rahulnamdev commited on
Commit
a0dc9ac
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1 Parent(s): d5b66b5

Update app.py

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Files changed (1) hide show
  1. app.py +5 -4
app.py CHANGED
@@ -8,13 +8,14 @@ dataset = load_dataset("bprateek/amazon_product_description", revision="main", t
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  @tool
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- def predict_price_tool(arg1:str)-> float: #it's import to specify the return type
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  #Keep this format for the description / args / args description but feel free to modify the tool
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- """This is a tool which look on a dataset as defined by user input and give you a price
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  Args:
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  arg1: the category of product
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  """
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  #filter_dataset = set(dataset['train']['Category'])
 
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  responses = dataset[dataset['Product Name'].str.contains(arg1)]
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  print(responses)
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  #filter_dataset_min = filter_dataset['Selling Price'].min()
@@ -25,8 +26,8 @@ def predict_price_tool(arg1:str)-> float: #it's import to specify the return typ
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  #Agent Example
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  model = HfApiModel(model_id="Qwen/Qwen2.5-Coder-32B-Instruct", token=os.getenv('Testing'))
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- agent = CodeAgent(tools=[predict_price_tool], model=model)
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- agent.run("Electronics")
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  # Access HF Hub
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  #from huggingface_hub import list_models
 
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  @tool
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+ def get_price_tool(arg1:str)-> float: #it's import to specify the return type
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  #Keep this format for the description / args / args description but feel free to modify the tool
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+ """This is a tool which look on a dataset and filter for products and their various atteibutes like prices description
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  Args:
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  arg1: the category of product
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  """
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  #filter_dataset = set(dataset['train']['Category'])
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+ print(arg1)
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  responses = dataset[dataset['Product Name'].str.contains(arg1)]
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  print(responses)
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  #filter_dataset_min = filter_dataset['Selling Price'].min()
 
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  #Agent Example
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  model = HfApiModel(model_id="Qwen/Qwen2.5-Coder-32B-Instruct", token=os.getenv('Testing'))
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+ agent = CodeAgent(tools=[get_price_tool], model=model)
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+ agent.run("Can you dispay prices of all Electronics products in a table")
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  # Access HF Hub
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  #from huggingface_hub import list_models