from transformers import pipeline
import gradio as gr
from gtts import gTTS

# Sentiment Analysis
sentiment = pipeline("sentiment-analysis")

def get_sentiment(text):
    result = sentiment(text)[0]
    return result["label"], result["score"]

sentiment_tab = gr.Interface(
    fn=get_sentiment,
    inputs=gr.Textbox(label="Enter your review: "),
    outputs=[gr.Textbox(label="Sentiment"), gr.Number(label="Score")],
    title="Reviews Sentiment Analysis"
)

# Summarization
summarize = pipeline("summarization", model="facebook/bart-large-cnn")

def summarization(text):
    return summarize(text)[0]["summary_text"]

summary_tab = gr.Interface(
    fn=summarization,
    inputs=gr.Textbox(label="Enter your text: "),
    outputs=gr.Textbox(label="Summarization"),
    title="Summarizer"
)

# Text to Speech
def convert(text):
    tts = gTTS(text)
    file_path = "output.mp3"
    tts.save(file_path)
    return file_path

text_to_speech_tab = gr.Interface(
    fn=convert,
    inputs=gr.Textbox(label="Enter your text to turn into audio:"),
    outputs=gr.Audio(label="Generated Audio", type="filepath"),
    title="Text to Speech Converter"
)

# Combine all in Tabs
demo = gr.TabbedInterface(
    [sentiment_tab, summary_tab, text_to_speech_tab],
    ["Sentiment", "Summarizer", "Text-To-Speech"],
    theme="soft"
)

if __name__ == "__main__":
    demo.launch()