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import pandas as pd
from smolagents import Tool
from typing import Any, Dict, Optional
class ReverseTextTool(Tool):
name = "reverse_text"
description = "Reverses the input text."
# tell the validator: I’m expecting a dict with key "text"
inputs = {"input": {"type": "any", "description": "The text to be reversed"}}
output_type = "string"
def forward(self, input: Any) -> Any:
return input[::-1]
class TableCommutativityTool(Tool):
name = "find_non_commutative_elements"
description = (
"Given a multiplication table (2D list) and its header elements, "
"returns the elements involved in any a*b != b*a."
)
inputs = {
"input": {
"type": "any",
"description": "Dict with keys 'table' (list of lists) and 'elements' (list of strings)."
}
}
output_type = "string"
def forward(self, input: dict) -> list[str]:
table = input["table"]
elements = input["elements"]
non_comm = set()
for i, a in enumerate(elements):
for j, b in enumerate(elements):
if table[i][j] != table[j][i]:
non_comm.update({a, b})
return str(sorted(non_comm))
class VegetableListTool(Tool):
name = "list_vegetables"
description = (
"From a list of grocery items, returns those that are true vegetables "
"(botanical definition), sorted alphabetically."
)
inputs = {
"input": {
"type": "any",
"description": "Dict with key 'items' containing a list of item strings."
}
}
output_type = "string"
_VEG_SET = {
"broccoli", "bell pepper", "celery", "corn",
"green beans", "lettuce", "sweet potatoes", "zucchini"
}
def forward(self, input: Any) -> Any:
items = input["items"]
return str(sorted(item for item in items if item in self._VEG_SET))
class ExcelSumFoodTool(Tool):
name = "sum_food_sales"
description = (
"Reads an Excel file with columns 'Category' and 'Sales', "
"and returns total sales where Category != 'Drink', rounded to two decimals."
)
inputs = {
"input": {
"type": "any",
"description": "Dict with key 'excel_path' pointing to the .xlsx file to read."
}
}
output_type = "string"
def forward(self, input: Any) -> Any:
excel_path = input["excel_path"]
df = pd.read_excel(excel_path)
total = df.loc[df["Category"] != "Drink", "Sales"].sum()
return str(round(float(total), 2))
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