app.py

from smolagents import CodeAgent  
from smolagents import HfApiModel
from smolagents import tool
#from smolagents import DuckDuckGoSearchTool
import os
import gradio as gr
from datasets import load_dataset
dataset = load_dataset("bprateek/amazon_product_description", revision="main", split="train", token=os.getenv('Testing'))


@tool
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 and filter for products and their various atteibutes like prices description
    Args:
        arg1: the category of product
    """    
    arg1 = arg1.lower()
    responses =  dataset.filter(lambda example: arg1 in example['Product Name'].lower())
    #filter_dataset_min = filter_dataset['Selling Price'].min()
    #filter_dataset_max = filter_dataset['Selling Price'].min()
    return responses


#Agent Example 
model = HfApiModel(model_id="Qwen/Qwen2.5-Coder-32B-Instruct", token=os.getenv('Testing'))
demo = gr.Interface(fn=CodeAgent(tools=[get_price_tool], model=model), inputs="textbox", outputs="textbox")

if __name__ == "__main__":
    demo.launch()

#agent.run("Can you dispay prices of all Electronics products in a table")

# Access HF Hub 
#from huggingface_hub import list_models

#for model in list_models(limit=10, sort="downloads", direction=-1):
#   print(model.id, model.downloads)