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

# Load models
sentiment_pipeline = pipeline("sentiment-analysis", model="distilbert-base-uncased-finetuned-sst-2-english")
summarization_pipeline = pipeline("summarization", model="facebook/bart-large-cnn")

# Task logic
def perform_task(task, text):
    if not text.strip():
        return "⚠️ Please enter some text.", None

    if task == "Sentiment Analysis":
        result = sentiment_pipeline(text)[0]
        label = result['label']
        score = round(result['score'], 3)
        return f"🧠 Sentiment: {label}\n📊 Confidence: {score}", None

    elif task == "Summarization":
        result = summarization_pipeline(text, max_length=100, min_length=30, do_sample=False)
        return f"✂️ Summary:\n{result[0]['summary_text']}", None

    elif task == "Text-to-Speech":
        tts = gTTS(text)
        filename = "tts_output.mp3"
        tts.save(filename)
        return "✅ Audio generated below:", filename

# UI with custom dark mode
with gr.Blocks(theme=gr.themes.Base()) as demo:
    # Custom CSS for dark mode
    gr.HTML("""
    <style>
        body, .gradio-container {
            background-color: #111 !important;
            color: #eee !important;
        }
        .gr-input, .gr-button, .gr-box {
            background-color: #222 !important;
            color: #eee !important;
            border: 1px solid #444 !important;
        }
        input::placeholder, textarea::placeholder {
            color: #888 !important;
        }
    </style>
    """)

    gr.Markdown("# 🤖 Multi-Task Chatbot", elem_id="title")

    with gr.Row():
        task_selector = gr.Dropdown(
            ["Sentiment Analysis", "Summarization", "Text-to-Speech"],
            label="Select Task",
            value="Sentiment Analysis"
        )

    textbox = gr.Textbox(lines=6, label="Enter your text here")
    output_text = gr.Textbox(label="Output Message")
    output_audio = gr.Audio(label="Generated Speech", type="filepath", visible=False)
    run_button = gr.Button("Run")

    def handle_all(task, text):
        message, audio_path = perform_task(task, text)
        return message, gr.update(value=audio_path, visible=audio_path is not None)

    run_button.click(fn=handle_all, inputs=[task_selector, textbox], outputs=[output_text, output_audio])

demo.launch()