import os
from flask import Flask, render_template, request, jsonify
from huggingface_hub import InferenceClient  # Import InferenceClient correctly
from dotenv import load_dotenv
import json

# Load environment variables from .env file
load_dotenv()

# Set up API keys
HUGGINGFACE_API_KEY = os.getenv('HUGGINGFACE_API_KEY')

# Set up Flask app
app = Flask(__name__)

# Initialize the Hugging Face API Client
client = InferenceClient(HUGGINGFACE_API_KEY)

def respond(message, history, system_message, max_tokens, temperature, top_p):
    messages = [{"role": "system", "content": system_message}]
    
    # Ensure history is a list of tuples
    history = json.loads(history) if isinstance(history, str) else history

    # Include message history (FAQs)
    for val in history:
        if val[0]:
            messages.append({"role": "user", "content": val[0]})
        if val[1]:
            messages.append({"role": "assistant", "content": val[1]})

    messages.append({"role": "user", "content": message})

    # Get response from Hugging Face API (for FAQ)
    response = ""
    try:
        # Use the correct method depending on the Hugging Face model you're using
        result = client.completion(
            model="gpt-3.5-turbo",  # Example, adjust to your model
            inputs=messages,
            max_tokens=max_tokens,
            temperature=temperature,
            top_p=top_p,
        )
        response = result['choices'][0]['text']
    except Exception as e:
        response = str(e)

    return response

# Endpoint for chat responses
@app.route('/chat', methods=['POST'])
def chat():
    user_message = request.form['message']
    history = request.form['history']
    system_message = "You are a helpful FAQ chatbot for customer support."
    max_tokens = 512
    temperature = 0.7
    top_p = 0.9
    
    # Get response from Hugging Face model
    bot_reply = respond(user_message, history, system_message, max_tokens, temperature, top_p)
    
    return jsonify({'response': bot_reply})

# Home page for the chatbot UI
@app.route('/')
def index():
    return render_template('index.html')

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