Add extra documentation

scripts/ai_config.py

@@ -3,7 +3,9 @@ import data
 
 
 class AIConfig:
+    """Class to store the AI's name, role, and goals."""
     def __init__(self, ai_name="", ai_role="", ai_goals=[]):
+        """Initialize the AIConfig class"""
         self.ai_name = ai_name
         self.ai_role = ai_role
         self.ai_goals = ai_goals
@@ -13,7 +15,7 @@ class AIConfig:
 
     @classmethod
     def load(cls, config_file=SAVE_FILE):
-        # Load variables from yaml file if it exists
+        """Load variables from yaml file if it exists, otherwise use defaults."""
         try:
             with open(config_file) as file:
                 config_params = yaml.load(file, Loader=yaml.FullLoader)
@@ -27,11 +29,13 @@ class AIConfig:
         return cls(ai_name, ai_role, ai_goals)
 
     def save(self, config_file=SAVE_FILE):
+        """Save variables to yaml file."""
         config = {"ai_name": self.ai_name, "ai_role": self.ai_role, "ai_goals": self.ai_goals}
         with open(config_file, "w") as file:
             yaml.dump(config, file)
 
     def construct_full_prompt(self):
+        """Construct the full prompt for the AI to use."""
         prompt_start = """Your decisions must always be made independently without seeking user assistance. Play to your strengths as an LLM and pursue simple strategies with no legal complications."""
 
         # Construct full prompt

scripts/call_ai_function.py

@@ -6,6 +6,7 @@ from llm_utils import create_chat_completion
 # This is a magic function that can do anything with no-code. See
 # https://github.com/Torantulino/AI-Functions for more info.
 def call_ai_function(function, args, description, model=cfg.smart_llm_model):
+    """Call an AI function with the given args and description."""
     # For each arg, if any are None, convert to "None":
     args = [str(arg) if arg is not None else "None" for arg in args]
     # parse args to comma seperated string

scripts/config.py

@@ -51,21 +51,27 @@ class Config(metaclass=Singleton):
         self.speak_mode = value
 
     def set_fast_llm_model(self, value: str):
+        """Set the fast LLM model value."""
         self.fast_llm_model = value
 
     def set_smart_llm_model(self, value: str):
+        """Set the smart LLM model value."""
         self.smart_llm_model = value
 
     def set_fast_token_limit(self, value: int):
+        """Set the fast token limit value."""
         self.fast_token_limit = value
 
     def set_smart_token_limit(self, value: int):
+        """Set the smart token limit value."""
         self.smart_token_limit = value
 
     def set_openai_api_key(self, value: str):
+        """Set the OpenAI API key value."""
         self.apiopenai_api_key_key = value
     
     def set_elevenlabs_api_key(self, value: str):
+        """Set the ElevenLabs API key value."""
         self.elevenlabs_api_key = value
 
 

scripts/file_operations.py

@@ -3,7 +3,7 @@ import os.path
 
 # Set a dedicated folder for file I/O
 working_directory = "auto_gpt_workspace"
-
+# Create the directory if it doesn't exist
 if not os.path.exists(working_directory):
     os.makedirs(working_directory)
 

scripts/json_parser.py

@@ -4,6 +4,7 @@ from config import Config
 cfg = Config()
 
 def fix_and_parse_json(json_str: str, try_to_fix_with_gpt: bool = True):
+    """Fix and parse the given JSON string."""
     json_schema = """
     {
     "command": {
@@ -50,6 +51,7 @@ def fix_and_parse_json(json_str: str, try_to_fix_with_gpt: bool = True):
         
 # TODO: Make debug a global config var
 def fix_json(json_str: str, schema: str, debug=False) -> str:
+    """Fix the given JSON string to make it parseable and fully complient with the provided schema."""
     # Try to fix the JSON using gpt:
     function_string = "def fix_json(json_str: str, schema:str=None) -> str:"
     args = [json_str, schema]

scripts/llm_utils.py

@@ -6,6 +6,7 @@ openai.api_key = cfg.openai_api_key
 
 # Overly simple abstraction until we create something better
 def create_chat_completion(messages, model=None, temperature=None, max_tokens=None)->str:
+    """Create a chat completion using the OpenAI API."""
     response = openai.ChatCompletion.create(
         model=model,
         messages=messages,

scripts/main.py

@@ -117,7 +117,7 @@ def print_assistant_thoughts(assistant_reply):
         print_to_console("Error: \n", Fore.RED, call_stack)
 
 def load_variables(config_file="config.yaml"):
-    # Load variables from yaml file if it exists
+    """Load variables from yaml file if it exists, otherwise prompt the user for input"""
     try:
         with open(config_file) as file:
             config = yaml.load(file, Loader=yaml.FullLoader)
@@ -200,6 +200,7 @@ Continue (y/n): """)
 
 
 def prompt_user():
+    """Prompt the user for input"""
     ai_name = ""
     # Construct the prompt
     print_to_console(