feat: merge main

metagpt/actions/skill_action.py

@@ -40,9 +40,8 @@ class ArgumentsParingAction(Action):
 
     async def run(self, *args, **kwargs) -> ActionOutput:
         prompt = self.prompt
-        logger.info(prompt)
         rsp = await self.llm.aask(msg=prompt, system_msgs=[])
-        logger.info(rsp)
+        logger.debug(f"SKILL:{prompt}\n, RESULT:{rsp}")
         self.args = ArgumentsParingAction.parse_arguments(skill_name=self.skill.name, txt=rsp)
         self.rsp = ActionOutput(content=rsp)
         return self.rsp

metagpt/actions/talk_action.py

@@ -44,11 +44,11 @@ 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}")
+        logger.debug(f"PROMPT: {prompt}")
         return prompt
 
     @property
-    def prompt_bad(self):
+    def prompt_gpt4(self):
         kvs = {
             "{role}": CONFIG.agent_description or "",
             "{history}": self._history_summary or "",
@@ -64,9 +64,8 @@ class TalkAction(Action):
 
     async def run(self, *args, **kwargs) -> ActionOutput:
         prompt = self.prompt
-        logger.info(prompt)
         rsp = await self.llm.aask(msg=prompt, system_msgs=[])
-        logger.info(rsp)
+        logger.debug(f"PROMPT:{prompt}\nRESULT:{rsp}\n")
         self._rsp = ActionOutput(content=rsp)
         return self._rsp
 

metagpt/document_store/faiss_store.py

@@ -20,9 +20,10 @@ from metagpt.logs import logger
 
 
 class FaissStore(LocalStore):
-    def __init__(self, raw_data: Path, cache_dir=None, meta_col="source", content_col="output"):
+    def __init__(self, raw_data: Path, cache_dir=None, meta_col="source", content_col="output", embedding_conf=None):
         self.meta_col = meta_col
         self.content_col = content_col
+        self.embedding_conf = embedding_conf or {}
         super().__init__(raw_data, cache_dir)
 
     def _load(self) -> Optional["FaissStore"]:
@@ -37,7 +38,7 @@ class FaissStore(LocalStore):
         return store
 
     def _write(self, docs, metadatas):
-        store = FAISS.from_texts(docs, OpenAIEmbeddings(openai_api_version="2020-11-07"), metadatas=metadatas)
+        store = FAISS.from_texts(docs, OpenAIEmbeddings(openai_api_version="2020-11-07", **self.embedding_conf), metadatas=metadatas)
         return store
 
     def persist(self):

metagpt/memory/brain_memory.py

@@ -72,7 +72,7 @@ class BrainMemory(pydantic.BaseModel):
         if not redis.is_valid() or not redis_key:
             return BrainMemory()
         v = await redis.get(key=redis_key)
-        logger.info(f"REDIS GET {redis_key} {v}")
+        logger.debug(f"REDIS GET {redis_key} {v}")
         if v:
             data = json.loads(v)
             bm = BrainMemory(**data)
@@ -86,7 +86,7 @@ class BrainMemory(pydantic.BaseModel):
             return False
         v = self.json()
         await redis.set(key=redis_key, data=v, timeout_sec=timeout_sec)
-        logger.info(f"REDIS SET {redis_key} {v}")
+        logger.debug(f"REDIS SET {redis_key} {v}")
         self.is_dirty = False
 
     @staticmethod

metagpt/provider/openai_api.py

@@ -257,9 +257,9 @@ class OpenAIGPTAPI(BaseGPTAPI, RateLimiter):
         else:
             command = f"Translate the above content into a summary of less than {max_words} words."
         msg = text + "\n\n" + command
-        logger.info(f"summary ask:{msg}")
+        logger.debug(f"summary ask:{msg}")
         response = await self.aask(msg=msg, system_msgs=[])
-        logger.info(f"summary rsp: {response}")
+        logger.debug(f"summary rsp: {response}")
         return response
 
     async def get_context_title(self, text: str, max_words=5) -> str:
@@ -270,9 +270,9 @@ class OpenAIGPTAPI(BaseGPTAPI, RateLimiter):
         command = f"Translate the above summary into a {language} title of less than {max_words} words."
         summaries = [summary, command]
         msg = "\n".join(summaries)
-        logger.info(f"title ask:{msg}")
+        logger.debug(f"title ask:{msg}")
         response = await self.aask(msg=msg, system_msgs=[])
-        logger.info(f"title rsp: {response}")
+        logger.debug(f"title rsp: {response}")
         return response
 
     async def is_related(self, text1, text2):
@@ -282,7 +282,7 @@ class OpenAIGPTAPI(BaseGPTAPI, RateLimiter):
         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}")
+        logger.info(f"IS_RELATED:\nParagraph 1: {p2}\nParagraph 2: {p1}\nRESULT: {result}\n")
         return result
 
     async def rewrite(self, sentence: str, context: str):
@@ -291,7 +291,7 @@ class OpenAIGPTAPI(BaseGPTAPI, RateLimiter):
         # )
         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}")
+        logger.info(f"REWRITE:\nCommand: {command}\nRESULT: {rsp}\n")
         return rsp
 
     @staticmethod

metagpt/roles/assistant.py

@@ -93,6 +93,7 @@ class Assistant(Role):
 
     async def talk_handler(self, text, **kwargs) -> bool:
         history = self.memory.history_text
+        text = kwargs.get("last_talk") or text
         action = TalkAction(
             talk=text, knowledge=self.memory.get_knowledge(), history_summary=history, llm=self._llm, **kwargs
         )