Update app/sentiment.py

app/sentiment.py

@@ -1,22 +1,24 @@
 """
-Safe lazy-loading sentiment pipeline that works in Hugging Face Spaces (no /.cache error).
+Safe, lazy-loading sentiment pipeline for HF Spaces with proper cache redirection.
 """
-
 import os
 import hashlib
 import logging
 from functools import lru_cache
 
-# Redirect the HF model cache to a writable directory
+# ─── Ensure all HF caching uses a writable directory ─────────────────────────
+# Set HF_HOME for huggingface_hub and TRANSFORMERS_CACHE for transformers
+os.environ["HF_HOME"] = "/tmp/huggingface"
 os.environ["TRANSFORMERS_CACHE"] = "/tmp/huggingface"
 os.makedirs("/tmp/huggingface", exist_ok=True)
 
 from transformers import pipeline
 
 class SentimentCache:
+    """Handles in-memory caching and streaming of sentiment results."""
     latest_id: int = 0
     latest_result: dict = {}
-    _pipeline = None  # Lazy init
+    _pipeline = None  # Will hold the loaded pipeline
 
     @classmethod
     def _get_pipeline(cls):
@@ -40,11 +42,12 @@ class SentimentCache:
 
     @classmethod
     def compute(cls, text: str):
+        """Trigger inference and update latest result."""
         res = cls._analyze(text)
         cls.latest_id += 1
         cls.latest_result = {
             "text": text,
-            "label": res["label"],
-            "score": round(res["score"], 4)
+            "label": res.get("label"),
+            "score": round(res.get("score", 0.0), 4)
         }
         logging.info("✅ Sentiment computed: %s", cls.latest_result)