System Documentation: An Interactive NL2SQL Simulation with Gemini API Integration Introduction This document outlines a self-contained web application designed to demonstrate the functionality of an Artificial Intelligence (AI) agent in querying a database through natural language processing. The application simulates the complete workflow, from the initial user query to the final database response, and incorporates supplementary features leveraging the Gemini Application Programming Interface (API).

System Features Natural Language to SQL Simulation: The system facilitates natural language queries, which are subsequently translated into Structured Query Language (SQL) by a simulated AI agent for execution against a mock database.

Live Interaction Logging: The application provides a detailed, real-time log that documents the sequence of interactions among the user interface, the AI agent, and the simulated server backend.

Gemini API-Powered Query Generation: The system can leverage the Gemini API to generate contextually relevant query suggestions based on the provided database schema.

Gemini API-Powered Result Summarization: Upon retrieval of a JSON-formatted result set, the Gemini API can be invoked to generate a concise, human-readable summary of the data.

Execution Procedure This application is delivered as a single HTML file and requires no external installation or dependencies.

Persist the provided HTML source code to a local file (e.g., index.html).

Launch the file using a contemporary web browser.

The application is now ready for direct user interaction.

Python API Authorization Examples The following sections detail standard methodologies for establishing a connection to a secure Application Programming Interface (API) utilizing the Python requests library.

1. HTTP Basic Authentication This widely adopted authentication scheme involves transmitting user credentials directly within the request header.

import requests import sys

try: print(f"Connecting to {API_ENDPOINT}...") response = requests.get(API_ENDPOINT, auth=(USERNAME, PASSWORD)) response.raise_for_status() # Raise an exception for bad status codes

print("✅ Connection successful!")
print("--- API Response Data ---")
print(response.json())

except requests.exceptions.RequestException as err: print(f"❌ An error occurred: {err}")

2. Credentials in a POST Request Body This method is typically employed for authentication endpoints that issue an access token upon successful validation. This token is then utilized for authorization in subsequent API calls.

import requests import sys

LOGIN_ENDPOINT = "https://your-instance.app.com/api/login" login_payload = { "username": "your_username", "password": "your_password" }

try: print(f"Attempting to log in to {LOGIN_ENDPOINT}...") response = requests.post(LOGIN_ENDPOINT, json=login_payload) response.raise_for_status()

print("✅ Login successful!")
access_token = response.json().get("token")
if access_token:
    print("Retrieved access token.")
    # Use this token in headers for future requests
    # headers = {'Authorization': f'Bearer {access_token}'}
else:
    print("⚠️ Login succeeded, but no token was found.")

except requests.exceptions.RequestException as err: print(f"❌ An error occurred: {err}")