import openai
import gradio as gr
from gtts import gTTS
from io import BytesIO
from IPython.display import Audio, display
import os

# Set OpenAI API key
openai.api_key = os.environ.get("OPENAI_API_KEY")

# Set OpenAI GPT-3 model
MODEL = "gpt-3.5-turbo"

# Load chat history from file
with open("chat_history.txt", "r") as f:
    chat_history = f.read().strip()

# Define chatbot response function
def chatbot_response(text_input, voice_input):
    # Concatenate text and voice input
    input_text = text_input + " " + voice_input

    # Concatenate input text with chat history
    input_text_with_history = input_text + "\n\n" + chat_history

    # Use OpenAI API to generate response
    response = openai.Completion.create(
        model=MODEL,
        prompt=input_text_with_history,
        max_tokens=3000,
        n=1,
        stop=None,
        temperature=0.5
    )

    # Extract response text from OpenAI API output
    response_text = response.choices[0].text.strip()

    # Convert response text to speech
    tts = gTTS(text=response_text)
    audio_bytes = BytesIO()
    tts.write_to_fp(audio_bytes)
    audio_bytes.seek(0)
    response_audio = Audio(audio_bytes, autoplay=True)

    # Update chat history with input and response text
    global chat_history
    chat_history += f"\n\nUser: {text_input}\nChatbot: {response_text}"

    # Save chat history to file
    with open("chat_history.txt", "w") as f:
        f.write(chat_history)

    # Return response text and audio for display in interface
    return response_text, response_audio

# Define chatbot interface
chatbot_interface = gr.Interface(
    fn=chatbot_response,
    inputs=["text", gr.inputs.Microphone(type="live", duration=10)],
    outputs=["text", "audio"],
    title="Chatbot",
    description="Talk to the chatbot using text and speech inputs."
)

# Launch chatbot interface
chatbot_interface.launch()