import gradio as gr
from transformers import pipeline
import soundfile as sf
from huggingface_hub import InferenceClient

# Initialize Facebook MMS ASR model
asr_model = pipeline("automatic-speech-recognition", model="facebook/mms-1b-all")

# Initialize Facebook MMS TTS model
tts_model = pipeline("text-to-speech", model="facebook/mms-tts")

# Initialize the Chat Model (Gemma-2-9B or Futuresony.gguf)
chat_client = InferenceClient("Futuresony/future_ai_12_10_2024.gguf")  # Change if needed

def asr_chat_tts(audio):
    """
    1. Convert Speech to Text (ASR)
    2. Process text through Chat Model (LLM)
    3. Convert response to Speech (TTS)
    """
    # Step 1: Transcribe speech using Facebook MMS ASR
    transcription = asr_model(audio)["text"]

    # Step 2: Process text through the chat model
    messages = [{"role": "system", "content": "You are a helpful AI assistant."}]
    messages.append({"role": "user", "content": transcription})

    response = ""
    for msg in chat_client.chat_completion(messages, max_tokens=512, stream=True):
        token = msg.choices[0].delta.content
        response += token

    # Step 3: Convert response to speech using Facebook MMS TTS
    speech = tts_model(response)
    output_file = "generated_speech.wav"
    sf.write(output_file, speech["audio"], samplerate=speech["sampling_rate"])

    return transcription, response, output_file

# Gradio Interface
with gr.Blocks() as demo:
    gr.Markdown("<h2 style='text-align: center;'>ASR → Chatbot → TTS</h2>")
    
    with gr.Row():
        audio_input = gr.Audio(source="microphone", type="filepath", label="🎤 Speak Here")
        text_transcription = gr.Textbox(label="📝 Transcription", interactive=False)
        text_response = gr.Textbox(label="🤖 Chatbot Response", interactive=False)
        audio_output = gr.Audio(label="🔊 Generated Speech")

    submit_button = gr.Button("Process Speech 🔄")

    submit_button.click(fn=asr_chat_tts, inputs=[audio_input], outputs=[text_transcription, text_response, audio_output])

# Run the App
if __name__ == "__main__":
    demo.launch()