app.py

import gradio as gr #importing the necessary libraries
from transformers import pipeline

sentiment_pipeline = pipeline("sentiment-analysis") #importing the model that we will use to work at, as explained in the output terminal
chatbot_pipeline = pipeline("text-generation")
summarization_pipeline = pipeline("summarization", model="t5-small")  # T5 for summarization

# Sentiment Analysis function 
def analyze_sentiment(text):
    result = sentiment_pipeline(text)[0]
    return result["label"], round(result["score"], 2)

def generate_response(user_input):
    response = chatbot_pipeline(user_input, max_length=100, num_return_sequences=1)
    return response[0]['generated_text']

# Summarization function
def summarize_text(long_text):
    summary = summarization_pipeline(long_text, max_length=50, min_length=25, do_sample=False)
    return summary[0]["summary_text"]

# Speech-to-Text function
def text_to_speech(text):
    from gtts import gTTS
    import os
    tts = gTTS(text)
    tts.save("output.mp3")
    return "output.mp3"


with gr.Blocks() as demo:
    gr.Markdown("# Multi-Task AI App with Alternative Models")
    with gr.Tabs():
        # tab for Sentiment Analysis 
        with gr.Tab("Sentiment Analysis"):
            gr.Markdown("### Sentiment Analysis")
            sentiment_input = gr.Textbox(label="Enter Text for Sentiment Analysis")
            sentiment_output_label = gr.Textbox(label="Sentiment")
            sentiment_output_score = gr.Textbox(label="Confidence Score")
            gr.Button("Analyze").click(analyze_sentiment, inputs=sentiment_input, outputs=[sentiment_output_label, sentiment_output_score])
        
        # tab for chatbot
        with gr.Tab("Chatbot"):
            gr.Markdown("### Chatbot")
            chatbot_input = gr.Textbox(label="Enter Your Message")
            chatbot_output = gr.Textbox(label="Chatbot Response", lines=5)
            gr.Button("Send").click(chatbot_response, inputs=chatbot_input, outputs=chatbot_output)
        
        # tab for summarization
        with gr.Tab("Summarization"):
            gr.Markdown("### Summarization")
            summarization_input = gr.Textbox(label="Enter Long Text for Summarization", lines=5)
            summarization_output = gr.Textbox(label="Summary", lines=5)
            gr.Button("Summarize").click(summarize_text, inputs=summarization_input, outputs=summarization_output)
        
        # tab for STT
        with gr.Tab("Speech-to-Text"):
            gr.Markdown("### Text-to-Speech")
            tts_input = gr.Textbox(label="Enter Text for Text-to-Speech")
            tts_output = gr.Audio(label="Generated Speech")
            gr.Button("Convert to Speech").click(text_to_speech, inputs=tts_input, outputs=tts_output)


demo.launch()