Make the json_parser more robust

For some reason the bot keeps prefacing its JSON. This fixes it for now.

scripts/ai_functions.py

@@ -3,46 +3,23 @@ import json
 import openai
 import dirtyjson
 from config import Config
-
+from call_ai_function import call_ai_function
+from json_parser import fix_and_parse_json
 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=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 = [
-        {
-            "role": "system",
-            "content": f"You are now the following python function: ```# {description}\n{function}```\n\nOnly respond with your `return` value.",
-        },
-        {"role": "user", "content": args},
-    ]
-
-    response = openai.ChatCompletion.create(
-        model=model, messages=messages, temperature=0
-    )
-
-    return response.choices[0].message["content"]
-
-
 # Evaluating code
 
-
 def evaluate_code(code: str) -> List[str]:
     function_string = "def analyze_code(code: str) -> List[str]:"
     args = [code]
     description_string = """Analyzes the given code and returns a list of suggestions for improvements."""
 
     result_string = call_ai_function(function_string, args, description_string)
-    return json.loads(result_string)
+    return fix_and_parse_json.loads(result_string)
 
 
 # Improving code
 
-
 def improve_code(suggestions: List[str], code: str) -> str:
     function_string = (
         "def generate_improved_code(suggestions: List[str], code: str) -> str:"
@@ -68,28 +45,3 @@ def write_tests(code: str, focus: List[str]) -> str:
     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 {}