gistfile1.txt

from llama_index.core import StorageContext
from llama_index.core import VectorStoreIndex
from llama_index.vector_stores.postgres import PGVectorStore
import openai
import os

openai.api_key = os.environ["OPENAI_API_KEY"]

from sqlalchemy import make_url

url = make_url("postgresql://user:password@localhost:5432/llamaindex_node_test")
vector_store = PGVectorStore.from_params(
    database="llamaindex_node_test",
    host=url.host,
    password=url.password,
    port=url.port,
    user=url.username,
    table_name="llamaindex_embedding",
    embed_dim=1536,  # openai embedding dimension
)

storage_context = StorageContext.from_defaults(vector_store=vector_store)
index = VectorStoreIndex.from_vector_store(
    vector_store, storage_context=storage_context, show_progress=True
)
query_engine = index.as_query_engine()

res = query_engine.query("What is the meaning of life?")
print(res)