Create app.py

app.py

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+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()