Update app.py

app.py

@@ -4,12 +4,12 @@ from transformers import pipeline, AutoModelForSequenceClassification, AutoToken
 # Model name
 model_name = "ElKulako/cryptobert"
 
-# Load model and tokenizer explicitly to prevent errors
+# Load model and tokenizer explicitly
 try:
     model = AutoModelForSequenceClassification.from_pretrained(model_name)
     tokenizer = AutoTokenizer.from_pretrained(model_name)
 
-    # Load the pipeline
+    # Load sentiment pipeline
     sentiment_pipeline = pipeline(
         "text-classification",
         model=model,
@@ -25,10 +25,10 @@ def analyze(text):
         return {"error": "No text provided."}
 
     try:
-        # Get the model's initial prediction
+        # Get model's prediction
         result = sentiment_pipeline(text)[0]
         
-        # Override logic for crypto-specific keywords (case-insensitive)
+        # Override logic for crypto-related keywords (case-insensitive)
         text_lower = text.lower()
         
         # Force "positive" for bullish terms
@@ -52,11 +52,11 @@ gr.Interface(
     fn=analyze,
     inputs=gr.Textbox(placeholder="Enter crypto news headline..."),
     outputs=gr.JSON(),
-    title="Crypto-Specific Sentiment Analysis",
-    description="Analyzes sentiment of crypto news headlines. Overrides neutral predictions for key terms like 'ETF approved' or 'SEC lawsuit'.",
-    allow_flagging="never"
+    title="Crypto Sentiment Analysis",
+    description="Analyzes sentiment of crypto-related news headlines.",
+    flagging_mode="never"  # Fixed deprecated warning
 ).launch(
     server_name="0.0.0.0",
-    server_port=7860,
-    enable_queue=True  # Ensures API requests are handled properly
+    server_port=7860
 )
+