From ca08a34a9869d0044254822fcba11299ea02a7c7 Mon Sep 17 00:00:00 2001
From: Harrison Chase <hw.chase.17@gmail.com>
Date: Mon, 1 May 2023 22:05:42 -0700
Subject: [PATCH] retry to parsing (#3696)

---
 langchain/agents/agent.py | 78 +++++++++++++++++++++++++++++++++------
 1 file changed, 66 insertions(+), 12 deletions(-)

diff --git a/langchain/agents/agent.py b/langchain/agents/agent.py
index ca382031bb..51972d69f9 100644
--- a/langchain/agents/agent.py
+++ b/langchain/agents/agent.py
@@ -17,7 +17,9 @@ from langchain.base_language import BaseLanguageModel
 from langchain.callbacks.base import BaseCallbackManager
 from langchain.callbacks.manager import (
     AsyncCallbackManagerForChainRun,
+    AsyncCallbackManagerForToolRun,
     CallbackManagerForChainRun,
+    CallbackManagerForToolRun,
     Callbacks,
 )
 from langchain.chains.base import Chain
@@ -578,6 +580,25 @@ class Agent(BaseSingleActionAgent):
         }
 
 
+class ExceptionTool(BaseTool):
+    name = "_Exception"
+    description = "Exception tool"
+
+    def _run(
+        self,
+        query: str,
+        run_manager: Optional[CallbackManagerForToolRun] = None,
+    ) -> str:
+        return query
+
+    async def _arun(
+        self,
+        query: str,
+        run_manager: Optional[AsyncCallbackManagerForToolRun] = None,
+    ) -> str:
+        return query
+
+
 class AgentExecutor(Chain):
     """Consists of an agent using tools."""
 
@@ -587,6 +608,7 @@ class AgentExecutor(Chain):
     max_iterations: Optional[int] = 15
     max_execution_time: Optional[float] = None
     early_stopping_method: str = "force"
+    handle_parsing_errors: bool = False
 
     @classmethod
     def from_agent_and_tools(
@@ -714,12 +736,28 @@ class AgentExecutor(Chain):
 
         Override this to take control of how the agent makes and acts on choices.
         """
-        # Call the LLM to see what to do.
-        output = self.agent.plan(
-            intermediate_steps,
-            callbacks=run_manager.get_child() if run_manager else None,
-            **inputs,
-        )
+        try:
+            # Call the LLM to see what to do.
+            output = self.agent.plan(
+                intermediate_steps,
+                callbacks=run_manager.get_child() if run_manager else None,
+                **inputs,
+            )
+        except Exception as e:
+            if not self.handle_parsing_errors:
+                raise e
+            text = str(e).split("`")[1]
+            observation = "Invalid or incomplete response"
+            output = AgentAction("_Exception", observation, text)
+            tool_run_kwargs = self.agent.tool_run_logging_kwargs()
+            observation = ExceptionTool().run(
+                output.tool,
+                verbose=self.verbose,
+                color=None,
+                callbacks=run_manager.get_child() if run_manager else None,
+                **tool_run_kwargs,
+            )
+            return [(output, observation)]
         # If the tool chosen is the finishing tool, then we end and return.
         if isinstance(output, AgentFinish):
             return output
@@ -772,12 +810,28 @@ class AgentExecutor(Chain):
 
         Override this to take control of how the agent makes and acts on choices.
         """
-        # Call the LLM to see what to do.
-        output = await self.agent.aplan(
-            intermediate_steps,
-            callbacks=run_manager.get_child() if run_manager else None,
-            **inputs,
-        )
+        try:
+            # Call the LLM to see what to do.
+            output = await self.agent.aplan(
+                intermediate_steps,
+                callbacks=run_manager.get_child() if run_manager else None,
+                **inputs,
+            )
+        except Exception as e:
+            if not self.handle_parsing_errors:
+                raise e
+            text = str(e).split("`")[1]
+            observation = "Invalid or incomplete response"
+            output = AgentAction("_Exception", observation, text)
+            tool_run_kwargs = self.agent.tool_run_logging_kwargs()
+            observation = await ExceptionTool().arun(
+                output.tool,
+                verbose=self.verbose,
+                color=None,
+                callbacks=run_manager.get_child() if run_manager else None,
+                **tool_run_kwargs,
+            )
+            return [(output, observation)]
         # If the tool chosen is the finishing tool, then we end and return.
         if isinstance(output, AgentFinish):
             return output