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Flask route handler that processes POST requests to generate field suggestions based on a user's natural language request by leveraging an enhanced SQL workflow system.

Purpose

This endpoint serves as an API interface for obtaining intelligent field suggestions from a database schema. It accepts a user's natural language request, initializes an EnhancedSQLWorkflow with statistical capabilities, and returns relevant field suggestions that match the user's intent. This is typically used in interactive query builders or data exploration interfaces where users need assistance identifying relevant database fields.

Source Code

def get_field_suggestions():
    """Get field suggestions based on user request"""
    try:
        data = request.get_json()
        user_request = data.get('user_request', '')
        
        if not user_request:
            return jsonify({
                'success': False,
                'error': 'User request is required'
            }), 400
        
        # Create enhanced workflow instance for suggestions
        from enhanced_sql_workflow import EnhancedSQLWorkflow
        from config import Config
        from statistical_agent import StatisticalAgent
        
        config = Config()
        statistical_agent = StatisticalAgent(config)
        workflow = EnhancedSQLWorkflow(
            config=config,
            statistical_agent=statistical_agent
        )
        
        # Get field suggestions
        suggestions = workflow.get_field_suggestions(user_request)
        
        return jsonify({
            'success': True,
            'suggestions': suggestions
        })
        
    except Exception as e:
        logger.error(f"Error getting field suggestions: {str(e)}")
        return jsonify({
            'success': False,
            'error': str(e)
        }), 500

Return Value

Returns a Flask JSON response tuple. On success (200): {'success': True, 'suggestions': <list of field suggestions>}. On missing user_request (400): {'success': False, 'error': 'User request is required'}. On exception (500): {'success': False, 'error': <error message>}. The suggestions field contains a list or dictionary of recommended database fields based on the user's request.

Dependencies

• flask
• logging
• enhanced_sql_workflow
• config
• statistical_agent

Required Imports

from flask import Flask, request, jsonify
import logging

Conditional/Optional Imports

These imports are only needed under specific conditions:

from enhanced_sql_workflow import EnhancedSQLWorkflow

from config import Config

from statistical_agent import StatisticalAgent

Usage Example

# Client-side usage (JavaScript fetch example):
fetch('/field_suggestions', {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    user_request: 'I need fields related to customer demographics'
  })
})
.then(response => response.json())
.then(data => {
  if (data.success) {
    console.log('Suggestions:', data.suggestions);
  } else {
    console.error('Error:', data.error);
  }
});

# Python requests example:
import requests

response = requests.post(
  'http://localhost:5000/field_suggestions',
  json={'user_request': 'sales and revenue fields'}
)
result = response.json()
if result['success']:
  print('Field suggestions:', result['suggestions'])
else:
  print('Error:', result['error'])

Best Practices

• Always include a non-empty 'user_request' in the JSON payload to avoid 400 errors
• Implement proper error handling on the client side to handle both 400 and 500 status codes
• The function creates new instances of Config, StatisticalAgent, and EnhancedSQLWorkflow on each request, which may have performance implications for high-traffic scenarios
• Consider implementing caching mechanisms if the same user requests are made frequently
• Ensure the logger is properly configured before using this endpoint to capture error information
• The lazy imports inside the function may cause initial request delays; consider moving them to module level if performance is critical
• Validate and sanitize user_request content if it will be used in database queries to prevent injection attacks
• Consider implementing rate limiting to prevent abuse of this computationally intensive endpoint
• The endpoint requires proper Flask application context and should be registered with the Flask app instance

Tags

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