Update app.py

app.py

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