Update app.py

app.py

@@ -1,14 +1,17 @@
 import gradio as gr
 from transformers import pipeline
 from sentence_transformers import SentenceTransformer
+import spaces  # Import Hugging Face ZeroGPU module
 
-# Load models into memory
+# Load models
 print("Loading BERT NER model...")
 ner_pipeline = pipeline("ner", model="yashpwr/resume-ner-bert-v2", aggregation_strategy="simple")
 
 print("Loading SBERT model...")
 similarity_model = SentenceTransformer("all-MiniLM-L6-v2")
 
+# Decorate GPU functions
+@spaces.GPU
 def parse_resume(text):
     if not text:
         return {"error": "Empty input"}
@@ -25,6 +28,7 @@ def parse_resume(text):
     except Exception as e:
         return {"error": str(e)}
 
+@spaces.GPU
 def get_embeddings(text):
     if not text:
         return {"error": "Empty input"}
@@ -34,7 +38,7 @@ def get_embeddings(text):
     except Exception as e:
         return {"error": str(e)}
 
-# Create Gradio UI blocks
+# Create Gradio UI
 with gr.Blocks() as demo:
     gr.Markdown("# AI Resume Matcher Serverless API")
     
@@ -50,5 +54,4 @@ with gr.Blocks() as demo:
         vector_output = gr.JSON(label="Embedding Vector")
         embed_btn.click(fn=get_embeddings, inputs=text_input_emb, outputs=vector_output, api_name="embed")
 
-# Launch the Gradio application
 demo.launch()