Create app.py

app.py

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+import warnings
+warnings.filterwarnings('ignore')
+import transformers
+import gradio as gr
+from transformers import pipeline
+from TTS.api import TTS
+
+#1 - Sentiment Analysis Tab:  
+sentiment =pipeline("text-classification", model="tabularisai/multilingual-sentiment-analysis")
+
+def get_sentiment(text):
+    result = sentiment(text)
+    label = result[0]['label']
+    score = result[0]['score']
+    return label, score
+
+#2 - Summarization Tab:  
+summary_pipe = pipeline("summarization", model="facebook/bart-large-cnn")
+
+def get_summary(text):
+    result = summary_pipe(text[:1000])
+    return result[0]['summary_text']
+
+#3 - text-to-Speech Tab:
+tts_model= TTS("tts_models/en/ljspeech/tacotron2-DDC", gpu=False)
+
+def text_to_speech(text):
+    filename = "output.wav"
+    tts_model.tts_to_file(text=text, file_path=filename)
+    return filename
+
+
+with gr.Blocks() as AI_applications:
+    with gr.Tab("Sentiment Analysis"):
+        sentiment_input = gr.Textbox(label="Enter Text")
+        output_label = gr.Text(label="Sentiment Label")
+        output_score = gr.Text(label="Confidence Score")
+        analyze_button = gr.Button("Analyze Sentiment")
+        analyze_button.click(fn=get_sentiment,inputs=sentiment_input ,outputs=[output_label, output_score])
+
+    with gr.Tab("Summarization"):
+
+        summary_input  = gr.Textbox(label="Enter Long Text", lines=10, placeholder="Paste your text here...")
+        output_summary = gr.Textbox(label="Summary", lines=5)
+        summarize_btn  = gr.Button("Summarize")
+        summarize_btn .click(fn=get_summary, inputs=summary_input, outputs=output_summary)
+
+    with gr.Tab("Text to Speech"):
+
+        tts_input = gr.Textbox(label="Enter Text to Speak", lines=4, placeholder="Type something...")
+        output_audio = gr.Audio(label="Generated Speech", type="filepath")
+        generate_btn = gr.Button("Generate Speech")
+        generate_btn.click(fn=text_to_speech, inputs=tts_input , outputs=output_audio)
+
+AI_applications.launch()