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| from langchain_core.tools.base import BaseTool | |
| from langchain_experimental.agents.agent_toolkits import create_pandas_dataframe_agent | |
| import pandas as pd | |
| from langchain_google_genai import ChatGoogleGenerativeAI | |
| from langchain.agents.agent_types import AgentType | |
| class AnswerExcelTool(BaseTool): | |
| name : str = "answer_excel_tool" | |
| description: str = "Given the path to a file containing an excel file and a query, this tool tries to get an answer by querying the excel file." | |
| def _run(query: str, file_path: str) -> str: | |
| df = pd.read_excel(file_path) | |
| llm = ChatGoogleGenerativeAI(model="gemini-2.0-flash", temperature=0), | |
| agent_executor = create_pandas_dataframe_agent( | |
| llm, | |
| df, | |
| agent_type=AgentType.ZERO_SHOT_REACT_DESCRIPTION, | |
| verbose=True, | |
| allow_dangerous_code=True # IMPORTANT: Understand the risks | |
| ) | |
| return agent_executor(query) |