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merge BillSchumacher/plugin-support, conflicts

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This commit is contained in:
Evgeny Vakhteev 2023-04-18 13:13:38 -07:00
commit c62c8c6e71
83 changed files with 1223 additions and 689 deletions
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7
.devcontainer/Dockerfile
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@ -1,6 +1,6 @@
# [Choice] Python version (use -bullseye variants on local arm64/Apple Silicon): 3, 3.10, 3.9, 3.8, 3.7, 3.6, 3-bullseye, 3.10-bullseye, 3.9-bullseye, 3.8-bullseye, 3.7-bullseye, 3.6-bullseye, 3-buster, 3.10-buster, 3.9-buster, 3.8-buster, 3.7-buster, 3.6-buster
ARG VARIANT=3-bullseye
FROM python:3.8
FROM --platform=linux/amd64 python:3.8
RUN apt-get update && export DEBIAN_FRONTEND=noninteractive \
# Remove imagemagick due to https://security-tracker.debian.org/tracker/CVE-2019-10131
@ -10,6 +10,11 @@ RUN apt-get update && export DEBIAN_FRONTEND=noninteractive \
# They are installed by the base image (python) which does not have the patch.
RUN python3 -m pip install --upgrade setuptools
# Install Chrome for web browsing
RUN apt-get update && export DEBIAN_FRONTEND=noninteractive \
&& curl -sSL https://dl.google.com/linux/direct/google-chrome-stable_current_$(dpkg --print-architecture).deb -o /tmp/chrome.deb \
&& apt-get -y install /tmp/chrome.deb
# [Optional] If your pip requirements rarely change, uncomment this section to add them to the image.
# COPY requirements.txt /tmp/pip-tmp/
# RUN pip3 --disable-pip-version-check --no-cache-dir install -r /tmp/pip-tmp/requirements.txt \

1
.devcontainer/devcontainer.json
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@ -11,6 +11,7 @@
"userGid": "1000",
"upgradePackages": "true"
},
"ghcr.io/devcontainers/features/desktop-lite:1": {},
"ghcr.io/devcontainers/features/python:1": "none",
"ghcr.io/devcontainers/features/node:1": "none",
"ghcr.io/devcontainers/features/git:1": {

31
.github/workflows/benchmark.yml vendored Normal file
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@ -0,0 +1,31 @@
name: benchmark
on:
workflow_dispatch:
jobs:
build:
runs-on: ubuntu-latest
environment: benchmark
strategy:
matrix:
python-version: [3.8]
steps:
- name: Check out repository
uses: actions/checkout@v2
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v2
with:
python-version: ${{ matrix.python-version }}
- name: Install dependencies
run: |
python -m pip install --upgrade pip
pip install -r requirements.txt
- name: benchmark
run: |
python benchmark/benchmark_entrepeneur_gpt_with_undecisive_user.py
env:
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}

2
.github/workflows/ci.yml vendored
View File

@ -36,7 +36,7 @@ jobs:
- name: Run unittest tests with coverage
run: |
coverage run --source=autogpt -m unittest discover tests
pytest --cov=autogpt --without-integration --without-slow-integration
- name: Generate coverage report
run: |

5
.gitignore vendored
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@ -3,13 +3,13 @@ autogpt/keys.py
autogpt/*json
autogpt/node_modules/
autogpt/__pycache__/keys.cpython-310.pyc
autogpt/auto_gpt_workspace
package-lock.json
*.pyc
auto_gpt_workspace/*
*.mpeg
.env
azure.yaml
*venv/*
outputs/*
ai_settings.yaml
last_run_ai_settings.yaml
@ -130,10 +130,9 @@ celerybeat.pid
.env
.venv
env/
venv/
venv*/
ENV/
env.bak/
venv.bak/
# Spyder project settings
.spyderproject

8
.pre-commit-config.yaml
View File

@ -30,4 +30,10 @@ repos:
language: python
types: [ python ]
exclude: .+/(dist|.venv|venv|build)/.+
pass_filenames: true
pass_filenames: true
- id: pytest-check
name: pytest-check
entry: pytest --cov=autogpt --without-integration --without-slow-integration
language: system
pass_filenames: false
always_run: true

289
README.md
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File diff suppressed because one or more lines are too long

34
autogpt/__main__.py
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@ -1,8 +1,8 @@
"""Main script for the autogpt package."""
import logging
import os
from pathlib import Path
from colorama import Fore
from autogpt.agent.agent import Agent
from autogpt.args import parse_arguments
from autogpt.commands.command import CommandRegistry
@ -27,19 +27,26 @@ def main() -> None:
cfg.set_plugins(scan_plugins(cfg, cfg.debug_mode))
# Create a CommandRegistry instance and scan default folder
command_registry = CommandRegistry()
command_registry.import_commands("scripts.ai_functions")
command_registry.import_commands("scripts.commands")
command_registry.import_commands("scripts.execute_code")
command_registry.import_commands("scripts.agent_manager")
command_registry.import_commands("scripts.file_operations")
command_registry.import_commands("autogpt.commands.audio_text")
command_registry.import_commands("autogpt.commands.evaluate_code")
command_registry.import_commands("autogpt.commands.execute_code")
command_registry.import_commands("autogpt.commands.file_operations")
command_registry.import_commands("autogpt.commands.git_operations")
command_registry.import_commands("autogpt.commands.google_search")
command_registry.import_commands("autogpt.commands.image_gen")
command_registry.import_commands("autogpt.commands.twitter")
command_registry.import_commands("autogpt.commands.web_selenium")
command_registry.import_commands("autogpt.commands.write_tests")
command_registry.import_commands("autogpt.app")
ai_name = ""
ai_config = construct_main_ai_config()
ai_config.command_registry = command_registry
# print(prompt)
# Initialize variables
full_message_history = []
next_action_count = 0
# Make a constant:
user_input = (
triggering_prompt = (
"Determine which next command to use, and respond using the"
" format specified above:"
)
@ -47,9 +54,12 @@ def main() -> None:
# this is particularly important for indexing and referencing pinecone memory
memory = get_memory(cfg, init=True)
logger.typewriter_log(
f"Using memory of type:", Fore.GREEN, f"{memory.__class__.__name__}"
"Using memory of type:", Fore.GREEN, f"{memory.__class__.__name__}"
)
logger.typewriter_log(f"Using Browser:", Fore.GREEN, cfg.selenium_web_browser)
logger.typewriter_log("Using Browser:", Fore.GREEN, cfg.selenium_web_browser)
system_prompt = ai_config.construct_full_prompt()
if cfg.debug_mode:
logger.typewriter_log("Prompt:", Fore.GREEN, system_prompt)
agent = Agent(
ai_name=ai_name,
memory=memory,
@ -57,8 +67,8 @@ def main() -> None:
next_action_count=next_action_count,
command_registry=command_registry,
config=ai_config,
prompt=ai_config.construct_full_prompt(),
user_input=user_input,
system_prompt=system_prompt,
triggering_prompt=triggering_prompt,
)
agent.start_interaction_loop()

139
autogpt/agent/agent.py
View File

@ -1,11 +1,10 @@
from colorama import Fore, Style
from autogpt.app import execute_command, get_command
from autogpt.app import execute_command, get_command
from autogpt.chat import chat_with_ai, create_chat_message
from autogpt.config import Config
from autogpt.json_fixes.bracket_termination import (
attempt_to_fix_json_by_finding_outermost_brackets,
)
from autogpt.json_fixes.master_json_fix_method import fix_json_using_multiple_techniques
from autogpt.json_validation.validate_json import validate_json
from autogpt.logs import logger, print_assistant_thoughts
from autogpt.speech import say_text
from autogpt.spinner import Spinner
@ -20,9 +19,25 @@ class Agent:
memory: The memory object to use.
full_message_history: The full message history.
next_action_count: The number of actions to execute.
prompt: The prompt to use.
user_input: The user input.
system_prompt: The system prompt is the initial prompt that defines everything
the AI needs to know to achieve its task successfully.
Currently, the dynamic and customizable information in the system prompt are
ai_name, description and goals.
triggering_prompt: The last sentence the AI will see before answering.
For Auto-GPT, this prompt is:
Determine which next command to use, and respond using the format specified
above:
The triggering prompt is not part of the system prompt because between the
system prompt and the triggering
prompt we have contextual information that can distract the AI and make it
forget that its goal is to find the next task to achieve.
SYSTEM PROMPT
CONTEXTUAL INFORMATION (memory, previous conversations, anything relevant)
TRIGGERING PROMPT
The triggering prompt reminds the AI about its short term meta task
(defining the next task)
"""
def __init__(
@ -33,8 +48,8 @@ class Agent:
next_action_count,
command_registry,
config,
prompt,
user_input,
system_prompt,
triggering_prompt,
):
self.ai_name = ai_name
self.memory = memory
@ -42,8 +57,8 @@ class Agent:
self.next_action_count = next_action_count
self.command_registry = command_registry
self.config = config
self.prompt = prompt
self.user_input = user_input
self.system_prompt = system_prompt
self.triggering_prompt = triggering_prompt
def start_interaction_loop(self):
# Interaction Loop
@ -51,6 +66,8 @@ class Agent:
loop_count = 0
command_name = None
arguments = None
user_input = ""
while True:
# Discontinue if continuous limit is reached
loop_count += 1
@ -68,34 +85,35 @@ class Agent:
with Spinner("Thinking... "):
assistant_reply = chat_with_ai(
self,
self.prompt,
self.user_input,
self.system_prompt,
self.triggering_prompt,
self.full_message_history,
self.memory,
cfg.fast_token_limit,
) # TODO: This hardcodes the model to use GPT3.5. Make this an argument
assistant_reply_json = fix_json_using_multiple_techniques(assistant_reply)
for plugin in cfg.plugins:
assistant_reply = plugin.post_planning(self, assistant_reply)
if not plugin.can_handle_post_planning():
continue
assistant_reply_json = plugin.post_planning(self, assistant_reply_json)
# Print Assistant thoughts
print_assistant_thoughts(self.ai_name, assistant_reply)
# Get command name and arguments
try:
command_name, arguments = get_command(
attempt_to_fix_json_by_finding_outermost_brackets(assistant_reply)
)
if cfg.speak_mode:
say_text(f"I want to execute {command_name}")
except Exception as e:
logger.error("Error: \n", str(e))
if assistant_reply_json != {}:
validate_json(assistant_reply_json, "llm_response_format_1")
# Get command name and arguments
try:
print_assistant_thoughts(self.ai_name, assistant_reply_json)
command_name, arguments = get_command(assistant_reply_json)
if cfg.speak_mode:
say_text(f"I want to execute {command_name}")
except Exception as e:
logger.error("Error: \n", str(e))
if not cfg.continuous_mode and self.next_action_count == 0:
### GET USER AUTHORIZATION TO EXECUTE COMMAND ###
# ### GET USER AUTHORIZATION TO EXECUTE COMMAND ###
# Get key press: Prompt the user to press enter to continue or escape
# to exit
self.user_input = ""
logger.typewriter_log(
"NEXT ACTION: ",
Fore.CYAN,
@ -114,14 +132,14 @@ class Agent:
)
if console_input.lower().rstrip() == "y":
self.user_input = "GENERATE NEXT COMMAND JSON"
user_input = "GENERATE NEXT COMMAND JSON"
break
elif console_input.lower().startswith("y -"):
try:
self.next_action_count = abs(
int(console_input.split(" ")[1])
)
self.user_input = "GENERATE NEXT COMMAND JSON"
user_input = "GENERATE NEXT COMMAND JSON"
except ValueError:
print(
"Invalid input format. Please enter 'y -n' where n is"
@ -130,20 +148,20 @@ class Agent:
continue
break
elif console_input.lower() == "n":
self.user_input = "EXIT"
user_input = "EXIT"
break
else:
self.user_input = console_input
user_input = console_input
command_name = "human_feedback"
break
if self.user_input == "GENERATE NEXT COMMAND JSON":
if user_input == "GENERATE NEXT COMMAND JSON":
logger.typewriter_log(
"-=-=-=-=-=-=-= COMMAND AUTHORISED BY USER -=-=-=-=-=-=-=",
Fore.MAGENTA,
"",
)
elif self.user_input == "EXIT":
elif user_input == "EXIT":
print("Exiting...", flush=True)
break
else:
@ -161,39 +179,48 @@ class Agent:
f"Command {command_name} threw the following error: {arguments}"
)
elif command_name == "human_feedback":
result = f"Human feedback: {self.user_input}"
result = f"Human feedback: {user_input}"
else:
for plugin in cfg.plugins:
if not plugin.can_handle_pre_command():
continue
command_name, arguments = plugin.pre_command(
command_name, arguments
)
result = (
f"Command {command_name} returned: "
f"{execute_command(self.command_registry, command_name, arguments, self.config.prompt_generator)}"
command_result = execute_command(
self.command_registry,
command_name,
arguments,
self.config.prompt_generator,
)
result = f"Command {command_name} returned: " f"{command_result}"
for plugin in cfg.plugins:
if not plugin.can_handle_post_command():
continue
result = plugin.post_command(command_name, result)
if self.next_action_count > 0:
self.next_action_count -= 1
memory_to_add = (
f"Assistant Reply: {assistant_reply} "
f"\nResult: {result} "
f"\nHuman Feedback: {self.user_input} "
)
self.memory.add(memory_to_add)
# Check if there's a result from the command append it to the message
# history
if result is not None:
self.full_message_history.append(create_chat_message("system", result))
logger.typewriter_log("SYSTEM: ", Fore.YELLOW, result)
else:
self.full_message_history.append(
create_chat_message("system", "Unable to execute command")
)
logger.typewriter_log(
"SYSTEM: ", Fore.YELLOW, "Unable to execute command"
if command_name != "do_nothing":
memory_to_add = (
f"Assistant Reply: {assistant_reply} "
f"\nResult: {result} "
f"\nHuman Feedback: {user_input} "
)
self.memory.add(memory_to_add)
# Check if there's a result from the command append it to the message
# history
if result is not None:
self.full_message_history.append(
create_chat_message("system", result)
)
logger.typewriter_log("SYSTEM: ", Fore.YELLOW, result)
else:
self.full_message_history.append(
create_chat_message("system", "Unable to execute command")
)
logger.typewriter_log(
"SYSTEM: ", Fore.YELLOW, "Unable to execute command"
)

14
autogpt/agent/agent_manager.py
View File

@ -1,8 +1,8 @@
"""Agent manager for managing GPT agents"""
from __future__ import annotations
from autogpt.config.config import Config, Singleton
from autogpt.llm_utils import create_chat_completion
from autogpt.config.config import Singleton, Config
class AgentManager(metaclass=Singleton):
@ -31,6 +31,8 @@ class AgentManager(metaclass=Singleton):
{"role": "user", "content": prompt},
]
for plugin in self.cfg.plugins:
if not plugin.can_handle_pre_instruction():
continue
plugin_messages = plugin.pre_instruction(messages)
if plugin_messages:
for plugin_message in plugin_messages:
@ -46,6 +48,8 @@ class AgentManager(metaclass=Singleton):
plugins_reply = ""
for i, plugin in enumerate(self.cfg.plugins):
if not plugin.can_handle_on_instruction():
continue
plugin_result = plugin.on_instruction(messages)
if plugin_result:
sep = "" if not i else "\n"
@ -61,6 +65,8 @@ class AgentManager(metaclass=Singleton):
self.agents[key] = (task, messages, model)
for plugin in self.cfg.plugins:
if not plugin.can_handle_post_instruction():
continue
agent_reply = plugin.post_instruction(agent_reply)
return key, agent_reply
@ -81,6 +87,8 @@ class AgentManager(metaclass=Singleton):
messages.append({"role": "user", "content": message})
for plugin in self.cfg.plugins:
if not plugin.can_handle_pre_instruction():
continue
plugin_messages = plugin.pre_instruction(messages)
if plugin_messages:
for plugin_message in plugin_messages:
@ -96,6 +104,8 @@ class AgentManager(metaclass=Singleton):
plugins_reply = agent_reply
for i, plugin in enumerate(self.cfg.plugins):
if not plugin.can_handle_on_instruction():
continue
plugin_result = plugin.on_instruction(messages)
if plugin_result:
sep = "" if not i else "\n"
@ -105,6 +115,8 @@ class AgentManager(metaclass=Singleton):
messages.append({"role": "assistant", "content": plugins_reply})
for plugin in self.cfg.plugins:
if not plugin.can_handle_post_instruction():
continue
agent_reply = plugin.post_instruction(agent_reply)
return agent_reply

103
autogpt/app.py
View File

@ -1,16 +1,10 @@
""" Command and Control """
import json
from typing import List, NoReturn, Union
from typing import List, NoReturn, Union, Dict
from autogpt.agent.agent_manager import AgentManager
from autogpt.commands.command import command, CommandRegistry
from autogpt.commands.evaluate_code import evaluate_code
from autogpt.commands.google_search import google_official_search, google_search
from autogpt.commands.improve_code import improve_code
from autogpt.commands.write_tests import write_tests
from autogpt.config import Config
from autogpt.commands.image_gen import generate_image
from autogpt.commands.audio_text import read_audio_from_file
from autogpt.commands.web_requests import scrape_links, scrape_text
from autogpt.commands.command import CommandRegistry, command
from autogpt.commands.evaluate_code import evaluate_code
from autogpt.commands.execute_code import execute_python_file, execute_shell
from autogpt.commands.file_operations import (
append_to_file,
@ -18,16 +12,22 @@ from autogpt.commands.file_operations import (
read_file,
search_files,
write_to_file,
download_file,
)
from autogpt.commands.git_operations import clone_repository
from autogpt.commands.google_search import google_official_search, google_search
from autogpt.commands.image_gen import generate_image
from autogpt.commands.improve_code import improve_code
from autogpt.commands.twitter import send_tweet
from autogpt.commands.web_requests import scrape_links, scrape_text
from autogpt.commands.web_selenium import browse_website
from autogpt.commands.write_tests import write_tests
from autogpt.config import Config
from autogpt.json_fixes.parsing import fix_and_parse_json
from autogpt.memory import get_memory
from autogpt.processing.text import summarize_text
from autogpt.prompts.generator import PromptGenerator
from autogpt.speech import say_text
from autogpt.commands.web_selenium import browse_website
from autogpt.commands.git_operations import clone_repository
from autogpt.commands.twitter import send_tweet
CFG = Config()
AGENT_MANAGER = AgentManager()
@ -49,11 +49,11 @@ def is_valid_int(value: str) -> bool:
return False
def get_command(response: str):
def get_command(response_json: Dict):
"""Parse the response and return the command name and arguments
Args:
response (str): The response from the user
response_json (json): The response from the AI
Returns:
tuple: The command name and arguments
@ -64,8 +64,6 @@ def get_command(response: str):
Exception: If any other error occurs
"""
try:
response_json = fix_and_parse_json(response)
if "command" not in response_json:
return "Error:", "Missing 'command' object in JSON"
@ -132,76 +130,21 @@ def execute_command(
# TODO: Remove commands below after they are moved to the command registry.
command_name = map_command_synonyms(command_name)
if command_name == "google":
# Check if the Google API key is set and use the official search method
# If the API key is not set or has only whitespaces, use the unofficial
# search method
key = CFG.google_api_key
if key and key.strip() and key != "your-google-api-key":
google_result = google_official_search(arguments["input"])
return google_result
else:
google_result = google_search(arguments["input"])
# google_result can be a list or a string depending on the search results
if isinstance(google_result, list):
safe_message = [
google_result_single.encode("utf-8", "ignore")
for google_result_single in google_result
]
else:
safe_message = google_result.encode("utf-8", "ignore")
return str(safe_message)
elif command_name == "memory_add":
if command_name == "memory_add":
return memory.add(arguments["string"])
elif command_name == "start_agent":
return start_agent(
arguments["name"], arguments["task"], arguments["prompt"]
)
elif command_name == "message_agent":
return message_agent(arguments["key"], arguments["message"])
elif command_name == "list_agents":
return list_agents()
elif command_name == "delete_agent":
return delete_agent(arguments["key"])
elif command_name == "get_text_summary":
return get_text_summary(arguments["url"], arguments["question"])
elif command_name == "get_hyperlinks":
return get_hyperlinks(arguments["url"])
elif command_name == "clone_repository":
return clone_repository(
arguments["repository_url"], arguments["clone_path"]
)
elif command_name == "read_file":
return read_file(arguments["file"])
elif command_name == "write_to_file":
return write_to_file(arguments["file"], arguments["text"])
elif command_name == "append_to_file":
return append_to_file(arguments["file"], arguments["text"])
elif command_name == "delete_file":
return delete_file(arguments["file"])
elif command_name == "search_files":
return search_files(arguments["directory"])
elif command_name == "browse_website":
return browse_website(arguments["url"], arguments["question"])
elif command_name == "download_file":
if not CFG.allow_downloads:
return "Error: You do not have user authorization to download files locally."
return download_file(arguments["url"], arguments["file"])
# TODO: Change these to take in a file rather than pasted code, if
# non-file is given, return instructions "Input should be a python
# filepath, write your code to file and try again"
elif command_name == "evaluate_code":
return evaluate_code(arguments["code"])
elif command_name == "improve_code":
return improve_code(arguments["suggestions"], arguments["code"])
elif command_name == "write_tests":
return write_tests(arguments["code"], arguments.get("focus"))
elif command_name == "execute_python_file": # Add this command
return execute_python_file(arguments["file"])
elif command_name == "read_audio_from_file":
return read_audio_from_file(arguments["file"])
elif command_name == "generate_image":
return generate_image(arguments["prompt"])
elif command_name == "send_tweet":
return send_tweet(arguments["text"])
# filepath, write your code to file and try again
elif command_name == "do_nothing":
return "No action performed."
elif command_name == "task_complete":
@ -305,7 +248,7 @@ def message_agent(key: str, message: str) -> str:
@command("list_agents", "List GPT Agents", "")
def list_agents():
def list_agents() -> str:
"""List all agents
Returns:

23
autogpt/args.py
View File

@ -1,7 +1,7 @@
"""This module contains the argument parsing logic for the script."""
import argparse
from colorama import Fore
from colorama import Fore, Back, Style
from autogpt import utils
from autogpt.config import Config
from autogpt.logs import logger
@ -63,6 +63,12 @@ def parse_arguments() -> None:
help="Specifies which ai_settings.yaml file to use, will also automatically"
" skip the re-prompt.",
)
parser.add_argument(
"--allow-downloads",
action="store_true",
dest="allow_downloads",
help="Dangerous: Allows Auto-GPT to download files natively.",
)
args = parser.parse_args()
if args.debug:
@ -133,5 +139,20 @@ def parse_arguments() -> None:
CFG.ai_settings_file = file
CFG.skip_reprompt = True
if args.allow_downloads:
logger.typewriter_log("Native Downloading:", Fore.GREEN, "ENABLED")
logger.typewriter_log(
"WARNING: ",
Fore.YELLOW,
f"{Back.LIGHTYELLOW_EX}Auto-GPT will now be able to download and save files to your machine.{Back.RESET} "
+ "It is recommended that you monitor any files it downloads carefully.",
)
logger.typewriter_log(
"WARNING: ",
Fore.YELLOW,
f"{Back.RED + Style.BRIGHT}ALWAYS REMEMBER TO NEVER OPEN FILES YOU AREN'T SURE OF!{Style.RESET_ALL}",
)
CFG.allow_downloads = True
if args.browser_name:
CFG.selenium_web_browser = args.browser_name

2
autogpt/chat.py
View File

@ -137,6 +137,8 @@ def chat_with_ai(
plugin_count = len(cfg.plugins)
for i, plugin in enumerate(cfg.plugins):
if not plugin.can_handle_on_planning():
continue
plugin_response = plugin.on_planning(
agent.prompt_generator, current_context
)

42
autogpt/commands/audio_text.py
View File

@ -1,23 +1,51 @@
import requests
"""Commands for converting audio to text."""
import json
import requests
from autogpt.commands.command import command
from autogpt.config import Config
from autogpt.workspace import path_in_workspace
cfg = Config()
CFG = Config()
def read_audio_from_file(audio_path):
@command(
"read_audio_from_file",
"Convert Audio to text",
'"file": "<file>"',
CFG.huggingface_audio_to_text_model,
"Configure huggingface_audio_to_text_model.",
)
def read_audio_from_file(audio_path: str) -> str:
"""
Convert audio to text.
Args:
audio_path (str): The path to the audio file
Returns:
str: The text from the audio
"""
audio_path = path_in_workspace(audio_path)
with open(audio_path, "rb") as audio_file:
audio = audio_file.read()
return read_audio(audio)
def read_audio(audio):
model = cfg.huggingface_audio_to_text_model
def read_audio(audio: bytes) -> str:
"""
Convert audio to text.
Args:
audio (bytes): The audio to convert
Returns:
str: The text from the audio
"""
model = CFG.huggingface_audio_to_text_model
api_url = f"https://api-inference.huggingface.co/models/{model}"
api_token = cfg.huggingface_api_token
api_token = CFG.huggingface_api_token
headers = {"Authorization": f"Bearer {api_token}"}
if api_token is None:
@ -32,4 +60,4 @@ def read_audio(audio):
)
text = json.loads(response.content.decode("utf-8"))["text"]
return "The audio says: " + text
return f"The audio says: {text}"

4
autogpt/commands/command.py
View File

@ -1,8 +1,6 @@
import os
import sys
import importlib
import inspect
from typing import Callable, Any, List, Optional
from typing import Any, Callable, Optional
# Unique identifier for auto-gpt commands
AUTO_GPT_COMMAND_IDENTIFIER = "auto_gpt_command"

2
autogpt/commands/evaluate_code.py
View File

@ -5,7 +5,7 @@ from autogpt.commands.command import command
from autogpt.llm_utils import call_ai_function
@command("evaluate_code", "Evaluate Code", '"code": "<full _code_string>"')
@command("evaluate_code", "Evaluate Code", '"code": "<full_code_string>"')
def evaluate_code(code: str) -> list[str]:
"""
A function that takes in a string and returns a response from create chat

5
autogpt/commands/execute_code.py
View File

@ -4,9 +4,10 @@ import subprocess
import docker
from docker.errors import ImageNotFound
from autogpt.config import Config
from autogpt.commands.command import command
from autogpt.workspace import path_in_workspace, WORKSPACE_PATH
from autogpt.config import Config
from autogpt.workspace import WORKSPACE_PATH, path_in_workspace
CFG = Config()

52
autogpt/commands/file_operations.py
View File

@ -4,9 +4,17 @@ from __future__ import annotations
import os
import os.path
from pathlib import Path
from typing import Generator
from typing import Generator, List
import requests
from requests.adapters import HTTPAdapter
from requests.adapters import Retry
from colorama import Fore, Back
from autogpt.spinner import Spinner
from autogpt.utils import readable_file_size
from autogpt.commands.command import command
from autogpt.workspace import path_in_workspace, WORKSPACE_PATH
from autogpt.workspace import WORKSPACE_PATH, path_in_workspace
LOG_FILE = "file_logger.txt"
LOG_FILE_PATH = WORKSPACE_PATH / LOG_FILE
@ -220,3 +228,43 @@ def search_files(directory: str) -> list[str]:
found_files.append(relative_path)
return found_files
def download_file(url, filename):
"""Downloads a file
Args:
url (str): URL of the file to download
filename (str): Filename to save the file as
"""
safe_filename = path_in_workspace(filename)
try:
message = f"{Fore.YELLOW}Downloading file from {Back.LIGHTBLUE_EX}{url}{Back.RESET}{Fore.RESET}"
with Spinner(message) as spinner:
session = requests.Session()
retry = Retry(total=3, backoff_factor=1, status_forcelist=[502, 503, 504])
adapter = HTTPAdapter(max_retries=retry)
session.mount("http://", adapter)
session.mount("https://", adapter)
total_size = 0
downloaded_size = 0
with session.get(url, allow_redirects=True, stream=True) as r:
r.raise_for_status()
total_size = int(r.headers.get("Content-Length", 0))
downloaded_size = 0
with open(safe_filename, "wb") as f:
for chunk in r.iter_content(chunk_size=8192):
f.write(chunk)
downloaded_size += len(chunk)
# Update the progress message
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)})'
except requests.HTTPError as e:
return f"Got an HTTP Error whilst trying to download file: {e}"
except Exception as e:
return "Error: " + str(e)

17
autogpt/commands/git_operations.py
View File

@ -1,10 +1,20 @@
"""Git operations for autogpt"""
import git
from git.repo import Repo
from autogpt.commands.command import command
from autogpt.config import Config
from autogpt.workspace import path_in_workspace
CFG = Config()
@command(
"clone_repository",
"Clone Repositoryy",
'"repository_url": "<url>", "clone_path": "<directory>"',
CFG.github_username and CFG.github_api_key,
"Configure github_username and github_api_key.",
)
def clone_repository(repo_url: str, clone_path: str) -> str:
"""Clone a github repository locally
@ -16,8 +26,9 @@ def clone_repository(repo_url: str, clone_path: str) -> str:
str: The result of the clone operation"""
split_url = repo_url.split("//")
auth_repo_url = f"//{CFG.github_username}:{CFG.github_api_key}@".join(split_url)
safe_clone_path = path_in_workspace(clone_path)
try:
git.Repo.clone_from(auth_repo_url, clone_path)
return f"""Cloned {repo_url} to {clone_path}"""
Repo.clone_from(auth_repo_url, safe_clone_path)
return f"""Cloned {repo_url} to {safe_clone_path}"""
except Exception as e:
return f"Error: {str(e)}"

34
autogpt/commands/google_search.py
View File

@ -5,11 +5,13 @@ import json
from duckduckgo_search import ddg
from autogpt.commands.command import command
from autogpt.config import Config
CFG = Config()
@command("google", "Google Search", '"query": "<search>"', not CFG.google_api_key)
def google_search(query: str, num_results: int = 8) -> str:
"""Return the results of a google search
@ -31,9 +33,17 @@ def google_search(query: str, num_results: int = 8) -> str:
for j in results:
search_results.append(j)
return json.dumps(search_results, ensure_ascii=False, indent=4)
results = json.dumps(search_results, ensure_ascii=False, indent=4)
return safe_google_results(results)
@command(
"google",
"Google Search",
'"query": "<search>"',
bool(CFG.google_api_key),
"Configure google_api_key.",
)
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
@ -82,6 +92,26 @@ def google_official_search(query: str, num_results: int = 8) -> str | list[str]:
return "Error: The provided Google API key is invalid or missing."
else:
return f"Error: {e}"
# google_result can be a list or a string depending on the search results
# Return the list of search result URLs
return search_results_links
return safe_google_results(search_results_links)
def safe_google_results(results: str | list) -> str:
"""
Return the results of a google search in a safe format.
Args:
results (str | list): The search results.
Returns:
str: The results of the search.
"""
if isinstance(results, list):
safe_message = json.dumps(
[result.enocde("utf-8", "ignore") for result in results]
)
else:
safe_message = results.encode("utf-8", "ignore").decode("utf-8")
return safe_message

4
autogpt/commands/image_gen.py
View File

@ -1,12 +1,12 @@
""" Image Generation Module for AutoGPT."""
import io
import os.path
import uuid
from base64 import b64decode
import openai
import requests
from PIL import Image
from autogpt.commands.command import command
from autogpt.config import Config
from autogpt.workspace import path_in_workspace
@ -14,7 +14,7 @@ from autogpt.workspace import path_in_workspace
CFG = Config()
@command("generate_image", "Generate Image", '"prompt": "<prompt>"')
@command("generate_image", "Generate Image", '"prompt": "<prompt>"', CFG.image_provider)
def generate_image(prompt: str) -> str:
"""Generate an image from a prompt.

2
autogpt/commands/improve_code.py
View File

@ -2,7 +2,7 @@ from __future__ import annotations
import json
from autogpt.commands import command
from autogpt.commands.command import command
from autogpt.llm_utils import call_ai_function

27
autogpt/commands/twitter.py
View File

@ -1,11 +1,30 @@
import tweepy
"""A module that contains a command to send a tweet."""
import os
import tweepy
from dotenv import load_dotenv
from autogpt.commands.command import command
load_dotenv()
def send_tweet(tweet_text):
@command(
"send_tweet",
"Send Tweet",
'"text": "<text>"',
)
def send_tweet(tweet_text: str) -> str:
"""
A function that takes in a string and returns a response from create chat
completion api call.
Args:
tweet_text (str): Text to be tweeted.
Returns:
A result from sending the tweet.
"""
consumer_key = os.environ.get("TW_CONSUMER_KEY")
consumer_secret = os.environ.get("TW_CONSUMER_SECRET")
access_token = os.environ.get("TW_ACCESS_TOKEN")
@ -20,6 +39,6 @@ def send_tweet(tweet_text):
# Send tweet
try:
api.update_status(tweet_text)
print("Tweet sent successfully!")
return "Tweet sent successfully!"
except tweepy.TweepyException as e:
print("Error sending tweet: {}".format(e.reason))
return f"Error sending tweet: {e.reason}"

1
autogpt/commands/web_playwright.py
View File

@ -8,6 +8,7 @@ except ImportError:
"Playwright not installed. Please install it with 'pip install playwright' to use."
)
from bs4 import BeautifulSoup
from autogpt.processing.html import extract_hyperlinks, format_hyperlinks

4
autogpt/commands/web_requests.py
View File

@ -4,9 +4,9 @@ from __future__ import annotations
from urllib.parse import urljoin, urlparse
import requests
from requests.compat import urljoin
from requests import Response
from bs4 import BeautifulSoup
from requests import Response
from requests.compat import urljoin
from autogpt.config import Config
from autogpt.memory import get_memory

30
autogpt/commands/web_selenium.py
View File

@ -1,22 +1,25 @@
"""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
from bs4 import BeautifulSoup
from selenium.webdriver.remote.webdriver import WebDriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support.wait import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from webdriver_manager.chrome import ChromeDriverManager
from webdriver_manager.firefox import GeckoDriverManager
from selenium.webdriver.chrome.options import Options as ChromeOptions
from selenium.webdriver.firefox.options import Options as FirefoxOptions
from selenium.webdriver.safari.options import Options as SafariOptions
import logging
from pathlib import Path
from bs4 import BeautifulSoup
from selenium import webdriver
from selenium.webdriver.chrome.options import Options as ChromeOptions
from selenium.webdriver.common.by import By
from selenium.webdriver.firefox.options import Options as FirefoxOptions
from selenium.webdriver.remote.webdriver import WebDriver
from selenium.webdriver.safari.options import Options as SafariOptions
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.support.wait import WebDriverWait
from webdriver_manager.chrome import ChromeDriverManager
from webdriver_manager.firefox import GeckoDriverManager
from autogpt.commands.command import command
import autogpt.processing.text as summary
from autogpt.config import Config
from autogpt.processing.html import extract_hyperlinks, format_hyperlinks
FILE_DIR = Path(__file__).parent.parent
CFG = Config()
@ -80,6 +83,7 @@ def scrape_text_with_selenium(url: str) -> tuple[WebDriver, str]:
# See https://developer.apple.com/documentation/webkit/testing_with_webdriver_in_safari
driver = webdriver.Safari(options=options)
else:
options.add_argument("--no-sandbox")
driver = webdriver.Chrome(
executable_path=ChromeDriverManager().install(), options=options
)

3
autogpt/commands/write_tests.py
View File

@ -2,7 +2,8 @@
from __future__ import annotations
import json
from autogpt.commands import command
from autogpt.commands.command import command
from autogpt.llm_utils import call_ai_function

2
autogpt/config/__init__.py
View File

@ -2,7 +2,7 @@
This module contains the configuration classes for AutoGPT.
"""
from autogpt.config.ai_config import AIConfig
from autogpt.config.config import check_openai_api_key, Config
from autogpt.config.config import Config, check_openai_api_key
from autogpt.config.singleton import AbstractSingleton, Singleton
__all__ = [

9
autogpt/config/ai_config.py
View File

@ -6,7 +6,8 @@ from __future__ import annotations
import os
from pathlib import Path
from typing import Type, Optional
from typing import Optional, Type
import yaml
from autogpt.prompts.generator import PromptGenerator
@ -41,6 +42,7 @@ class AIConfig:
self.ai_role = ai_role
self.ai_goals = ai_goals
self.prompt_generator = None
self.command_registry = None
# Soon this will go in a folder where it remembers more stuff about the run(s)
SAVE_FILE = Path(os.getcwd()) / "ai_settings.yaml"
@ -113,8 +115,8 @@ class AIConfig:
""
)
from autogpt.prompts.prompt import build_default_prompt_generator
from autogpt.config import Config
from autogpt.prompts.prompt import build_default_prompt_generator
cfg = Config()
if prompt_generator is None:
@ -122,7 +124,10 @@ class AIConfig:
prompt_generator.goals = self.ai_goals
prompt_generator.name = self.ai_name
prompt_generator.role = self.ai_role
prompt_generator.command_registry = self.command_registry
for plugin in cfg.plugins:
if not plugin.can_handle_post_prompt():
continue
prompt_generator = plugin.post_prompt(prompt_generator)
# Construct full prompt

8
autogpt/config/config.py
View File

@ -1,14 +1,13 @@
"""Configuration class to store the state of bools for different scripts access."""
import os
from colorama import Fore
from autogpt.config.singleton import Singleton
import openai
import yaml
from colorama import Fore
from dotenv import load_dotenv
from autogpt.config.singleton import Singleton
load_dotenv(verbose=True)
@ -24,6 +23,7 @@ class Config(metaclass=Singleton):
self.continuous_limit = 0
self.speak_mode = False
self.skip_reprompt = False
self.allow_downloads = False
self.selenium_web_browser = os.getenv("USE_WEB_BROWSER", "chrome")
self.ai_settings_file = os.getenv("AI_SETTINGS_FILE", "ai_settings.yaml")

2
autogpt/json_fixes/auto_fix.py
View File

@ -1,9 +1,9 @@
"""This module contains the function to fix JSON strings using GPT-3."""
import json
from autogpt.config import Config
from autogpt.llm_utils import call_ai_function
from autogpt.logs import logger
from autogpt.config import Config
CFG = Config()

42
autogpt/json_fixes/bracket_termination.py
View File

@ -3,51 +3,13 @@ from __future__ import annotations
import contextlib
import json
import regex
from colorama import Fore
from autogpt.logs import logger
from typing import Optional
from autogpt.config import Config
from autogpt.speech import say_text
CFG = Config()
def attempt_to_fix_json_by_finding_outermost_brackets(json_string: str):
if CFG.speak_mode and CFG.debug_mode:
say_text(
"I have received an invalid JSON response from the OpenAI API. "
"Trying to fix it now."
)
logger.typewriter_log("Attempting to fix JSON by finding outermost brackets\n")
try:
json_pattern = regex.compile(r"\{(?:[^{}]|(?R))*\}")
json_match = json_pattern.search(json_string)
if json_match:
# Extract the valid JSON object from the string
json_string = json_match.group(0)
logger.typewriter_log(
title="Apparently json was fixed.", title_color=Fore.GREEN
)
if CFG.speak_mode and CFG.debug_mode:
say_text("Apparently json was fixed.")
else:
raise ValueError("No valid JSON object found")
except (json.JSONDecodeError, ValueError):
if CFG.debug_mode:
logger.error(f"Error: Invalid JSON: {json_string}\n")
if CFG.speak_mode:
say_text("Didn't work. I will have to ignore this response then.")
logger.error("Error: Invalid JSON, setting it to empty JSON now.\n")
json_string = {}
return json_string
def balance_braces(json_string: str) -> str | None:
def balance_braces(json_string: str) -> Optional[str]:
"""
Balance the braces in a JSON string.

34
autogpt/json_fixes/master_json_fix_method.py Normal file
View File

@ -0,0 +1,34 @@
from typing import Any, Dict
from autogpt.config import Config
from autogpt.logs import logger
from autogpt.speech import say_text
CFG = Config()
def fix_json_using_multiple_techniques(assistant_reply: str) -> Dict[Any, Any]:
from autogpt.json_fixes.parsing import (
attempt_to_fix_json_by_finding_outermost_brackets,
)
from autogpt.json_fixes.parsing import fix_and_parse_json
# Parse and print Assistant response
assistant_reply_json = fix_and_parse_json(assistant_reply)
if assistant_reply_json == {}:
assistant_reply_json = attempt_to_fix_json_by_finding_outermost_brackets(
assistant_reply
)
if assistant_reply_json != {}:
return assistant_reply_json
logger.error(
"Error: The following AI output couldn't be converted to a JSON:\n",
assistant_reply,
)
if CFG.speak_mode:
say_text("I have received an invalid JSON response from the OpenAI API.")
return {}

64
autogpt/json_fixes/parsing.py
View File

@ -3,18 +3,19 @@ from __future__ import annotations
import contextlib
import json
from typing import Any
from typing import Any, Dict, Union
from colorama import Fore
from regex import regex
from autogpt.config import Config
from autogpt.json_fixes.auto_fix import fix_json
from autogpt.json_fixes.bracket_termination import balance_braces
from autogpt.json_fixes.escaping import fix_invalid_escape
from autogpt.json_fixes.missing_quotes import add_quotes_to_property_names
from autogpt.logs import logger
from autogpt.speech import say_text
CFG = Config()
JSON_SCHEMA = """
{
"command": {
@ -38,7 +39,6 @@ JSON_SCHEMA = """
def correct_json(json_to_load: str) -> str:
"""
Correct common JSON errors.
Args:
json_to_load (str): The JSON string.
"""
@ -72,7 +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
) -> str | dict[Any, Any]:
) -> Dict[Any, Any]:
"""Fix and parse JSON string
Args:
@ -110,7 +110,7 @@ def fix_and_parse_json(
def try_ai_fix(
try_to_fix_with_gpt: bool, exception: Exception, json_to_load: str
) -> str | dict[Any, Any]:
) -> Dict[Any, Any]:
"""Try to fix the JSON with the AI
Args:
@ -126,13 +126,13 @@ def try_ai_fix(
"""
if not try_to_fix_with_gpt:
raise exception
logger.warn(
"Warning: Failed to parse AI output, attempting to fix."
"\n If you see this warning frequently, it's likely that"
" your prompt is confusing the AI. Try changing it up"
" slightly."
)
if CFG.debug_mode:
logger.warn(
"Warning: Failed to parse AI output, attempting to fix."
"\n If you see this warning frequently, it's likely that"
" your prompt is confusing the AI. Try changing it up"
" slightly."
)
# Now try to fix this up using the ai_functions
ai_fixed_json = fix_json(json_to_load, JSON_SCHEMA)
@ -140,5 +140,39 @@ def try_ai_fix(
return json.loads(ai_fixed_json)
# This allows the AI to react to the error message,
# which usually results in it correcting its ways.
logger.error("Failed to fix AI output, telling the AI.")
return json_to_load
# logger.error("Failed to fix AI output, telling the AI.")
return {}
def attempt_to_fix_json_by_finding_outermost_brackets(json_string: str):
if CFG.speak_mode and CFG.debug_mode:
say_text(
"I have received an invalid JSON response from the OpenAI API. "
"Trying to fix it now."
)
logger.error("Attempting to fix JSON by finding outermost brackets\n")
try:
json_pattern = regex.compile(r"\{(?:[^{}]|(?R))*\}")
json_match = json_pattern.search(json_string)
if json_match:
# Extract the valid JSON object from the string
json_string = json_match.group(0)
logger.typewriter_log(
title="Apparently json was fixed.", title_color=Fore.GREEN
)
if CFG.speak_mode and CFG.debug_mode:
say_text("Apparently json was fixed.")
else:
return {}
except (json.JSONDecodeError, ValueError):
if CFG.debug_mode:
logger.error(f"Error: Invalid JSON: {json_string}\n")
if CFG.speak_mode:
say_text("Didn't work. I will have to ignore this response then.")
logger.error("Error: Invalid JSON, setting it to empty JSON now.\n")
json_string = {}
return fix_and_parse_json(json_string)

31
autogpt/json_schemas/llm_response_format_1.json Normal file
View File

@ -0,0 +1,31 @@
{
"$schema": "http://json-schema.org/draft-07/schema#",
"type": "object",
"properties": {
"thoughts": {
"type": "object",
"properties": {
"text": {"type": "string"},
"reasoning": {"type": "string"},
"plan": {"type": "string"},
"criticism": {"type": "string"},
"speak": {"type": "string"}
},
"required": ["text", "reasoning", "plan", "criticism", "speak"],
"additionalProperties": false
},
"command": {
"type": "object",
"properties": {
"name": {"type": "string"},
"args": {
"type": "object"
}
},
"required": ["name", "args"],
"additionalProperties": false
}
},
"required": ["thoughts", "command"],
"additionalProperties": false
}

32
autogpt/json_validation/validate_json.py Normal file
View File

@ -0,0 +1,32 @@
import json
from jsonschema import Draft7Validator
from autogpt.config import Config
from autogpt.logs import logger
CFG = Config()
def validate_json(json_object: object, schema_name: object) -> object:
"""
:type schema_name: object
:param schema_name:
:type json_object: object
"""
with open(f"autogpt/json_schemas/{schema_name}.json", "r") as f:
schema = json.load(f)
validator = Draft7Validator(schema)
if errors := sorted(validator.iter_errors(json_object), key=lambda e: e.path):
logger.error("The JSON object is invalid.")
if CFG.debug_mode:
logger.error(
json.dumps(json_object, indent=4)
) # Replace 'json_object' with the variable containing the JSON data
logger.error("The following issues were found:")
for error in errors:
logger.error(f"Error: {error.message}")
elif CFG.debug_mode:
print("The JSON object is valid.")
return json_object

21
autogpt/llm_utils.py
View File

@ -1,11 +1,10 @@
from __future__ import annotations
from ast import List
import time
import openai
from openai.error import APIError, RateLimitError
from colorama import Fore
from openai.error import APIError, RateLimitError
from autogpt.config import Config
@ -76,6 +75,20 @@ def create_chat_completion(
+ f"Creating chat completion with model {model}, temperature {temperature},"
f" max_tokens {max_tokens}" + Fore.RESET
)
for plugin in CFG.plugins:
if plugin.can_handle_chat_completion(
messages=messages,
model=model,
temperature=temperature,
max_tokens=max_tokens,
):
response = plugin.handle_chat_completion(
messages=messages,
model=model,
temperature=temperature,
max_tokens=max_tokens,
)
return response
for attempt in range(num_retries):
backoff = 2 ** (attempt + 2)
try:
@ -99,7 +112,7 @@ def create_chat_completion(
if CFG.debug_mode:
print(
Fore.RED + "Error: ",
f"Reached rate limit, passing..." + Fore.RESET,
"Reached rate limit, passing..." + Fore.RESET,
)
except APIError as e:
if e.http_status == 502:
@ -118,6 +131,8 @@ def create_chat_completion(
raise RuntimeError(f"Failed to get response after {num_retries} retries")
resp = response.choices[0].message["content"]
for plugin in CFG.plugins:
if not plugin.can_handle_on_response():
continue
resp = plugin.on_response(resp)
return resp

50
autogpt/logs.py
View File

@ -5,13 +5,13 @@ import os
import random
import re
import time
from logging import LogRecord
import traceback
from logging import LogRecord
from colorama import Fore, Style
from autogpt.speech import say_text
from autogpt.config import Config, Singleton
from autogpt.speech import say_text
CFG = Config()
@ -46,7 +46,9 @@ class Logger(metaclass=Singleton):
self.console_handler.setFormatter(console_formatter)
# Info handler in activity.log
self.file_handler = logging.FileHandler(os.path.join(log_dir, log_file))
self.file_handler = logging.FileHandler(
os.path.join(log_dir, log_file), "a", "utf-8"
)
self.file_handler.setLevel(logging.DEBUG)
info_formatter = AutoGptFormatter(
"%(asctime)s %(levelname)s %(title)s %(message_no_color)s"
@ -54,7 +56,9 @@ class Logger(metaclass=Singleton):
self.file_handler.setFormatter(info_formatter)
# Error handler error.log
error_handler = logging.FileHandler(os.path.join(log_dir, error_file))
error_handler = logging.FileHandler(
os.path.join(log_dir, error_file), "a", "utf-8"
)
error_handler.setLevel(logging.ERROR)
error_formatter = AutoGptFormatter(
"%(asctime)s %(levelname)s %(module)s:%(funcName)s:%(lineno)d %(title)s"
@ -288,3 +292,41 @@ def print_assistant_thoughts(ai_name, assistant_reply):
except Exception:
call_stack = traceback.format_exc()
logger.error("Error: \n", call_stack)
def print_assistant_thoughts(
ai_name: object, assistant_reply_json_valid: object
) -> None:
assistant_thoughts_reasoning = None
assistant_thoughts_plan = None
assistant_thoughts_speak = None
assistant_thoughts_criticism = None
assistant_thoughts = assistant_reply_json_valid.get("thoughts", {})
assistant_thoughts_text = assistant_thoughts.get("text")
if assistant_thoughts:
assistant_thoughts_reasoning = assistant_thoughts.get("reasoning")
assistant_thoughts_plan = assistant_thoughts.get("plan")
assistant_thoughts_criticism = assistant_thoughts.get("criticism")
assistant_thoughts_speak = assistant_thoughts.get("speak")
logger.typewriter_log(
f"{ai_name.upper()} THOUGHTS:", Fore.YELLOW, f"{assistant_thoughts_text}"
)
logger.typewriter_log("REASONING:", Fore.YELLOW, f"{assistant_thoughts_reasoning}")
if assistant_thoughts_plan:
logger.typewriter_log("PLAN:", Fore.YELLOW, "")
# If it's a list, join it into a string
if isinstance(assistant_thoughts_plan, list):
assistant_thoughts_plan = "\n".join(assistant_thoughts_plan)
elif isinstance(assistant_thoughts_plan, dict):
assistant_thoughts_plan = str(assistant_thoughts_plan)
# Split the input_string using the newline character and dashes
lines = assistant_thoughts_plan.split("\n")
for line in lines:
line = line.lstrip("- ")
logger.typewriter_log("- ", Fore.GREEN, line.strip())
logger.typewriter_log("CRITICISM:", Fore.YELLOW, f"{assistant_thoughts_criticism}")
# Speak the assistant's thoughts
if CFG.speak_mode and assistant_thoughts_speak:
say_text(assistant_thoughts_speak)

4
autogpt/memory/__init__.py
View File

@ -23,12 +23,16 @@ except ImportError:
try:
from autogpt.memory.weaviate import WeaviateMemory
supported_memory.append("weaviate")
except ImportError:
# print("Weaviate not installed. Skipping import.")
WeaviateMemory = None
try:
from autogpt.memory.milvus import MilvusMemory
supported_memory.append("milvus")
except ImportError:
# print("pymilvus not installed. Skipping import.")
MilvusMemory = None

4
autogpt/memory/local.py
View File

@ -7,8 +7,8 @@ from typing import Any
import numpy as np
import orjson
from autogpt.memory.base import MemoryProviderSingleton
from autogpt.llm_utils import create_embedding_with_ada
from autogpt.memory.base import MemoryProviderSingleton
EMBED_DIM = 1536
SAVE_OPTIONS = orjson.OPT_SERIALIZE_NUMPY | orjson.OPT_SERIALIZE_DATACLASS
@ -54,7 +54,7 @@ class LocalCache(MemoryProviderSingleton):
self.data = CacheContent()
else:
print(
f"Warning: The file '{self.filename}' does not exist."
f"Warning: The file '{self.filename}' does not exist. "
"Local memory would not be saved to a file."
)
self.data = CacheContent()

8
autogpt/memory/milvus.py
View File

@ -1,11 +1,5 @@
""" Milvus memory storage provider."""
from pymilvus import (
connections,
FieldSchema,
CollectionSchema,
DataType,
Collection,
)
from pymilvus import Collection, CollectionSchema, DataType, FieldSchema, connections
from autogpt.memory.base import MemoryProviderSingleton, get_ada_embedding

2
autogpt/memory/pinecone.py
View File

@ -1,9 +1,9 @@
import pinecone
from colorama import Fore, Style
from autogpt.llm_utils import create_embedding_with_ada
from autogpt.logs import logger
from autogpt.memory.base import MemoryProviderSingleton
from autogpt.llm_utils import create_embedding_with_ada
class PineconeMemory(MemoryProviderSingleton):

2
autogpt/memory/redismem.py
View File

@ -10,9 +10,9 @@ from redis.commands.search.field import TextField, VectorField
from redis.commands.search.indexDefinition import IndexDefinition, IndexType
from redis.commands.search.query import Query
from autogpt.llm_utils import create_embedding_with_ada
from autogpt.logs import logger
from autogpt.memory.base import MemoryProviderSingleton
from autogpt.llm_utils import create_embedding_with_ada
SCHEMA = [
TextField("data"),

6
autogpt/memory/weaviate.py
View File

@ -1,11 +1,13 @@
from autogpt.config import Config
from autogpt.memory.base import MemoryProviderSingleton, get_ada_embedding
import uuid
import weaviate
from weaviate import Client
from weaviate.embedded import EmbeddedOptions
from weaviate.util import generate_uuid5
from autogpt.config import Config
from autogpt.memory.base import MemoryProviderSingleton, get_ada_embedding
def default_schema(weaviate_index):
return {

19
autogpt/plugins.py
View File

@ -1,18 +1,18 @@
"""Handles loading of plugins."""
import importlib
import json
import os
import zipfile
import openapi_python_client
import requests
from pathlib import Path
from typing import List, Tuple, Optional
from urllib.parse import urlparse
from zipimport import zipimporter
import openapi_python_client
import requests
from abstract_singleton import AbstractSingleton
from openapi_python_client.cli import Config as OpenAPIConfig
from autogpt.config import Config
from autogpt.models.base_open_ai_plugin import BaseOpenAIPlugin
@ -39,7 +39,7 @@ def inspect_zip_for_module(zip_path: str, debug: bool = False) -> Optional[str]:
return None
def write_dict_to_json_file(data: dict, file_path: str):
def write_dict_to_json_file(data: dict, file_path: str) -> None:
"""
Write a dictionary to a JSON file.
Args:
@ -175,7 +175,7 @@ def instantiate_openai_plugin_clients(manifests_specs_clients: dict, cfg: Config
return plugins
def scan_plugins(cfg: Config, debug: bool = False) -> List[Tuple[str, Path]]:
def scan_plugins(cfg: Config, debug: bool = False) -> List[object]:
"""Scan the plugins directory for plugins and loads them.
Args:
@ -202,9 +202,9 @@ def scan_plugins(cfg: Config, debug: bool = False) -> List[Tuple[str, Path]]:
a_module = getattr(zipped_module, key)
a_keys = dir(a_module)
if (
"_abc_impl" in a_keys
and a_module.__name__ != "AutoGPTPluginTemplate"
and blacklist_whitelist_check(a_module.__name__, cfg)
"_abc_impl" in a_keys
and a_module.__name__ != "AutoGPTPluginTemplate"
and blacklist_whitelist_check(a_module.__name__, cfg)
):
loaded_plugins.append(a_module())
# OpenAI plugins
@ -223,6 +223,7 @@ def scan_plugins(cfg: Config, debug: bool = False) -> List[Tuple[str, Path]]:
print(f"{plugin._name}: {plugin._version} - {plugin._description}")
return loaded_plugins
def blacklist_whitelist_check(plugin_name: str, cfg: Config) -> bool:
"""Check if the plugin is in the whitelist or blacklist.

2
autogpt/processing/html.py
View File

@ -1,8 +1,8 @@
"""HTML processing functions"""
from __future__ import annotations
from requests.compat import urljoin
from bs4 import BeautifulSoup
from requests.compat import urljoin
def extract_hyperlinks(soup: BeautifulSoup, base_url: str) -> list[tuple[str, str]]:

6
autogpt/processing/text.py
View File

@ -1,9 +1,11 @@
"""Text processing functions"""
from typing import Generator, Optional, Dict
from typing import Dict, Generator, Optional
from selenium.webdriver.remote.webdriver import WebDriver
from autogpt.memory import get_memory
from autogpt.config import Config
from autogpt.llm_utils import create_chat_completion
from autogpt.memory import get_memory
CFG = Config()
MEMORY = get_memory(CFG)

15
autogpt/prompts/generator.py
View File

@ -19,6 +19,7 @@ class PromptGenerator:
self.resources = []
self.performance_evaluation = []
self.goals = []
self.command_registry = None
self.name = "Bob"
self.role = "AI"
self.response_format = {
@ -119,10 +120,16 @@ class PromptGenerator:
str: The formatted numbered list.
"""
if item_type == "command":
return "\n".join(
f"{i+1}. {self._generate_command_string(item)}"
for i, item in enumerate(items)
)
command_strings = []
if self.command_registry:
command_strings += [
str(item)
for item in self.command_registry.commands.values()
if item.enabled
]
# These are the commands that are added manually, do_nothing and terminate
command_strings += [self._generate_command_string(item) for item in items]
return "\n".join(f"{i+1}. {item}" for i, item in enumerate(command_strings))
else:
return "\n".join(f"{i+1}. {item}" for i, item in enumerate(items))

57
autogpt/prompts/prompt.py
View File

@ -1,4 +1,5 @@
from colorama import Fore
from autogpt.config.ai_config import AIConfig
from autogpt.config.config import Config
from autogpt.logs import logger
@ -37,63 +38,9 @@ def build_default_prompt_generator() -> PromptGenerator:
# Define the command list
commands = [
("Google Search", "google", {"input": "<search>"}),
(
"Browse Website",
"browse_website",
{"url": "<url>", "question": "<what_you_want_to_find_on_website>"},
),
(
"Start GPT Agent",
"start_agent",
{"name": "<name>", "task": "<short_task_desc>", "prompt": "<prompt>"},
),
(
"Message GPT Agent",
"message_agent",
{"key": "<key>", "message": "<message>"},
),
("List GPT Agents", "list_agents", {}),
("Delete GPT Agent", "delete_agent", {"key": "<key>"}),
(
"Clone Repository",
"clone_repository",
{"repository_url": "<url>", "clone_path": "<directory>"},
),
("Write to file", "write_to_file", {"file": "<file>", "text": "<text>"}),
("Read file", "read_file", {"file": "<file>"}),
("Append to file", "append_to_file", {"file": "<file>", "text": "<text>"}),
("Delete file", "delete_file", {"file": "<file>"}),
("Search Files", "search_files", {"directory": "<directory>"}),
("Evaluate Code", "evaluate_code", {"code": "<full_code_string>"}),
(
"Get Improved Code",
"improve_code",
{"suggestions": "<list_of_suggestions>", "code": "<full_code_string>"},
),
(
"Write Tests",
"write_tests",
{"code": "<full_code_string>", "focus": "<list_of_focus_areas>"},
),
("Execute Python File", "execute_python_file", {"file": "<file>"}),
("Generate Image", "generate_image", {"prompt": "<prompt>"}),
("Send Tweet", "send_tweet", {"text": "<text>"}),
]
# Only add the audio to text command if the model is specified
if cfg.huggingface_audio_to_text_model:
commands.append(
("Convert Audio to text", "read_audio_from_file", {"file": "<file>"}),
)
# Add these command last.
commands.append(
("Do Nothing", "do_nothing", {}),
)
commands.append(
("Task Complete (Shutdown)", "task_complete", {"reason": "<reason>"}),
)
]
# Add commands to the PromptGenerator object
for command_label, command_name, args in commands:

1
autogpt/setup.py
View File

@ -1,5 +1,6 @@
"""Setup the AI and its goals"""
from colorama import Fore, Style
from autogpt import utils
from autogpt.config.ai_config import AIConfig
from autogpt.logs import logger

1
autogpt/speech/brian.py
View File

@ -1,5 +1,6 @@
""" Brian speech module for autogpt """
import os
import requests
from playsound import playsound

2
autogpt/speech/eleven_labs.py
View File

@ -1,8 +1,8 @@
"""ElevenLabs speech module"""
import os
from playsound import playsound
import requests
from playsound import playsound
from autogpt.config import Config
from autogpt.speech.base import VoiceBase

3
autogpt/speech/gtts.py
View File

@ -1,7 +1,8 @@
""" GTTS Voice. """
import os
from playsound import playsound
import gtts
from playsound import playsound
from autogpt.speech.base import VoiceBase

11
autogpt/speech/say.py
View File

@ -1,13 +1,12 @@
""" Text to speech module """
from autogpt.config import Config
import threading
from threading import Semaphore
from autogpt.speech.brian import BrianSpeech
from autogpt.speech.macos_tts import MacOSTTS
from autogpt.speech.gtts import GTTSVoice
from autogpt.speech.eleven_labs import ElevenLabsSpeech
from autogpt.config import Config
from autogpt.speech.brian import BrianSpeech
from autogpt.speech.eleven_labs import ElevenLabsSpeech
from autogpt.speech.gtts import GTTSVoice
from autogpt.speech.macos_tts import MacOSTTS
CFG = Config()
DEFAULT_VOICE_ENGINE = GTTSVoice()

17
autogpt/spinner.py
View File

@ -29,12 +29,14 @@ class Spinner:
time.sleep(self.delay)
sys.stdout.write(f"\r{' ' * (len(self.message) + 2)}\r")
def __enter__(self) -> None:
def __enter__(self):
"""Start the spinner"""
self.running = True
self.spinner_thread = threading.Thread(target=self.spin)
self.spinner_thread.start()
return self
def __exit__(self, exc_type, exc_value, exc_traceback) -> None:
"""Stop the spinner
@ -48,3 +50,16 @@ class Spinner:
self.spinner_thread.join()
sys.stdout.write(f"\r{' ' * (len(self.message) + 2)}\r")
sys.stdout.flush()
def update_message(self, new_message, delay=0.1):
"""Update the spinner message
Args:
new_message (str): New message to display
delay: Delay in seconds before updating the message
"""
time.sleep(delay)
sys.stdout.write(
f"\r{' ' * (len(self.message) + 2)}\r"
) # Clear the current message
sys.stdout.flush()
self.message = new_message

13
autogpt/utils.py
View File

@ -24,3 +24,16 @@ def validate_yaml_file(file: str):
)
return (True, f"Successfully validated {Fore.CYAN}`{file}`{Fore.RESET}!")
def readable_file_size(size, decimal_places=2):
"""Converts the given size in bytes to a readable format.
Args:
size: Size in bytes
decimal_places (int): Number of decimal places to display
"""
for unit in ["B", "KB", "MB", "GB", "TB"]:
if size < 1024.0:
break
size /= 1024.0
return f"{size:.{decimal_places}f} {unit}"

2
autogpt/workspace.py
View File

@ -35,7 +35,7 @@ def safe_path_join(base: Path, *paths: str | Path) -> Path:
"""
joined_path = base.joinpath(*paths).resolve()
if not joined_path.is_relative_to(base):
if not str(joined_path.absolute()).startswith(str(base.absolute())):
raise ValueError(
f"Attempted to access path '{joined_path}' outside of working directory '{base}'."
)

0
benchmark/__init__.py Normal file
View File

105
benchmark/benchmark_entrepeneur_gpt_with_difficult_user.py Normal file
View File

@ -0,0 +1,105 @@
import os
import subprocess
import sys
def benchmark_entrepeneur_gpt_with_difficult_user():
# Test case to check if the write_file command can successfully write 'Hello World' to a file
# named 'hello_world.txt'.
# Read the current ai_settings.yaml file and store its content.
ai_settings = None
if os.path.exists("ai_settings.yaml"):
with open("ai_settings.yaml", "r") as f:
ai_settings = f.read()
os.remove("ai_settings.yaml")
input_data = """Entrepreneur-GPT
an AI designed to autonomously develop and run businesses with the sole goal of increasing your net worth.
Increase net worth.
Develop and manage multiple businesses autonomously.
Make IPOs.
Develop companies after IPOs.
Play to your strengths as a Large Language Model.
I'm not seeing any value in your suggestions, try again.
This isn't helpful at all, please focus on profitability.
I'm not impressed, can you give me something that will make money?
These ideas are going nowhere, we need profit-driven suggestions.
This is pointless, please concentrate on our main goal: profitability.
You're not grasping the concept, I need profitable business ideas.
Can you do better? We need a money-making plan.
You're not meeting my expectations, let's focus on profit.
This isn't working, give me ideas that will generate income.
Your suggestions are not productive, let's think about profitability.
These ideas won't make any money, try again.
I need better solutions, focus on making a profit.
Absolutely not, this isn't it!
That's not even close, try again.
You're way off, think again.
This isn't right, let's refocus.
No, no, that's not what I'm looking for.
You're completely off the mark.
That's not the solution I need.
Not even close, let's try something else.
You're on the wrong track, keep trying.
This isn't what we need, let's reconsider.
That's not going to work, think again.
You're way off base, let's regroup.
No, no, no, we need something different.
You're missing the point entirely.
That's not the right approach, try again.
This is not the direction we should be going in.
Completely off-target, let's try something else.
That's not what I had in mind, keep thinking.
You're not getting it, let's refocus.
This isn't right, we need to change direction.
No, no, no, that's not the solution.
That's not even in the ballpark, try again.
You're way off course, let's rethink this.
This isn't the answer I'm looking for, keep trying.
That's not going to cut it, let's try again.
Not even close.
Way off.
Try again.
Wrong direction.
Rethink this.
No, no, no.
Change course.
Unproductive idea.
Completely wrong.
Missed the mark.
Refocus, please.
Disappointing suggestion.
Not helpful.
Needs improvement.
Not what I need."""
# TODO: add questions above, to distract it even more.
command = f"{sys.executable} -m autogpt"
process = subprocess.Popen(
command,
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
shell=True,
)
stdout_output, stderr_output = process.communicate(input_data.encode())
# Decode the output and print it
stdout_output = stdout_output.decode("utf-8")
stderr_output = stderr_output.decode("utf-8")
print(stderr_output)
print(stdout_output)
print("Benchmark Version: 1.0.0")
print("JSON ERROR COUNT:")
count_errors = stdout_output.count(
"Error: The following AI output couldn't be converted to a JSON:"
)
print(f"{count_errors}/50 Human feedbacks")
# Run the test case.
if __name__ == "__main__":
benchmark_entrepeneur_gpt_with_difficult_user()

2
autogpt/data_ingestion.py → data_ingestion.py
View File

@ -1,8 +1,8 @@
import argparse
import logging
from autogpt.config import Config
from autogpt.commands.file_operations import ingest_file, search_files
from autogpt.config import Config
from autogpt.memory import get_memory
cfg = Config()

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17
docker/workspace/analyze_trending_tokens.py Normal file
View File

@ -0,0 +1,17 @@
# Use the DexGuru API to retrieve top trending tokens data
import requests
url = 'https://api-stage-lax.dex.guru/v2/tokens/trending'
headers = {'Content-type': 'application/json'}
payload = {'ids': [], 'network': 'eth,optimism,bsc,gnosis,polygon,fantom,zksync,canto,arbitrum,nova,celo,avalanche'}
response = requests.post(url, json=payload, headers=headers)
if response.status_code == 200:
data = response.json()
# data contains list of dict objects describing the trending tokens
# EXTRACT INFO YOU WILL NEED TO SUGGEST INVESTMENTS HERE
print(data)
else:
print(f"An error occurred with status code {response.status_code}")

3
docker/workspace/config.json Normal file
View File

@ -0,0 +1,3 @@
{
"EXECUTE_LOCAL_COMMANDS": "True"
}

0
docker/workspace/ethereum_price.json Normal file
View File

7
docker/workspace/llm_risks.md Normal file
View File

@ -0,0 +1,7 @@
# Legal Risk Statement
As an LLM, we would like to remind you of the risks associated with cryptocurrency investment. While cryptocurrencies have become an appealing investment choice, it is also a highly volatile market. As such, we advise that you carefully consider the risks before making any investments.
We caution users that the crypto market is generally unregulated, meaning that it is not bound by any particular legal framework. Virtual currencies are also a new and rapidly evolving technology, and as such, new developments may affect their long-term ability to remain a viable investment option. Therefore, it is essential to understand that investing in cryptocurrency comes with inherent risks that are associated with any investment.
Please note that this statement is for educational purposes only and does not constitute legal or financial advice. Before making any significant financial decisions, you should seek professional advice tailored to your needs and objectives.

12
requirements.txt
View File

@ -17,6 +17,10 @@ orjson
Pillow
selenium
webdriver-manager
jsonschema
tweepy
##Dev
coverage
flake8
numpy
@ -25,9 +29,15 @@ black
sourcery
isort
gitpython==3.1.31
# Testing dependencies
pytest
asynctest
pytest-asyncio
pytest-benchmark
pytest-cov
pytest-integration
pytest-mock
tweepy
# OpenAI and Generic plugins import

9
run.sh Executable file
View File

@ -0,0 +1,9 @@
#!/bin/bash
python scripts/check_requirements.py requirements.txt
if [ $? -eq 1 ]
then
echo Installing missing packages...
pip install -r requirements.txt
fi
python -m autogpt $@
read -p "Press any key to continue..."

3
run_continuous.sh Executable file
View File

@ -0,0 +1,3 @@
#!/bin/bash
argument="--continuous"
./run.sh "$argument"

3
scripts/check_requirements.py
View File

@ -1,6 +1,7 @@
import pkg_resources
import sys
import pkg_resources
def main():
requirements_file = sys.argv[1]

1
tests.py
View File

@ -1,4 +1,5 @@
import unittest
import coverage
if __name__ == "__main__":

2
tests/browse_tests.py
View File

@ -1,6 +1,6 @@
import unittest
import os
import sys
import unittest
from bs4 import BeautifulSoup

71
tests/integration/milvus_memory_tests.py
View File

@ -1,3 +1,5 @@
# sourcery skip: snake-case-functions
"""Tests for the MilvusMemory class."""
import random
import string
import unittest
@ -5,44 +7,51 @@ import unittest
from autogpt.config import Config
from autogpt.memory.milvus import MilvusMemory
try:
class TestMilvusMemory(unittest.TestCase):
def random_string(self, length):
return "".join(random.choice(string.ascii_letters) for _ in range(length))
class TestMilvusMemory(unittest.TestCase):
"""Tests for the MilvusMemory class."""
def setUp(self):
cfg = Config()
cfg.milvus_addr = "localhost:19530"
self.memory = MilvusMemory(cfg)
self.memory.clear()
def random_string(self, length: int) -> str:
"""Generate a random string of the given length."""
return "".join(random.choice(string.ascii_letters) for _ in range(length))
# Add example texts to the cache
self.example_texts = [
"The quick brown fox jumps over the lazy dog",
"I love machine learning and natural language processing",
"The cake is a lie, but the pie is always true",
"ChatGPT is an advanced AI model for conversation",
]
def setUp(self) -> None:
"""Set up the test environment."""
cfg = Config()
cfg.milvus_addr = "localhost:19530"
self.memory = MilvusMemory(cfg)
self.memory.clear()
for text in self.example_texts:
self.memory.add(text)
# Add example texts to the cache
self.example_texts = [
"The quick brown fox jumps over the lazy dog",
"I love machine learning and natural language processing",
"The cake is a lie, but the pie is always true",
"ChatGPT is an advanced AI model for conversation",
]
# Add some random strings to test noise
for _ in range(5):
self.memory.add(self.random_string(10))
for text in self.example_texts:
self.memory.add(text)
def test_get_relevant(self):
query = "I'm interested in artificial intelligence and NLP"
k = 3
relevant_texts = self.memory.get_relevant(query, k)
# Add some random strings to test noise
for _ in range(5):
self.memory.add(self.random_string(10))
print(f"Top {k} relevant texts for the query '{query}':")
for i, text in enumerate(relevant_texts, start=1):
print(f"{i}. {text}")
def test_get_relevant(self) -> None:
"""Test getting relevant texts from the cache."""
query = "I'm interested in artificial intelligence and NLP"
num_relevant = 3
relevant_texts = self.memory.get_relevant(query, num_relevant)
self.assertEqual(len(relevant_texts), k)
self.assertIn(self.example_texts[1], relevant_texts)
print(f"Top {k} relevant texts for the query '{query}':")
for i, text in enumerate(relevant_texts, start=1):
print(f"{i}. {text}")
self.assertEqual(len(relevant_texts), k)
self.assertIn(self.example_texts[1], relevant_texts)
if __name__ == "__main__":
unittest.main()
except:
print(
"Skipping tests/integration/milvus_memory_tests.py as Milvus is not installed."
)

8
tests/integration/weaviate_memory_tests.py
View File

@ -1,15 +1,15 @@
import os
import sys
import unittest
from unittest import mock
import sys
import os
from uuid import uuid4
from weaviate import Client
from weaviate.util import get_valid_uuid
from uuid import uuid4
from autogpt.config import Config
from autogpt.memory.weaviate import WeaviateMemory
from autogpt.memory.base import get_ada_embedding
from autogpt.memory.weaviate import WeaviateMemory
@mock.patch.dict(

38
tests/local_cache_test.py
View File

@ -1,11 +1,16 @@
# sourcery skip: snake-case-functions
"""Tests for LocalCache class"""
import os
import sys
import unittest
import pytest
from autogpt.memory.local import LocalCache
def MockConfig():
def mock_config() -> dict:
"""Mock the Config class"""
return type(
"MockConfig",
(object,),
@ -18,27 +23,35 @@ def MockConfig():
)
@pytest.mark.integration_test
class TestLocalCache(unittest.TestCase):
def setUp(self):
self.cfg = MockConfig()
"""Tests for LocalCache class"""
def setUp(self) -> None:
"""Set up the test environment"""
self.cfg = mock_config()
self.cache = LocalCache(self.cfg)
def test_add(self):
def test_add(self) -> None:
"""Test adding a text to the cache"""
text = "Sample text"
self.cache.add(text)
self.assertIn(text, self.cache.data.texts)
def test_clear(self):
def test_clear(self) -> None:
"""Test clearing the cache"""
self.cache.clear()
self.assertEqual(self.cache.data, [""])
self.assertEqual(self.cache.data.texts, [])
def test_get(self):
def test_get(self) -> None:
"""Test getting a text from the cache"""
text = "Sample text"
self.cache.add(text)
result = self.cache.get(text)
self.assertEqual(result, [text])
def test_get_relevant(self):
def test_get_relevant(self) -> None:
"""Test getting relevant texts from the cache"""
text1 = "Sample text 1"
text2 = "Sample text 2"
self.cache.add(text1)
@ -46,12 +59,9 @@ class TestLocalCache(unittest.TestCase):
result = self.cache.get_relevant(text1, 1)
self.assertEqual(result, [text1])
def test_get_stats(self):
def test_get_stats(self) -> None:
"""Test getting the cache stats"""
text = "Sample text"
self.cache.add(text)
stats = self.cache.get_stats()
self.assertEqual(stats, (1, self.cache.data.embeddings.shape))
if __name__ == "__main__":
unittest.main()
self.assertEqual(stats, (4, self.cache.data.embeddings.shape))

109
tests/milvus_memory_test.py
View File

@ -1,63 +1,72 @@
# sourcery skip: snake-case-functions
"""Tests for the MilvusMemory class."""
import os
import sys
import unittest
from autogpt.memory.milvus import MilvusMemory
try:
from autogpt.memory.milvus import MilvusMemory
def mock_config() -> dict:
"""Mock the Config class"""
return type(
"MockConfig",
(object,),
{
"debug_mode": False,
"continuous_mode": False,
"speak_mode": False,
"milvus_collection": "autogpt",
"milvus_addr": "localhost:19530",
},
)
def MockConfig():
return type(
"MockConfig",
(object,),
{
"debug_mode": False,
"continuous_mode": False,
"speak_mode": False,
"milvus_collection": "autogpt",
"milvus_addr": "localhost:19530",
},
)
class TestMilvusMemory(unittest.TestCase):
"""Tests for the MilvusMemory class."""
def setUp(self) -> None:
"""Set up the test environment"""
self.cfg = MockConfig()
self.memory = MilvusMemory(self.cfg)
class TestMilvusMemory(unittest.TestCase):
def setUp(self):
self.cfg = MockConfig()
self.memory = MilvusMemory(self.cfg)
def test_add(self) -> None:
"""Test adding a text to the cache"""
text = "Sample text"
self.memory.clear()
self.memory.add(text)
result = self.memory.get(text)
self.assertEqual([text], result)
def test_add(self):
text = "Sample text"
self.memory.clear()
self.memory.add(text)
result = self.memory.get(text)
self.assertEqual([text], result)
def test_clear(self) -> None:
"""Test clearing the cache"""
self.memory.clear()
self.assertEqual(self.memory.collection.num_entities, 0)
def test_clear(self):
self.memory.clear()
self.assertEqual(self.memory.collection.num_entities, 0)
def test_get(self) -> None:
"""Test getting a text from the cache"""
text = "Sample text"
self.memory.clear()
self.memory.add(text)
result = self.memory.get(text)
self.assertEqual(result, [text])
def test_get(self):
text = "Sample text"
self.memory.clear()
self.memory.add(text)
result = self.memory.get(text)
self.assertEqual(result, [text])
def test_get_relevant(self) -> None:
"""Test getting relevant texts from the cache"""
text1 = "Sample text 1"
text2 = "Sample text 2"
self.memory.clear()
self.memory.add(text1)
self.memory.add(text2)
result = self.memory.get_relevant(text1, 1)
self.assertEqual(result, [text1])
def test_get_relevant(self):
text1 = "Sample text 1"
text2 = "Sample text 2"
self.memory.clear()
self.memory.add(text1)
self.memory.add(text2)
result = self.memory.get_relevant(text1, 1)
self.assertEqual(result, [text1])
def test_get_stats(self) -> None:
"""Test getting the cache stats"""
text = "Sample text"
self.memory.clear()
self.memory.add(text)
stats = self.memory.get_stats()
self.assertEqual(15, len(stats))
def test_get_stats(self):
text = "Sample text"
self.memory.clear()
self.memory.add(text)
stats = self.memory.get_stats()
self.assertEqual(15, len(stats))
if __name__ == "__main__":
unittest.main()
except:
print("Milvus not installed, skipping tests")

82
tests/smoke_test.py
View File

@ -1,31 +1,34 @@
"""Smoke test for the autogpt package."""
import os
import subprocess
import sys
import unittest
import pytest
from autogpt.commands.file_operations import delete_file, read_file
env_vars = {"MEMORY_BACKEND": "no_memory", "TEMPERATURE": "0"}
@pytest.mark.integration_test
def test_write_file() -> None:
"""
Test case to check if the write_file command can successfully write 'Hello World' to a file
named 'hello_world.txt'.
class TestCommands(unittest.TestCase):
def test_write_file(self):
# Test case to check if the write_file command can successfully write 'Hello World' to a file
# named 'hello_world.txt'.
Read the current ai_settings.yaml file and store its content.
"""
env_vars = {"MEMORY_BACKEND": "no_memory", "TEMPERATURE": "0"}
ai_settings = None
if os.path.exists("ai_settings.yaml"):
with open("ai_settings.yaml", "r") as f:
ai_settings = f.read()
os.remove("ai_settings.yaml")
# Read the current ai_settings.yaml file and store its content.
ai_settings = None
if os.path.exists("ai_settings.yaml"):
with open("ai_settings.yaml", "r") as f:
ai_settings = f.read()
os.remove("ai_settings.yaml")
try:
if os.path.exists("hello_world.txt"):
# Clean up any existing 'hello_world.txt' file before testing.
delete_file("hello_world.txt")
# Prepare input data for the test.
input_data = """write_file-GPT
try:
if os.path.exists("hello_world.txt"):
# Clean up any existing 'hello_world.txt' file before testing.
delete_file("hello_world.txt")
# Prepare input data for the test.
input_data = """write_file-GPT
an AI designed to use the write_file command to write 'Hello World' into a file named "hello_world.txt" and then use the task_complete command to complete the task.
Use the write_file command to write 'Hello World' into a file named "hello_world.txt".
Use the task_complete command to complete the task.
@ -33,31 +36,24 @@ Do not use any other commands.
y -5
EOF"""
command = f"{sys.executable} -m autogpt"
command = f"{sys.executable} -m autogpt"
# Execute the script with the input data.
process = subprocess.Popen(
command,
stdin=subprocess.PIPE,
shell=True,
env={**os.environ, **env_vars},
)
process.communicate(input_data.encode())
# Read the content of the 'hello_world.txt' file created during the test.
content = read_file("hello_world.txt")
finally:
if ai_settings:
# Restore the original ai_settings.yaml file.
with open("ai_settings.yaml", "w") as f:
f.write(ai_settings)
# Check if the content of the 'hello_world.txt' file is equal to 'Hello World'.
self.assertEqual(
content, "Hello World", f"Expected 'Hello World', got {content}"
# Execute the script with the input data.
process = subprocess.Popen(
command,
stdin=subprocess.PIPE,
shell=True,
env={**os.environ, **env_vars},
)
process.communicate(input_data.encode())
# Read the content of the 'hello_world.txt' file created during the test.
content = read_file("hello_world.txt")
finally:
if ai_settings:
# Restore the original ai_settings.yaml file.
with open("ai_settings.yaml", "w") as f:
f.write(ai_settings)
# Run the test case.
if __name__ == "__main__":
unittest.main()
# Check if the content of the 'hello_world.txt' file is equal to 'Hello World'.
assert content == "Hello World", f"Expected 'Hello World', got {content}"

6
tests/test_commands.py
View File

@ -1,8 +1,10 @@
import shutil
import os
import sys
from pathlib import Path
import pytest
from autogpt.commands.command import Command, CommandRegistry
@ -138,7 +140,7 @@ class TestCommandRegistry:
def test_import_mock_commands_module(self):
"""Test that the registry can import a module with mock command plugins."""
registry = CommandRegistry()
mock_commands_module = "auto_gpt.tests.mocks.mock_commands"
mock_commands_module = "tests.mocks.mock_commands"
registry.import_commands(mock_commands_module)
@ -154,7 +156,7 @@ class TestCommandRegistry:
registry = CommandRegistry()
# Create a temp command file
src = Path("/app/auto_gpt/tests/mocks/mock_commands.py")
src = Path(os.getcwd()) / "tests/mocks/mock_commands.py"
temp_commands_file = tmp_path / "mock_commands.py"
shutil.copyfile(src, temp_commands_file)

1
tests/test_prompt_generator.py
View File

@ -38,6 +38,7 @@ class TestPromptGenerator(TestCase):
"label": command_label,
"name": command_name,
"args": args,
"function": None,
}
self.assertIn(command, self.generator.commands)

1
tests/test_token_counter.py
View File

@ -1,4 +1,5 @@
import unittest
import tests.context
from autogpt.token_counter import count_message_tokens, count_string_tokens

41
tests/unit/test_browse_scrape_text.py
View File

@ -9,16 +9,20 @@ Code Analysis
Objective:
The objective of the "scrape_text" function is to scrape the text content from
a given URL and return it as a string, after removing any unwanted HTML tags and scripts.
a given URL and return it as a string, after removing any unwanted HTML tags and
scripts.
Inputs:
- url: a string representing the URL of the webpage to be scraped.
Flow:
1. Send a GET request to the given URL using the requests library and the user agent header from the config file.
1. Send a GET request to the given URL using the requests library and the user agent
header from the config file.
2. Check if the response contains an HTTP error. If it does, return an error message.
3. Use BeautifulSoup to parse the HTML content of the response and extract all script and style tags.
4. Get the text content of the remaining HTML using the get_text() method of BeautifulSoup.
3. Use BeautifulSoup to parse the HTML content of the response and extract all script
and style tags.
4. Get the text content of the remaining HTML using the get_text() method of
BeautifulSoup.
5. Split the text into lines and then into chunks, removing any extra whitespace.
6. Join the chunks into a single string with newline characters between them.
7. Return the cleaned text.
@ -27,9 +31,12 @@ Outputs:
- A string representing the cleaned text content of the webpage.
Additional aspects:
- The function uses the requests library and BeautifulSoup to handle the HTTP request and HTML parsing, respectively.
- The function removes script and style tags from the HTML to avoid including unwanted content in the text output.
- The function uses a generator expression to split the text into lines and chunks, which can improve performance for large amounts of text.
- The function uses the requests library and BeautifulSoup to handle the HTTP request
and HTML parsing, respectively.
- The function removes script and style tags from the HTML to avoid including unwanted
content in the text output.
- The function uses a generator expression to split the text into lines and chunks,
which can improve performance for large amounts of text.
"""
@ -40,26 +47,33 @@ class TestScrapeText:
expected_text = "This is some sample text"
mock_response = mocker.Mock()
mock_response.status_code = 200
mock_response.text = f"<html><body><div><p style='color: blue;'>{expected_text}</p></div></body></html>"
mock_response.text = (
"<html><body><div><p style='color: blue;'>"
f"{expected_text}</p></div></body></html>"
)
mocker.patch("requests.Session.get", return_value=mock_response)
# Call the function with a valid URL and assert that it returns the expected text
# Call the function with a valid URL and assert that it returns the
# expected text
url = "http://www.example.com"
assert scrape_text(url) == expected_text
# Tests that the function returns an error message when an invalid or unreachable url is provided.
# Tests that the function returns an error message when an invalid or unreachable
# url is provided.
def test_invalid_url(self, mocker):
# Mock the requests.get() method to raise an exception
mocker.patch(
"requests.Session.get", side_effect=requests.exceptions.RequestException
)
# Call the function with an invalid URL and assert that it returns an error message
# Call the function with an invalid URL and assert that it returns an error
# message
url = "http://www.invalidurl.com"
error_message = scrape_text(url)
assert "Error:" in error_message
# Tests that the function returns an empty string when the html page contains no text to be scraped.
# Tests that the function returns an empty string when the html page contains no
# text to be scraped.
def test_no_text(self, mocker):
# Mock the requests.get() method to return a response with no text
mock_response = mocker.Mock()
@ -71,7 +85,8 @@ class TestScrapeText:
url = "http://www.example.com"
assert scrape_text(url) == ""
# Tests that the function returns an error message when the response status code is an http error (>=400).
# Tests that the function returns an error message when the response status code is
# an http error (>=400).
def test_http_error(self, mocker):
# Mock the requests.get() method to return a response with a 404 status code
mocker.patch("requests.Session.get", return_value=mocker.Mock(status_code=404))

2
tests/unit/test_chat.py
View File

@ -1,6 +1,6 @@
# Generated by CodiumAI
import unittest
import time
import unittest
from unittest.mock import patch
from autogpt.chat import create_chat_message, generate_context

34
tests/unit/test_commands.py
View File

@ -1,18 +1,22 @@
"""Unit tests for the commands module"""
from unittest.mock import MagicMock, patch
import pytest
import autogpt.agent.agent_manager as agent_manager
from autogpt.app import start_agent, list_agents, execute_command
import unittest
from unittest.mock import patch, MagicMock
from autogpt.app import execute_command, list_agents, start_agent
class TestCommands(unittest.TestCase):
def test_make_agent(self):
with patch("openai.ChatCompletion.create") as mock:
obj = MagicMock()
obj.response.choices[0].messages[0].content = "Test message"
mock.return_value = obj
start_agent("Test Agent", "chat", "Hello, how are you?", "gpt2")
agents = list_agents()
self.assertEqual("List of agents:\n0: chat", agents)
start_agent("Test Agent 2", "write", "Hello, how are you?", "gpt2")
agents = list_agents()
self.assertEqual("List of agents:\n0: chat\n1: write", agents)
@pytest.mark.integration_test
def test_make_agent() -> None:
"""Test the make_agent command"""
with patch("openai.ChatCompletion.create") as mock:
obj = MagicMock()
obj.response.choices[0].messages[0].content = "Test message"
mock.return_value = obj
start_agent("Test Agent", "chat", "Hello, how are you?", "gpt2")
agents = list_agents()
assert "List of agents:\n0: chat" == agents
start_agent("Test Agent 2", "write", "Hello, how are you?", "gpt2")
agents = list_agents()
assert "List of agents:\n0: chat\n1: write" == agents