LlamaIndex Managed Integration: PostgresML
PostgresML provides an all in one platform for production ready RAG applications.
Setup
First, make sure you have the latest LlamaIndex version installed and a connection string to your PostgresML database.
If you don't already have a connection string, you can get one on postgresml.org.
pip install llama-index-indices-managed-postgresmlUsage
Getting started is easy!
import os
os.environ[
"PGML_DATABASE_URL"
] = "..." # Can provide in the environment or constructor later on
from llama_index.core import Document
from llama_index.indices.managed.postgresml import PostgresMLIndex
# Create an index
index = PostgresMLIndex.from_documents(
"llama-index-test-1", [Document.example()]
)
# Connect to an index
index = PostgresMLIndex("llama-index-test-1")You can use the index as a retriever
# Create a retriever from an index
retriever = index.as_retriever()
results = retriever.retrieve("What managed index is the best?")
print(results)You can also use the index as a query engine
# Create an engine from an index
query_engine = index.as_query_engine()
response = retriever.retrieve("What managed index is the best?")
print(response)
