Merge pull request #16 from iorisa/feature/bug-1113

fixbug: exceed length

metagpt/memory/brain_memory.py

@@ -8,7 +8,7 @@
 """
 
 from enum import Enum
-from typing import List, Dict
+from typing import Dict, List
 
 import pydantic
 
@@ -45,10 +45,20 @@ class BrainMemory(pydantic.BaseModel):
     def history_text(self):
         if len(self.history) == 0:
             return ""
-        texts = [Message(**m).content for m in self.history[:-1]]
+        texts = []
+        for m in self.history[:-1]:
+            if isinstance(m, Dict):
+                t = Message(**m).content
+            elif isinstance(m, Message):
+                t = m.content
+            else:
+                continue
+            texts.append(t)
+
         return "\n".join(texts)
 
-    def move_to_solution(self):
+    def move_to_solution(self, history_summary):
+        """放入solution队列，以备后续长程检索。目前还未加此功能，先用history_summary顶替"""
         if len(self.history) < 2:
             return
         msgs = self.history[:-1]
@@ -58,6 +68,7 @@ class BrainMemory(pydantic.BaseModel):
             self.history = []
         else:
             self.history = self.history[-1:]
+        self.history.insert(0, Message(content="RESOLVED: " + history_summary))
 
     @property
     def last_talk(self):

metagpt/provider/openai_api.py

@@ -242,14 +242,18 @@ class OpenAIGPTAPI(BaseGPTAPI, RateLimiter):
         """Generate text title"""
         max_response_token_count = 50
         max_token_count = max_token_count_per_ask or CONFIG.MAX_TOKENS or DEFAULT_MAX_TOKENS
-        text_windows = self.split_texts(text, window_size=max_token_count - max_response_token_count)
+        while True:
+            text_windows = self.split_texts(text, window_size=max_token_count - max_response_token_count)
 
-        summaries = []
-        for ws in text_windows:
-            response = await self.get_summary(ws)
-            summaries.append(response)
-        if len(summaries) == 1:
-            return summaries[0]
+            summaries = []
+            for ws in text_windows:
+                response = await self.get_summary(ws, max_words=max_response_token_count)
+                summaries.append(response)
+            if len(summaries) == 1:
+                return summaries[0]
+            text = "\n".join(summaries)
+            if len(text) <= max_words * 2 and len(text) <= max_token_count:
+                break
 
         language = CONFIG.language or DEFAULT_LANGUAGE
         command = f"Translate the above summary into a {language} title of less than {max_words} words."

metagpt/roles/assistant.py

@@ -18,7 +18,7 @@ import asyncio
 from pathlib import Path
 
 from metagpt.actions import ActionOutput
-from metagpt.actions.skill_action import SkillAction, ArgumentsParingAction
+from metagpt.actions.skill_action import ArgumentsParingAction, SkillAction
 from metagpt.actions.talk_action import TalkAction
 from metagpt.config import CONFIG
 from metagpt.learn.skill_loader import SkillLoader
@@ -31,10 +31,19 @@ from metagpt.schema import Message
 class Assistant(Role):
     """Assistant for solving common issues."""
 
-    def __init__(self, name="Lily", profile="An assistant", goal="Help to solve problem",
-                 constraints="Talk in {language}", desc="", *args, **kwargs):
-        super(Assistant, self).__init__(name=name, profile=profile,
-                                        goal=goal, constraints=constraints, desc=desc, *args, **kwargs)
+    def __init__(
+        self,
+        name="Lily",
+        profile="An assistant",
+        goal="Help to solve problem",
+        constraints="Talk in {language}",
+        desc="",
+        *args,
+        **kwargs,
+    ):
+        super(Assistant, self).__init__(
+            name=name, profile=profile, goal=goal, constraints=constraints, desc=desc, *args, **kwargs
+        )
         brain_memory = CONFIG.BRAIN_MEMORY
         self.memory = BrainMemory(**brain_memory) if brain_memory else BrainMemory()
         skill_path = Path(CONFIG.SKILL_PATH) if CONFIG.SKILL_PATH else None
@@ -65,8 +74,9 @@ class Assistant(Role):
             msg = Message(content=result)
             output = ActionOutput(content=result)
         else:
-            msg = Message(content=result.content, instruct_content=result.instruct_content,
-                          cause_by=type(self._rc.todo))
+            msg = Message(
+                content=result.content, instruct_content=result.instruct_content, cause_by=type(self._rc.todo)
+            )
             output = result
         self.memory.add_answer(msg)
         return output
@@ -85,8 +95,10 @@ class Assistant(Role):
         return await handler(text, **kwargs)
 
     async def talk_handler(self, text, **kwargs) -> bool:
-        action = TalkAction(talk=text, knowledge=self.memory.get_knowledge(), llm=self._llm,
-                            **kwargs)
+        history = self.memory.history_text
+        action = TalkAction(
+            talk=text, knowledge=self.memory.get_knowledge(), history_summary=history, llm=self._llm, **kwargs
+        )
         self.add_to_do(action)
         return True
 
@@ -111,17 +123,18 @@ class Assistant(Role):
             return None
         if history_text == "":
             return last_talk
-        history_summary = await self._llm.get_context_title(history_text, max_words=20)
+        history_summary = await self._llm.get_context_title(history_text, max_token_count_per_ask=1000, max_words=500)
         if last_talk and await self._llm.is_related(last_talk, history_summary):  # Merge relevant content.
             last_talk = await self._llm.rewrite(sentence=last_talk, context=history_text)
             return last_talk
 
-        self.memory.move_to_solution()  # Promptly clear memory after the issue is resolved.
+        self.memory.move_to_solution(history_summary)  # Promptly clear memory after the issue is resolved.
         return last_talk
 
     @staticmethod
     def extract_info(input_string):
         from metagpt.provider.openai_api import OpenAIGPTAPI
+
         return OpenAIGPTAPI.extract_info(input_string)
 
     def get_memory(self) -> str:
@@ -150,6 +163,6 @@ async def main():
         await role.talk(talk)
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     CONFIG.language = "Chinese"
     asyncio.run(main())