Update app.py

app.py

@@ -25,12 +25,17 @@ labels = [
     "education", "engineering", "entertainment", "environment",
     "fashion", "finance", "food commerce", "general",
     "gaming", "healthcare", "history", "html",
-    "information technology", "IT", "keywords", "legal",
+    "information technology", "keywords", "legal",
     "literature", "machine learning", "marketing", "medicine",
-    "music", "personal development", "philosophy", "physics",
-    "politics", "poetry", "programming", "real estate", "retail", 
+    "music", "philosophy", "physics", "politics", "programming", "real estate", "retail", 
     "robotics", "slang", "social media", "speech", "sports",
-    "sustained", "technical", "theater", "tourism", "travel"
+    "technical", "theater", "tourism", "travel"
+]
+
+styles = [
+    "formal", "positive", "negative", "poetic", "polite", "subtle", "casual", "neutral",
+    "informal", "pompous", "sustained", "rude", "sustained",
+    "sophisticated", "playful", "serious", "friendly"
 ]
 
 @lru_cache(maxsize=1)
@@ -58,6 +63,11 @@ def detect_context(input_text, top_n=3):
     # Compute cosine similarities
     similarities = cosine_similarity(input_embedding, label_embeddings)[0]
 
+    # Debugging: Print all labels and their similarity scores
+    print("Debug: Similarity scores for all labels:")
+    for label, score in zip(labels, similarities):
+        print(f"{label}: {score:.4f}")
+
     # Apply softmax to convert similarities to probabilities
     probabilities = softmax(similarities)