What did the author do?")
import textwrap

print(textwrap.fill(str(response), 100))