How to Query Live Cvent Data in Natural Language in Python using LlamaIndex

Use LlamaIndex to query live Cvent data data in natural language using Python.

Start querying live data from Cvent using the CData Python Connector for Cvent. 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 Cvent data in Python. When you issue complex SQL queries from Python, the driver pushes supported SQL operations, like filters and aggregations, directly to Cvent 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 Cvent 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 Cvent 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.cvent 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 Cvent using the CData connector using a connection string with the required connection properties.

Before you can authenticate to Cvent, you must create a workspace and an OAuth application.

Creating a Workspace

To create a workspace:

Sign into Cvent and navigate to App Switcher (the blue button in the upper right corner of the page) >> Admin.
In the Admin menu, navigate to Integrations >> REST API.
A new tab launches for Developer Management. Click on Manage API Access in the new tab.

Create a Workspace and name it. Select the scopes you would like your developers to have access to. Scopes control what data domains the developer can access.

Choose All to allow developers to choose any scope, and any future scopes added to the REST API.

Choose Custom to limit the scopes developers can choose for their OAuth apps to selected scopes. To access all tables exposed by the driver, you need to set the following scopes:

event/attendees:read	event/attendees:write	event/contacts:read
event/contacts:write	event/custom-fields:read	event/custom-fields:write
event/events:read	event/events:write	event/sessions:delete
event/sessions:read	event/sessions:write	event/speakers:delete
event/speakers:read	event/speakers:write	budget/budget-items:read
budget/budget-items:write	exhibitor/exhibitors:read	exhibitor/exhibitors:write
survey/surveys:read	survey/surveys:write

Creating an OAuth Application

After you have set up a Workspace and invited them, developers can sign up and create a custom OAuth app. See the Creating a Custom OAuth Application section in the Help documentation for more information.

Connecting to Cvent

After creating an OAuth application, set the following connection properties to connect to Cvent:

InitiateOAuth: GETANDREFRESH. Used to automatically get and refresh the OAuthAccessToken.
OAuthClientId: The Client ID associated with the OAuth application. You can find this on the Applications page in the Cvent Developer Portal.
OAuthClientSecret: The Client secret associated with the OAuth application. You can find this on the Applications page in the Cvent Developer Portal.

Connecting to Cvent


# Create a database engine using the CData Python Connector for Cvent
engine = create_engine("cdata_cvent_2:///?User=OAuthClientId=MyOAuthClientId;OAuthClientSecret=MyOAuthClientSecret;")

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 Cvent and start querying your live data seamlessly. Experience the power of natural language processing and unlock valuable insights from your data today.

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How to Query Live Cvent Data in Natural Language in Python using LlamaIndex

Overview

Import Required Modules

Set Your OpenAI API Key

Create a Database Connection

Creating a Workspace

Creating an OAuth Application

Connecting to Cvent

Connecting to Cvent

Initialize the OpenAI Instance

Set Up the Database and Query Engine

Execute a Query

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