# Required Libraries
import os
import tempfile
import whisper
from groq import Groq
from gtts import gTTS
import gradio as gr
from pydub import AudioSegment

# ---------------------------
# 🔑 API Key Configuration
# ---------------------------
os.environ['GROQ_API_KEY'] = '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'

# ---------------------------
# 📥 Load Whisper Model
# ---------------------------
try:
    whisper_model = whisper.load_model("base")
    print("[INFO] Whisper model loaded successfully.")
except AttributeError:
    from whisper import Whisper
    whisper_model = Whisper.load_model("base")
    print("[INFO] Whisper model loaded using alternative syntax.")

# ---------------------------
# 🎙️ Audio Processing
# ---------------------------

def validate_audio_file(audio_file):
    """Validate if the audio file exists and is not empty."""
    if not audio_file or not os.path.exists(audio_file) or os.path.getsize(audio_file) == 0:
        print(f"[ERROR] Invalid or empty audio file: {audio_file}")
        return False
    return True


def convert_to_wav(audio_file):
    """Convert audio file to WAV format if needed."""
    try:
        audio = AudioSegment.from_file(audio_file)
        wav_path = tempfile.NamedTemporaryFile(suffix=".wav", delete=False).name
        audio.export(wav_path, format="wav")
        print(f"[INFO] Audio converted to WAV: {wav_path}")
        return wav_path
    except Exception as e:
        print(f"[ERROR] Audio Conversion Error: {e}")
        return None


def transcribe_audio(audio_file):
    """Transcribe audio using Whisper."""
    try:
        print(f"[INFO] Transcribing audio file: {audio_file}")
        if not validate_audio_file(audio_file):
            raise FileNotFoundError("Audio file not found or invalid path.")
        
        audio_file = convert_to_wav(audio_file)
        if not audio_file:
            raise Exception("Failed to convert audio to WAV format.")
        
        result = whisper_model.transcribe(audio_file)
        print(f"[INFO] Transcription result: {result['text']}")
        return result['text']
    except Exception as e:
        print(f"[ERROR] Transcription Error: {e}")
        return f"Transcription Error: {e}"


# ---------------------------
# 🤖 LLM Interaction
# ---------------------------

def get_groq_response(user_input):
    """Get chatbot response from Groq's API."""
    try:
        print(f"[INFO] Sending input to Groq: {user_input}")
        client = Groq(api_key=os.environ['GROQ_API_KEY'])
        chat_completion = client.chat.completions.create(
            messages=[
                {"role": "user", "content": user_input}
            ],
            model="llama-3.3-70b-versatile",
            stream=False,
        )
        response = chat_completion.choices[0].message.content
        print(f"[INFO] Groq response: {response}")
        return response
    except Exception as e:
        print(f"[ERROR] Groq API Error: {e}")
        return f"Groq API Error: {e}"


# ---------------------------
# 🗣️ Text-to-Speech
# ---------------------------

def text_to_speech(text):
    """Convert text to speech using gTTS."""
    try:
        print(f"[INFO] Converting text to speech: {text}")
        tts = gTTS(text)
        audio_path = tempfile.NamedTemporaryFile(suffix=".mp3", delete=False).name
        tts.save(audio_path)
        print(f"[INFO] Audio file saved: {audio_path}")
        return audio_path
    except Exception as e:
        print(f"[ERROR] TTS Error: {e}")
        return f"TTS Error: {e}"


# ---------------------------
# 🛠️ Main Interaction Logic
# ---------------------------

def chatbot(audio_input):
    """Handle full chatbot interaction."""
    try:
        print(f"[INFO] Audio Input Path: {audio_input}")
        
        # Validate Audio File
        if not validate_audio_file(audio_input):
            return "Error: Audio file not found or invalid path", None

        # Step 1: Transcribe Audio
        text_input = transcribe_audio(audio_input)
        if "Error" in text_input:
            return text_input, None

        # Step 2: Get Response from Groq
        llm_response = get_groq_response(text_input)
        if "Error" in llm_response:
            return llm_response, None

        # Step 3: Convert Response to Audio
        audio_output = text_to_speech(llm_response)
        if "Error" in audio_output:
            return audio_output, None

        return llm_response, audio_output
    except Exception as e:
        print(f"[ERROR] General Error: {e}")
        return f"General Error: {e}", None


# ---------------------------
# 🌐 Gradio Interface
# ---------------------------

interface = gr.Interface(
    fn=chatbot,
    inputs=gr.Audio(type="filepath"),
    outputs=[
        gr.Textbox(label="LLM Response"),
        gr.Audio(label="Audio Response")
    ],
    title="Real-Time Voice-to-Voice Chatbot",
    description="Speak into the microphone, and the chatbot will respond with audio.",
    live=True  # Ensures real-time interaction
)

# Launch Gradio App
if __name__ == "__main__":
    print("[INFO] Starting Gradio Interface...")
    interface.launch(share=True)