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| import os | |
| from pathlib import Path | |
| from typing import Optional, Union | |
| import pandas as pd | |
| from dotenv import load_dotenv | |
| from smolagents import (CodeAgent, DuckDuckGoSearchTool, FinalAnswerTool, | |
| LiteLLMModel, PythonInterpreterTool, | |
| WikipediaSearchTool) | |
| from smolagents.tools import Tool | |
| from tabulate import tabulate | |
| # Load environment variables | |
| load_dotenv() | |
| # Initialize the model | |
| model = LiteLLMModel( | |
| model_id=os.getenv("GEMINI_MODEL"), api_key=os.getenv("GEMINI_API_KEY") | |
| ) | |
| class ExcelToTextTool(Tool): | |
| """Render an Excel worksheet as a Markdown table.""" | |
| name = "excel_to_text" | |
| description = ( | |
| "Read an Excel file and return a Markdown table of the requested sheet. " | |
| "Accepts either the sheet name or a zero-based index (as a string)." | |
| ) | |
| inputs = { | |
| "excel_path": { | |
| "type": "string", | |
| "description": "Path to the Excel file (.xlsx or .xls).", | |
| }, | |
| "sheet_name": { | |
| "type": "string", | |
| "description": ( | |
| "Worksheet name or zero-based index (as a string). " | |
| "Optional; defaults to the first sheet." | |
| ), | |
| "nullable": True, | |
| }, | |
| } | |
| output_type = "string" | |
| def forward(self, excel_path: str, sheet_name: Optional[str] = None) -> str: | |
| """Load the Excel file and return the sheet as a Markdown table. | |
| Args: | |
| excel_path: Path to the Excel file. | |
| sheet_name: Optional name or index of the sheet to read. If None, reads the first sheet. | |
| Returns: | |
| A Markdown table representing the Excel sheet, or an error message if the file is not found or cannot be read. | |
| """ | |
| file_path = Path(excel_path).expanduser().resolve() | |
| if not file_path.is_file(): | |
| return f"Error: Excel file not found at {file_path}" | |
| try: | |
| sheet: Union[str, int] = ( | |
| int(sheet_name) | |
| if sheet_name and sheet_name.isdigit() | |
| else sheet_name or 0 | |
| ) | |
| df = pd.read_excel(file_path, sheet_name=sheet) | |
| if hasattr(df, "to_markdown"): | |
| return df.to_markdown(index=False) | |
| return tabulate(df, headers="keys", tablefmt="github", showindex=False) | |
| except Exception as e: | |
| return f"Error reading Excel file: {e}" | |
| class GaiaAgent: | |
| """An agent capable of using tools to answer general questions.""" | |
| def __init__(self): | |
| """Initializes the GaiaAgent with a set of tools.""" | |
| print("GaiaAgent initialized with tools.") | |
| tools = [ | |
| DuckDuckGoSearchTool(), | |
| WikipediaSearchTool(), | |
| ExcelToTextTool(), | |
| PythonInterpreterTool(), | |
| FinalAnswerTool(), | |
| ] | |
| self.agent = CodeAgent( | |
| model=model, | |
| tools=tools, | |
| add_base_tools=True, | |
| additional_authorized_imports=["pandas", "numpy", "csv", "subprocess"], | |
| ) | |
| def __call__(self, task_id: str, question: str) -> str: | |
| """Processes a question using the agent and its tools. | |
| Args: | |
| task_id: A unique identifier for the task. | |
| question: The question to be answered. | |
| Returns: | |
| The answer generated by the agent. | |
| """ | |
| print(f"Agent received task_id='{task_id}' | question='{question[:50]}...'") | |
| answer = self.agent.run(question) | |
| print(f"Agent returning answer: {answer}") | |
| return answer | |