from flask import Flask, render_template, request, jsonify, send_file
import requests
from dotenv import load_dotenv
import os
from io import BytesIO
import tempfile

# import namespaces
from azure.core.credentials import AzureKeyCredential
from azure.ai.language.questionanswering import QuestionAnsweringClient
from azure.cognitiveservices.speech import SpeechConfig, SpeechSynthesizer, AudioConfig
from azure.cognitiveservices.speech.audio import AudioOutputConfig

# Create a Flask app
app = Flask(__name__)

# Azure Bot Service configuration
AZURE_BOT_ENDPOINT = "https://iti109-sectionb.cognitiveservices.azure.com/"
AZURE_BOT_KEY = "2ou0CMAjUutj0D4In8U8AkxEIXtCrvYFOBMhqSW4rZ7x6yZ033GdJQQJ99ALACqBBLyXJ3w3AAAaACOGtVJj"

# Get Configuration Settings
load_dotenv()
ai_endpoint = os.getenv('AI_SERVICE_ENDPOINT')
ai_key = os.getenv('AI_SERVICE_KEY')
ai_project_name = os.getenv('QA_PROJECT_NAME')
ai_deployment_name = os.getenv('QA_DEPLOYMENT_NAME')
speech_key = os.getenv('SPEECH_KEY')
speech_region = os.getenv('SPEECH_REGION')

# Create client using endpoint and key
credential = AzureKeyCredential(ai_key)
ai_client = QuestionAnsweringClient(endpoint=ai_endpoint, credential=credential)

# Web Interface
@app.route('/')
def home():
    return render_template('index.html')  # HTML file for the web interface

@app.route('/ask', methods=['POST'])
def ask_bot():
    user_question = request.json.get("question", "") # Get the question from the request
    
    if not user_question:
        return jsonify({"error": "No question provided"}), 400 # Return an error if no question is provided

    try:
        # Get the answer from the bot
        response = ai_client.get_answers(question=user_question,
                                         project_name=ai_project_name,
                                         deployment_name=ai_deployment_name)                                           

        # Get the answer from the response   
        bot_response = response.answers[0].answer if response.answers else "No response from bot"
        
        # Text-to-Speech
        speech_config = SpeechConfig(subscription=speech_key, region=speech_region) # Create a speech config
        #audio_config = AudioConfig(filename="./response.wav") # Save the audio to a file
        with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as temp_audio_file:
            audio_config = AudioConfig(filename=temp_audio_file.name)
            synthesizer = SpeechSynthesizer(speech_config=speech_config, audio_config=audio_config)
            synthesizer.speak_text(bot_response)
        print("Dir content: ", os.listdir("."))
        #audio_output_config = AudioOutputConfig(use_default_speaker=True)  # Correct usage
        #audio_config = AudioConfig(use_default_microphone=True) # Use the default microphone
        synthesizer = SpeechSynthesizer(speech_config=speech_config, audio_config=audio_config) # Create a synthesizer
        #synthesizer.speak_text(bot_response)
       
        try:
            synthesizer.speak_text(bot_response)
            print("Audio file created successfully!")
        except Exception as e:
            print(f"Error generating audio: {e}")

        # Return the answer from the bot        
        return jsonify({"answer": bot_response, "audio": temp_audio_file.name})
        #return jsonify({"answer": bot_response})    
    except requests.exceptions.RequestException as e:
        return jsonify({"error": str(e)}), 500

# Return the audio file
@app.route('/response.wav')
def get_audio():
    return send_file(temp_audio_file.name, mimetype="audio/wav")

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