Upload model.py

model.py

@@ -1,18 +1,50 @@
 import os
-from transformers import AutoTokenizer, AutoModelForTokenClassification, pipeline
+#from transformers import AutoTokenizer, AutoModelForTokenClassification, pipeline
+from transformers import pipeline
+from huggingface_hub import login
 
-# Safe writable cache dirs in Hugging Face Spaces
-os.environ["TRANSFORMERS_CACHE"] = "/tmp/hf_cache"
-os.environ["HF_HOME"] = "/tmp/hf_home"
-os.environ["HF_HUB_CACHE"] = "/tmp/hf_hub"
+# Safe writable cache dirs in Hugging Face Spaces move to space settings vars`
+#os.environ["TRANSFORMERS_CACHE"] = "/tmp/hf_cache"
+#os.environ["HF_HOME"] = "/tmp/hf_home"
+#os.environ["HF_HUB_CACHE"] = "/tmp/hf_hub"
 
 
 
-HF_TOKEN = os.getenv("HF_TOKEN")
 MODEL_ID = "TypicaAI/magbert-ner"
 
-tokenizer = AutoTokenizer.from_pretrained(MODEL_ID, token=HF_TOKEN)
-model = AutoModelForTokenClassification.from_pretrained(MODEL_ID, token=HF_TOKEN)
+#HF_TOKEN = os.getenv("HF_TOKEN")
+#tokenizer = AutoTokenizer.from_pretrained(MODEL_ID, token=HF_TOKEN)
+#model = AutoModelForTokenClassification.from_pretrained(MODEL_ID, token=HF_TOKEN)
+#ner_pipeline = pipeline("ner", model=model, tokenizer=tokenizer, aggregation_strategy="first")
 
 
-ner_pipeline = pipeline("ner", model=model, tokenizer=tokenizer, aggregation_strategy="first")
+# Authenticate using the secret `HFTOKEN`
+def authenticate_with_token():
+    """Authenticate with the Hugging Face API using the HFTOKEN secret."""
+    hf_token = os.getenv("HF_TOKEN")  # Retrieve the token from environment variables
+    if not hf_token:
+        raise ValueError("HF_TOKEN is not set. Please add it to the Secrets in your Space settings.")
+    login(token=hf_token)
+	
+    
+def load_healthcare_ner_pipeline():
+    """Load the Hugging Face pipeline for Healthcare NER."""
+    global ner_pipeline
+    if ner_pipeline is None:        
+        
+        # Authenticate and initialize pipeline
+        authenticate_with_token()
+        
+        ner_pipeline = pipeline(
+            "token-classification",
+            model=MODEL_ID,
+            aggregation_strategy="first"  # Groups B- and I- tokens into entities
+        )
+    return ner_pipeline
+
+
+
+
+# Initialize global pipeline
+ner_pipeline = load_healthcare_ner_pipeline()	
+