Merge pull request #33 from iorisa/feature/talk_prompt

metagpt/actions/talk_action.py

@@ -26,7 +26,7 @@ class TalkAction(Action):
         self._rsp = None
 
     @property
-    def prompt(self):
+    def prompt_old(self):
         prompt = ""
         if CONFIG.agent_description:
             prompt = (
@@ -46,7 +46,7 @@ class TalkAction(Action):
         return prompt
 
     @property
-    def formation_prompt(self):
+    def prompt(self):
         kvs = {
             "{role}": CONFIG.agent_description or "",
             "{history}": self._history_summary or "",
@@ -57,6 +57,7 @@ class TalkAction(Action):
         prompt = TalkAction.__FORMATION_LOOSE__
         for k, v in kvs.items():
             prompt = prompt.replace(k, v)
+        logger.info(f"PROMPT: {prompt}")
         return prompt
 
     async def run(self, *args, **kwargs) -> ActionOutput:

metagpt/memory/brain_memory.py

@@ -34,7 +34,7 @@ class BrainMemory(pydantic.BaseModel):
     historical_summary: str = ""
     last_history_id: str = ""
     is_dirty: bool = False
-    last_talk: str = ""
+    last_talk: str = None
 
     def add_talk(self, msg: Message):
         msg.add_tag(MessageType.Talk.value)
@@ -109,7 +109,6 @@ class BrainMemory(pydantic.BaseModel):
         if msg.id:
             if self.to_int(msg.id, 0) < self.to_int(self.last_history_id, -1):
                 return
-            self.last_history_id = str(self.to_int(msg.id, 0))
         self.history.append(msg.dict())
         self.is_dirty = True
 
@@ -125,3 +124,8 @@ class BrainMemory(pydantic.BaseModel):
             return int(v)
         except:
             return default_value
+
+    def pop_last_talk(self):
+        v = self.last_talk
+        self.last_talk = None
+        return v

metagpt/provider/openai_api.py

@@ -226,21 +226,24 @@ class OpenAIGPTAPI(BaseGPTAPI, RateLimiter):
     async def get_summary(self, text: str, max_words=200, keep_language: bool = False):
         max_token_count = DEFAULT_MAX_TOKENS
         max_count = 100
+        text_length = len(text)
         while max_count > 0:
-            if len(text) < max_token_count:
+            if text_length < max_token_count:
                 return await self._get_summary(text=text, max_words=max_words, keep_language=keep_language)
 
             padding_size = 20 if max_token_count > 20 else 0
             text_windows = self.split_texts(text, window_size=max_token_count - padding_size)
+            part_max_words = min(int(max_words / len(text_windows)) + 1, 100)
             summaries = []
             for ws in text_windows:
-                response = await self._get_summary(text=ws, max_words=max_words, keep_language=keep_language)
+                response = await self._get_summary(text=ws, max_words=part_max_words, keep_language=keep_language)
                 summaries.append(response)
             if len(summaries) == 1:
                 return summaries[0]
 
             # Merged and retry
             text = "\n".join(summaries)
+            text_length = len(text)
 
             max_count -= 1  # safeguard
         raise openai.error.InvalidRequestError("text too long")

metagpt/roles/assistant.py

@@ -120,12 +120,12 @@ class Assistant(Role):
 
     async def refine_memory(self) -> str:
         history_text = self.memory.history_text
-        last_talk = self.memory.last_talk
+        last_talk = self.memory.pop_last_talk()
         if last_talk is None:  # No user feedback, unsure if past conversation is finished.
             return None
         if history_text == "":
             return last_talk
-        history_summary = await self._llm.get_summary(history_text, max_words=500)
+        history_summary = await self._llm.get_summary(history_text, max_words=800, keep_language=True)
         await self.memory.set_history_summary(
             history_summary=history_summary, redis_key=CONFIG.REDIS_KEY, redis_conf=CONFIG.REDIS
         )

metagpt/utils/redis.py

@@ -4,6 +4,7 @@
 # @Desc: { redis client }
 # @Date: 2022/11/28 10:12
 import json
+import traceback
 from datetime import timedelta
 from enum import Enum
 from typing import Awaitable, Callable, Dict, Optional, Union
@@ -203,12 +204,19 @@ class Redis:
     async def get(self, key: str) -> str:
         if not self.is_valid() or not key:
             return None
-        v = await RedisManager.get_with_cache_info(redis_cache_info=RedisCacheInfo(key=key))
-        return v
+        try:
+            v = await RedisManager.get_with_cache_info(redis_cache_info=RedisCacheInfo(key=key))
+            return v
+        except Exception as e:
+            logger.exception(f"{e}, stack:{traceback.format_exc()}")
+            return None
 
     async def set(self, key: str, data: str, timeout_sec: int):
         if not self.is_valid() or not key:
             return
-        await RedisManager.set_with_cache_info(
-            redis_cache_info=RedisCacheInfo(key=key, timeout=timeout_sec), value=data
-        )
+        try:
+            await RedisManager.set_with_cache_info(
+                redis_cache_info=RedisCacheInfo(key=key, timeout=timeout_sec), value=data
+            )
+        except Exception as e:
+            logger.exception(f"{e}, stack:{traceback.format_exc()}")