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Flask API endpoint that saves a new instruction template by accepting a POST request with template name and instructions, then persisting it via the chat_engine.

Purpose

This endpoint provides a REST API interface for creating and storing instruction templates. It validates incoming JSON data, checks for required fields (name and instructions), and delegates the actual saving operation to the chat_engine's save_instruction_template method. It's designed to be used in a web application where users can create reusable instruction templates for chat interactions.

Source Code

def api_save_template():
    """Save a new instruction template"""
    try:
        data = request.get_json()
        name = data.get('name')
        instructions = data.get('instructions')
        
        if not name or not instructions:
            return jsonify({'error': 'Template name and instructions are required'}), 400
        
        if chat_engine and hasattr(chat_engine, 'save_instruction_template'):
            chat_engine.save_instruction_template(name, instructions)
            return jsonify({'message': 'Template saved successfully'})
        else:
            return jsonify({'error': 'Template saving not supported'}), 400
            
    except Exception as e:
        logger.error(f"Save template error: {e}")
        return jsonify({'error': 'Failed to save template'}), 500

Return Value

Returns a Flask JSON response tuple. On success: (jsonify({'message': 'Template saved successfully'}), 200). On validation error: (jsonify({'error': 'Template name and instructions are required'}), 400). On unsupported operation: (jsonify({'error': 'Template saving not supported'}), 400). On exception: (jsonify({'error': 'Failed to save template'}), 500).

Dependencies

• flask
• logging
• hybrid_rag_engine

Required Imports

from flask import Flask
from flask import request
from flask import jsonify
import logging
from hybrid_rag_engine import OneCo_hybrid_RAG

Usage Example

# Client-side usage example (JavaScript fetch):
fetch('/api/templates', {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'Authorization': 'Bearer YOUR_AUTH_TOKEN'
  },
  body: JSON.stringify({
    name: 'customer_support_template',
    instructions: 'You are a helpful customer support agent. Be polite and professional.'
  })
})
.then(response => response.json())
.then(data => console.log(data.message))
.catch(error => console.error('Error:', error));

# Python requests example:
import requests
response = requests.post(
  'http://localhost:5000/api/templates',
  json={
    'name': 'code_review_template',
    'instructions': 'Review code for best practices and security issues.'
  },
  headers={'Authorization': 'Bearer YOUR_AUTH_TOKEN'}
)
print(response.json())

Best Practices

• Always include both 'name' and 'instructions' fields in the request body to avoid 400 errors
• Ensure the chat_engine is properly initialized before this endpoint is called
• Handle all possible HTTP status codes (200, 400, 500) in client code
• The endpoint requires authentication via the require_auth decorator - ensure valid credentials are provided
• Template names should be unique to avoid overwriting existing templates (validation depends on chat_engine implementation)
• Consider implementing rate limiting to prevent abuse of template creation
• The function relies on global 'chat_engine' and 'logger' objects - ensure these are properly initialized in the application context
• Error messages are logged server-side but generic messages are returned to clients for security

Tags

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