Update chat_a.py

chat_a.py

@@ -15,7 +15,7 @@ from css import log_and_render
 HOME = pathlib.Path.home()
 
 # ✅ ENV가 있으면 따르고, 없으면 홈 밑 .cache/hf-cache 사용
-CACHE_DIR = os.getenv("TRANSFORMERS_CACHE") or str(HOME / ".cache" / "hf-cache")
+CACHE_DIR = os.getenv("TRANSFORMERS_CACHE") or os.path.expanduser("~/.cache/hf-cache")
 os.makedirs(CACHE_DIR, exist_ok=True)
 
 HF_DATASET_REPO = os.getenv("HF_DATASET_REPO", "emisdfde/moai-travel-data")
@@ -1038,16 +1038,20 @@ def override_emotion_if_needed(text):
             return [(emotion_label, 50.0)], [emotion_group]
     return None
     
-def analyze_emotion(user_input):
-    sentiment_model = load_sentiment_model()
+def analyze_emotion(text: str):
     tokenizer = load_tokenizer()
-    override = override_emotion_if_needed(user_input)
-    if override:
-        return override
-    inputs = tokenizer(user_input, return_tensors="pt", truncation=True)
-    
+    model = load_sentiment_model()
+
+    inputs = tokenizer(
+        text,
+        return_tensors="pt",
+        truncation=True,
+        padding=False,
+        max_length=256,
+    )
     with torch.no_grad():
-        probs = F.softmax(sentiment_model(**inputs).logits, dim=1)[0]
+        logits = model(**inputs).logits
+        probs = F.softmax(logits, dim=1)[0].tolist()
     top_indices = torch.topk(probs, k=5).indices.tolist()
     top_emotions = [(klue_emotions[i], float(probs[i]) * 100) for i in top_indices]
     top_emotion_groups = list(dict.fromkeys([klue_to_general[i] for i in top_indices if probs[i] > 0.05]))