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from flask import Flask, render_template, request, jsonify | |
from simple_salesforce import Salesforce | |
from dotenv import load_dotenv | |
import os | |
import logging | |
import uuid | |
from datetime import datetime | |
# Load environment variables | |
load_dotenv() | |
# Set up logging | |
logging.basicConfig(level=logging.INFO) | |
logger = logging.getLogger(__name__) | |
app = Flask(__name__, template_folder='templates', static_folder='static') | |
# Salesforce connection function | |
def get_salesforce_connection(): | |
try: | |
sf = Salesforce( | |
username=os.getenv('SFDC_USERNAME'), | |
password=os.getenv('SFDC_PASSWORD'), | |
security_token=os.getenv('SFDC_SECURITY_TOKEN'), | |
domain=os.getenv('SFDC_DOMAIN', 'login') | |
) | |
logger.info("Successfully connected to Salesforce") | |
return sf | |
except Exception as e: | |
logger.error(f"Error connecting to Salesforce: {e}") | |
return None | |
# Initialize Salesforce connection | |
sf = get_salesforce_connection() | |
# Initialize OpenAI client | |
openai_api_key = os.getenv('OPENAI_API_KEY') | |
if not openai_api_key: | |
logger.error("OPENAI_API_KEY not found in .env. ChatGPT functionality disabled.") | |
client = None | |
else: | |
try: | |
client = OpenAI(api_key=openai_api_key) | |
test_response = client.chat.completions.create( | |
model="gpt-3.5-turbo", | |
messages=[{"role": "user", "content": "Test API key"}] | |
) | |
logger.info("OpenAI API key validated successfully") | |
except Exception as e: | |
logger.error(f"Invalid OpenAI API key or connection issue: {e}") | |
client = None | |
# Conversation storage | |
conversation_sessions = {} | |
def is_restaurant_related(query): | |
keywords = ['use', 'uses', 'dish', 'recipe', 'ingredient', 'food', 'menu', 'vegetarian', 'non-vegetarian', | |
'rice', 'chicken', 'pasta', 'veggie', 'mutton', 'lamb', 'beef', 'pork', 'fish', 'seafood', | |
'ingredients', 'nutrition', 'nutritional', 'info', 'message', 'messages'] | |
return bool(query.strip() and any(keyword in query.lower() for keyword in keywords)) or any(item in query.lower() for item in ['mutton', 'rice', 'chicken']) | |
def get_chatgpt_response(prompt, session_id): | |
if not client: | |
logger.warning("No OpenAI client available, using mock ChatGPT response") | |
if any(item in prompt.lower() for item in ['mutton', 'rice', 'chicken']): | |
return f"{prompt.capitalize()} is great for curries or roasts in a restaurant!" | |
return "I can help with food! Try 'uses of mutton' or 'ingredients for rice'." | |
if session_id not in conversation_sessions: | |
conversation_sessions[session_id] = [ | |
{"role": "system", "content": "You are a restaurant culinary assistant. Respond only to queries about ingredients, dishes, or recipes. Provide concise, friendly answers. For unclear queries, suggest: 'Try 'uses of mutton' or 'ingredients for rice'.'"} | |
] | |
prompt = prompt.strip().lower() | |
logger.info(f"Processing prompt: {prompt}") | |
if not is_restaurant_related(prompt): | |
logger.info(f"Off-topic or empty query: {prompt}") | |
return "I can help with food! Try 'uses of mutton' or 'ingredients for rice'." | |
intent = "uses" | |
item = prompt | |
if "what is the use of" in prompt or "uses of" in prompt: | |
item = prompt.replace("what is the use of ", "").replace("uses of ", "").strip() or prompt | |
prompt = f"Provide the culinary uses of '{item}' for a restaurant. Be concise and friendly. If unknown, say 'Great for many dishes!'" | |
elif any(word in prompt for word in ['suggest', 'recipe', 'dish']): | |
intent = "suggest" | |
prompt = f"Suggest a restaurant dish based on: {prompt}. Include ingredients and be concise." | |
elif any(word in prompt for word in ['ingredients', 'ingredient']): | |
intent = "ingredients" | |
item = prompt.replace("ingredients for ", "").replace("ingredient of ", "").strip() or prompt | |
prompt = f"List common ingredients for a restaurant dish using '{item}'. Be concise and realistic." | |
elif any(word in prompt for word in ['nutrition', 'nutritional', 'info']): | |
intent = "nutrition" | |
item = prompt.replace("nutrition of ", "").replace("nutritional info for ", "").strip() or prompt | |
prompt = f"Provide a concise, approximate nutritional overview (calories, protein, fat, carbs) for a restaurant portion of '{item}'. Use general culinary knowledge and keep it friendly." | |
elif any(item in prompt for item in ['mutton', 'rice', 'chicken', 'pasta', 'veggie', 'lamb', 'beef', 'pork', 'fish', 'seafood']): | |
prompt = f"Provide the culinary uses of '{item}' for a restaurant. Be concise and friendly. If unknown, say 'Great for many dishes!'" | |
else: | |
logger.info(f"Unclear intent, defaulting to uses for: {prompt}") | |
prompt = f"Provide the culinary uses of '{prompt}' for a restaurant. Be concise and friendly. If unknown, say 'Great for many dishes!'" | |
conversation_sessions[session_id].append({"role": "user", "content": prompt}) | |
try: | |
response = client.chat.completions.create( | |
model="gpt-3.5-turbo", | |
messages=conversation_sessions[session_id], | |
max_tokens=150, | |
timeout=10 | |
) | |
reply = response.choices[0].message.content.strip() | |
conversation_sessions[session_id].append({"role": "assistant", "content": reply}) | |
logger.info(f"ChatGPT response for '{prompt}': {reply}") | |
return reply | |
except Exception as e: | |
logger.error(f"OpenAI API error: {e}") | |
return f"Sorry, API failed. Mock response: {prompt.capitalize()} is great for curries or roasts!" | |
def index(): | |
return render_template('index.html') | |
def get_menu_items(): | |
global sf | |
if not sf: | |
sf = get_salesforce_connection() | |
if not sf: | |
return jsonify({"error": "Unable to connect to Salesforce"}), 500 | |
data = request.json | |
dietary_preference = data.get('dietary_preference', 'both').lower() | |
search_term = data.get('search_term', '').strip() | |
try: | |
items = [] | |
if not search_term: | |
soql = "SELECT Name, Image_URL__c, Category__c, Description__c FROM Sector_Detail__c" | |
if dietary_preference == 'vegetarian': | |
soql += " WHERE Category__c = 'Veg'" | |
elif dietary_preference == 'non-vegetarian': | |
soql += " WHERE Category__c = 'Non-Veg'" | |
soql += " LIMIT 200" | |
result = sf.query(soql) | |
items = [ | |
{ | |
"name": r['Name'], | |
"image_url": r.get('Image_URL__c', ''), | |
"category": r.get('Category__c', ''), | |
"description": r.get('Description__c', 'No description'), | |
"source": "Sector_Detail__c" | |
} | |
for r in result['records'] if 'Name' in r | |
] | |
else: | |
soql_menu = "SELECT Name, Description__c, Image1__c, Ingredientsinfo__c, NutritionalInfo__c, Price__c, Sector__c, Spice_Levels__c, Veg_NonVeg__c, Category__c, Dynamic_Dish__c FROM Menu_Item__c" | |
soql_menu += f" WHERE Name LIKE '%{search_term}%' OR Ingredientsinfo__c LIKE '%{search_term}%'" | |
if dietary_preference == 'vegetarian': | |
soql_menu += " AND Veg_NonVeg__c = 'Vegetarian'" | |
elif dietary_preference == 'non-vegetarian': | |
soql_menu += " AND Veg_NonVeg__c = 'Non-Vegetarian'" | |
soql_menu += " LIMIT 200" | |
logger.info(f"Executing SOQL query for Menu_Item__c: {soql_menu}") | |
result_menu = sf.query(soql_menu) | |
menu_items = [ | |
{ | |
"name": record['Name'], | |
"description": record.get('Description__c', 'No description available'), | |
"image_url": record.get('Image1__c', ''), | |
"ingredients": record.get('Ingredientsinfo__c', ''), | |
"nutritional_info": record.get('NutritionalInfo__c', ''), | |
"price": record.get('Price__c', 0.0), | |
"sector": record.get('Sector__c', ''), | |
"spice_levels": record.get('Spice_Levels__c', ''), | |
"veg_nonveg": record.get('Veg_NonVeg__c', ''), | |
"category": record.get('Category__c', ''), | |
"dynamic_dish": record.get('Dynamic_Dish__c', False), | |
"source": "Menu_Item__c" | |
} | |
for record in result_menu['records'] if 'Name' in record | |
] | |
items.extend(menu_items) | |
return jsonify({"menu_items": items}) | |
except Exception as e: | |
logger.error(f"Failed to fetch items: {e}") | |
return jsonify({"error": f"Failed to fetch items: {e}"}), 500 | |
def get_sector_item_details(): | |
global sf | |
if not sf: | |
sf = get_salesforce_connection() | |
if not sf: | |
return jsonify({"error": "Unable to connect to Salesforce"}), 500 | |
item_name = request.json.get('item_name', '').strip() | |
if not item_name: | |
return jsonify({"error": "Item name is required"}), 400 | |
try: | |
soql = f"SELECT Name, Image_URL__c, Category__c, Description__c FROM Sector_Detail__c WHERE Name LIKE '%{item_name}%' LIMIT 1" | |
logger.info(f"Executing SOQL query: {soql}") | |
result = sf.query(soql) | |
if result['totalSize'] == 0: | |
return jsonify({"error": f"No item found matching '{item_name}' in Sector_Detail__c"}), 404 | |
record = result['records'][0] | |
item_details = { | |
"name": record.get('Name', ''), | |
"image_url": record.get('Image_URL__c', 'https://via.placeholder.com/30'), | |
"category": record.get('Category__c', ''), | |
"description": record.get('Description__c', 'No description available') | |
} | |
logger.info(f"Fetched details for '{item_name}' from Sector_Detail__c") | |
return jsonify({"item_details": item_details}) | |
except Exception as e: | |
logger.error(f"Failed to fetch item details from Sector_Detail__c: {e}") | |
return jsonify({"error": f"Failed to fetch item details: {e}"}), 500 | |
def suggest_items(): | |
global sf | |
if not sf: | |
sf = get_salesforce_connection() | |
if not sf: | |
return jsonify({"error": "Unable to connect to Salesforce"}), 500 | |
search_term = request.json.get('search_term', '').strip() | |
if not search_term: | |
return jsonify({"error": "Search term is required"}), 400 | |
try: | |
soql = f"SELECT Ingredient_Name__c, Image_URL__c FROM Ingredient_Object__c WHERE Ingredient_Name__c LIKE '%{search_term}%' LIMIT 10" | |
logger.info(f"Executing SOQL query: {soql}") | |
result = sf.query(soql) | |
suggestions = [ | |
{"name": record['Ingredient_Name__c'], "image_url": record.get('Image_URL__c', '')} | |
for record in result['records'] if 'Ingredient_Name__c' in record | |
] | |
logger.info(f"Fetched {len(suggestions)} suggestions for '{search_term}'") | |
return jsonify({"suggestions": suggestions}) | |
except Exception as e: | |
logger.error(f"Failed to fetch suggestions: {e}") | |
return jsonify({"error": f"Failed to fetch suggestions: {e}"}), 500 | |
def get_item_details(): | |
global sf | |
if not sf: | |
sf = get_salesforce_connection() | |
if not sf: | |
return jsonify({"error": "Unable to connect to Salesforce"}), 500 | |
item_name = request.json.get('item_name', '').strip() | |
if not item_name: | |
return jsonify({"error": "Item name is required"}), 400 | |
try: | |
soql = f"SELECT Ingredient_Name__c, Image_URL__c FROM Ingredient_Object__c WHERE Ingredient_Name__c LIKE '%{item_name}%' LIMIT 1" | |
logger.info(f"Executing SOQL query: {soql}") | |
result = sf.query(soql) | |
if result['totalSize'] == 0: | |
return jsonify({"error": f"No item found matching '{item_name}' in Ingredient_Object__c"}), 404 | |
record = result['records'][0] | |
item_details = { | |
"name": record.get('Ingredient_Name__c', ''), | |
"image_url": record.get('Image_URL__c', '') | |
} | |
logger.info(f"Fetched details for '{item_name}'") | |
return jsonify({"item_details": item_details}) | |
except Exception as e: | |
logger.error(f"Failed to fetch item details: {e}") | |
return jsonify({"error": f"Failed to fetch item details: {e}"}), 500 | |
def submit_items(): | |
global sf | |
if not sf: | |
sf = get_salesforce_connection() | |
if not sf: | |
return jsonify({"error": "Unable to connect to Salesforce"}), 500 | |
items = request.json.get('items', []) | |
custom_order_name = request.json.get('custom_order_name', '') | |
if not items: | |
return jsonify({"error": "No items to submit"}), 400 | |
try: | |
ingredient_name = custom_order_name or f"Order_{datetime.now().strftime('%Y%m%d')}_{uuid.uuid4().hex[:8]}" | |
item_names = ', '.join(item['name'] for item in items) | |
description = f"Contains: {item_names}" | |
for item in items: | |
sf.Ingredient_Object__c.create({ | |
'Ingredient_Name__c': ingredient_name, | |
'Category__c': item.get('category', ''), | |
'Description__c': f"{item.get('description', 'No description')} - {description}", | |
'Image_URL__c': item.get('image_url', ''), | |
'Quantity__c': item.get('quantity', 1) | |
}) | |
return jsonify({"success": f"Submitted {len(items)} items under {ingredient_name}", "ingredient_name": ingredient_name}) | |
except Exception as e: | |
logger.error(f"Failed to submit items: {e}") | |
return jsonify({"error": f"Failed to submit items: {e}"}), 500 | |
def get_item_info(): | |
global sf, client | |
item_name = request.json.get('item_name', '').strip() | |
if not item_name or not client: | |
return jsonify({"error": "Item name required or OpenAI unavailable"}), 400 | |
try: | |
soql = f"SELECT Name, Description__c FROM Sector_Detail__c WHERE Name LIKE '%{item_name}%' LIMIT 1" | |
result = sf.query(soql) | |
if result['totalSize'] == 0: | |
return jsonify({"error": f"No item found matching '{item_name}'"}), 404 | |
record = result['records'][0] | |
base_info = record.get('Description__c', 'No description available') | |
prompt = f"Based on general culinary knowledge, provide a concise list of common ingredients and an approximate nutritional overview (calories, protein, fat, carbs) for a restaurant portion of '{item_name}'. Use realistic values and keep it friendly." | |
response = client.chat.completions.create( | |
model="gpt-3.5-turbo", | |
messages=[{"role": "user", "content": prompt}], | |
max_tokens=150, | |
timeout=10 | |
) | |
ai_response = response.choices[0].message.content.strip() | |
item_info = { | |
"name": record['Name'], | |
"description": base_info, | |
"details": ai_response | |
} | |
logger.info(f"Generated info for '{item_name}'") | |
return jsonify({"item_info": item_info}) | |
except Exception as e: | |
logger.error(f"Failed to get item info: {e}") | |
return jsonify({"error": f"Failed to get item info: {e}"}), 500 | |
def chat(): | |
user_message = request.json.get('message', '').strip() | |
session_id = request.json.get('session_id', 'default') | |
if not user_message: | |
return jsonify({"error": "No message provided"}), 400 | |
response = get_chatgpt_response(user_message, session_id) | |
logger.info(f"Chat response sent: {response}") | |
return jsonify({"response": response, "search_term": user_message}) | |
if __name__ == '__main__': | |
app.run(debug=True, host='0.0.0.0', port=7860) |