How to Query Live Oracle Eloqua Reporting Data in Natural Language in Python using LlamaIndex

Start querying live data from Oracle Eloqua Reporting using the CData Python Connector for Oracle Eloqua Reporting. Leverage the power of AI with LlamaIndex and retrieve insights using simple English, eliminating the need for complex SQL queries. Benefit from real-time data access that enhances your decision-making process, while easily integrating with your existing Python applications.

With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Oracle Eloqua Reporting data in Python. When you issue complex SQL queries from Python, the driver pushes supported SQL operations, like filters and aggregations, directly to Oracle Eloqua Reporting and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Whether you're analyzing trends, generating reports, or visualizing data, our Python connectors enable you to harness the full potential of your live data source with ease.

Overview

Here's how to query live data with CData's Python connector for Oracle Eloqua Reporting data using LlamaIndex:

• Import required Python, CData, and LlamaIndex modules for logging, database connectivity, and NLP.
• Retrieve your OpenAI API key for authenticating API requests from your application.
• Connect to live Oracle Eloqua Reporting data using the CData Python Connector.
• Initialize OpenAI and create instances of SQLDatabase and NLSQLTableQueryEngine for handling natural language queries.
• Create the query engine and specific database instance.
• Execute natural language queries (e.g., "Who are the top-earning employees?") to get structured responses from the database.
• Analyze retrieved data to gain insights and inform data-driven decisions.

Import Required Modules

Import the necessary modules CData, database connections, and natural language querying.

import os
import logging
import sys

# Configure logging
logging.basicConfig(stream=sys.stdout, level=logging.INFO, force=True)
logging.getLogger().addHandler(logging.StreamHandler(stream=sys.stdout))

# Import required modules for CData and LlamaIndex
import cdata.oracleeloquareporting as mod
from sqlalchemy import create_engine
from llama_index.core.query_engine import NLSQLTableQueryEngine
from llama_index.core import SQLDatabase
from llama_index.llms.openai import OpenAI

Set Your OpenAI API Key

To use OpenAI's language model, you need to set your API key as an environment variable. Make sure you have your OpenAI API key available in your system's environment variables.

# Retrieve the OpenAI API key from the environment variables
OPENAI_API_KEY = os.environ["OPENAI_API_KEY"]

''as an alternative, you can also add your API key directly within your code (though this method is not recommended for production environments due to security risks):''

# Directly set the API key (not recommended for production use)
OPENAI_API_KEY = "your-api-key-here"

Create a Database Connection

Next, establish a connection to Oracle Eloqua Reporting using the CData connector using a connection string with the required connection properties.

Oracle Eloqua Reporting supports the following authentication methods:

• Basic authentication (User and Password)
• OAuth 2.0 code grant flow
• OAuth 2.0 password grant flow

Basic Authentication (User and Password)

To perform authentication with a user and password, specify these properties:

• AuthScheme: Basic.
• Company: The company name associated with your Oracle Eloqua Reporting account.
• User: Your login account name.
• Password: Your login password.

OAuth Authentication (Code Grant Flow)

To authenticate with the OAuth code grant flow, you must set AuthScheme to OAuth and create a custom OAuth application. For information about how to create a custom OAuth application, see the Help documentation.

Then set the following properties:

• InitiateOAuth: GETANDREFRESH. Used to automatically get and refresh the OAuthAccessToken.
• OAuthClientId: The client Id assigned when you registered your application.
• OAuthClientSecret: The client secret that was assigned when you registered your application.
• CallbackURL: The redirect URI that was defined when you registered your application.

When you connect, the driver opens Oracle Eloqua Reporting's OAuth endpoint in your default browser. Log in and grant permissions to the application. When the access token expires, the driver refreshes it automatically.

OAuth Authentication (Password Grant Flow)

With the OAuth password grant flow, you can use your OAuth application's credentials alongside your user credentials to authenticate without the need to grant permission manually via a browser prompt. You must create an OAuth app (see the Help documentation) to use this authentication method.

Set the following properties:

• AuthScheme: OAuthPassword
• Company: The company's unique identifier.
• User: Your login account name.
• Password: Your login password.
• OAuthClientId: The client Id assigned when you registered your custom OAuth application.
• OAuthClientSecret: The client secret assigned when you registered your custom OAuth application.

Connecting to Oracle Eloqua Reporting

# Create a database engine using the CData Python Connector for Oracle Eloqua Reporting
engine = create_engine("cdata_oracleeloquareporting_2:///?User=AuthScheme=Basic;User=user;Password=password;Company=MyCompany;")

Initialize the OpenAI Instance

Create an instance of the OpenAI language model. Here, you can specify parameters like temperature and the model version.

# Initialize the OpenAI language model instance
llm = OpenAI(temperature=0.0, model="gpt-3.5-turbo")

Set Up the Database and Query Engine

Now, set up the SQL database and the query engine. The NLSQLTableQueryEngine allows you to perform natural language queries against your SQL database.

# Create a SQL database instance
sql_db = SQLDatabase(engine)  # This includes all tables

# Initialize the query engine for natural language SQL queries
query_engine = NLSQLTableQueryEngine(sql_database=sql_db)

Execute a Query

Now, you can execute a natural language query against your live data source. In this example, we will query for the top two earning employees.

# Define your query string
query_str = "Who are the top earning employees?"

# Get the response from the query engine
response = query_engine.query(query_str)

# Print the response
print(response)

Download a free, 30-day trial of the CData Python Connector for Oracle Eloqua Reporting and start querying your live data seamlessly. Experience the power of natural language processing and unlock valuable insights from your data today.