Implement caching for configuration and personality prompt retrieval

In an effort to improve efficiency and reduce unnecessary disk reads, caching has been implemented for the retrieval of configuration files and personality prompts. The functools.lru_cache decorator has been employed to this end, ensuring that repeated calls to these functions will return cached results when available. This change should result in a noticeable performance improvement, particularly in scenarios where these functions are called frequently.

Author: TechNickAI

aicodebot/config.py

@@ -1,8 +1,9 @@
 from aicodebot.helpers import logger
 from pathlib import Path
-import os, yaml
+import functools, os, yaml
 
 
+@functools.lru_cache
 def get_config_file():
     if "AICODEBOT_CONFIG_FILE" in os.environ:
         config_file = Path(os.getenv("AICODEBOT_CONFIG_FILE"))
@@ -12,6 +13,7 @@ def get_config_file():
     return config_file
 
 
+@functools.lru_cache
 def read_config():
     """Read the config file and return its contents as a dictionary."""
     config_file = get_config_file()

aicodebot/prompts.py

@@ -4,7 +4,7 @@
 from langchain import PromptTemplate
 from pathlib import Path
 from types import SimpleNamespace
-import os
+import functools, os
 
 # ---------------------------------------------------------------------------- #
 #                              Personality helpers                             #
@@ -97,6 +97,7 @@
 DEFAULT_PERSONALITY = PERSONALITIES["Spock"]
 
 
+@functools.lru_cache
 def get_personality_prompt():
     """Generates a prompt for the sidekick personality."""
     default_personality = DEFAULT_PERSONALITY.name