import requests import pandas as pd from io import BytesIO from typing import List from langchain_core.tools import tool from langchain_community.tools import DuckDuckGoSearchResults from langchain_community.tools.tavily_search import TavilySearchResults from langchain_community.document_loaders import ArxivLoader, WikipediaLoader @tool def add(a: int, b: int) -> int: """Add two numbers. Args: a: first int b: second int """ return a + b @tool def subtract(a: int, b: int) -> int: """Subtract two numbers. Args: a: first int b: second int """ return a - b @tool def multiply(a: int, b: int) -> int: """Multiply two numbers. Args: a: first int b: second int """ return a * b @tool def divide(a: int, b: int) -> int: """Divide two numbers. Args: a: first int b: second int """ if b == 0: raise ValueError("Cannot divide by zero.") return a / b @tool def modulo(a: int, b: int) -> int: """Get the modulus of two numbers. Args: a: first int b: second int """ return a % b @tool def add_list(lst: List[float]) -> float: """Sum up a list of numbers. Args: lst: A list of numbers. """ return sum(lst) @tool def web_search(query: str) -> str: """Web search with Tavily for a query and return maximum 3 results. Args: query: The search query.""" # search_docs = DuckDuckGoSearchResults(max_results=3).invoke({'query': query}) search_docs = TavilySearchResults(max_results=3).invoke({'query': query}) formatted_search_docs = "\n\n---\n\n".join( [ f'"\n{doc["content"]}\n' for doc in search_docs ]) return f"web_results:\n{formatted_search_docs}" @tool def arxiv_search(query: str) -> str: """Search ArXiv for a query and return maximum 3 result. Args: query: The search query.""" search_docs = ArxivLoader(query=query, load_max_docs=3).load() formatted_search_docs = "\n\n---\n\n".join( [ f'"\n{doc.metadata["Summary"]}\n' for doc in search_docs ]) return f"arxiv_content:\n{formatted_search_docs}" @tool def wiki_search(query: str) -> str: """Search Wikipedia for a query and return maximum 2 results. Args: query: The search query.""" search_docs = WikipediaLoader(query=query, load_max_docs=2).load() formatted_search_docs = "\n\n---\n\n".join( [ f'"\n{doc.metadata["Summary"]}\n' for doc in search_docs ]) return f"wikipedia_content:\n{formatted_search_docs}" @tool def read_xlsx_file(file_location: str) -> str: """Read an .xlsx file from a path and return its contents as a string. Args: file_location (str): Path to the xlsx file. """ base_name = file_location.split(".")[0] file_url = f"https://agents-course-unit4-scoring.hf.space/files/{base_name}" # Download the file response = requests.get(file_url) if response.status_code != 200: raise RuntimeError(f"Failed to download file: {file_url}") # Load the xlsx file into a pandas ExcelFile object df_dict = pd.read_excel(BytesIO(response.content), sheet_name=None) # Convert all sheets to a single formatted string text_output = "" for sheet_name, sheet_df in df_dict.items(): text_output += f"--- Sheet: {sheet_name} ---\n" text_output += sheet_df.to_string(index=False) text_output += "\n\n" return f"xlsx file content:\n{text_output.strip()}" @tool def get_python_file(file_location: str) -> str: """ Get the content of a Python file from a path. Args: file_location: path to the Python file. """ base_name = file_location.split(".")[0] file_url = f"https://agents-course-unit4-scoring.hf.space/files/{base_name}" # Download the file response = requests.get(file_url) if response.status_code != 200: raise RuntimeError(f"Failed to download file: {file_url}") return f'python file:\n{response.content}'