unify annotations to future syntax

autogpt/agent/agent_manager.py

@@ -1,5 +1,6 @@
 """Agent manager for managing GPT agents"""
-from typing import List, Tuple, Union
+from __future__ import annotations
+
 from autogpt.llm_utils import create_chat_completion
 from autogpt.config.config import Singleton
 
@@ -14,7 +15,7 @@ def __init__(self):
  # Create new GPT agent
  # TODO: Centralise use of create_chat_completion() to globally enforce token limit
 
- def create_agent(self, task: str, prompt: str, model: str) -> Tuple[int, str]:
+ def create_agent(self, task: str, prompt: str, model: str) -> tuple[int, str]:
  """Create a new agent and return its key
 
  Args:
@@ -47,7 +48,7 @@ def create_agent(self, task: str, prompt: str, model: str) -> Tuple[int, str]:
 
  return key, agent_reply
 
- def message_agent(self, key: Union[str, int], message: str) -> str:
+ def message_agent(self, key: str | int, message: str) -> str:
  """Send a message to an agent and return its response
 
  Args:
@@ -73,7 +74,7 @@ def message_agent(self, key: Union[str, int], message: str) -> str:
 
  return agent_reply
 
- def list_agents(self) -> List[Tuple[Union[str, int], str]]:
+ def list_agents(self) -> list[tuple[str | int, str]]:
  """Return a list of all agents
 
  Returns:

autogpt/commands/evaluate_code.py

@@ -1,10 +1,10 @@
 """Code evaluation module."""
-from typing import List
+from __future__ import annotations
 
 from autogpt.llm_utils import call_ai_function
 
 
-def evaluate_code(code: str) -> List[str]:
+def evaluate_code(code: str) -> list[str]:
  """
  A function that takes in a string and returns a response from create chat
  completion api call.

autogpt/commands/file_operations.py

@@ -1,8 +1,11 @@
 """File operations for AutoGPT"""
+from __future__ import annotations
+
 import os
 import os.path
+from pathlib import Path
+from typing import Generator
 from autogpt.workspace import path_in_workspace, WORKSPACE_PATH
-from typing import Generator, List
 
 LOG_FILE = "file_logger.txt"
 LOG_FILE_PATH = WORKSPACE_PATH / LOG_FILE
@@ -187,14 +190,14 @@ def delete_file(filename: str) -> str:
  return f"Error: {str(e)}"
 
 
-def search_files(directory: str) -> List[str]:
+def search_files(directory: str) -> list[str]:
  """Search for files in a directory
 
  Args:
  directory (str): The directory to search in
 
  Returns:
- List[str]: A list of files found in the directory
+ list[str]: A list of files found in the directory
  """
  found_files = []
 

autogpt/commands/google_search.py

@@ -1,6 +1,7 @@
 """Google search command for Autogpt."""
+from __future__ import annotations
+
 import json
-from typing import List, Union
 
 from duckduckgo_search import ddg
 
@@ -33,7 +34,7 @@ def google_search(query: str, num_results: int = 8) -> str:
  return json.dumps(search_results, ensure_ascii=False, indent=4)
 
 
-def google_official_search(query: str, num_results: int = 8) -> Union[str, List[str]]:
+def google_official_search(query: str, num_results: int = 8) -> str | list[str]:
  """Return the results of a google search using the official Google API
 
  Args:

autogpt/commands/improve_code.py

@@ -1,10 +1,11 @@
+from __future__ import annotations
+
 import json
-from typing import List
 
 from autogpt.llm_utils import call_ai_function
 
 
-def improve_code(suggestions: List[str], code: str) -> str:
+def improve_code(suggestions: list[str], code: str) -> str:
  """
  A function that takes in code and suggestions and returns a response from create
  chat completion api call.

autogpt/commands/web_playwright.py

@@ -1,4 +1,6 @@
 """Web scraping commands using Playwright"""
+from __future__ import annotations
+
 try:
  from playwright.sync_api import sync_playwright
 except ImportError:
@@ -7,7 +9,6 @@
  )
 from bs4 import BeautifulSoup
 from autogpt.processing.html import extract_hyperlinks, format_hyperlinks
-from typing import List, Union
 
 
 def scrape_text(url: str) -> str:
@@ -45,7 +46,7 @@ def scrape_text(url: str) -> str:
  return text
 
 
-def scrape_links(url: str) -> Union[str, List[str]]:
+def scrape_links(url: str) -> str | list[str]:
  """Scrape links from a webpage
 
  Args:

autogpt/commands/web_requests.py

@@ -1,5 +1,6 @@
 """Browse a webpage and summarize it using the LLM model"""
-from typing import List, Tuple, Union
+from __future__ import annotations
+
 from urllib.parse import urljoin, urlparse
 
 import requests
@@ -66,15 +67,15 @@ def check_local_file_access(url: str) -> bool:
 
 def get_response(
  url: str, timeout: int = 10
-) -> Union[Tuple[None, str], Tuple[Response, None]]:
+) -> tuple[None, str] | tuple[Response, None]:
  """Get the response from a URL
 
  Args:
  url (str): The URL to get the response from
  timeout (int): The timeout for the HTTP request
 
  Returns:
- Tuple[None, str] | Tuple[Response, None]: The response and error message
+ tuple[None, str] | tuple[Response, None]: The response and error message
 
  Raises:
  ValueError: If the URL is invalid
@@ -136,14 +137,14 @@ def scrape_text(url: str) -> str:
  return text
 
 
-def scrape_links(url: str) -> Union[str, List[str]]:
+def scrape_links(url: str) -> str | list[str]:
  """Scrape links from a webpage
 
  Args:
  url (str): The URL to scrape links from
 
  Returns:
-  Union[str, List[str]]: The scraped links
+ str | list[str]: The scraped links
  """
  response, error_message = get_response(url)
  if error_message:

autogpt/commands/web_selenium.py

@@ -1,4 +1,6 @@
 """Selenium web scraping module."""
+from __future__ import annotations
+
 from selenium import webdriver
 from autogpt.processing.html import extract_hyperlinks, format_hyperlinks
 import autogpt.processing.text as summary
@@ -15,13 +17,12 @@
 import logging
 from pathlib import Path
 from autogpt.config import Config
-from typing import List, Tuple, Union
 
 FILE_DIR = Path(__file__).parent.parent
 CFG = Config()
 
 
-def browse_website(url: str, question: str) -> Tuple[str, WebDriver]:
+def browse_website(url: str, question: str) -> tuple[str, WebDriver]:
  """Browse a website and return the answer and links to the user
 
  Args:
@@ -43,7 +44,7 @@ def browse_website(url: str, question: str) -> Tuple[str, WebDriver]:
  return f"Answer gathered from website: {summary_text} \n \n Links: {links}", driver
 
 
-def scrape_text_with_selenium(url: str) -> Tuple[WebDriver, str]:
+def scrape_text_with_selenium(url: str) -> tuple[WebDriver, str]:
  """Scrape text from a website using selenium
 
  Args:
@@ -97,7 +98,7 @@ def scrape_text_with_selenium(url: str) -> Tuple[WebDriver, str]:
  return driver, text
 
 
-def scrape_links_with_selenium(driver: WebDriver, url: str) -> List[str]:
+def scrape_links_with_selenium(driver: WebDriver, url: str) -> list[str]:
  """Scrape links from a website using selenium
 
  Args:

autogpt/commands/write_tests.py

@@ -1,16 +1,17 @@
 """A module that contains a function to generate test cases for the submitted code."""
+from __future__ import annotations
+
 import json
-from typing import List
 from autogpt.llm_utils import call_ai_function
 
 
-def write_tests(code: str, focus: List[str]) -> str:
+def write_tests(code: str, focus: list[str]) -> str:
  """
  A function that takes in code and focus topics and returns a response from create
  chat completion api call.
 
  Parameters:
- focus (List): A list of suggestions around what needs to be improved.
+ focus (list): A list of suggestions around what needs to be improved.
  code (str): Code for test cases to be generated against.
  Returns:
  A result string from create chat completion. Test cases for the submitted code

autogpt/config/ai_config.py

@@ -2,8 +2,10 @@
 """
 A module that contains the AIConfig class object that contains the configuration
 """
+from __future__ import annotations
+
 import os
-from typing import List, Optional, Type
+from typing import Type
 import yaml
 
 
@@ -18,7 +20,7 @@ class AIConfig:
  """
 
  def __init__(
- self, ai_name: str = "", ai_role: str = "", ai_goals: Optional[List] = None
+ self, ai_name: str = "", ai_role: str = "", ai_goals: list | None = None
  ) -> None:
  """
  Initialize a class instance

autogpt/json_fixes/bracket_termination.py

@@ -1,7 +1,8 @@
 """Fix JSON brackets."""
+from __future__ import annotations
+
 import contextlib
 import json
-from typing import Optional
 import regex
 from colorama import Fore
 
@@ -46,7 +47,7 @@ def attempt_to_fix_json_by_finding_outermost_brackets(json_string: str):
  return json_string
 
 
-def balance_braces(json_string: str) -> Optional[str]:
+def balance_braces(json_string: str) -> str | None:
  """
  Balance the braces in a JSON string.
 

autogpt/json_fixes/parsing.py

@@ -1,8 +1,9 @@
 """Fix and parse JSON strings."""
+from __future__ import annotations
 
 import contextlib
 import json
-from typing import Any, Dict, Union
+from typing import Any
 
 from autogpt.config import Config
 from autogpt.json_fixes.auto_fix import fix_json
@@ -71,7 +72,7 @@ def correct_json(json_to_load: str) -> str:
 
 def fix_and_parse_json(
  json_to_load: str, try_to_fix_with_gpt: bool = True
-) -> Union[str, Dict[Any, Any]]:
+) -> str | dict[Any, Any]:
  """Fix and parse JSON string
 
  Args:
@@ -80,7 +81,7 @@ def fix_and_parse_json(
  Defaults to True.
 
  Returns:
- Union[str, Dict[Any, Any]]: The parsed JSON.
+ str or dict[Any, Any]: The parsed JSON.
  """
 
  with contextlib.suppress(json.JSONDecodeError):
@@ -109,7 +110,7 @@ def fix_and_parse_json(
 
 def try_ai_fix(
  try_to_fix_with_gpt: bool, exception: Exception, json_to_load: str
-) -> Union[str, Dict[Any, Any]]:
+) -> str | dict[Any, Any]:
  """Try to fix the JSON with the AI
 
  Args:
@@ -121,7 +122,7 @@ def try_ai_fix(
  exception: If try_to_fix_with_gpt is False.
 
  Returns:
- Union[str, Dict[Any, Any]]: The JSON string or dictionary.
+ str or dict[Any, Any]: The JSON string or dictionary.
  """
  if not try_to_fix_with_gpt:
  raise exception

autogpt/llm_utils.py

@@ -1,6 +1,7 @@
+from __future__ import annotations
+
 from ast import List
 import time
-from typing import Dict, Optional
 
 import openai
 from openai.error import APIError, RateLimitError
@@ -14,7 +15,7 @@
 
 
 def call_ai_function(
- function: str, args: List, description: str, model: Optional[str] = None
+ function: str, args: list, description: str, model: str | None = None
 ) -> str:
  """Call an AI function
 
@@ -51,15 +52,15 @@ def call_ai_function(
 # Overly simple abstraction until we create something better
 # simple retry mechanism when getting a rate error or a bad gateway
 def create_chat_completion(
- messages: List, # type: ignore
- model: Optional[str] = None,
+ messages: list, # type: ignore
+ model: str | None = None,
  temperature: float = CFG.temperature,
- max_tokens: Optional[int] = None,
+ max_tokens: int | None = None,
 ) -> str:
  """Create a chat completion using the OpenAI API
 
  Args:
- messages (List[Dict[str, str]]): The messages to send to the chat completion
+ messages (list[dict[str, str]]): The messages to send to the chat completion
  model (str, optional): The model to use. Defaults to None.
  temperature (float, optional): The temperature to use. Defaults to 0.9.
  max_tokens (int, optional): The max tokens to use. Defaults to None.

autogpt/memory/local.py

@@ -1,6 +1,8 @@
+from __future__ import annotations
+
 import dataclasses
 import os
-from typing import Any, List, Optional, Tuple
+from typing import Any
 
 import numpy as np
 import orjson
@@ -97,7 +99,7 @@ def clear(self) -> str:
  self.data = CacheContent()
  return "Obliviated"
 
- def get(self, data: str) -> Optional[List[Any]]:
+ def get(self, data: str) -> list[Any] | None:
  """
  Gets the data from the memory that is most relevant to the given data.
 
@@ -108,7 +110,7 @@ def get(self, data: str) -> Optional[List[Any]]:
  """
  return self.get_relevant(data, 1)
 
- def get_relevant(self, text: str, k: int) -> List[Any]:
+ def get_relevant(self, text: str, k: int) -> list[Any]:
  """ "
  matrix-vector mult to find score-for-each-row-of-matrix
  get indices for top-k winning scores
@@ -127,7 +129,7 @@ def get_relevant(self, text: str, k: int) -> List[Any]:
 
  return [self.data.texts[i] for i in top_k_indices]
 
- def get_stats(self) -> Tuple[int, Tuple[int, ...]]:
+ def get_stats(self) -> tuple[int, tuple[int, ...]]:
  """
  Returns: The stats of the local cache.
  """