[FEAT-FALLBACK][Added agent model fallback, if primary model fails]

swarms/structs/agent.py

@@ -202,6 +202,8 @@ class Agent:
         list_of_pdf (str): The list of pdf
         tokenizer (Any): The tokenizer
         long_term_memory (BaseVectorDatabase): The long term memory
+        fallback_model_name (str): The fallback model name to use if primary model fails
+        fallback_models (List[str]): List of fallback model names to try in order if primary model fails
         preset_stopping_token (bool): Enable preset stopping token
         traceback (Any): The traceback
         traceback_handlers (Any): The traceback handlers
@@ -302,6 +304,15 @@ class Agent:
     >>> response = agent.run("Tell me a long story.")  # Will stream in real-time
     >>> print(response)  # Final complete response
 
+    >>> # Fallback model example
+    >>> agent = Agent(
+    ...     model_name="gpt-4o",
+    ...     fallback_models=["gpt-4o-mini", "gpt-3.5-turbo"],
+    ...     max_loops=1
+    ... )
+    >>> response = agent.run("Generate a report on the financials.")
+    >>> # If gpt-4o fails, it will automatically try gpt-4o-mini, then gpt-3.5-turbo
+
     """
 
     def __init__(
@@ -340,6 +351,7 @@ class Agent:
         tokenizer: Optional[Any] = None,
         long_term_memory: Optional[Union[Callable, Any]] = None,
         fallback_model_name: Optional[str] = None,
+        fallback_models: Optional[List[str]] = None,
         preset_stopping_token: Optional[bool] = False,
         traceback: Optional[Any] = None,
         traceback_handlers: Optional[Any] = None,
@@ -605,6 +617,9 @@ class Agent:
         self.thinking_tokens = thinking_tokens
         self.reasoning_enabled = reasoning_enabled
         self.fallback_model_name = fallback_model_name
+        self.fallback_models = fallback_models or []
+        self.current_model_index = 0
+        self.model_attempts = {}
 
         # self.init_handling()
         self.setup_config()
@@ -729,6 +744,9 @@ class Agent:
         if self.model_name is None:
             self.model_name = "gpt-4o-mini"
         
+        # Use current model (which may be a fallback)
+        current_model = self.get_current_model()
+
         # Determine if parallel tool calls should be enabled
         if exists(self.tools) and len(self.tools) >= 2:
             parallel_tool_calls = True
@@ -2551,10 +2569,45 @@ class Agent:
 
                 return out
 
-        except AgentLLMError as e:
+        except (AgentLLMError, Exception) as e:
+            logger.error(
+                f"Error calling LLM with model '{self.get_current_model()}': {e}. "
+                f"Task: {task}, Args: {args}, Kwargs: {kwargs} Traceback: {traceback.format_exc()}"
+            )
+            
+            # Try fallback models if available
+            if self.is_fallback_available() and self.switch_to_next_model():
+                logger.info(
+                    f"Retrying with fallback model '{self.get_current_model()}' for agent '{self.agent_name}'"
+                )
+                try:
+                    # Recursive call with the new model
+                    return self.call_llm(
+                        task=task,
+                        img=img,
+                        current_loop=current_loop,
+                        streaming_callback=streaming_callback,
+                        *args,
+                        **kwargs
+                    )
+                except Exception as fallback_error:
                     logger.error(
-                f"Error calling LLM: {e}. Task: {task}, Args: {args}, Kwargs: {kwargs} Traceback: {traceback.format_exc()}"
+                        f"Fallback model '{self.get_current_model()}' also failed: {fallback_error}"
                     )
+                    # Continue to next fallback or raise if no more models
+                    if self.is_fallback_available() and self.switch_to_next_model():
+                        return self.call_llm(
+                            task=task,
+                            img=img,
+                            current_loop=current_loop,
+                            streaming_callback=streaming_callback,
+                            *args,
+                            **kwargs
+                        )
+                    else:
+                        raise e
+            else:
+                # No fallback available or all fallbacks exhausted
                 raise e
 
     def handle_sop_ops(self):
@@ -2976,6 +3029,85 @@ class Agent:
             api_key=self.llm_api_key,
         )
 
+    def get_available_models(self) -> List[str]:
+        """
+        Get the list of available models including primary and fallback models.
+        
+        Returns:
+            List[str]: List of model names in order of preference
+        """
+        models = [self.model_name] if self.model_name else []
+        
+        # Add single fallback model if specified
+        if self.fallback_model_name and self.fallback_model_name not in models:
+            models.append(self.fallback_model_name)
+        
+        # Add fallback models list if specified
+        if self.fallback_models:
+            for model in self.fallback_models:
+                if model not in models:
+                    models.append(model)
+        
+        return models
+
+    def get_current_model(self) -> str:
+        """
+        Get the current model being used.
+        
+        Returns:
+            str: Current model name
+        """
+        available_models = self.get_available_models()
+        if self.current_model_index < len(available_models):
+            return available_models[self.current_model_index]
+        return self.model_name or "gpt-4o-mini"
+
+    def switch_to_next_model(self) -> bool:
+        """
+        Switch to the next available model in the fallback list.
+        
+        Returns:
+            bool: True if successfully switched to next model, False if no more models available
+        """
+        available_models = self.get_available_models()
+        
+        if self.current_model_index + 1 < len(available_models):
+            self.current_model_index += 1
+            new_model = available_models[self.current_model_index]
+            
+            logger.warning(
+                f"Agent '{self.agent_name}' switching to fallback model: {new_model} "
+                f"(attempt {self.current_model_index + 1}/{len(available_models)})"
+            )
+            
+            # Update the model name and reinitialize LLM
+            self.model_name = new_model
+            self.llm = self.llm_handling()
+            
+            return True
+        else:
+            logger.error(
+                f"Agent '{self.agent_name}' has exhausted all available models. "
+                f"Tried {len(available_models)} models: {available_models}"
+            )
+            return False
+
+    def reset_model_index(self) -> None:
+        """Reset the model index to use the primary model."""
+        self.current_model_index = 0
+        if self.model_name:
+            self.llm = self.llm_handling()
+
+    def is_fallback_available(self) -> bool:
+        """
+        Check if fallback models are available.
+        
+        Returns:
+            bool: True if fallback models are configured
+        """
+        available_models = self.get_available_models()
+        return len(available_models) > 1
+
     def execute_tools(self, response: any, loop_count: int):
         # Handle None response gracefully
         if response is None: