Update app.py

app.py

@@ -1,49 +1,52 @@
 import gradio as gr
 from transformers import pipeline
 from gtts import gTTS
+import tempfile
 
-# تحميل النماذج من Hugging Face
+# Load models from Hugging Face
 sentiment_model = pipeline("sentiment-analysis")
 summarizer_model = pipeline("summarization")
 
-# دالة تحليل المشاعر
+# Sentiment analysis function
 def analyze_sentiment(text):
     result = sentiment_model(text)[0]
     label = result['label']
     score = round(result['score'], 2)
     return f"Sentiment: {label}, Confidence: {score}"
 
-# دالة التلخيص
+# Summarization function
 def summarize_text(text):
     summary = summarizer_model(text, max_length=60, min_length=15, do_sample=False)
     return summary[0]['summary_text']
 
-# دالة تحويل النص إلى صوت
+# Text-to-speech function
 def text_to_speech(text):
-    filename = "output_audio.mp3"
     tts = gTTS(text)
-    tts.save(filename)
-    return filename
+    with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as fp:
+        tts.save(fp.name)
+        return fp.name
 
-# بناء الواجهة بـ Gradio
+# Build Gradio interface with Tabs
 with gr.Blocks() as demo:
-    gr.Markdown("## 🧠 NLP Tools: Sentiment Analysis | Summarization | Text-to-Speech")
-
-    with gr.Row():
-        input_text = gr.Textbox(label="Enter your text", lines=6, placeholder="Type or paste your text here...")
-
-    with gr.Row():
-        btn_sentiment = gr.Button("🔍 Analyze Sentiment")
-        btn_summarize = gr.Button("📝 Summarize")
-        btn_tts = gr.Button("🔊 Convert to Speech")
-
-    with gr.Row():
-        output_sentiment = gr.Textbox(label="Sentiment Result")
-        output_summary = gr.Textbox(label="Summary")
-        output_audio = gr.Audio(label="Text to Speech Output")
-
-    btn_sentiment.click(analyze_sentiment, inputs=input_text, outputs=output_sentiment)
-    btn_summarize.click(summarize_text, inputs=input_text, outputs=output_summary)
-    btn_tts.click(text_to_speech, inputs=input_text, outputs=output_audio)
+    gr.Markdown("## 📘 Homework - Tuwaiq Academy")
+
+    with gr.Tabs():
+        with gr.TabItem("🔍 Sentiment Analysis"):
+            input_sentiment = gr.Textbox(label="Enter your text", lines=6, placeholder="Type your text here...")
+            output_sentiment = gr.Textbox(label="Sentiment Result")
+            btn_sentiment = gr.Button("Analyze Sentiment")
+            btn_sentiment.click(analyze_sentiment, inputs=input_sentiment, outputs=output_sentiment)
+
+        with gr.TabItem("📝 Summarization"):
+            input_summary = gr.Textbox(label="Enter your text", lines=6, placeholder="Type your text here...")
+            output_summary = gr.Textbox(label="Summary")
+            btn_summarize = gr.Button("Summarize")
+            btn_summarize.click(summarize_text, inputs=input_summary, outputs=output_summary)
+
+        with gr.TabItem("🔊 Text to Speech"):
+            input_tts = gr.Textbox(label="Enter your text", lines=6, placeholder="Type your text here...")
+            output_audio = gr.Audio(label="Speech Output", type="filepath")
+            btn_tts = gr.Button("Convert to Speech")
+            btn_tts.click(text_to_speech, inputs=input_tts, outputs=output_audio)
 
 demo.launch()