diff --git a/autogpt/__main__.py b/autogpt/__main__.py index c721088ac..c2e2e5c16 100644 --- a/autogpt/__main__.py +++ b/autogpt/__main__.py @@ -74,9 +74,9 @@ 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) diff --git a/autogpt/agent/agent.py b/autogpt/agent/agent.py index 6683aae5f..e65c7e617 100644 --- a/autogpt/agent/agent.py +++ b/autogpt/agent/agent.py @@ -19,18 +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. - 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. + 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. + 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) + The triggering prompt reminds the AI about its short term meta task + (defining the next task) """ def __init__( @@ -96,14 +103,13 @@ class Agent: try: print_assistant_thoughts(self.ai_name, assistant_reply_json) command_name, arguments = get_command(assistant_reply_json) - # command_name, arguments = assistant_reply_json_valid["command"]["name"], assistant_reply_json_valid["command"]["args"] 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 logger.typewriter_log( @@ -177,10 +183,13 @@ class Agent: 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: result = plugin.post_command(command_name, result) diff --git a/tests/unit/test_browse_scrape_text.py b/tests/unit/test_browse_scrape_text.py index fea5ebfc0..1a36e19b5 100644 --- a/tests/unit/test_browse_scrape_text.py +++ b/tests/unit/test_browse_scrape_text.py @@ -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"

{expected_text}

" + mock_response.text = ( + "

" + f"{expected_text}

" + ) 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))