app.py

import json
from sentence_transformers import SentenceTransformer, util
from flask import Flask, request, jsonify
from flask_cors import CORS

app = Flask(__name__)
CORS(app)
# Load the model
model = SentenceTransformer('all-MiniLM-L6-v2')

# Load JSON data
with open('resume_data.json') as f:
    data = json.load(f)

def get_response(user_input):
    user_input = user_input.lower()  # Normalize user input
    user_embedding = model.encode(user_input)
    responses = [
        (util.cos_sim(user_embedding, model.encode(pattern.lower())).item(), item["response"])  # Normalize patterns
        for item in data["questions"] 
        for pattern in item["patterns"]
    ]
    best_response = max(responses, key=lambda x: x[0])
    return best_response[1] if best_response[0] > 0.5 else "Sorry, I couldn't understand that."

@app.route('/chat', methods=['POST'])
def chat():
    user_input = request.json.get('input')
    response = get_response(user_input)
    return jsonify({'response': response})

# def main():
#     print("Welcome to the CLI Chatbot. Type 'exit' to quit.")
#     while True:
#         user_input = input("You: ")
#         if user_input.lower() == 'exit':
#             break
#         answer = get_response(user_input)
#         if not answer.strip():
#             answer = "I'm not sure how to answer that."
#         print(f"Bot: {answer}")

if __name__ == "__main__":
    app.run(debug=True)