Update app.py

app.py

@@ -8,13 +8,14 @@ session = ort.InferenceSession(MODEL_FILE)
 tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-fr")
 
 labels = [
-    "general", "pharma", "legal", "technical", "UI", "user interface", "medicine", "information technology", "IT", "marketing", 
-    "e-commerce", "programming", "website", "html", "keywords", "food commerce", 
-    "personal development", "literature", "poetry", "physics", "chemistry", "biology", 
-    "theater", "finance", "sports", "education", "politics", "economics", "art", 
-    "history", "music", "gaming", "aerospace", "engineering", "robotics", "travel", 
-    "tourism", "healthcare", "psychology", "environment", "fashion", "design", 
-    "real estate", "retail", "news", "entertainment", "social media", "automotive", 
+    "general", "pharma", "legal", "technical", "UI", "user interface", "medicine",
+    "information technology", "IT", "marketing", "e-commerce", "programming",
+    "website", "html", "keywords", "food commerce", "personal development", 
+    "literature", "poetry", "physics", "chemistry", "biology", "theater", "finance",
+    "sports", "education", "politics", "economics", "art", "history", "music",
+    "gaming", "aerospace", "engineering", "robotics", "travel", "tourism", 
+    "healthcare", "psychology", "environment", "fashion", "design", "real estate",
+    "retail", "news", "entertainment", "social media", "automotive", "AI",
     "machine learning", "cryptocurrency", "blockchain", "philosophy", "anthropology", 
     "archaeology", "data science"
 ]
@@ -61,7 +62,7 @@ def translate_text(input_text, context):
 def process_request(input_text):
     contexts = detect_context(input_text)
     translation = translate_text(input_text, contexts[0])  # Use the first detected context
-    return translation, contexts[0]
+    return translation
 
 gr.Interface(
     fn=process_request,