Creating app.py file

app.py

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+import gradio as gr
+import torch
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+
+# Defining the model path relative to the repository root.
+#model_path = "abdullah123456/NLP_Project"
+#model_path = "nlptown/bert-base-multilingual-uncased-sentiment"
+model_path = "abdullah123456/NLP_Project_SA"
+
+# Loading the model and tokenizer from the local directory.
+model = AutoModelForSequenceClassification.from_pretrained(model_path)
+tokenizer = AutoTokenizer.from_pretrained(model_path)
+
+
+# Defining a simple text cleaning function
+def clean_text(text):
+    return " ".join(text.split())
+    
+
+# Defining the prediction function that the web interface will use.
+def predict_sentiment(tweet: str) -> str:
+
+    # Cleaning the tweet
+    tweet_clean = clean_text(tweet)
+
+    # Tokenizing the tweet. 
+    inputs = tokenizer(tweet_clean, return_tensors="pt", truncation=True, padding="max_length", max_length=128)
+
+    # Moving the input tensors to the same device as the model.
+    inputs = {k: v.to(model.device) for k, v in inputs.items()}
+
+    with torch.no_grad():
+        outputs = model(**inputs)
+    # Getting the predicted class index.
+    predicted_class = torch.argmax(outputs.logits, dim=1).item()
+    
+    # Defining label mapping.
+    label_mapping = {0: "negative", 1: "neutral", 2: "positive"}
+    return label_mapping.get(predicted_class, "unknown")
+
+# Creating the Gradio Interface.
+iface = gr.Interface(
+    fn=predict_sentiment,
+    inputs=gr.Textbox(lines=4, placeholder="Enter an Urdu tweet here...", label="Urdu Tweet"),
+    outputs=gr.Textbox(label="Predicted Sentiment"),
+    title="Urdu Tweet Sentiment Analysis",
+    description="This app uses a fine-tuned transformer model to predict the sentiment of Urdu tweets. "
+                "Enter your tweet in the textbox below and click 'Submit' to see the prediction.",
+    examples=[
+        ["السلام علیکم! آج کا دن بہت خوبصورت ہے۔"],
+        ["میں بہت غمگین ہوں، دل بہت دکھ رہا ہے۔"],
+        ["آپ کا کام بہت اچھا ہے!"]
+    ]
+)
+
+# Launching the interface.
+if __name__ == "__main__":
+    iface.launch()