Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+
+# Load the sentiment analysis model
+sentiment_analysis = pipeline(
+  "sentiment-analysis",
+  framework="pt",
+  model="SamLowe/roberta-base-go_emotions"
+)
+
+def analyze_sentiment(text):
+  results = sentiment_analysis(text)
+  # Sort the results by score in descending order
+  sorted_results = sorted(results, key=lambda x: x['score'], reverse=True)
+  # Select the top 3 labels and their scores
+  top_3_labels_scores = {result['label']: result['score'] for result in sorted_results[:3]}
+  return top_3_labels_scores
+
+def get_sentiment_emoji(sentiment):
+  emoji_mapping = {
+    "disappointment": "😞",
+    "sadness": "😢",
+    "annoyance": "😠",
+    "neutral": "😐",
+    "disapproval": "👎",
+    "realization": "😮",
+    "nervousness": "😬",
+    "approval": "👍",
+    "joy": "😄",
+    "anger": "😡",
+    "embarrassment": "😳",
+    "caring": "🤗",
+    "remorse": "😔",
+    "disgust": "🤢",
+    "grief": "😥",
+    "confusion": "😕",
+    "relief": "😌",
+    "desire": "😍",
+    "admiration": "😌",
+    "optimism": "😊",
+    "fear": "😨",
+    "love": "❤️",
+    "excitement": "🎉",
+    "curiosity": "🤔",
+    "amusement": "😄",
+    "surprise": "😲",
+    "gratitude": "🙏",
+    "pride": "🦁"
+  }
+  return emoji_mapping.get(sentiment, "")
+
+def display_sentiment_results(sentiment_results, option):
+    sentiment_text = ""
+    for sentiment, score in sentiment_results.items():
+        emoji = get_sentiment_emoji(sentiment)
+        score_percentage = score * 100
+        if option == "Sentiment Only":
+            sentiment_text += f"{sentiment} {emoji}\n"
+        elif option == "Sentiment + Score":
+            sentiment_text += f"{sentiment} {emoji}: {score_percentage:.2f}%\n"
+    return sentiment_text
+
+def inference(text_input, sentiment_option):
+    sentiment_results = analyze_sentiment(text_input)
+    sentiment_output = display_sentiment_results(sentiment_results, sentiment_option)
+
+    return sentiment_output
+
+title = "🎤 Gradio UI"
+description = "we have deployed our model on Gradio"
+
+block = gr.Blocks()
+
+with block:
+    gr.Markdown("#  🕵️")
+    gr.Markdown("Between the Lines, Emotions Speak 🤫📖 - Decode the Silent Echoes with Mood Reader 🕵️‍♂️💬 Every Sentence with Mood Reader 🕵️‍♂️💬")
+    with gr.Column():
+        text_input = gr.Textbox(label="Input Text", lines=4)
+        sentiment_option = gr.Radio(choices=["Sentiment Only", "Sentiment + Score"], label="Select an option")
+        analyze_btn = gr.Button("Analyze")
+    sentiment_output = gr.Textbox(label="Sentiment Analysis Results")
+
+    analyze_btn.click(
+        inference,
+        inputs=[text_input, sentiment_option],
+        outputs=[sentiment_output]
+    )
+
+block.launch()