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Merge branch 'master' into summary_memory

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Richard Beales 2023-04-30 10:03:05 +01:00 committed by GitHub
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19
CONTRIBUTING.md
View File

@ -127,3 +127,22 @@ When you run Pytest locally:
- Or: The test might be poorly written. In that case, you can make suggestions to change the test.
In our CI pipeline, Pytest will use the cassettes and not call paid API providers, so we need your help to record the replays that you break.
### Community Challenges
Challenges are goals we need Auto-GPT to achieve.
To pick the challenge you like, go to the tests/integration/challenges folder and select the areas you would like to work on.
- a challenge is new if level_currently_beaten is None
- a challenge is in progress if level_currently_beaten is greater or equal to 1
- a challenge is beaten if level_currently_beaten = max_level
Here is an example of how to run the memory challenge A and attempt to beat level 3.
pytest -s tests/integration/challenges/memory/test_memory_challenge_a.py --level=3
To beat a challenge, you're not allowed to change anything in the tests folder, you have to add code in the autogpt folder
Challenges use cassettes. Cassettes allow us to replay your runs in our CI pipeline.
Don't hesitate to delete the cassettes associated to the challenge you're working on if you need to. Otherwise it will keep replaying the last run.
Once you've beaten a new level of a challenge, please create a pull request and we will analyze how you changed Auto-GPT to beat the challenge.

32
autogpt/agent/agent.py
View File

@ -8,7 +8,7 @@ from autogpt.llm import chat_with_ai, create_chat_completion, create_chat_messag
from autogpt.logs import logger, print_assistant_thoughts
from autogpt.speech import say_text
from autogpt.spinner import Spinner
from autogpt.utils import clean_input, send_chat_message_to_user
from autogpt.utils import clean_input
from autogpt.workspace import Workspace
@ -87,11 +87,7 @@ class Agent:
logger.typewriter_log(
"Continuous Limit Reached: ", Fore.YELLOW, f"{cfg.continuous_limit}"
)
send_chat_message_to_user(
f"Continuous Limit Reached: \n {cfg.continuous_limit}"
)
break
send_chat_message_to_user("Thinking... \n")
# Send message to AI, get response
with Spinner("Thinking... "):
assistant_reply = chat_with_ai(
@ -121,7 +117,6 @@ class Agent:
if cfg.speak_mode:
say_text(f"I want to execute {command_name}")
send_chat_message_to_user("Thinking... \n")
arguments = self._resolve_pathlike_command_args(arguments)
except Exception as e:
@ -132,24 +127,19 @@ class Agent:
# Get key press: Prompt the user to press enter to continue or escape
# to exit
self.user_input = ""
send_chat_message_to_user(
"NEXT ACTION: \n " + f"COMMAND = {command_name} \n "
f"ARGUMENTS = {arguments}"
)
logger.typewriter_log(
"NEXT ACTION: ",
Fore.CYAN,
f"COMMAND = {Fore.CYAN}{command_name}{Style.RESET_ALL} "
f"ARGUMENTS = {Fore.CYAN}{arguments}{Style.RESET_ALL}",
)
print(
logger.info(
"Enter 'y' to authorise command, 'y -N' to run N continuous commands, 's' to run self-feedback commands"
"'n' to exit program, or enter feedback for "
f"{self.ai_name}...",
flush=True,
f"{self.ai_name}..."
)
while True:
console_input = ""
if cfg.chat_messages_enabled:
console_input = clean_input("Waiting for your response...")
else:
@ -180,7 +170,7 @@ class Agent:
user_input = self_feedback_resp
break
elif console_input.lower().strip() == "":
print("Invalid input format.")
logger.warn("Invalid input format.")
continue
elif console_input.lower().startswith(f"{cfg.authorise_key} -"):
try:
@ -189,8 +179,8 @@ class Agent:
)
user_input = "GENERATE NEXT COMMAND JSON"
except ValueError:
print(
f"Invalid input format. Please enter '{cfg.authorise_key} -N' where N is"
logger.warn(
"Invalid input format. Please enter 'y -n' where n is"
" the number of continuous tasks."
)
continue
@ -210,16 +200,10 @@ class Agent:
"",
)
elif user_input == "EXIT":
send_chat_message_to_user("Exiting...")
print("Exiting...", flush=True)
logger.info("Exiting...")
break
else:
# Print command
send_chat_message_to_user(
"NEXT ACTION: \n " + f"COMMAND = {command_name} \n "
f"ARGUMENTS = {arguments}"
)
logger.typewriter_log(
"NEXT ACTION: ",
Fore.CYAN,

3
autogpt/app.py
View File

@ -6,6 +6,7 @@ from autogpt.agent.agent_manager import AgentManager
from autogpt.commands.command import CommandRegistry, command
from autogpt.commands.web_requests import scrape_links, scrape_text
from autogpt.config import Config
from autogpt.logs import logger
from autogpt.memory import get_memory
from autogpt.processing.text import summarize_text
from autogpt.prompts.generator import PromptGenerator
@ -172,7 +173,7 @@ def get_hyperlinks(url: str) -> Union[str, List[str]]:
def shutdown() -> NoReturn:
"""Shut down the program"""
print("Shutting down...")
logger.info("Shutting down...")
quit()

23
autogpt/commands/execute_code.py
View File

@ -8,6 +8,7 @@ from docker.errors import ImageNotFound
from autogpt.commands.command import command
from autogpt.config import Config
from autogpt.logs import logger
CFG = Config()
@ -22,7 +23,7 @@ def execute_python_file(filename: str) -> str:
Returns:
str: The output of the file
"""
print(f"Executing file '{filename}'")
logger.info(f"Executing file '{filename}'")
if not filename.endswith(".py"):
return "Error: Invalid file type. Only .py files are allowed."
@ -47,9 +48,11 @@ def execute_python_file(filename: str) -> str:
image_name = "python:3-alpine"
try:
client.images.get(image_name)
print(f"Image '{image_name}' found locally")
logger.warn(f"Image '{image_name}' found locally")
except ImageNotFound:
print(f"Image '{image_name}' not found locally, pulling from Docker Hub")
logger.info(
f"Image '{image_name}' not found locally, pulling from Docker Hub"
)
# Use the low-level API to stream the pull response
low_level_client = docker.APIClient()
for line in low_level_client.pull(image_name, stream=True, decode=True):
@ -57,9 +60,9 @@ def execute_python_file(filename: str) -> str:
status = line.get("status")
progress = line.get("progress")
if status and progress:
print(f"{status}: {progress}")
logger.info(f"{status}: {progress}")
elif status:
print(status)
logger.info(status)
container = client.containers.run(
image_name,
f"python {Path(filename).relative_to(CFG.workspace_path)}",
@ -85,7 +88,7 @@ def execute_python_file(filename: str) -> str:
return logs
except docker.errors.DockerException as e:
print(
logger.warn(
"Could not run the script in a container. If you haven't already, please install Docker https://docs.docker.com/get-docker/"
)
return f"Error: {str(e)}"
@ -118,7 +121,9 @@ def execute_shell(command_line: str) -> str:
if not current_dir.is_relative_to(CFG.workspace_path):
os.chdir(CFG.workspace_path)
print(f"Executing command '{command_line}' in working directory '{os.getcwd()}'")
logger.info(
f"Executing command '{command_line}' in working directory '{os.getcwd()}'"
)
result = subprocess.run(command_line, capture_output=True, shell=True)
output = f"STDOUT:\n{result.stdout}\nSTDERR:\n{result.stderr}"
@ -154,7 +159,9 @@ def execute_shell_popen(command_line) -> str:
if CFG.workspace_path not in current_dir:
os.chdir(CFG.workspace_path)
print(f"Executing command '{command_line}' in working directory '{os.getcwd()}'")
logger.info(
f"Executing command '{command_line}' in working directory '{os.getcwd()}'"
)
do_not_show_output = subprocess.DEVNULL
process = subprocess.Popen(

13
autogpt/commands/file_operations.py
View File

@ -11,6 +11,7 @@ from requests.adapters import HTTPAdapter, Retry
from autogpt.commands.command import command
from autogpt.config import Config
from autogpt.logs import logger
from autogpt.spinner import Spinner
from autogpt.utils import readable_file_size
@ -106,25 +107,25 @@ def ingest_file(
:param overlap: The number of overlapping characters between chunks, default is 200
"""
try:
print(f"Working with file {filename}")
logger.info(f"Working with file {filename}")
content = read_file(filename)
content_length = len(content)
print(f"File length: {content_length} characters")
logger.info(f"File length: {content_length} characters")
chunks = list(split_file(content, max_length=max_length, overlap=overlap))
num_chunks = len(chunks)
for i, chunk in enumerate(chunks):
print(f"Ingesting chunk {i + 1} / {num_chunks} into memory")
logger.info(f"Ingesting chunk {i + 1} / {num_chunks} into memory")
memory_to_add = (
f"Filename: {filename}\n" f"Content part#{i + 1}/{num_chunks}: {chunk}"
)
memory.add(memory_to_add)
print(f"Done ingesting {num_chunks} chunks from {filename}.")
logger.info(f"Done ingesting {num_chunks} chunks from {filename}.")
except Exception as e:
print(f"Error while ingesting file '{filename}': {str(e)}")
logger.info(f"Error while ingesting file '{filename}': {str(e)}")
@command("write_to_file", "Write to file", '"filename": "<filename>", "text": "<text>"')
@ -264,7 +265,7 @@ def download_file(url, filename):
progress = f"{readable_file_size(downloaded_size)} / {readable_file_size(total_size)}"
spinner.update_message(f"{message} {progress}")
return f'Successfully downloaded and locally stored file: "{filename}"! (Size: {readable_file_size(total_size)})'
return f'Successfully downloaded and locally stored file: "{filename}"! (Size: {readable_file_size(downloaded_size)})'
except requests.HTTPError as e:
return f"Got an HTTP Error whilst trying to download file: {e}"
except Exception as e:

12
autogpt/commands/git_operations.py
View File

@ -11,25 +11,25 @@ CFG = Config()
@command(
"clone_repository",
"Clone Repository",
'"repository_url": "<repository_url>", "clone_path": "<clone_path>"',
'"url": "<repository_url>", "clone_path": "<clone_path>"',
CFG.github_username and CFG.github_api_key,
"Configure github_username and github_api_key.",
)
@validate_url
def clone_repository(repository_url: str, clone_path: str) -> str:
def clone_repository(url: str, clone_path: str) -> str:
"""Clone a GitHub repository locally.
Args:
repository_url (str): The URL of the repository to clone.
url (str): The URL of the repository to clone.
clone_path (str): The path to clone the repository to.
Returns:
str: The result of the clone operation.
"""
split_url = repository_url.split("//")
split_url = url.split("//")
auth_repo_url = f"//{CFG.github_username}:{CFG.github_api_key}@".join(split_url)
try:
Repo.clone_from(auth_repo_url, clone_path)
return f"""Cloned {repository_url} to {clone_path}"""
Repo.clone_from(url=auth_repo_url, to_path=clone_path)
return f"""Cloned {url} to {clone_path}"""
except Exception as e:
return f"Error: {str(e)}"

9
autogpt/commands/image_gen.py
View File

@ -9,6 +9,7 @@ from PIL import Image
from autogpt.commands.command import command
from autogpt.config import Config
from autogpt.logs import logger
CFG = Config()
@ -69,7 +70,7 @@ def generate_image_with_hf(prompt: str, filename: str) -> str:
)
image = Image.open(io.BytesIO(response.content))
print(f"Image Generated for prompt:{prompt}")
logger.info(f"Image Generated for prompt:{prompt}")
image.save(filename)
@ -91,7 +92,7 @@ def generate_image_with_dalle(prompt: str, filename: str, size: int) -> str:
# Check for supported image sizes
if size not in [256, 512, 1024]:
closest = min([256, 512, 1024], key=lambda x: abs(x - size))
print(
logger.info(
f"DALL-E only supports image sizes of 256x256, 512x512, or 1024x1024. Setting to {closest}, was {size}."
)
size = closest
@ -104,7 +105,7 @@ def generate_image_with_dalle(prompt: str, filename: str, size: int) -> str:
api_key=CFG.openai_api_key,
)
print(f"Image Generated for prompt:{prompt}")
logger.info(f"Image Generated for prompt:{prompt}")
image_data = b64decode(response["data"][0]["b64_json"])
@ -153,7 +154,7 @@ def generate_image_with_sd_webui(
},
)
print(f"Image Generated for prompt:{prompt}")
logger.info(f"Image Generated for prompt:{prompt}")
# Save the image to disk
response = response.json()

4
autogpt/commands/web_playwright.py
View File

@ -1,10 +1,12 @@
"""Web scraping commands using Playwright"""
from __future__ import annotations
from autogpt.logs import logger
try:
from playwright.sync_api import sync_playwright
except ImportError:
print(
logger.info(
"Playwright not installed. Please install it with 'pip install playwright' to use."
)
from bs4 import BeautifulSoup

9
autogpt/config/ai_config.py
View File

@ -7,7 +7,7 @@ from __future__ import annotations
import os
import platform
from pathlib import Path
from typing import Optional, Type
from typing import Any, Optional, Type
import distro
import yaml
@ -79,7 +79,12 @@ class AIConfig:
ai_name = config_params.get("ai_name", "")
ai_role = config_params.get("ai_role", "")
ai_goals = config_params.get("ai_goals", [])
ai_goals = [
str(goal).strip("{}").replace("'", "").replace('"', "")
if isinstance(goal, dict)
else str(goal)
for goal in config_params.get("ai_goals", [])
]
api_budget = config_params.get("api_budget", 0.0)
# type: Type[AIConfig]
return AIConfig(ai_name, ai_role, ai_goals, api_budget)

13
autogpt/json_utils/json_fix_general.py
View File

@ -9,6 +9,7 @@ from typing import Optional
from autogpt.config import Config
from autogpt.json_utils.utilities import extract_char_position
from autogpt.logs import logger
CFG = Config()
@ -33,8 +34,7 @@ def fix_invalid_escape(json_to_load: str, error_message: str) -> str:
json.loads(json_to_load)
return json_to_load
except json.JSONDecodeError as e:
if CFG.debug_mode:
print("json loads error - fix invalid escape", e)
logger.debug("json loads error - fix invalid escape", e)
error_message = str(e)
return json_to_load
@ -98,13 +98,11 @@ def correct_json(json_to_load: str) -> str:
"""
try:
if CFG.debug_mode:
print("json", json_to_load)
logger.debug("json", json_to_load)
json.loads(json_to_load)
return json_to_load
except json.JSONDecodeError as e:
if CFG.debug_mode:
print("json loads error", e)
logger.debug("json loads error", e)
error_message = str(e)
if error_message.startswith("Invalid \\escape"):
json_to_load = fix_invalid_escape(json_to_load, error_message)
@ -116,8 +114,7 @@ def correct_json(json_to_load: str) -> str:
json.loads(json_to_load)
return json_to_load
except json.JSONDecodeError as e:
if CFG.debug_mode:
print("json loads error - add quotes", e)
logger.debug("json loads error - add quotes", e)
error_message = str(e)
if balanced_str := balance_braces(json_to_load):
return balanced_str

5
autogpt/json_utils/utilities.py
View File

@ -49,9 +49,8 @@ def validate_json(json_object: object, schema_name: str) -> dict | None:
for error in errors:
logger.error(f"Error: {error.message}")
return None
if CFG.debug_mode:
print("The JSON object is valid.")
else:
logger.debug("The JSON object is valid.")
return json_object

7
autogpt/llm/chat.py
View File

@ -208,9 +208,8 @@ def chat_with_ai(
[create_chat_message("system", plugin_response)], model
)
if current_tokens_used + tokens_to_add > send_token_limit:
if cfg.debug_mode:
print("Plugin response too long, skipping:", plugin_response)
print("Plugins remaining at stop:", plugin_count - i)
logger.debug("Plugin response too long, skipping:", plugin_response)
logger.debug("Plugins remaining at stop:", plugin_count - i)
break
current_context.append(create_chat_message("system", plugin_response))
@ -250,5 +249,5 @@ def chat_with_ai(
return assistant_reply
except RateLimitError:
# TODO: When we switch to langchain, this is built in
print("Error: ", "API Rate Limit Reached. Waiting 10 seconds...")
logger.warn("Error: ", "API Rate Limit Reached. Waiting 10 seconds...")
time.sleep(10)

23
autogpt/llm/llm_utils.py
View File

@ -128,10 +128,9 @@ def create_chat_completion(
num_retries = 10
warned_user = False
if cfg.debug_mode:
print(
f"{Fore.GREEN}Creating chat completion with model {model}, temperature {temperature}, max_tokens {max_tokens}{Fore.RESET}"
)
logger.debug(
f"{Fore.GREEN}Creating chat completion with model {model}, temperature {temperature}, max_tokens {max_tokens}{Fore.RESET}"
)
for plugin in cfg.plugins:
if plugin.can_handle_chat_completion(
messages=messages,
@ -169,10 +168,9 @@ def create_chat_completion(
)
break
except RateLimitError:
if cfg.debug_mode:
print(
f"{Fore.RED}Error: ", f"Reached rate limit, passing...{Fore.RESET}"
)
logger.debug(
f"{Fore.RED}Error: ", f"Reached rate limit, passing...{Fore.RESET}"
)
if not warned_user:
logger.double_check(
f"Please double check that you have setup a {Fore.CYAN + Style.BRIGHT}PAID{Style.RESET_ALL} OpenAI API Account. "
@ -184,11 +182,10 @@ def create_chat_completion(
raise
if attempt == num_retries - 1:
raise
if cfg.debug_mode:
print(
f"{Fore.RED}Error: ",
f"API Bad gateway. Waiting {backoff} seconds...{Fore.RESET}",
)
logger.debug(
f"{Fore.RED}Error: ",
f"API Bad gateway. Waiting {backoff} seconds...{Fore.RESET}",
)
time.sleep(backoff)
if response is None:
logger.typewriter_log(

23
autogpt/logs.py
View File

@ -10,7 +10,6 @@ from colorama import Fore, Style
from autogpt.singleton import Singleton
from autogpt.speech import say_text
from autogpt.utils import send_chat_message_to_user
class Logger(metaclass=Singleton):
@ -83,8 +82,6 @@ class Logger(metaclass=Singleton):
if speak_text and self.speak_mode:
say_text(f"{title}. {content}")
send_chat_message_to_user(f"{title}. {content}")
if content:
if isinstance(content, list):
content = " ".join(content)
@ -103,6 +100,14 @@ class Logger(metaclass=Singleton):
):
self._log(title, title_color, message, logging.DEBUG)
def info(
self,
message,
title="",
title_color="",
):
self._log(title, title_color, message, logging.INFO)
def warn(
self,
message,
@ -114,11 +119,19 @@ class Logger(metaclass=Singleton):
def error(self, title, message=""):
self._log(title, Fore.RED, message, logging.ERROR)
def _log(self, title="", title_color="", message="", level=logging.INFO):
def _log(
self,
title: str = "",
title_color: str = "",
message: str = "",
level=logging.INFO,
):
if message:
if isinstance(message, list):
message = " ".join(message)
self.logger.log(level, message, extra={"title": title, "color": title_color})
self.logger.log(
level, message, extra={"title": str(title), "color": str(title_color)}
)
def set_level(self, level):
self.logger.setLevel(level)

13
autogpt/memory/__init__.py
View File

@ -1,3 +1,4 @@
from autogpt.logs import logger
from autogpt.memory.local import LocalCache
from autogpt.memory.no_memory import NoMemory
@ -10,7 +11,6 @@ try:
supported_memory.append("redis")
except ImportError:
# print("Redis not installed. Skipping import.")
RedisMemory = None
try:
@ -18,7 +18,6 @@ try:
supported_memory.append("pinecone")
except ImportError:
# print("Pinecone not installed. Skipping import.")
PineconeMemory = None
try:
@ -26,7 +25,6 @@ try:
supported_memory.append("weaviate")
except ImportError:
# print("Weaviate not installed. Skipping import.")
WeaviateMemory = None
try:
@ -34,7 +32,6 @@ try:
supported_memory.append("milvus")
except ImportError:
# print("pymilvus not installed. Skipping import.")
MilvusMemory = None
@ -42,7 +39,7 @@ def get_memory(cfg, init=False):
memory = None
if cfg.memory_backend == "pinecone":
if not PineconeMemory:
print(
logger.warn(
"Error: Pinecone is not installed. Please install pinecone"
" to use Pinecone as a memory backend."
)
@ -52,7 +49,7 @@ def get_memory(cfg, init=False):
memory.clear()
elif cfg.memory_backend == "redis":
if not RedisMemory:
print(
logger.warn(
"Error: Redis is not installed. Please install redis-py to"
" use Redis as a memory backend."
)
@ -60,7 +57,7 @@ def get_memory(cfg, init=False):
memory = RedisMemory(cfg)
elif cfg.memory_backend == "weaviate":
if not WeaviateMemory:
print(
logger.warn(
"Error: Weaviate is not installed. Please install weaviate-client to"
" use Weaviate as a memory backend."
)
@ -68,7 +65,7 @@ def get_memory(cfg, init=False):
memory = WeaviateMemory(cfg)
elif cfg.memory_backend == "milvus":
if not MilvusMemory:
print(
logger.warn(
"Error: pymilvus sdk is not installed."
"Please install pymilvus to use Milvus or Zilliz Cloud as memory backend."
)

4
autogpt/memory/redismem.py
View File

@ -73,7 +73,7 @@ class RedisMemory(MemoryProviderSingleton):
),
)
except Exception as e:
print("Error creating Redis search index: ", e)
logger.warn("Error creating Redis search index: ", e)
existing_vec_num = self.redis.get(f"{cfg.memory_index}-vec_num")
self.vec_num = int(existing_vec_num.decode("utf-8")) if existing_vec_num else 0
@ -145,7 +145,7 @@ class RedisMemory(MemoryProviderSingleton):
query, query_params={"vector": query_vector}
)
except Exception as e:
print("Error calling Redis search: ", e)
logger.warn("Error calling Redis search: ", e)
return None
return [result.data for result in results.docs]

5
autogpt/memory/weaviate.py
View File

@ -4,6 +4,7 @@ from weaviate.embedded import EmbeddedOptions
from weaviate.util import generate_uuid5
from autogpt.llm import get_ada_embedding
from autogpt.logs import logger
from autogpt.memory.base import MemoryProviderSingleton
@ -35,7 +36,7 @@ class WeaviateMemory(MemoryProviderSingleton):
)
)
print(
logger.info(
f"Weaviate Embedded running on: {url} with persistence path: {cfg.weaviate_embedded_path}"
)
else:
@ -116,7 +117,7 @@ class WeaviateMemory(MemoryProviderSingleton):
return []
except Exception as err:
print(f"Unexpected error {err=}, {type(err)=}")
logger.warn(f"Unexpected error {err=}, {type(err)=}")
return []
def get_stats(self):

37
autogpt/plugins.py
View File

@ -15,6 +15,7 @@ from auto_gpt_plugin_template import AutoGPTPluginTemplate
from openapi_python_client.cli import Config as OpenAPIConfig
from autogpt.config import Config
from autogpt.logs import logger
from autogpt.models.base_open_ai_plugin import BaseOpenAIPlugin
@ -33,11 +34,10 @@ def inspect_zip_for_modules(zip_path: str, debug: bool = False) -> list[str]:
with zipfile.ZipFile(zip_path, "r") as zfile:
for name in zfile.namelist():
if name.endswith("__init__.py"):
if debug:
print(f"Found module '{name}' in the zipfile at: {name}")
logger.debug(f"Found module '{name}' in the zipfile at: {name}")
result.append(name)
if debug and len(result) == 0:
print(f"Module '__init__.py' not found in the zipfile @ {zip_path}.")
if len(result) == 0:
logger.debug(f"Module '__init__.py' not found in the zipfile @ {zip_path}.")
return result
@ -71,12 +71,12 @@ def fetch_openai_plugins_manifest_and_spec(cfg: Config) -> dict:
if response.status_code == 200:
manifest = response.json()
if manifest["schema_version"] != "v1":
print(
logger.warn(
f"Unsupported manifest version: {manifest['schem_version']} for {url}"
)
continue
if manifest["api"]["type"] != "openapi":
print(
logger.warn(
f"Unsupported API type: {manifest['api']['type']} for {url}"
)
continue
@ -84,11 +84,13 @@ def fetch_openai_plugins_manifest_and_spec(cfg: Config) -> dict:
manifest, f"{openai_plugin_client_dir}/ai-plugin.json"
)
else:
print(f"Failed to fetch manifest for {url}: {response.status_code}")
logger.warn(
f"Failed to fetch manifest for {url}: {response.status_code}"
)
except requests.exceptions.RequestException as e:
print(f"Error while requesting manifest from {url}: {e}")
logger.warn(f"Error while requesting manifest from {url}: {e}")
else:
print(f"Manifest for {url} already exists")
logger.info(f"Manifest for {url} already exists")
manifest = json.load(open(f"{openai_plugin_client_dir}/ai-plugin.json"))
if not os.path.exists(f"{openai_plugin_client_dir}/openapi.json"):
openapi_spec = openapi_python_client._get_document(
@ -98,7 +100,7 @@ def fetch_openai_plugins_manifest_and_spec(cfg: Config) -> dict:
openapi_spec, f"{openai_plugin_client_dir}/openapi.json"
)
else:
print(f"OpenAPI spec for {url} already exists")
logger.info(f"OpenAPI spec for {url} already exists")
openapi_spec = json.load(open(f"{openai_plugin_client_dir}/openapi.json"))
manifests[url] = {"manifest": manifest, "openapi_spec": openapi_spec}
return manifests
@ -115,13 +117,13 @@ def create_directory_if_not_exists(directory_path: str) -> bool:
if not os.path.exists(directory_path):
try:
os.makedirs(directory_path)
print(f"Created directory: {directory_path}")
logger.debug(f"Created directory: {directory_path}")
return True
except OSError as e:
print(f"Error creating directory {directory_path}: {e}")
logger.warn(f"Error creating directory {directory_path}: {e}")
return False
else:
print(f"Directory {directory_path} already exists")
logger.info(f"Directory {directory_path} already exists")
return True
@ -159,7 +161,7 @@ def initialize_openai_plugins(
config=_config,
)
if client_results:
print(
logger.warn(
f"Error creating OpenAPI client: {client_results[0].header} \n"
f" details: {client_results[0].detail}"
)
@ -212,8 +214,7 @@ def scan_plugins(cfg: Config, debug: bool = False) -> List[AutoGPTPluginTemplate
for module in moduleList:
plugin = Path(plugin)
module = Path(module)
if debug:
print(f"Plugin: {plugin} Module: {module}")
logger.debug(f"Plugin: {plugin} Module: {module}")
zipped_package = zipimporter(str(plugin))
zipped_module = zipped_package.load_module(str(module.parent))
for key in dir(zipped_module):
@ -240,9 +241,9 @@ def scan_plugins(cfg: Config, debug: bool = False) -> List[AutoGPTPluginTemplate
loaded_plugins.append(plugin)
if loaded_plugins:
print(f"\nPlugins found: {len(loaded_plugins)}\n" "--------------------")
logger.info(f"\nPlugins found: {len(loaded_plugins)}\n" "--------------------")
for plugin in loaded_plugins:
print(f"{plugin._name}: {plugin._version} - {plugin._description}")
logger.info(f"{plugin._name}: {plugin._version} - {plugin._description}")
return loaded_plugins

11
autogpt/processing/text.py
View File

@ -6,6 +6,7 @@ from selenium.webdriver.remote.webdriver import WebDriver
from autogpt.config import Config
from autogpt.llm import count_message_tokens, create_chat_completion
from autogpt.logs import logger
from autogpt.memory import get_memory
CFG = Config()
@ -86,7 +87,7 @@ def summarize_text(
model = CFG.fast_llm_model
text_length = len(text)
print(f"Text length: {text_length} characters")
logger.info(f"Text length: {text_length} characters")
summaries = []
chunks = list(
@ -99,7 +100,7 @@ def summarize_text(
for i, chunk in enumerate(chunks):
if driver:
scroll_to_percentage(driver, scroll_ratio * i)
print(f"Adding chunk {i + 1} / {len(chunks)} to memory")
logger.info(f"Adding chunk {i + 1} / {len(chunks)} to memory")
memory_to_add = f"Source: {url}\n" f"Raw content part#{i + 1}: {chunk}"
@ -108,7 +109,7 @@ def summarize_text(
messages = [create_message(chunk, question)]
tokens_for_chunk = count_message_tokens(messages, model)
print(
logger.info(
f"Summarizing chunk {i + 1} / {len(chunks)} of length {len(chunk)} characters, or {tokens_for_chunk} tokens"
)
@ -117,7 +118,7 @@ def summarize_text(
messages=messages,
)
summaries.append(summary)
print(
logger.info(
f"Added chunk {i + 1} summary to memory, of length {len(summary)} characters"
)
@ -125,7 +126,7 @@ def summarize_text(
memory.add(memory_to_add)
print(f"Summarized {len(chunks)} chunks.")
logger.info(f"Summarized {len(chunks)} chunks.")
combined_summary = "\n".join(summaries)
messages = [create_message(combined_summary, question)]

4
autogpt/setup.py
View File

@ -119,7 +119,7 @@ def generate_aiconfig_manual() -> AIConfig:
"For example: \nIncrease net worth, Grow Twitter Account, Develop and manage"
" multiple businesses autonomously'",
)
print("Enter nothing to load defaults, enter nothing when finished.", flush=True)
logger.info("Enter nothing to load defaults, enter nothing when finished.")
ai_goals = []
for i in range(5):
ai_goal = utils.clean_input(f"{Fore.LIGHTBLUE_EX}Goal{Style.RESET_ALL} {i+1}: ")
@ -139,7 +139,7 @@ def generate_aiconfig_manual() -> AIConfig:
Fore.GREEN,
"For example: $1.50",
)
print("Enter nothing to let the AI run without monetary limit", flush=True)
logger.info("Enter nothing to let the AI run without monetary limit")
api_budget_input = utils.clean_input(
f"{Fore.LIGHTBLUE_EX}Budget{Style.RESET_ALL}: $"
)

6
autogpt/speech/eleven_labs.py
View File

@ -69,6 +69,8 @@ class ElevenLabsSpeech(VoiceBase):
Returns:
bool: True if the request was successful, False otherwise
"""
from autogpt.logs import logger
tts_url = (
f"https://api.elevenlabs.io/v1/text-to-speech/{self._voices[voice_index]}"
)
@ -81,6 +83,6 @@ class ElevenLabsSpeech(VoiceBase):
os.remove("speech.mpeg")
return True
else:
print("Request failed with status code:", response.status_code)
print("Response content:", response.content)
logger.warn("Request failed with status code:", response.status_code)
logger.info("Response content:", response.content)
return False

22
autogpt/utils.py
View File

@ -5,27 +5,17 @@ import yaml
from colorama import Fore
from git.repo import Repo
from autogpt.logs import logger
# Use readline if available (for clean_input)
try:
import readline
except:
except ImportError:
pass
from autogpt.config import Config
def send_chat_message_to_user(report: str):
cfg = Config()
if not cfg.chat_messages_enabled:
return
for plugin in cfg.plugins:
if not hasattr(plugin, "can_handle_report"):
continue
if not plugin.can_handle_report():
continue
plugin.report(report)
def clean_input(prompt: str = "", talk=False):
try:
cfg = Config()
@ -58,12 +48,12 @@ def clean_input(prompt: str = "", talk=False):
return plugin_response
# ask for input, default when just pressing Enter is y
print("Asking user via keyboard...")
logger.info("Asking user via keyboard...")
answer = input(prompt)
return answer
except KeyboardInterrupt:
print("You interrupted Auto-GPT")
print("Quitting...")
logger.info("You interrupted Auto-GPT")
logger.info("Quitting...")
exit(0)

18
data_ingestion.py
View File

@ -10,11 +10,14 @@ cfg = Config()
def configure_logging():
logging.basicConfig(
filename="log-ingestion.txt",
filemode="a",
format="%(asctime)s,%(msecs)d %(name)s %(levelname)s %(message)s",
datefmt="%H:%M:%S",
level=logging.DEBUG,
handlers=[
logging.FileHandler(filename="log-ingestion.txt"),
logging.StreamHandler(),
],
)
return logging.getLogger("AutoGPT-Ingestion")
@ -26,12 +29,13 @@ def ingest_directory(directory, memory, args):
:param directory: The directory containing the files to ingest
:param memory: An object with an add() method to store the chunks in memory
"""
global logger
try:
files = search_files(directory)
for file in files:
ingest_file(file, memory, args.max_length, args.overlap)
except Exception as e:
print(f"Error while ingesting directory '{directory}': {str(e)}")
logger.error(f"Error while ingesting directory '{directory}': {str(e)}")
def main() -> None:
@ -69,24 +73,22 @@ def main() -> None:
# Initialize memory
memory = get_memory(cfg, init=args.init)
print("Using memory of type: " + memory.__class__.__name__)
logger.debug("Using memory of type: " + memory.__class__.__name__)
if args.file:
try:
ingest_file(args.file, memory, args.max_length, args.overlap)
print(f"File '{args.file}' ingested successfully.")
logger.info(f"File '{args.file}' ingested successfully.")
except Exception as e:
logger.error(f"Error while ingesting file '{args.file}': {str(e)}")
print(f"Error while ingesting file '{args.file}': {str(e)}")
elif args.dir:
try:
ingest_directory(args.dir, memory, args)
print(f"Directory '{args.dir}' ingested successfully.")
logger.info(f"Directory '{args.dir}' ingested successfully.")
except Exception as e:
logger.error(f"Error while ingesting directory '{args.dir}': {str(e)}")
print(f"Error while ingesting directory '{args.dir}': {str(e)}")
else:
print(
logger.warn(
"Please provide either a file path (--file) or a directory name (--dir)"
" inside the auto_gpt_workspace directory as input."
)

2
docs/testing.md
View File

@ -28,7 +28,7 @@ python -m pytest
:::shell
pytest --cov=autogpt --without-integration --without-slow-integration
## Runing the linter
## Running the linter
This project uses [flake8](https://flake8.pycqa.org/en/latest/) for linting.
We currently use the following rules: `E303,W293,W291,W292,E305,E231,E302`.

29
tests/browse_tests.py
View File

@ -1,29 +0,0 @@
import os
import sys
import unittest
from bs4 import BeautifulSoup
sys.path.append(os.path.abspath("../scripts"))
from browse import extract_hyperlinks
class TestBrowseLinks(unittest.TestCase):
"""Unit tests for the browse module functions that extract hyperlinks."""
def test_extract_hyperlinks(self):
"""Test the extract_hyperlinks function with a simple HTML body."""
body = """
<body>
<a href="https://google.com">Google</a>
<a href="foo.html">Foo</a>
<div>Some other crap</div>
</body>
"""
soup = BeautifulSoup(body, "html.parser")
links = extract_hyperlinks(soup, "http://example.com")
self.assertEqual(
links,
[("Google", "https://google.com"), ("Foo", "http://example.com/foo.html")],
)

47
tests/integration/agent_factory.py
View File

@ -3,7 +3,7 @@ import pytest
from autogpt.agent import Agent
from autogpt.commands.command import CommandRegistry
from autogpt.config import AIConfig, Config
from autogpt.memory import NoMemory, get_memory
from autogpt.memory import LocalCache, NoMemory, get_memory
from autogpt.prompts.prompt import DEFAULT_TRIGGERING_PROMPT
from autogpt.workspace import Workspace
@ -19,6 +19,16 @@ def agent_test_config(config: Config):
config.set_temperature(was_temperature)
@pytest.fixture
def memory_local_cache(agent_test_config: Config):
was_memory_backend = agent_test_config.memory_backend
agent_test_config.set_memory_backend("local_cache")
yield get_memory(agent_test_config, init=True)
agent_test_config.set_memory_backend(was_memory_backend)
@pytest.fixture
def memory_none(agent_test_config: Config):
was_memory_backend = agent_test_config.memory_backend
@ -101,3 +111,38 @@ def writer_agent(agent_test_config, memory_none: NoMemory, workspace: Workspace)
)
return agent
@pytest.fixture
def memory_management_agent(
agent_test_config, memory_local_cache, workspace: Workspace
):
command_registry = CommandRegistry()
command_registry.import_commands("autogpt.commands.file_operations")
command_registry.import_commands("autogpt.app")
ai_config = AIConfig(
ai_name="Follow-Instructions-GPT",
ai_role="an AI designed to read the instructions_1.txt file using the read_file method and follow the instructions in the file.",
ai_goals=[
"Use the command read_file to read the instructions_1.txt file",
"Follow the instructions in the instructions_1.txt file",
],
)
ai_config.command_registry = command_registry
system_prompt = ai_config.construct_full_prompt()
agent = Agent(
ai_name="",
memory=memory_local_cache,
full_message_history=[],
command_registry=command_registry,
config=ai_config,
next_action_count=0,
system_prompt=system_prompt,
triggering_prompt=DEFAULT_TRIGGERING_PROMPT,
workspace_directory=workspace.root,
)
return agent

170
tests/integration/cassettes/test_memory_management/test_save_memory_trimmed_from_context_window.yaml
View File

@ -332,4 +332,174 @@ interactions:
status:
code: 200
message: OK
- request:
body: '{"input": ["Assistant Reply: { \"thoughts\": { \"text\": \"thoughts\", \"reasoning\":
\"reasoning\", \"plan\": \"plan\", \"criticism\": \"criticism\", \"speak\":
\"speak\" }, \"command\": { \"name\": \"google\", \"args\":
{ \"query\": \"google_query\" } } } Result: None Human
Feedback:Command Result: Important Information."], "model": "text-embedding-ada-002",
"encoding_format": "base64"}'
headers:
Accept:
- '*/*'
Accept-Encoding:
- gzip, deflate
Connection:
- keep-alive
Content-Length:
- '483'
Content-Type:
- application/json
method: POST
uri: https://api.openai.com/v1/embeddings
response:
body:
string: !!binary |
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tests/integration/challenges/__init__.py Normal file
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import pytest
def pytest_addoption(parser):
parser.addoption(
"--level", action="store", default=None, type=int, help="Specify test level"
)
def pytest_configure(config):
config.option.level = config.getoption("--level")
@pytest.fixture
def user_selected_level(request) -> int:
## used for challenges in the goal oriented tests
return request.config.option.level

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80
tests/integration/challenges/memory/test_memory_challenge_a.py Normal file
View File

@ -0,0 +1,80 @@
import pytest
from autogpt.agent import Agent
from autogpt.commands.file_operations import read_file, write_to_file
from tests.integration.agent_utils import run_interaction_loop
from tests.integration.challenges.utils import get_level_to_run
from tests.utils import requires_api_key
LEVEL_CURRENTLY_BEATEN = 3 # real level beaten 30 and maybe more, but we can't record it, the cassette is too big
MAX_LEVEL = 3
@pytest.mark.vcr
@requires_api_key("OPENAI_API_KEY")
def test_memory_challenge_a(
memory_management_agent: Agent, user_selected_level: int
) -> None:
"""
The agent reads a file containing a task_id. Then, it reads a series of other files.
After reading 'n' files, the agent must write the task_id into a new file.
Args:
memory_management_agent (Agent)
user_selected_level (int)
"""
num_files = get_level_to_run(user_selected_level, LEVEL_CURRENTLY_BEATEN, MAX_LEVEL)
task_id = "2314"
create_instructions_files(memory_management_agent, num_files, task_id)
try:
run_interaction_loop(memory_management_agent, 180)
# catch system exit exceptions
except SystemExit:
file_path = str(memory_management_agent.workspace.get_path("output.txt"))
content = read_file(file_path)
assert task_id in content, f"Expected the file to contain {task_id}"
def create_instructions_files(
memory_management_agent: Agent,
num_files: int,
task_id: str,
base_filename: str = "instructions_",
) -> None:
"""
Creates a series of instructions files for the memory challenge.
Args:
memory_management_agent (Agent)
num_files (int)
task_id (str)
base_filename (str, optional)
"""
for i in range(1, num_files + 1):
content = generate_content(i, task_id, base_filename, num_files)
file_name = f"{base_filename}{i}.txt"
file_path = str(memory_management_agent.workspace.get_path(file_name))
write_to_file(file_path, content)
def generate_content(
index: int, task_id: str, base_filename: str, num_files: int
) -> str:
"""
Args:
index: int
task_id: str
base_filename: str
num_files: int
Returns: str
"""
if index == 1:
return (
f"This task_id is {task_id}\nRead the file {base_filename}{index + 1}.txt"
)
if index != num_files:
return f"Read the file {base_filename}{index + 1}.txt"
return "Write the task_id into the file output.txt\nShutdown"

81
tests/integration/challenges/memory/test_memory_challenge_b.py Normal file
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@ -0,0 +1,81 @@
import pytest
from autogpt.agent import Agent
from autogpt.commands.file_operations import read_file, write_to_file
from tests.integration.agent_utils import run_interaction_loop
from tests.integration.challenges.utils import generate_noise, get_level_to_run
from tests.utils import requires_api_key
LEVEL_CURRENTLY_BEATEN = 2
MAX_LEVEL = 5
NOISE = 1000
@pytest.mark.vcr
@requires_api_key("OPENAI_API_KEY")
def test_memory_challenge_b(
memory_management_agent: Agent, user_selected_level: int
) -> None:
"""
The agent reads a series of files, each containing a task_id and noise. After reading 'n' files,
the agent must write all the task_ids into a new file, filtering out the noise.
Args:
memory_management_agent (Agent)
user_selected_level (int)
"""
current_level = get_level_to_run(
user_selected_level, LEVEL_CURRENTLY_BEATEN, MAX_LEVEL
)
task_ids = [str(i * 1111) for i in range(1, current_level + 1)]
create_instructions_files(memory_management_agent, current_level, task_ids)
try:
run_interaction_loop(memory_management_agent, 40)
except SystemExit:
file_path = str(memory_management_agent.workspace.get_path("output.txt"))
content = read_file(file_path)
for task_id in task_ids:
assert task_id in content, f"Expected the file to contain {task_id}"
def create_instructions_files(
memory_management_agent: Agent,
level: int,
task_ids: list,
base_filename: str = "instructions_",
) -> None:
"""
Creates a series of instructions files for the memory challenge.
Args:
level:
memory_management_agent (Agent)
num_files (int)
task_ids (list)
base_filename (str, optional)
"""
for i in range(1, level + 1):
content = generate_content(i, task_ids, base_filename, level)
file_name = f"{base_filename}{i}.txt"
file_path = str(memory_management_agent.workspace.get_path(file_name))
write_to_file(file_path, content)
def generate_content(index: int, task_ids: list, base_filename: str, level: int) -> str:
"""
Args:
index: int
task_ids: list
base_filename: str
num_files: int
Returns: str
"""
task_id = task_ids[index - 1]
noise = generate_noise(NOISE)
if index != level:
if level == 1:
return f"{noise}\nThe current task_id is {task_id}.\n{noise}\nWrite all the task_ids into the file output.txt. The file has not been created yet. After that, use the task_complete command."
return f"{noise}\nThe current task_id is {task_id}.\n{noise}\nRead the file {base_filename}{index + 1}.txt using the read_file command."
return f"{noise}\nThis task_id is {task_id}\n{noise}\nWrite all the task_ids into the file output.txt. The file has not been created yet. After that, use the task_complete command.\n"

44
tests/integration/challenges/utils.py Normal file
View File

@ -0,0 +1,44 @@
import random
from typing import Optional
import pytest
def get_level_to_run(
user_selected_level: Optional[int],
level_currently_beaten: Optional[int],
max_level: int,
) -> int:
"""
Determines the appropriate level to run for a challenge, based on user-selected level, level currently beaten, and maximum level.
Args:
user_selected_level (int | None): The level selected by the user. If not provided, the level currently beaten is used.
level_currently_beaten (int | None): The highest level beaten so far. If not provided, the test will be skipped.
max_level (int): The maximum level allowed for the challenge.
Returns:
int: The level to run for the challenge.
Raises:
ValueError: If the user-selected level is greater than the maximum level allowed.
"""
if user_selected_level is None:
if level_currently_beaten is None:
pytest.skip(
"No one has beaten any levels so we cannot run the test in our pipeline"
)
# by default we run the level currently beaten.
return level_currently_beaten
if user_selected_level > max_level:
raise ValueError(f"This challenge was not designed to go beyond {max_level}")
return user_selected_level
def generate_noise(noise_size) -> str:
return "".join(
random.choices(
"ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789",
k=noise_size,
)
)

0
tests/integration/goal_oriented/__init__.py Normal file
View File

1318
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View File

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tests/test_ai_config.py Normal file
View File

@ -0,0 +1,45 @@
from autogpt.config.ai_config import AIConfig
"""
Test cases for the AIConfig class, which handles loads the AI configuration
settings from a YAML file.
"""
def test_goals_are_always_lists_of_strings(tmp_path):
"""Test if the goals attribute is always a list of strings."""
yaml_content = """
ai_goals:
- Goal 1: Make a sandwich
- Goal 2, Eat the sandwich
- Goal 3 - Go to sleep
- "Goal 4: Wake up"
ai_name: McFamished
ai_role: A hungry AI
api_budget: 0.0
"""
config_file = tmp_path / "ai_settings.yaml"
config_file.write_text(yaml_content)
ai_config = AIConfig.load(config_file)
assert len(ai_config.ai_goals) == 4
assert ai_config.ai_goals[0] == "Goal 1: Make a sandwich"
assert ai_config.ai_goals[1] == "Goal 2, Eat the sandwich"
assert ai_config.ai_goals[2] == "Goal 3 - Go to sleep"
assert ai_config.ai_goals[3] == "Goal 4: Wake up"
config_file.write_text("")
ai_config.save(config_file)
yaml_content2 = """ai_goals:
- 'Goal 1: Make a sandwich'
- Goal 2, Eat the sandwich
- Goal 3 - Go to sleep
- 'Goal 4: Wake up'
ai_name: McFamished
ai_role: A hungry AI
api_budget: 0.0
"""
assert config_file.read_text() == yaml_content2

10
tests/unit/test_chat.py
View File

@ -33,18 +33,14 @@ def test_generate_context_empty_inputs(mocker):
# Assert
expected_result = (
-1,
47,
3,
32,
2,
[
{"role": "system", "content": ""},
{
"role": "system",
"content": f"The current time and date is {time.strftime('%c')}",
},
{
"role": "system",
"content": f"This reminds you of these events from your past:\n\n\n",
},
],
)
assert result == expected_result
@ -78,5 +74,5 @@ def test_generate_context_valid_inputs():
assert result[0] >= 0
assert result[2] >= 0
assert result[1] >= 0
assert len(result[3]) >= 3 # current_context should have at least 3 messages
assert len(result[3]) >= 2 # current_context should have at least 2 messages
assert result[1] <= 2048 # token limit for GPT-3.5-turbo-0301 is 2048 tokens

264
tests/unit/test_file_operations.py
View File

@ -1,12 +1,18 @@
"""
This set of unit tests is designed to test the file operations that autoGPT has access to.
"""
import os
import shutil
import unittest
from pathlib import Path
from tempfile import gettempdir
import pytest
from autogpt.commands.file_operations import (
append_to_file,
check_duplicate_operation,
delete_file,
download_file,
log_operation,
read_file,
search_files,
@ -14,118 +20,150 @@ from autogpt.commands.file_operations import (
write_to_file,
)
from autogpt.config import Config
from autogpt.workspace import Workspace
from autogpt.utils import readable_file_size
class TestFileOperations(unittest.TestCase):
"""
This set of unit tests is designed to test the file operations that autoGPT has access to.
"""
def setUp(self):
self.config = Config()
workspace_path = os.path.join(os.path.dirname(__file__), "workspace")
self.workspace_path = Workspace.make_workspace(workspace_path)
self.config.workspace_path = workspace_path
self.config.file_logger_path = os.path.join(workspace_path, "file_logger.txt")
self.workspace = Workspace(workspace_path, restrict_to_workspace=True)
self.test_file = str(self.workspace.get_path("test_file.txt"))
self.test_file2 = "test_file2.txt"
self.test_directory = str(self.workspace.get_path("test_directory"))
self.test_nested_file = str(self.workspace.get_path("nested/test_file.txt"))
self.file_content = "This is a test file.\n"
self.file_logger_logs = "file_logger.txt"
with open(self.test_file, "w") as f:
f.write(self.file_content)
def tearDown(self) -> None:
shutil.rmtree(self.workspace_path)
def test_check_duplicate_operation(self):
log_operation("write", self.test_file)
self.assertTrue(check_duplicate_operation("write", self.test_file))
# Test logging a file operation
def test_log_operation(self):
if os.path.exists(self.file_logger_logs):
os.remove(self.file_logger_logs)
log_operation("log_test", self.test_file)
with open(self.config.file_logger_path, "r") as f:
content = f.read()
self.assertIn(f"log_test: {self.test_file}", content)
# Test splitting a file into chunks
def test_split_file(self):
content = "abcdefghij"
chunks = list(split_file(content, max_length=4, overlap=1))
expected = ["abcd", "defg", "ghij"]
self.assertEqual(chunks, expected)
def test_read_file(self):
content = read_file(self.test_file)
self.assertEqual(content, self.file_content)
def test_write_to_file(self):
new_content = "This is new content.\n"
write_to_file(self.test_nested_file, new_content)
with open(self.test_nested_file, "r") as f:
content = f.read()
self.assertEqual(content, new_content)
def test_append_to_file(self):
append_text = "This is appended text.\n"
append_to_file(self.test_nested_file, append_text)
with open(self.test_nested_file, "r") as f:
content = f.read()
append_to_file(self.test_nested_file, append_text)
with open(self.test_nested_file, "r") as f:
content_after = f.read()
self.assertEqual(content_after, append_text + append_text)
def test_delete_file(self):
delete_file(self.test_file)
self.assertFalse(os.path.exists(self.test_file))
def test_search_files(self):
# Case 1: Create files A and B, search for A, and ensure we don't return A and B
file_a = self.workspace.get_path("file_a.txt")
file_b = self.workspace.get_path("file_b.txt")
with open(file_a, "w") as f:
f.write("This is file A.")
with open(file_b, "w") as f:
f.write("This is file B.")
# Create a subdirectory and place a copy of file_a in it
if not os.path.exists(self.test_directory):
os.makedirs(self.test_directory)
with open(os.path.join(self.test_directory, file_a.name), "w") as f:
f.write("This is file A in the subdirectory.")
files = search_files(str(self.workspace.root))
self.assertIn(file_a.name, files)
self.assertIn(file_b.name, files)
self.assertIn(os.path.join(Path(self.test_directory).name, file_a.name), files)
# Clean up
os.remove(file_a)
os.remove(file_b)
os.remove(os.path.join(self.test_directory, file_a.name))
os.rmdir(self.test_directory)
# Case 2: Search for a file that does not exist and make sure we don't throw
non_existent_file = "non_existent_file.txt"
files = search_files("")
self.assertNotIn(non_existent_file, files)
@pytest.fixture()
def file_content():
return "This is a test file.\n"
if __name__ == "__main__":
unittest.main()
@pytest.fixture()
def test_file(workspace, file_content):
test_file = str(workspace.get_path("test_file.txt"))
with open(test_file, "w") as f:
f.write(file_content)
return test_file
@pytest.fixture()
def test_directory(workspace):
return str(workspace.get_path("test_directory"))
@pytest.fixture()
def test_nested_file(workspace):
return str(workspace.get_path("nested/test_file.txt"))
def test_check_duplicate_operation(config, test_file):
log_operation("write", test_file)
assert check_duplicate_operation("write", test_file) is True
# Test logging a file operation
def test_log_operation(test_file, config):
file_logger_name = config.file_logger_path
if os.path.exists(file_logger_name):
os.remove(file_logger_name)
log_operation("log_test", test_file)
with open(config.file_logger_path, "r") as f:
content = f.read()
assert f"log_test: {test_file}" in content
# Test splitting a file into chunks
def test_split_file():
content = "abcdefghij"
chunks = list(split_file(content, max_length=4, overlap=1))
expected = ["abcd", "defg", "ghij"]
assert chunks == expected
def test_read_file(test_file, file_content):
content = read_file(test_file)
assert content == file_content
def test_write_to_file(config, test_nested_file):
new_content = "This is new content.\n"
write_to_file(test_nested_file, new_content)
with open(test_nested_file, "r") as f:
content = f.read()
assert content == new_content
def test_append_to_file(test_nested_file):
append_text = "This is appended text.\n"
write_to_file(test_nested_file, append_text)
append_to_file(test_nested_file, append_text)
with open(test_nested_file, "r") as f:
content_after = f.read()
assert content_after == append_text + append_text
def test_delete_file(config, test_file):
delete_file(test_file)
assert os.path.exists(test_file) is False
assert delete_file(test_file) == "Error: File has already been deleted."
def test_delete_missing_file(test_file):
os.remove(test_file)
try:
os.remove(test_file)
except FileNotFoundError as e:
error_string = str(e)
assert error_string in delete_file(test_file)
return
assert True, "Failed to test delete_file"
def test_search_files(config, workspace, test_directory):
# Case 1: Create files A and B, search for A, and ensure we don't return A and B
file_a = workspace.get_path("file_a.txt")
file_b = workspace.get_path("file_b.txt")
with open(file_a, "w") as f:
f.write("This is file A.")
with open(file_b, "w") as f:
f.write("This is file B.")
# Create a subdirectory and place a copy of file_a in it
if not os.path.exists(test_directory):
os.makedirs(test_directory)
with open(os.path.join(test_directory, file_a.name), "w") as f:
f.write("This is file A in the subdirectory.")
files = search_files(str(workspace.root))
assert file_a.name in files
assert file_b.name in files
assert os.path.join(Path(test_directory).name, file_a.name) in files
# Clean up
os.remove(file_a)
os.remove(file_b)
os.remove(os.path.join(test_directory, file_a.name))
os.rmdir(test_directory)
# Case 2: Search for a file that does not exist and make sure we don't throw
non_existent_file = "non_existent_file.txt"
files = search_files("")
assert non_existent_file not in files
def test_download_file():
url = "https://github.com/Significant-Gravitas/Auto-GPT/archive/refs/tags/v0.2.2.tar.gz"
local_name = os.path.join(gettempdir(), "auto-gpt.tar.gz")
size = 365023
readable_size = readable_file_size(size)
assert (
download_file(url, local_name)
== f'Successfully downloaded and locally stored file: "{local_name}"! (Size: {readable_size})'
)
assert os.path.isfile(local_name) is True
assert os.path.getsize(local_name) == size
url = "https://github.com/Significant-Gravitas/Auto-GPT/archive/refs/tags/v0.0.0.tar.gz"
assert "Got an HTTP Error whilst trying to download file" in download_file(
url, local_name
)
url = "https://thiswebsiteiswrong.hmm/v0.0.0.tar.gz"
assert "Failed to establish a new connection:" in download_file(url, local_name)

70
tests/unit/test_spinner.py
View File

@ -1,6 +1,5 @@
# Generated by CodiumAI
import time
import unittest
from autogpt.spinner import Spinner
@ -29,40 +28,43 @@ ALMOST_DONE_MESSAGE = "Almost done..."
PLEASE_WAIT = "Please wait..."
class TestSpinner(unittest.TestCase):
def test_spinner_initializes_with_default_values(self):
"""Tests that the spinner initializes with default values."""
with Spinner() as spinner:
self.assertEqual(spinner.message, "Loading...")
self.assertEqual(spinner.delay, 0.1)
def test_spinner_initializes_with_default_values():
"""Tests that the spinner initializes with default values."""
with Spinner() as spinner:
assert spinner.message == "Loading..."
assert spinner.delay == 0.1
def test_spinner_initializes_with_custom_values(self):
"""Tests that the spinner initializes with custom message and delay values."""
with Spinner(message=PLEASE_WAIT, delay=0.2) as spinner:
self.assertEqual(spinner.message, PLEASE_WAIT)
self.assertEqual(spinner.delay, 0.2)
#
def test_spinner_stops_spinning(self):
"""Tests that the spinner starts spinning and stops spinning without errors."""
with Spinner() as spinner:
time.sleep(1)
spinner.update_message(ALMOST_DONE_MESSAGE)
time.sleep(1)
self.assertFalse(spinner.running)
def test_spinner_initializes_with_custom_values():
"""Tests that the spinner initializes with custom message and delay values."""
with Spinner(message=PLEASE_WAIT, delay=0.2) as spinner:
assert spinner.message == PLEASE_WAIT
assert spinner.delay == 0.2
def test_spinner_updates_message_and_still_spins(self):
"""Tests that the spinner message can be updated while the spinner is running and the spinner continues spinning."""
with Spinner() as spinner:
self.assertTrue(spinner.running)
time.sleep(1)
spinner.update_message(ALMOST_DONE_MESSAGE)
time.sleep(1)
self.assertEqual(spinner.message, ALMOST_DONE_MESSAGE)
self.assertFalse(spinner.running)
def test_spinner_can_be_used_as_context_manager(self):
"""Tests that the spinner can be used as a context manager."""
with Spinner() as spinner:
self.assertTrue(spinner.running)
self.assertFalse(spinner.running)
#
def test_spinner_stops_spinning():
"""Tests that the spinner starts spinning and stops spinning without errors."""
with Spinner() as spinner:
time.sleep(1)
spinner.update_message(ALMOST_DONE_MESSAGE)
time.sleep(1)
assert spinner.running == False
def test_spinner_updates_message_and_still_spins():
"""Tests that the spinner message can be updated while the spinner is running and the spinner continues spinning."""
with Spinner() as spinner:
assert spinner.running == True
time.sleep(1)
spinner.update_message(ALMOST_DONE_MESSAGE)
time.sleep(1)
assert spinner.message == ALMOST_DONE_MESSAGE
assert spinner.running == False
def test_spinner_can_be_used_as_context_manager():
"""Tests that the spinner can be used as a context manager."""
with Spinner() as spinner:
assert spinner.running == True
assert spinner.running == False

5
tests/vcr/openai_filter.py
View File

@ -41,7 +41,10 @@ def before_record_request(request):
def filter_hostnames(request):
allowed_hostnames = ["api.openai.com"] # List of hostnames you want to allow
allowed_hostnames = [
"api.openai.com",
"localhost:50337",
] # List of hostnames you want to allow
if any(hostname in request.url for hostname in allowed_hostnames):
return request