feat: add plan in model output

core/agents/parser.py

@@ -11,10 +11,13 @@ class EvalOutputParser(BaseOutputParser):
         return EVAL_FORMAT_INSTRUCTIONS
 
     def parse(self, text: str) -> Dict[str, str]:
-        regex = r"Action: (.*?)[\n]*Action Input: (.*)"
+        regex = r"Action: (.*?)[\n]Plan:(.*)Action Input: (.*)"
         match = re.search(regex, text, re.DOTALL)
         if not match:
             raise Exception("parse error")
         action = match.group(1).strip()
-        action_input = match.group(2)
+        action_input = match.group(3)
         return {"action": action, "action_input": action_input.strip(" ").strip('"')}
+
+    def __str__(self):
+        return "EvalOutputParser"

core/prompts/input.py

@@ -18,6 +18,7 @@ Use this if you want the human to use a tool.
 Your response should be in the following schema:
 
 Action: the action to take, should be one of [{tool_names}]
+Plan: All remaining detailed plans after this action in bullet points.
 Action Input: the input to the action
 
 **Option #2:**
@@ -26,6 +27,7 @@ You should replace sensitive data or encrypted data with "d1dy0uth1nk7hat1t1s7ha
 Your response should be in the following schema:
 
 Action: Final Answer
+Plan: None
 Action Input: string \\ You should put what you want to return to use here.
 """