FIX: Infer runnable agent single or multi action (#13412)

libs/langchain/langchain/agents/agent.py

@@ -319,7 +319,7 @@ class BaseMultiActionAgent(BaseModel):
         return {}
 
 
-class AgentOutputParser(BaseOutputParser):
+class AgentOutputParser(BaseOutputParser[Union[AgentAction, AgentFinish]]):
     """Base class for parsing agent output into agent action/finish."""
 
     @abstractmethod
@@ -327,7 +327,9 @@ class AgentOutputParser(BaseOutputParser):
         """Parse text into agent action/finish."""
 
 
-class MultiActionAgentOutputParser(BaseOutputParser):
+class MultiActionAgentOutputParser(
+    BaseOutputParser[Union[List[AgentAction], AgentFinish]]
+):
     """Base class for parsing agent output into agent actions/finish."""
 
     @abstractmethod
@@ -335,17 +337,87 @@ class MultiActionAgentOutputParser(BaseOutputParser):
         """Parse text into agent actions/finish."""
 
 
-class RunnableAgent(BaseMultiActionAgent):
+class RunnableAgent(BaseSingleActionAgent):
     """Agent powered by runnables."""
 
-    runnable: Union[
-        Runnable[dict, Union[AgentAction, AgentFinish]],
-        Runnable[dict, Union[List[AgentAction], AgentFinish]],
-    ]
+    runnable: Runnable[dict, Union[AgentAction, AgentFinish]]
     """Runnable to call to get agent action."""
     _input_keys: List[str] = []
     """Input keys."""
 
+    class Config:
+        """Configuration for this pydantic object."""
+
+        arbitrary_types_allowed = True
+
+    @property
+    def return_values(self) -> List[str]:
+        """Return values of the agent."""
+        return []
+
+    @property
+    def input_keys(self) -> List[str]:
+        """Return the input keys.
+
+        Returns:
+            List of input keys.
+        """
+        return self._input_keys
+
+    def plan(
+        self,
+        intermediate_steps: List[Tuple[AgentAction, str]],
+        callbacks: Callbacks = None,
+        **kwargs: Any,
+    ) -> Union[AgentAction, AgentFinish]:
+        """Given input, decided what to do.
+
+        Args:
+            intermediate_steps: Steps the LLM has taken to date,
+                along with the observations.
+            callbacks: Callbacks to run.
+            **kwargs: User inputs.
+
+        Returns:
+            Action specifying what tool to use.
+        """
+        inputs = {**kwargs, **{"intermediate_steps": intermediate_steps}}
+        output = self.runnable.invoke(inputs, config={"callbacks": callbacks})
+        return output
+
+    async def aplan(
+        self,
+        intermediate_steps: List[Tuple[AgentAction, str]],
+        callbacks: Callbacks = None,
+        **kwargs: Any,
+    ) -> Union[
+        AgentAction,
+        AgentFinish,
+    ]:
+        """Given input, decided what to do.
+
+        Args:
+            intermediate_steps: Steps the LLM has taken to date,
+                along with observations
+            callbacks: Callbacks to run.
+            **kwargs: User inputs.
+
+        Returns:
+            Action specifying what tool to use.
+        """
+        inputs = {**kwargs, **{"intermediate_steps": intermediate_steps}}
+        output = await self.runnable.ainvoke(inputs, config={"callbacks": callbacks})
+        return output
+
+
+class RunnableMultiActionAgent(BaseMultiActionAgent):
+    """Agent powered by runnables."""
+
+    runnable: Runnable[dict, Union[List[AgentAction], AgentFinish]]
+    """Runnable to call to get agent actions."""
+    _input_keys: List[str] = []
+    """Input keys."""
+
     class Config:
         """Configuration for this pydantic object."""
 
@@ -387,8 +459,6 @@ class RunnableAgent(BaseMultiActionAgent):
         """
         inputs = {**kwargs, **{"intermediate_steps": intermediate_steps}}
         output = self.runnable.invoke(inputs, config={"callbacks": callbacks})
-        if isinstance(output, AgentAction):
-            output = [output]
         return output
 
     async def aplan(
@@ -413,8 +483,6 @@ class RunnableAgent(BaseMultiActionAgent):
         """
         inputs = {**kwargs, **{"intermediate_steps": intermediate_steps}}
         output = await self.runnable.ainvoke(inputs, config={"callbacks": callbacks})
-        if isinstance(output, AgentAction):
-            output = [output]
         return output
 
 
@@ -840,6 +908,16 @@ class AgentExecutor(Chain):
         """Convert runnable to agent if passed in."""
         agent = values["agent"]
         if isinstance(agent, Runnable):
+            try:
+                output_type = agent.OutputType
+            except Exception as _:
+                multi_action = False
+            else:
+                multi_action = output_type == Union[List[AgentAction], AgentFinish]
+
+            if multi_action:
+                values["agent"] = RunnableMultiActionAgent(runnable=agent)
+            else:
                 values["agent"] = RunnableAgent(runnable=agent)
         return values