Create app.py

app.py

@@ -0,0 +1,77 @@
+import gradio as gr
+from transformers import pipeline
+
+# Load pre-trained models
+sentiment_model = pipeline("sentiment-analysis")
+chatbot_model = pipeline("text-generation", model="microsoft/DialoGPT-medium")
+summarization_model = pipeline("summarization")
+text_to_speech_model = pipeline("text-to-speech")
+
+# Sentiment Analysis Function
+def analyze_sentiment(text):
+    result = sentiment_model(text)[0]
+    return result["label"], round(result["score"], 4)
+
+# Chatbot Function
+chat_history = []
+def chatbot_response(user_input):
+    global chat_history
+    response = chatbot_model(f"User: {user_input} Chatbot:", max_length=100, num_return_sequences=1)
+    chat_history.append(f"User: {user_input}")
+    chat_history.append(f"Bot: {response[0]['generated_text']}")
+    return "\n".join(chat_history)
+
+# Summarization Function
+def summarize_text(text):
+    summary = summarization_model(text, max_length=150, min_length=50, do_sample=False)
+    return summary[0]["summary_text"]
+
+# Text-to-Speech Function
+def text_to_speech(text):
+    audio_output = text_to_speech_model(text)
+    return audio_output["audio"]
+
+# Create Gradio Interface with Tabs
+with gr.Blocks(theme="dark") as app:
+    gr.Markdown("# 🚀 Multi-Tab Language Application")
+    
+    with gr.Tabs():
+        # Sentiment Analysis Tab
+        with gr.Tab("Sentiment Analysis"):
+            gr.Markdown("## 📊 Sentiment Analysis")
+            text_input = gr.Textbox(label="Enter text:")
+            sentiment_output = gr.Textbox(label="Sentiment")
+            confidence_output = gr.Textbox(label="Confidence Score")
+            analyze_button = gr.Button("Analyze")
+            
+            analyze_button.click(analyze_sentiment, inputs=text_input, outputs=[sentiment_output, confidence_output])
+
+        # Chatbot Tab
+        with gr.Tab("Chatbot"):
+            gr.Markdown("## 🤖 Chatbot")
+            chatbot_input = gr.Textbox(label="Chat with AI")
+            chatbot_output = gr.Textbox(label="Response", interactive=False)
+            chat_button = gr.Button("Send")
+            
+            chat_button.click(chatbot_response, inputs=chatbot_input, outputs=chatbot_output)
+
+        # Summarization Tab
+        with gr.Tab("Summarization"):
+            gr.Markdown("## ✍️ Text Summarization")
+            summary_input = gr.Textbox(label="Enter long text:", lines=5)
+            summary_output = gr.Textbox(label="Summary", interactive=False)
+            summarize_button = gr.Button("Summarize")
+            
+            summarize_button.click(summarize_text, inputs=summary_input, outputs=summary_output)
+
+        # Text-to-Speech Tab
+        with gr.Tab("Text-to-Speech"):
+            gr.Markdown("## 🎙️ Text-to-Speech")
+            tts_input = gr.Textbox(label="Enter text to convert to speech:")
+            tts_output = gr.Audio(label="Generated Speech", autoplay=True)
+            tts_button = gr.Button("Convert to Speech")
+
+            tts_button.click(text_to_speech, inputs=tts_input, outputs=tts_output)
+
+# Launch the application
+app.launch()