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

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

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

Start by setting the Profile connection property to the location of the TypeForm Profile on disk (e.g. C:\profiles\TypeForm.apip). Next, set the ProfileSettings connection property to the connection string for TypeForm (see below).

TypeForm API Profile Settings

Authentication to TypeForm uses the OAuth standard.

To authenticate to TypeForm, you must first register and configure an OAuth application with TypeForm here: https://admin.typeform.com/account#/section/tokens. Your app will be assigned a client ID and a client secret which can be set in the connection string. More information on setting up an OAuth application can be found at https://developer.typeform.com/get-started/.

Note that there are several different use scenarios which all require different redirect URIs:

CData Desktop Applications: CData desktop applications (Sync, API Server, ArcESB) accept OAuth tokens at /src/oauthCallback.rst. The host and port is the same as the default port used by the application. For example, if you use http://localhost:8019/ to access CData Sync then the redirect URI will be http://localhost:8019/src/oauthCallback.rst.
CData Cloud Applications: CData cloud applications are similar to their desktop counterparts. If you access Connect Cloud at https://1.2.3.4/ then you should use the redirect https://1.2.3.4/src/oauthCallback.rst.
Desktop Application: When using a desktop application, the URI https://localhost:33333 is recommended.
Web Application: When developing a web application using the driver, use your own URI here such as https://my-website.com/oauth.

After setting the following connection properties, you are ready to connect:

AuthScheme: Set this to OAuth.
InitiateOAuth: Set this to GETANDREFRESH. You can use InitiateOAuth to manage the process to obtain the OAuthAccessToken.
OAuthClientId: Set this to the Client Id that is specified in your app settings.
OAuthClientSecret: Set this to Client Secret that is specified in your app settings.
CallbackURL: Set this to the Redirect URI you specified in your app settings.

Connecting to Typeform


# Create a database engine using the CData API Driver for Python
engine = create_engine("cdata_api_2:///?User=Profile=C:\profiles\TypeForm.apip;Authscheme=OAuth;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;CallbackUrl=your_callback_url;")

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 API Driver for Python 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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