import gradio as gr
from openai import OpenAI
client = OpenAI()
import speech_recognition as sr
from pydub import AudioSegment
from gtts import gTTS
import io
import os
import tempfile
import time

Log_aan = True
Klant_profiel = True
Google_TTS_gebruiken = True
AI_taal_model = "gpt-3.5-turbo"
OpenAI.api_key = os.getenv("OPENAI_API_KEY")

if Log_aan:
    print("Start programma")

# def change_TTS():
#    global Google_TTS_gebruiken
#    Google_TTS_gebruiken = not Google_TTS_gebruiken
#    print("TTS gewisseld")

def toggle_google_openai(huidige_status):
    nieuwe_status = "Google" if huidige_status == "Openai" else "Openai"
    Google_TTS_gebruiken = True if nieuwe_status == "Google" else False
    print("TTS door middel van ", nieuwe_status)
    return nieuwe_status, nieuwe_status

def toggle_taal_model(huidige_status):
    nieuwe_status = "gpt-3.5-turbo" if huidige_status == "gpt-4o" else "gpt-4o"
    print("Gebruikt ChatGPT model:", nieuwe_status)
    return nieuwe_status, nieuwe_status

def mentor_audio_2_text(audio_file):
    recognizer = sr.Recognizer()

    if audio_file is None:
        return "Geen audio ontvangen.", "", None

    audio = AudioSegment.from_file(audio_file, format="wav")
    wav_io = io.BytesIO()
    audio.export(wav_io, format="wav")
    wav_io.seek(0)

    with sr.AudioFile(wav_io) as source:
        try:
            audio_data = recognizer.record(source)
            text = recognizer.recognize_google(audio_data, language="nl-NL")
            if Log_aan:
                print("Ingesproken rol van de ondernemer :", text)
            return text
        except Exception as e:
            return "Fout bij spraakherkenning of verwerking.", str(e), None
    
def transcribe_and_respond(audio_file, klant_profiel):
    if Log_aan:
        print("functie TTS en AI antwoord gestart")
        start = time.time()
    
    recognizer = sr.Recognizer()

    if audio_file is None:
        return "Geen audio ontvangen.", "", None

    audio = AudioSegment.from_file(audio_file, format="wav")
    wav_io = io.BytesIO()
    audio.export(wav_io, format="wav")
    wav_io.seek(0)

    with sr.AudioFile(wav_io) as source:
        try:
            audio_data = recognizer.record(source)
            text = recognizer.recognize_google(audio_data, language="nl-NL")
            if Log_aan:
                print("Ingesproken tekst :", text)
        except Exception as e:
            return "Fout bij spraakherkenning of verwerking.", str(e), None

    if Log_aan:        
         print(f"Audio to text is klaar in {time.time() - start:.2f} seconden")

    try:
        response = client.chat.completions.create(
            model= AI_taal_model,
            messages=[
                {"role": "system", "content": f"Je speelt de rol van een MKB ondernemer en een potentiële klant in een professioneel gesprek. {klant_profiel}. Geef korte, duidelijke antwoorden van maximaal 2 zinnen. Sluit elk antwoord volledig af"},
                {"role": "user", "content": text}
            ],
            temperature=0.7,
            max_tokens = 100,
            stream=True
        )
#        ai_reply = response.choices[0].message.content
        ai_reply = ""
        for chunk in response:
            if chunk.choices and chunk.choices[0].delta.content:
                ai_reply += chunk.choices[0].delta.content 
                
        if Log_aan:
            print("AI antwoordtekst :", ai_reply)        
            print(f"AI antwoord tekst is klaar in {time.time() - start:.2f} seconden")

    except Exception as e:
        return text, "Fout bij AI-chatgeneratie.", None

    try:    
        bestand = tempfile.NamedTemporaryFile(delete=False, suffix=".mp3")
        
        if Google_TTS_gebruiken:
            tts = gTTS(text=ai_reply, lang='nl')    
            tts.save(bestand.name)
        else: 
            response = client.audio.speech.create(
                model="tts-1",
                voice="nova",  # Of bijv. alloy, echo, fable
                input=ai_reply
            )
            with open(bestand.name, "wb") as f:
                for chunk in response.iter_bytes():
                    f.write(chunk)
        
#            bestand = tempfile.NamedTemporaryFile(delete=False, suffix=".mp3")
#            response.stream_to_file(bestand.name)
#            vertraagd_pad = slow_down_audio(bestand.name)

        if Log_aan:        
            print(f"AI tekst to audio is klaar in {time.time() - start:.2f} seconden")
    
        return text, ai_reply, bestand.name
    except Exception as e:
        return "Fout bij spraakgeneratie.", str(e), None

def slow_down_audio(input_file):
    if Log_aan:
        print("slow_douwn_audio functie gestart")
    speed = 0.3                                 # 0.30 = 70% trager
    sound = AudioSegment.from_file(input_file)
    new_frame_rate = int(sound.frame_rate * speed)
    slowed_sound = sound._spawn(sound.raw_data, overrides={
         "frame_rate": new_frame_rate
    }).set_frame_rate(sound.frame_rate)  # om pitch gelijk te houden

    output_file = tempfile.NamedTemporaryFile(delete=False, suffix=".mp3")
    slowed_sound.export(output_file.name, format="mp3")
    return output_file.name

def ai_evaluation():
    print("AI evaluatie gestart")

with gr.Blocks(css="""
body {
    font-family: 'Poppins', sans-serif;
    background-color: #c7e5f3;
}
#logo {
    width: 120px;
    margin: 10px;
}
.instructions {
    background-color: #008bce;
    color: white;
    padding: 12px;
    border-radius: 5px;
    font-size: 16px;
}
""") as demo:
    if Log_aan:
        with gr.Row():
            with gr.Column(scale=1):
                status = gr.State("Google")  # startwaarde
                output_vak = gr.Textbox(value="Google", label="Soort Text-2-Speech", interactive=False)
                toggle_knop = gr.Button("Wissel tussen Google/Openai").click(fn=toggle_google_openai, inputs=status, outputs=[output_vak, status])
            with gr.Column(scale=1):
                status = gr.State("gpt-3.5-turbo")  # startwaarde
                output_vak = gr.Textbox(value=status, label="Soort Text-2-Speech", interactive=False)
                toggle_knop = gr.Button("Wissel tussen gpt-3.5-turbo en gpt-4o").click(fn=toggle_taal_model, inputs=status, outputs=[output_vak, status])
            with gr.Column(scale=1):
                gr.Button("optie 3")
            with gr.Column(scale=1):
                gr.Button("optie 4")
    
    with gr.Row():
        with gr.Column(scale=2):
            gr.HTML("<div class='instructions'><b>Definieer eerst je prospect en start daarna het gesprek.</b> De AI reageert automatisch.</div>")
        with gr.Column(scale=1):
            gr.Button("Verander Tekst2Speech techniek")
        with gr.Column(scale=2, min_width=250):
            gr.Image(value="thexton_logo_resized.png", elem_id="logo", show_label=False, show_download_button=False)
            
    with gr.Row():
        with gr.Column(scale=1):
            klant_input = gr.Audio(label="🎤 Beschrijf je klant", type="filepath")
        with gr.Column(scale=1):
            klantbeschrijving = gr.Textbox(label="Zo heb je de klant gedefinieerd")
        with gr.Column(scale=2):
            gr.Button("Stop gesprek en start evaluatie").click(fn=ai_evaluation)
            
    with gr.Row():
        audio_input = gr.Audio(label="🎤 Spreek hier in", type="filepath")
        transcript = gr.Textbox(label="Herkenning van jouw spraak")
        ai_response = gr.Textbox(label="AI-reactie")
        ai_uitgesproken = gr.Audio(label="🎧 AI-reactie uitgesproken", type="filepath")
        
 #   toggle_knop.click(fn=toggle_google_openai, inputs=status, outputs=[output_vak, status])
    klant_input.change(fn=mentor_audio_2_text, inputs=[klant_input], outputs=[klantbeschrijving])
    audio_input.change(fn=transcribe_and_respond, inputs=[audio_input, klantbeschrijving], outputs=[transcript, ai_response, ai_uitgesproken])

demo.launch()