File size: 2,873 Bytes
f52d0d2 754ea08 f52d0d2 9a5c5cb f52d0d2 9a5c5cb | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 | import os
import pandas as pd
from langchain.tools import BaseTool
class ExcelTool(BaseTool):
"""
Инструмент для анализа Excel-файлов.
Формат input: "<file_url>[,col=<ColumnName>[,agg=<sum|mean>]]".
Если задан только file_url, возвращает сумму всех числовых значений.
"""
name: str = "excel_tool"
description: str = ("Load and analyze Excel (.xls/.xlsx) files. Use for computing totals, filtering rows, summarizing sales data, or any spreadsheet-based calculation.")
def _run(self, input: str) -> str:
parts = [p.strip() for p in input.split(',') if p.strip()]
file_url = parts[0]
opts = {}
# Парсим key=value параметры
for param in parts[1:]:
if '=' in param:
k, v = param.split('=', 1)
opts[k.strip()] = v.strip()
# Читаем файл
try:
df = pd.read_excel(file_url)
except Exception as e:
return f"ERROR: Unable to read Excel file: {e}"
# Если нет опций: сумма всех числовых
# Применяем фильтры, если указаны
filt = opts.get('filter')
if filt:
try:
df = df.query(filt)
except Exception as e:
return f"ERROR: Filter failed: {e}"
if len(opts) == (1 if filt else 0):
try:
total = df.select_dtypes(include='number').sum().sum()
return f"{total:.2f}"
except Exception as e:
return f"ERROR: Summation failed: {e}"
if not opts:
try:
total = df.select_dtypes(include='number').sum().sum()
return str(total)
except Exception as e:
return f"ERROR: Summation failed: {e}"
# Обработка опций
col = opts.get('col')
agg = opts.get('agg', 'sum')
if col and col not in df.columns:
return f"ERROR: Column '{col}' not found."
data = df[col] if col else df.select_dtypes(include='number')
try:
if agg == 'sum':
result = data.sum()
elif agg == 'mean':
result = data.mean()
else:
return f"ERROR: Unsupported aggregation '{agg}'"
# Если результат — серия, переводим в число
if hasattr(result, 'sum') and not isinstance(result, (int, float)):
result = result.sum()
return str(result)
except Exception as e:
return f"ERROR: Aggregation failed: {e}"
async def _arun(self, input: str) -> str:
raise NotImplementedError("Async not supported.")
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