docs(fallback_handler.py): add detailed docstrings to FallbackHandler methods to improve code documentation and clarity on functionality

ra_aid/fallback_handler.py

@@ -7,7 +7,21 @@ from ra_aid.llm import initialize_llm, merge_chat_history, validate_provider_env
 
 
 class FallbackHandler:
+    """
+    FallbackHandler manages fallback logic when tool execution fails.
+    
+    It loads fallback models from configuration and validated provider settings,
+    maintains failure counts, and triggers appropriate fallback methods for both
+    prompt-based and function-calling tool invocations. It also resets internal
+    counters when a tool call succeeds.
+    """
     def __init__(self, config):
+        """
+        Initialize the FallbackHandler with the given configuration.
+
+        Args:
+            config (dict): Configuration dictionary that may include fallback settings.
+        """
         self.config = config
         self.fallback_enabled = config.get("fallback_tool_enabled", True)
         self.fallback_tool_models = self._load_fallback_tool_models(config)
@@ -15,6 +29,19 @@ class FallbackHandler:
         self.tool_failure_used_fallbacks = set()
 
     def _load_fallback_tool_models(self, config):
+        """
+        Load and return fallback tool models based on the provided configuration.
+
+        If the config specifies 'fallback_tool_models', those are used (assuming comma-separated names).
+        Otherwise, this method filters the supported_top_tool_models based on provider environment validation,
+        selecting up to FALLBACK_TOOL_MODEL_LIMIT models.
+
+        Args:
+            config (dict): Configuration dictionary.
+
+        Returns:
+            list of dict: Each dictionary contains keys 'model' and 'type' representing a fallback model.
+        """
         fallback_tool_models_config = config.get("fallback_tool_models")
         if fallback_tool_models_config:
             # Assume comma-separated model names; wrap each in a dict with default type "prompt"
@@ -46,6 +73,15 @@ class FallbackHandler:
             return final_models
 
     def handle_failure(self, code: str, error: Exception, logger, agent):
+        """
+        Handle a tool failure by incrementing the failure counter and triggering fallback if thresholds are exceeded.
+
+        Args:
+            code (str): The code that failed to execute.
+            error (Exception): The exception raised during execution.
+            logger: Logger instance for logging.
+            agent: The agent instance on which fallback may be executed.
+        """
         logger.debug(
             f"_handle_tool_failure: tool failure encountered for code '{code}' with error: {error}"
         )
@@ -65,6 +101,14 @@ class FallbackHandler:
             self.attempt_fallback(code, logger, agent)
 
     def attempt_fallback(self, code: str, logger, agent):
+        """
+        Initiate the fallback process by selecting a fallback model and triggering the appropriate fallback method.
+
+        Args:
+            code (str): The tool code that triggered the fallback.
+            logger: Logger instance for logging messages.
+            agent: The agent for which fallback is being executed.
+        """
         logger.debug(f"_attempt_fallback: initiating fallback for code: {code}")
         fallback_model = self.fallback_tool_models[0]
         failed_tool_call_name = code.split("(")[0].strip()
@@ -78,9 +122,28 @@ class FallbackHandler:
             self.attempt_fallback_prompt(code, logger, agent)
 
     def reset_fallback_handler(self):
+        """
+        Reset the fallback handler's internal failure counters and clear the record of used fallback models.
+        """
         self.tool_failure_consecutive_failures = 0
         self.tool_failure_used_fallbacks.clear()
     def attempt_fallback_prompt(self, code: str, logger, agent):
+        """
+        Attempt a prompt-based fallback by iterating over fallback models and invoking the provided code.
+
+        This method tries each fallback model (with retry logic configured) until one successfully executes the code.
+
+        Args:
+            code (str): The tool code to invoke via fallback.
+            logger: Logger instance for logging messages.
+            agent: The agent instance to update with the new model upon success.
+
+        Returns:
+            The response from the fallback model invocation.
+
+        Raises:
+            Exception: If all prompt-based fallback models fail.
+        """
         logger.debug("Attempting prompt-based fallback using fallback models")
         failed_tool_call_name = code.split("(")[0].strip()
         for fallback_model in self.fallback_tool_models:
@@ -99,6 +162,22 @@ class FallbackHandler:
         raise Exception("All prompt-based fallback models failed")
 
     def attempt_fallback_function(self, code: str, logger, agent):
+        """
+        Attempt a function-calling fallback by iterating over fallback models and invoking the provided code.
+
+        This method tries each fallback model (with retry logic configured) until one successfully executes the code.
+
+        Args:
+            code (str): The tool code to invoke via fallback.
+            logger: Logger instance for logging messages.
+            agent: The agent instance to update with the new model upon success.
+
+        Returns:
+            The response from the fallback model invocation.
+
+        Raises:
+            Exception: If all function-calling fallback models fail.
+        """
         logger.debug("Attempting function-calling fallback using fallback models")
         failed_tool_call_name = code.split("(")[0].strip()
         for fallback_model in self.fallback_tool_models: