Make compatible with gpt-3.5

I made the json parsing more forgivable. I improved the prompt, using things I learned from: Koobah/Auto-GPT

scripts/ai_config.py

@@ -0,0 +1,56 @@
+import yaml
+import data
+
+class AIConfig:
+    def __init__(self, ai_name="", ai_role="", ai_goals=[]):
+        self.ai_name = ai_name
+        self.ai_role = ai_role
+        self.ai_goals = ai_goals
+
+    # @classmethod
+    # def create_from_user_prompts(cls):
+    #     ai_name = input("Name your AI: ") or "Entrepreneur-GPT"
+    #     ai_role = input(f"{ai_name} is: ") or "an AI designed to autonomously develop and run businesses with the sole goal of increasing your net worth."
+    #     print("Enter up to 5 goals for your AI: ")
+    #     print("For example: \nIncrease net worth, Grow Twitter Account, Develop and manage multiple businesses autonomously'")
+    #     print("Enter nothing to load defaults, enter nothing when finished.")
+    #     ai_goals = []
+    #     for i in range(5):
+    #         ai_goal = input(f"Goal {i+1}: ")
+    #         if ai_goal == "":
+    #             break
+    #         ai_goals.append(ai_goal)
+    #     if len(ai_goals) == 0:
+    #         ai_goals = ["Increase net worth", "Grow Twitter Account", "Develop and manage multiple businesses autonomously"]
+    #     return cls(ai_name, ai_role, ai_goals)
+
+    @classmethod
+    def load(cls, config_file="config.yaml"):
+        # Load variables from yaml file if it exists
+        try:
+            with open(config_file) as file:
+                config_params = yaml.load(file, Loader=yaml.FullLoader)
+        except FileNotFoundError:
+            config_params = {}
+
+        ai_name = config_params.get("ai_name", "")
+        ai_role = config_params.get("ai_role", "")
+        ai_goals = config_params.get("ai_goals", [])
+
+        return cls(ai_name, ai_role, ai_goals)
+
+    def save(self, config_file="config.yaml"):
+        config = {"ai_name": self.ai_name, "ai_role": self.ai_role, "ai_goals": self.ai_goals}
+        with open(config_file, "w") as file:
+            documents = yaml.dump(config, file)
+
+    def construct_full_prompt(self):
+        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
+        full_prompt = f"You are {self.ai_name}, {self.ai_role}\n{prompt_start}\n\nGOALS:\n\n"
+        for i, goal in enumerate(self.ai_goals):
+            full_prompt += f"{i+1}. {goal}\n"
+
+        full_prompt += f"\n\n{data.load_prompt()}"
+        return full_prompt

scripts/ai_functions.py

@@ -1,11 +1,16 @@
 from typing import List, Optional
 import json
 import openai
+import dirtyjson
+from config import Config
 
+cfg = Config()
 
 # 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="gpt-4"):
+def call_ai_function(function, args, description, model=cfg.smart_llm_model):
+    # 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
     args = ", ".join(args)
     messages = [
@@ -61,3 +66,30 @@ def write_tests(code: str, focus: List[str]) -> str:
 
     result_string = call_ai_function(function_string, args, description_string)
     return result_string
+
+
+# TODO: Make debug a global config var
+def fix_json(json_str: str, schema:str = None, debug=True) -> str:
+    # Try to fix the JSON using gpt:
+    function_string = "def fix_json(json_str: str, schema:str=None) -> str:"
+    args = [json_str, schema]
+    description_string = """Fixes the provided JSON string to make it parseable. If the schema is provided, the JSON will be made to look like the schema, otherwise it will be made to look like a valid JSON object."""
+
+    result_string = call_ai_function(
+        function_string, args, description_string, model=cfg.fast_llm_model
+    )
+    if debug:
+        print("------------ JSON FIX ATTEMPT ---------------")
+        print(f"Original JSON: {json_str}")
+        print(f"Fixed JSON: {result_string}")
+        print("----------- END OF FIX ATTEMPT ----------------")
+    try:
+        return dirtyjson.loads(result_string)
+    except:
+        # Log the exception:
+        print("Failed to fix JSON")
+        # Get the call stack:
+        import traceback
+        call_stack = traceback.format_exc()
+        print(call_stack)
+        return {}

scripts/data/prompt.txt

@@ -1,6 +1,6 @@
 CONSTRAINTS:
 
-1. 6000-word count limit for memory
+1. 4000-word count limit for memory
 2. No user assistance
 
 COMMANDS:
@@ -38,22 +38,24 @@ PERFORMANCE EVALUATION:
 3. Reflect on past decisions and strategies to refine your approach.
 4. Every command has a cost, so be smart and efficent. Aim to complete tasks in the least number of steps.
 
+You should only respond in JSON format as described below
+
 RESPONSE FORMAT:
 {
-"command":
-{
-"name": "command name",
-"args":
-{
-"arg name": "value"
+    "command": {
+        "name": "command name",
+        "args":{
+            "arg name": "value"
+        }
+    },
+    "thoughts":
+    {
+        "text": "thought",
+        "reasoning": "reasoning",
+        "plan": "- short bulleted\n- list that conveys\n- long-term plan",
+        "criticism": "constructive self-criticism"
+        "speak": "thoughts summary to say to user"
+    }
 }
-},
-"thoughts":
-{
-"text": "thought",
-"reasoning": "reasoning",
-"plan": "short bulleted long-term plan",
-"criticism": "constructive self-criticism"
-"speak": "thoughts summary to say to user"
-}
-}
+
+Ensure the response can be parsed by Python json.loads

scripts/main.py

@@ -11,16 +11,15 @@
 from enum import Enum, auto
 import sys
 from config import Config
-
+from json_parser import fix_and_parse_json
+from ai_config import AIConfig
+import traceback
+import yaml
 
 class Argument(Enum):
     CONTINUOUS_MODE = "continuous-mode"
     SPEAK_MODE = "speak-mode"
 
-# normally 6000 for gpt-4
-TOKEN_LIMIT=4000
-
-
 def print_to_console(
         title,
         title_color,
@@ -53,7 +52,7 @@ def print_assistant_thoughts(assistant_reply):
     global cfg
     try:
         # Parse and print Assistant response
-        assistant_reply_json = json.loads(assistant_reply)
+        assistant_reply_json = fix_and_parse_json(assistant_reply)
 
         assistant_thoughts = assistant_reply_json.get("thoughts")
         if assistant_thoughts:
@@ -80,8 +79,13 @@ def print_assistant_thoughts(assistant_reply):
         if assistant_thoughts_plan:
             print_to_console("PLAN:", Fore.YELLOW, "")
             if assistant_thoughts_plan:
-
-                # Split the input_string using the newline character and dash
+                # 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 dash
+
                 lines = assistant_thoughts_plan.split('\n')
 
                 # Iterate through the lines and print each one with a bullet
@@ -103,11 +107,89 @@ def print_assistant_thoughts(assistant_reply):
         print_to_console("Error: Invalid JSON\n", Fore.RED, assistant_reply)
     # All other errors, return "Error: + error message"
     except Exception as e:
-        print_to_console("Error: \n", Fore.RED, str(e))
+        call_stack = traceback.format_exc()
+        print_to_console("Error: \n", Fore.RED, call_stack)
+
+def load_variables(config_file="config.yaml"):
+    # Load variables from yaml file if it exists
+    try:
+        with open(config_file) as file:
+            config = yaml.load(file, Loader=yaml.FullLoader)
+        ai_name = config.get("ai_name")
+        ai_role = config.get("ai_role")
+        ai_goals = config.get("ai_goals")
+    except FileNotFoundError:
+        ai_name = ""
+        ai_role = ""
+        ai_goals = []
+
+    # Prompt the user for input if config file is missing or empty values
+    if not ai_name:
+        ai_name = input("Name your AI: ")
+        if ai_name == "":
+            ai_name = "Entrepreneur-GPT"
+
+    if not ai_role:        
+        ai_role = input(f"{ai_name} is: ")
+        if ai_role == "":
+            ai_role = "an AI designed to autonomously develop and run businesses with the sole goal of increasing your net worth."
+
+    if not ai_goals:
+        print("Enter up to 5 goals for your AI: ")
+        print("For example: \nIncrease net worth, Grow Twitter Account, Develop and manage multiple businesses autonomously'")
+        print("Enter nothing to load defaults, enter nothing when finished.")
+        ai_goals = []
+        for i in range(5):
+            ai_goal = input(f"Goal {i+1}: ")
+            if ai_goal == "":
+                break
+            ai_goals.append(ai_goal)
+        if len(ai_goals) == 0:
+            ai_goals = ["Increase net worth", "Grow Twitter Account", "Develop and manage multiple businesses autonomously"]
+
+    # Save variables to yaml file
+    config = {"ai_name": ai_name, "ai_role": ai_role, "ai_goals": ai_goals}
+    with open(config_file, "w") as file:
+        documents = yaml.dump(config, file)
+
+    prompt = data.load_prompt()
+    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
+    full_prompt = f"You are {ai_name}, {ai_role}\n{prompt_start}\n\nGOALS:\n\n"
+    for i, goal in enumerate(ai_goals):
+        full_prompt += f"{i+1}. {goal}\n"
+
+    full_prompt += f"\n\n{prompt}"
+    return full_prompt
 
 
 def construct_prompt():
+    config = AIConfig.load()
+    if config.ai_name:
+        print_to_console(
+            f"Welcome back, {config.ai_name}!",
+            Fore.GREEN,
+            "Let's continue our journey.",
+            speak_text=True)
+        should_continue = input(f"Continue with the last settings? (Settings: {config.ai_name}, {config.ai_role}, {config.ai_goals}) (Y/n): ")
+        if should_continue.lower() == "n":
+            config = AIConfig()
+
+    if not config.ai_name:         
+        config = prompt_user()
+        config.save()
+
+    # Get rid of this global:
     global ai_name
+    ai_name = config.ai_name
+
+    full_prompt = config.construct_full_prompt()
+    return full_prompt
+
+
+def prompt_user():
+    ai_name = ""
     # Construct the prompt
     print_to_console(
         "Welcome to Auto-GPT! ",
@@ -155,19 +237,8 @@ def construct_prompt():
         ai_goals = ["Increase net worth", "Grow Twitter Account",
                     "Develop and manage multiple businesses autonomously"]
 
-    prompt = data.load_prompt()
-    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
-    full_prompt = f"You are {ai_name}, {ai_role}\n{prompt_start}\n\nGOALS:\n\n"
-    for i, goal in enumerate(ai_goals):
-        full_prompt += f"{i+1}. {goal}\n"
-
-    full_prompt += f"\n\n{prompt}"
-    return full_prompt
-
-# Check if the python script was executed with arguments, get those arguments
-
+    config = AIConfig(ai_name, ai_role, ai_goals)
+    return config
 
 def parse_arguments():
     global cfg
@@ -185,6 +256,8 @@ def parse_arguments():
             print_to_console("Speak Mode: ", Fore.GREEN, "ENABLED")
             cfg.set_speak_mode(True)
 
+    # TODO: Better argument parsing:
+    # TODO: fill in llm values here
 
 cfg = Config()
 
@@ -194,9 +267,10 @@ def parse_arguments():
 print(prompt)
 # Initialize variables
 full_message_history = []
-token_limit = TOKEN_LIMIT  # The maximum number of tokens allowed in the API call
+token_limit = cfg.thinking_token_limit  # The maximum number of tokens allowed in the API call
 result = None
-user_input = "GENERATE NEXT COMMAND JSON"
+# Make a constant:
+user_input = "Determine which next command to use, and respond using the format specified above:"
 
 # Interaction Loop
 while True:

tests/json_tests.py

@@ -0,0 +1,34 @@
+import unittest
+import os
+import sys
+# Probably a better way:
+sys.path.append(os.path.abspath('../scripts'))
+from json_parser import fix_and_parse_json
+
+class TestParseJson(unittest.TestCase):
+    def test_valid_json(self):
+        # Test that a valid JSON string is parsed correctly
+        json_str = '{"name": "John", "age": 30, "city": "New York"}'
+        obj = fix_and_parse_json(json_str)
+        self.assertEqual(obj, {"name": "John", "age": 30, "city": "New York"})
+
+    def test_invalid_json_minor(self):
+        # Test that an invalid JSON string can be fixed with gpt
+        json_str = '{"name": "John", "age": 30, "city": "New York",}'
+        self.assertEqual(fix_and_parse_json(json_str, try_to_fix_with_gpt=False), {"name": "John", "age": 30, "city": "New York"})
+
+    def test_invalid_json_major_with_gpt(self):
+        # Test that an invalid JSON string raises an error when try_to_fix_with_gpt is False
+        json_str = 'BEGIN: "name": "John" - "age": 30 - "city": "New York" :END'
+        self.assertEqual(fix_and_parse_json(json_str, try_to_fix_with_gpt=True), {"name": "John", "age": 30, "city": "New York"})
+
+    def test_invalid_json_major_without_gpt(self):
+        # Test that a REALLY invalid JSON string raises an error when try_to_fix_with_gpt is False
+        json_str = 'BEGIN: "name": "John" - "age": 30 - "city": "New York" :END'
+        # Assert that this raises an exception:
+        with self.assertRaises(Exception):
+            fix_and_parse_json(json_str, try_to_fix_with_gpt=False)
+
+
+if __name__ == '__main__':
+    unittest.main()