Revised to support debug mode from command line

.gitignore

@@ -8,4 +8,5 @@ auto_gpt_workspace/*
 *.mpeg
 .env
 outputs/*
-ai_settings.yaml
+ai_settings.yaml
+.venv/*

scripts/chat.py

@@ -62,13 +62,13 @@ def chat_with_ai(
             """
             model = cfg.fast_llm_model # TODO: Change model from hardcode to argument
             # Reserve 1000 tokens for the response
-            if debug:
+            if cfg.debug_mode:
                 print(f"Token limit: {token_limit}")
             send_token_limit = token_limit - 1000
 
             relevant_memory = permanent_memory.get_relevant(str(full_message_history[-5:]), 10)
 
-            if debug:
+            if cfg.debug_mode:
                 print('Memory Stats: ', permanent_memory.get_stats())
 
             next_message_to_add_index, current_tokens_used, insertion_index, current_context = generate_context(
@@ -107,7 +107,7 @@ def chat_with_ai(
             # assert tokens_remaining >= 0, "Tokens remaining is negative. This should never happen, please submit a bug report at https://www.github.com/Torantulino/Auto-GPT"
 
             # Debug print the current context
-            if debug:
+            if cfg.debug_mode:
                 print(f"Token limit: {token_limit}")
                 print(f"Send Token Count: {current_tokens_used}")
                 print(f"Tokens remaining for response: {tokens_remaining}")

scripts/config.py

@@ -28,6 +28,7 @@ class Config(metaclass=Singleton):
     def __init__(self):
         self.continuous_mode = False
         self.speak_mode = False
+        self.debug_mode = False
         # TODO - make these models be self-contained, using langchain, so we can configure them once and call it good 
         self.fast_llm_model = os.getenv("FAST_LLM_MODEL", "gpt-3.5-turbo") 
         self.smart_llm_model = os.getenv("SMART_LLM_MODEL", "gpt-4")
@@ -66,6 +67,9 @@ class Config(metaclass=Singleton):
     def set_speak_mode(self, value: bool):
         self.speak_mode = value
 
+    def set_debug_mode(self, value: bool):
+        self.debug_mode = value
+
     def set_fast_llm_model(self, value: str):
         self.fast_llm_model = value
 

scripts/json_parser.py

@@ -61,7 +61,7 @@ def fix_json(json_str: str, schema: str, debug=False) -> str:
     result_string = call_ai_function(
         function_string, args, description_string, model=cfg.fast_llm_model
     )
-    if debug:
+    if cfg.debug_mode:
         print("------------ JSON FIX ATTEMPT ---------------")
         print(f"Original JSON: {json_str}")
         print("-----------")

scripts/main.py

@@ -262,6 +262,10 @@ def parse_arguments():
         print_to_console("Speak Mode: ", Fore.GREEN, "ENABLED")
         cfg.set_speak_mode(True)
 
+    if args.debug:
+        print_to_console("Debug Mode: ", Fore.GREEN, "ENABLED")
+        cfg.set_debug_mode(True)        
+
     if args.gpt3only:
         print_to_console("GPT3.5 Only Mode: ", Fore.GREEN, "ENABLED")
         cfg.set_smart_llm_model(cfg.fast_llm_model)