refactor: think

metagpt/actions/talk_action.py

@@ -44,6 +44,7 @@ class TalkAction(Action):
             f"Answer the following questions strictly in {language}, and the answers must follow the Markdown format.\n "
             f"{self._talk}"
         )
+        logger.info(f"PROMPT: {prompt}")
         return prompt
 
     @property

metagpt/provider/openai_api.py

@@ -276,16 +276,22 @@ class OpenAIGPTAPI(BaseGPTAPI, RateLimiter):
         return response
 
     async def is_related(self, text1, text2):
-        command = f"{text1}\n{text2}\n\nIf the two sentences above are related, return [TRUE] brief and clear. Otherwise, return [FALSE]."
+        # command = f"{text1}\n{text2}\n\nIf the two sentences above are related, return [TRUE] brief and clear. Otherwise, return [FALSE]."
+        command = f"{text2}\n\nIs there any sentence above related to the following sentence: {text1}.\nIf is there any relevance, return [TRUE] brief and clear. Otherwise, return [FALSE] brief and clear."
         rsp = await self.aask(msg=command, system_msgs=[])
-        result, _ = self.extract_info(rsp)
-        return result == "TRUE"
+        result = True if "TRUE" in rsp else False
+        p2 = text2.replace("\n", "")
+        p1 = text1.replace("\n", "")
+        logger.info(f"IS_RELATED:\nParagraph 1: {p2}\nParagraph 2: {p1}\nRESULT: {result}")
+        return result
 
     async def rewrite(self, sentence: str, context: str):
-        command = (
-            f"{context}\n\nConsidering the content above, rewrite and return this sentence brief and clear:\n{sentence}"
-        )
+        # command = (
+        #     f"{context}\n\nConsidering the content above, rewrite and return this sentence brief and clear:\n{sentence}"
+        # )
+        command = f"{context}\n\nExtract relevant information from every preceding sentence and use it to succinctly supplement or rewrite the following text in brief and clear:\n{sentence}"
         rsp = await self.aask(msg=command, system_msgs=[])
+        logger.info(f"REWRITE:\nCommand: {command}\nRESULT: {rsp}")
         return rsp
 
     @staticmethod
@@ -316,8 +322,7 @@ class OpenAIGPTAPI(BaseGPTAPI, RateLimiter):
         return windows
 
     @staticmethod
-    def extract_info(input_string):
-        pattern = r"\[([A-Z]+)\]:\s*(.+)"
+    def extract_info(input_string, pattern=r"\[([A-Z]+)\]:\s*(.+)"):
         match = re.match(pattern, input_string)
         if match:
             return match.group(1), match.group(2)

metagpt/roles/assistant.py

@@ -54,18 +54,15 @@ class Assistant(Role):
         last_talk = await self.refine_memory()
         if not last_talk:
             return False
-        prompt = f"Refer to this sentence:\n {last_talk}\n"
+        prompt = ""
         skills = self.skills.get_skill_list()
         for desc, name in skills.items():
-            prompt += (
-                f"If want you to do {desc}, return `[SKILL]: {name}` brief and clear. For instance: [SKILL]: {name}\n"
-            )
-        prompt += "If the preceding text presents a complete question and solution, rewrite and return `[SOLUTION]: {problem}` brief and clear. For instance: [SOLUTION]: Solution for distributing watermelon\n"
-        prompt += "If the preceding text presents an unresolved issue and its corresponding discussion, rewrite and return `[PROBLEM]: {problem}` brief and clear. For instance: [PROBLEM]: How to distribute watermelon?\n"
-        prompt += "Otherwise, rewrite and return `[TALK]: {talk}` brief and clear. For instance: [TALK]: distribute watermelon"
+            prompt += f"If the text explicitly want you to {desc}, return `[SKILL]: {name}` brief and clear. For instance: [SKILL]: {name}\n"
+        prompt += 'Otherwise, return `[TALK]: {talk}` brief and clear. For instance: if {talk} is "xxxx" return [TALK]: xxxx\n\n'
+        prompt += f"Now what specific action is explicitly mentioned in the text: {last_talk}\n"
         logger.info(prompt)
         rsp = await self._llm.aask(prompt, [])
-        logger.info(rsp)
+        logger.info(f"THINK: {prompt}\n, THINK RESULT: {rsp}\n")
         return await self._plan(rsp, last_talk=last_talk)
 
     async def act(self) -> ActionOutput:
@@ -90,7 +87,6 @@ class Assistant(Role):
         skill, text = Assistant.extract_info(input_string=rsp)
         handlers = {
             MessageType.Talk.value: self.talk_handler,
-            MessageType.Problem.value: self.talk_handler,
             MessageType.Skill.value: self.skill_handler,
         }
         handler = handlers.get(skill, self.talk_handler)