from pathlib import Path from typing import Annotated, Optional from langchain_community.tools.tavily_search import TavilySearchResults from langchain_core.tools import tool from agents import simple_rag_chain WORKING_DIRECTORY = Path("/tmp/content/data") WORKING_DIRECTORY.mkdir(parents=True, exist_ok=True) tavily_tool = TavilySearchResults(max_results=5) @tool def retrieve_information( query: Annotated[str, "query to ask the retrieve information tool"] ): """Use Retrieval Augmented Generation to retrieve information about the 'Extending Llama-3’s Context Ten-Fold Overnight' paper.""" return simple_rag_chain.invoke({"question" : query}) @tool def create_outline(points: List[str], file_name: str) -> str: """Create and save an outline.""" with (WORKING_DIRECTORY / file_name).open("w") as file: for i, point in enumerate(points): file.write(f"{i + 1}. {point}\n") return f"Outline saved to {file_name}" @tool def read_document(file_name: str, start: Optional[int] = None, end: Optional[int] = None) -> str: """Read the specified document.""" with (WORKING_DIRECTORY / file_name).open("r") as file: lines = file.readlines() if start is not None: start = 0 return "\n".join(lines[start:end]) @tool def write_document(content: str, file_name: str) -> str: """Create and save a text document.""" with (WORKING_DIRECTORY / file_name).open("w") as file: file.write(content) return f"Document saved to {file_name}" @tool def edit_document(file_name: str, inserts: Dict[int, str] = {}) -> str: """Edit a document by inserting text at specific line numbers.""" with (WORKING_DIRECTORY / file_name).open("r") as file: lines = file.readlines() sorted_inserts = sorted(inserts.items()) for line_number, text in sorted_inserts: if 1 <= line_number <= len(lines) + 1: lines.insert(line_number - 1, text + "\n") else: return f"Error: Line number {line_number} is out of range." with (WORKING_DIRECTORY / file_name).open("w") as file: file.writelines(lines) return f"Document edited and saved to {file_name}"