Create app.py

app.py

@@ -0,0 +1,48 @@
+from flask import Flask, request, jsonify
+from transformers import pipeline
+
+app = Flask(__name__)
+
+# Load Hugging Face model for conversation
+chatbot = pipeline("conversational", model="facebook/blenderbot-400M-distill")
+
+# Endpoint for chat with the chatbot
+@app.route('/chat', methods=['POST'])
+def chat():
+    user_message = request.json.get('message')
+
+    if user_message.lower() == 'hi':
+        # Send a greeting message when the user says "hi"
+        return jsonify({"response": "Hello! Welcome to the Indian Recipe Bot. What ingredients do you have today?"})
+
+    # Get response from the chatbot model
+    chatbot_response = chatbot(user_message)
+    return jsonify({"response": chatbot_response[0]['generated_text']})
+
+
+@app.route('/ingredients', methods=['POST'])
+def ingredients():
+    user_ingredients = request.json.get('ingredients')
+    
+    # Example logic to suggest Indian recipes based on ingredients
+    recipes = {
+        'rice': ['Biryani', 'Pulao'],
+        'potato': ['Aloo Gobi', 'Aloo Paratha'],
+        'spinach': ['Palak Paneer', 'Saag Aloo'],
+        'chicken': ['Butter Chicken', 'Chicken Curry'],
+        'paneer': ['Paneer Butter Masala', 'Shahi Paneer'],
+    }
+
+    suggested_recipes = []
+    for ingredient in user_ingredients:
+        if ingredient in recipes:
+            suggested_recipes.extend(recipes[ingredient])
+
+    if not suggested_recipes:
+        suggested_recipes.append('Sorry, no recipes found for the ingredients you provided.')
+
+    return jsonify({"suggested_recipes": suggested_recipes})
+
+
+if __name__ == '__main__':
+    app.run(debug=True)