Update Python code formatting, configuration loading, and local model additions

1. Code Formatting:
   - Standardized Python code formatting across multiple files to align with PEP 8 guidelines. This includes adjustments to whitespace, line breaks, and inline comments.

2. Configuration Loader Enhancements:
   - Enhanced the `get_settings` function in `config_loader.py` to provide more robust handling of settings retrieval. Added detailed documentation to improve code maintainability and clarity.

3. Model Addition in __init__.py:
   - Added a new model "ollama/llama3" with a token limit to the MAX_TOKENS dictionary in `__init__.py` to support new AI capabilities and configurations.

pr_agent/algo/ai_handlers/langchain_ai_handler.py

@@ -1,7 +1,7 @@
 try:
     from langchain.chat_models import ChatOpenAI, AzureChatOpenAI
     from langchain.schema import SystemMessage, HumanMessage
-except: # we don't enforce langchain as a dependency, so if it's not installed, just move on
+except:  # we don't enforce langchain as a dependency, so if it's not installed, just move on
     pass
 
 from pr_agent.algo.ai_handlers.base_ai_handler import BaseAiHandler
@@ -14,6 +14,7 @@ import functools
 
 OPENAI_RETRIES = 5
 
+
 class LangChainOpenAIHandler(BaseAiHandler):
     def __init__(self):
         # Initialize OpenAIHandler specific attributes here
@@ -36,7 +37,7 @@ class LangChainOpenAIHandler(BaseAiHandler):
                 raise ValueError(f"OpenAI {e.name} is required") from e
             else:
                 raise e
-    
+
     @property
     def chat(self):
         if self.azure:
@@ -51,17 +52,18 @@ class LangChainOpenAIHandler(BaseAiHandler):
         Returns the deployment ID for the OpenAI API.
         """
         return get_settings().get("OPENAI.DEPLOYMENT_ID", None)
+
     @retry(exceptions=(APIError, Timeout, TryAgain, AttributeError, RateLimitError),
            tries=OPENAI_RETRIES, delay=2, backoff=2, jitter=(1, 3))
     async def chat_completion(self, model: str, system: str, user: str, temperature: float = 0.2):
         try:
-            messages=[SystemMessage(content=system), HumanMessage(content=user)]
-            
+            messages = [SystemMessage(content=system), HumanMessage(content=user)]
+
             # get a chat completion from the formatted messages
             resp = self.chat(messages, model=model, temperature=temperature)
-            finish_reason="completed"
+            finish_reason = "completed"
             return resp.content, finish_reason
-        
+
         except (Exception) as e:
             get_logger().error("Unknown error during OpenAI inference: ", e)
-            raise e
+            raise e