timofey commited on
Commit
06ad2f7
·
1 Parent(s): 4f11796

fix gradio

Browse files
Files changed (1) hide show
  1. app.py +7 -6
app.py CHANGED
@@ -8,9 +8,9 @@ try:
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  router_pipeline = pipeline(
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  "text-classification",
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  model=MODEL_NAME,
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- return_all_scores=True
 
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  )
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- router_pipeline.to('cuda')
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  except Exception as e:
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  print(f"Error loading model: {e}")
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  router_pipeline = None
@@ -18,7 +18,7 @@ except Exception as e:
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  @spaces.GPU
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  def classify_query(query_text):
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  if not router_pipeline:
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- return {"Error": "Model could not be loaded. Check Space logs for details."}
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  if not query_text or not query_text.strip():
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  return {"Vector Search": 0.0, "Lexical Search": 0.0}
@@ -44,9 +44,9 @@ Enter an e-commerce query to determine if it's better for **vector search** (con
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  examples = [
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  ["father day gift"],
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  ["16x16 pillow cover"],
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- ["something to wear for a wedding"],
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- ["logitech mx master 3s mouse"],
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- ["comfortable office chair"],
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  ]
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  app = gr.Interface(
@@ -69,3 +69,4 @@ app = gr.Interface(
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  if __name__ == "__main__":
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  app.launch()
 
 
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  router_pipeline = pipeline(
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  "text-classification",
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  model=MODEL_NAME,
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+ return_all_scores=True,
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+ device='cuda'
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  )
 
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  except Exception as e:
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  print(f"Error loading model: {e}")
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  router_pipeline = None
 
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  @spaces.GPU
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  def classify_query(query_text):
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  if not router_pipeline:
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+ raise gr.Error("Model could not be loaded. Check Space logs for details.")
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  if not query_text or not query_text.strip():
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  return {"Vector Search": 0.0, "Lexical Search": 0.0}
 
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  examples = [
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  ["father day gift"],
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  ["16x16 pillow cover"],
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+ ["office chair"],
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+ ["prom dress"],
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+ ["sony wh1000xm4"],
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  ]
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  app = gr.Interface(
 
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  if __name__ == "__main__":
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  app.launch()
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+