healthcheck+

app.py

@@ -6,13 +6,18 @@ import os
 
 os.environ["HF_HOME"] = "/tmp" 
 
-spam = pipeline("text-classification", model="valurank/distilroberta-spam-comments-detection")
+SPAM_MODEL = "valurank/distilroberta-spam-comments-detection"
+TOXIC_MODEL = "s-nlp/roberta_toxicity_classifier"
+SENTIMENT_MODEL =  "nlptown/bert-base-multilingual-uncased-sentiment"
+NSFW_MODEL = "michellejieli/NSFW_text_classifier"
 
-toxic = pipeline("text-classification", model="s-nlp/roberta_toxicity_classifier")
+spam = pipeline("text-classification", model=SPAM_MODEL)
 
-sentiment = pipeline("text-classification", model = "nlptown/bert-base-multilingual-uncased-sentiment")
+toxic = pipeline("text-classification", model=TOXIC_MODEL)
 
-nsfw = pipeline("text-classification", model = "michellejieli/NSFW_text_classifier")
+sentiment = pipeline("text-classification", model = SENTIMENT_MODEL)
+
+nsfw = pipeline("text-classification", model = NSFW_MODEL)
 
 
 app = FastAPI()
@@ -53,10 +58,10 @@ def health_check():
     }
 
     models = {
-        "spam": ("valurank/distilroberta-spam-comments-detection", spam),
-        "toxic": ("s-nlp/roberta_toxicity_classifier", toxic),
-        "sentiment": ("nlptown/bert-base-multilingual-uncased-sentiment", sentiment),
-        "nsfw": ("michellejieli/NSFW_text_classifier", nsfw),
+        "spam": (SPAM_MODEL, spam),
+        "toxic": (TOXIC_MODEL, toxic),
+        "sentiment": (SENTIMENT_MODEL, sentiment),
+        "nsfw": (NSFW_MODEL, nsfw),
     }
 
     for key, (model_name, model_pipeline) in models.items():