How to Query Live SAP SuccessFactors Data in Natural Language in Python using LlamaIndex

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

You can authenticate to SAP Success Factors using Basic authentication or OAuth with SAML assertion.

Basic Authentication

You must provide values for the following properties to successfully authenticate to SAP Success Factors. Note that the provider will reuse the session opened by SAP Success Factors using cookies. Which means that your credentials will be used only on the first request to open the session. After that, cookies returned from SAP Success Factors will be used for authentication.

• Url: set this to the URL of the server hosting Success Factors. Some of the servers are listed in the SAP support documentation (external link).
• User: set this to the username of your account.
• Password: set this to the password of your account.
• CompanyId: set this to the unique identifier of your company.

OAuth Authentication

You must provide values for the following properties, which will be used to get the access token.

• Url: set this to the URL of the server hosting Success Factors. Some of the servers are listed in the SAP support documentation (external link).
• User: set this to the username of your account.
• CompanyId: set this to the unique identifier of your company.
• OAuthClientId: set this to the API Key that was generated in API Center.
• OAuthClientSecret: the X.509 private key used to sign SAML assertion. The private key can be found in the certificate you downloaded in Registering your OAuth Client Application.
• InitiateOAuth: set this to GETANDREFRESH.

Connecting to SAP SuccessFactors

# Create a database engine using the CData Python Connector for SAP SuccessFactors
engine = create_engine("cdata_sapsuccessfactors_2:///?User=User=username;Password=password;CompanyId=CompanyId;Url=https://api4.successfactors.com;")

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