diff --git a/test/agents/metagpt/role_2_streamlit_prompt.py b/test/agents/metagpt/role_2_streamlit_prompt.py index 2043edf..b283add 100644 --- a/test/agents/metagpt/role_2_streamlit_prompt.py +++ b/test/agents/metagpt/role_2_streamlit_prompt.py @@ -80,7 +80,7 @@ class stylize(Action): 请用自己的语气改写{instruction} """ - name: str = "rerask" + name: str = "stylize" async def run(self, instruction: str): prompt = self.PROMPT_TEMPLATE.format(instruction=instruction) diff --git a/test/agents/metagpt/role_3_streamlit_prompt.py b/test/agents/metagpt/role_3_streamlit_prompt.py index c30a3df..0738361 100644 --- a/test/agents/metagpt/role_3_streamlit_prompt.py +++ b/test/agents/metagpt/role_3_streamlit_prompt.py @@ -9,7 +9,10 @@ import json from typing import Optional from tianji.utils.json_from import SharedDataSingleton -from tianji.utils.knowledge_tool import get_docs_list_query_openai +from tianji.utils.knowledge_tool import ( + get_docs_list_query_openai, + get_docs_list_query_zhipuai, +) from tianji.utils.common_llm_api import LLMApi from tianji.agents.metagpt_agents.ruyi_agent import ruyi from tianji.agents.metagpt_agents.qianbianzhe_agent import qianbianzhe @@ -45,7 +48,7 @@ async def run(self, instruction: str): dict ] = SharedDataSingleton.get_instance().json_from_data knowledge_key = json_from_data["festival"] + json_from_data["requirement"] - knowledge = get_docs_list_query_openai( + knowledge = get_docs_list_query_zhipuai( query_str=knowledge_key, loader_file_path=KNOWLEDGE_PATH, persist_directory=SAVE_PATH, diff --git a/test/knowledges/test_get_docs_list_query.py b/test/knowledges/test_get_docs_list_query.py index dc0770d..c3615ef 100644 --- a/test/knowledges/test_get_docs_list_query.py +++ b/test/knowledges/test_get_docs_list_query.py @@ -1,17 +1,25 @@ import tianji.utils.knowledge_tool as knowledgetool from dotenv import load_dotenv + load_dotenv() -KNOWLEDGE_PATH = r"D:\1-wsl\TIANJI\Tianji\tianji\knowledges\04-Wishes\knowledges.txt" -SAVE_PATH = r"D:\1-wsl\TIANJI\Tianji\temp" +# KNOWLEDGE_PATH = r"D:\1-wsl\TIANJI\Tianji\tianji\knowledges\04-Wishes\knowledges.txt" +# SAVE_PATH = r"D:\1-wsl\TIANJI\Tianji\temp" + +KNOWLEDGE_PATH = r"/Users/fengzetao/Workspace/Github/SocialAI/Tianji/tianji/knowledges/04-Wishes/knowledges.txt" +SAVE_PATH = r"/Users/fengzetao/Workspace/Github/SocialAI/Tianji/temp" -# doclist = knowledgetool.get_docs_list_query_zhipu(query_str="春节",loader_file_path=KNOWLEDGE_PATH, \ +# doclist = knowledgetool.get_docs_list_query_openai(query_str="春节",loader_file_path=KNOWLEDGE_PATH, \ # persist_directory = SAVE_PATH,k_num=5) -doclist = knowledgetool.get_docs_list_query_openai(query_str="春节",loader_file_path=KNOWLEDGE_PATH, \ - persist_directory = SAVE_PATH,k_num=5) +doclist = knowledgetool.get_docs_list_query_zhipuai( + query_str="春节", + loader_file_path=KNOWLEDGE_PATH, + persist_directory=SAVE_PATH, + k_num=5, +) if doclist is not []: print(doclist) else: - print("doclist is [] !") \ No newline at end of file + print("doclist is [] !") diff --git a/tianji/agents/metagpt_agents/qianbianzhe_agent/action.py b/tianji/agents/metagpt_agents/qianbianzhe_agent/action.py index a66e8c6..d6c24c3 100644 --- a/tianji/agents/metagpt_agents/qianbianzhe_agent/action.py +++ b/tianji/agents/metagpt_agents/qianbianzhe_agent/action.py @@ -27,9 +27,9 @@ # "wish": "家庭成员平安" # }w + # 设计思路 给定人设并导入参考聊天话术、历史聊天语料进行聊天。 class ansWrite(Action): - # 这是对json中每个key的解释： # 语言场景（scene），目前的聊天场合，比如工作聚会。 # 节日（festival），对话目前背景所在的节日，比如生日。 @@ -42,7 +42,7 @@ class ansWrite(Action): # 聊天对象爱好（hobby），和role相关，就是聊天对象的兴趣爱好，例如下象棋。 # 聊天对象愿望（wish），和role相关，就是聊天对象目前的愿望是什么，例如果希望家庭成员平安。 - name: str = "read_and_ana" + name: str = "ansWrite" async def run(self, instruction: str): sharedData: Optional[SharedDataSingleton] = SharedDataSingleton.get_instance() @@ -80,8 +80,7 @@ class stylize(Action): 请用自己的语气改写{instruction} """ - def __init__(self, name="rerask", context=None, llm=None): - super().__init__(name, context, llm) + name: str = "stylize" async def run(self, instruction: str): prompt = self.PROMPT_TEMPLATE.format(instruction=instruction) diff --git a/tianji/agents/metagpt_agents/qianbianzhe_agent/role.py b/tianji/agents/metagpt_agents/qianbianzhe_agent/role.py index f53fd77..330f824 100644 --- a/tianji/agents/metagpt_agents/qianbianzhe_agent/role.py +++ b/tianji/agents/metagpt_agents/qianbianzhe_agent/role.py @@ -1,30 +1,36 @@ -from .action import * +from dotenv import load_dotenv + +load_dotenv() + from metagpt.roles import Role from metagpt.schema import Message from metagpt.logs import logger +from .action import ansWrite, stylize + # 千变者 以自己的身份回答问题 class qianbianzhe(Role): name: str = "qianbianzhe" profile: str = "stylize" - + def __init__(self, **kwargs): - super.__init__(**kwargs) - self._init_actions([ansWrite,stylize]) + super().__init__(**kwargs) + self._init_actions([ansWrite, stylize]) self._set_react_mode(react_mode="by_order") async def _act(self) -> Message: logger.info(f"{self._setting}: to do {self.rc.todo}({self.rc.todo.name})") - + todo = self.rc.todo - msg = self.get_memories(k=1)[0] # find the most k recent messagesA + msg = self.get_memories(k=1)[0] # find the most k recent messagesA result = await todo.run(msg.content) msg = Message(content=result, role=self.profile, cause_by=type(todo)) self.rc.memory.add(msg) return msg + # async def main(): # # 对话导入 # msg = "test" diff --git a/tianji/agents/metagpt_agents/ruyi_agent/action.py b/tianji/agents/metagpt_agents/ruyi_agent/action.py index 50e9e34..99ef5e9 100644 --- a/tianji/agents/metagpt_agents/ruyi_agent/action.py +++ b/tianji/agents/metagpt_agents/ruyi_agent/action.py @@ -9,7 +9,13 @@ from typing import Optional from metagpt.actions import Action from tianji.utils.json_from import SharedDataSingleton -from tianji.utils.knowledge_tool import get_docs_list_query_openai +from tianji.utils.knowledge_tool import ( + get_docs_list_query_openai, + get_docs_list_query_zhipuai, +) + +KNOWLEDGE_PATH = r"/Users/fengzetao/Workspace/Github/SocialAI/Tianji/tianji/knowledges/04-Wishes/knowledges.txt" +SAVE_PATH = r"/Users/fengzetao/Workspace/Github/SocialAI/Tianji/temp" # 给出针对回答的知识 并用md展示 @@ -35,7 +41,12 @@ async def run(self, instruction: str): # knowledges = "" json_from_data = SharedDataSingleton.get_instance().json_from_data knowledge_key = json_from_data["festival"] + json_from_data["requirement"] - knowledge = get_docs_list_query_openai(query_str=knowledge_key) + knowledge = get_docs_list_query_zhipuai( + query_str=knowledge_key, + loader_file_path=KNOWLEDGE_PATH, + persist_directory=SAVE_PATH, + k_num=5, + ) PROMPT_TEMPLATE: str = f""" 你是一个{json_from_data["festival"]}的祝福大师。 你需要写一段关于如何写{json_from_data["festival"]}{json_from_data["requirement"]}的思路总结。目前了解到这段{json_from_data["festival"]}{json_from_data["requirement"]}是在{json_from_data["scene"]}送给{json_from_data["role"]}的。 @@ -54,4 +65,5 @@ async def run(self, instruction: str): print("回复生成：", rsp) return rsp -# 如何写 如意如意如我心意 \ No newline at end of file + +# 如何写 如意如意如我心意 diff --git a/tianji/agents/metagpt_agents/ruyi_agent/role.py b/tianji/agents/metagpt_agents/ruyi_agent/role.py index 6ac539b..fe42038 100644 --- a/tianji/agents/metagpt_agents/ruyi_agent/role.py +++ b/tianji/agents/metagpt_agents/ruyi_agent/role.py @@ -1,13 +1,13 @@ -from .action import * -from metagpt.actions import Action from metagpt.roles import Role from metagpt.schema import Message from metagpt.logs import logger +from .action import writeMD + class ruyi(Role): name: str = "ruyi" profile: str = "stylize" - + def __init__(self, **kwargs): super().__init__(**kwargs) self._init_actions([writeMD]) @@ -15,12 +15,12 @@ def __init__(self, **kwargs): async def _act(self) -> Message: logger.info(f"{self._setting}: to do {self.rc.todo}({self.rc.todo.name})") - + todo = self.rc.todo - msg = self.get_memories(k=1)[0] # find the most k recent messagesA + msg = self.get_memories(k=1)[0] # find the most k recent messagesA result = await todo.run(msg.content) msg = Message(content=result, role=self.profile, cause_by=type(todo)) self.rc.memory.add(msg) - return msg \ No newline at end of file + return msg diff --git a/tianji/knowledges/04-Wishes/knowledges.txt b/tianji/knowledges/04-Wishes/knowledges.txt index 4718ca9..52c675d 100644 --- a/tianji/knowledges/04-Wishes/knowledges.txt +++ b/tianji/knowledges/04-Wishes/knowledges.txt @@ -75,4 +75,87 @@ 28、元旦到，祝福来报道：大财、小财、意外财，财源滚滚；亲情、爱情、朋友情，份份真情；官运、财运、桃花运，运运亨通；爱人、亲人、家里人，人人平安。 -29、元旦到，祝福来：愿财神把你骚扰，把忧愁收购；愿开心把你套牢，把无聊抛售；愿幸福把你绑架，把烦恼抢走。祝元旦快乐！ \ No newline at end of file +29、元旦到，祝福来：愿财神把你骚扰，把忧愁收购；愿开心把你套牢，把无聊抛售；愿幸福把你绑架，把烦恼抢走。祝元旦快乐！ + + + +1. 芙蓉入眼，逢秋意绵。祝你见月圆，祝你得心欢，祝你自由如云霓漫天，亦有爱的人常驻身边。在新的一岁，温柔不失果敢，顺遂且平安。 + +2. 愿你在漫长岁月里，一身长久磊落，知世故而天真，风日洒然扶摇直上。 + +3. 我衷心地希望，你的日子里总有光亮，笑起来的时候可以什么都不想。对的要坚持，错的要遗忘。世间山河之广，祝你如愿以偿。 + +4. Happy Birthday祝我的甜妹永远甜！希望你能从小朋友变快乐的大朋友，祝你年年岁岁不挂科，朝朝暮暮有帅哥。年年有今日，岁岁有今朝。 + +5. 愿你平安无疾，前程似锦。希望你能活成自己的模样，无论什么时候都不应该停止努力，愿你能变得更好，也愿你在以后的每一天里，眼中有银河，心中有日月。心想事成，生日快乐！ + +6. 祝你生日快乐！不是生日这天快乐，而是到下一个生日之前的每一天都要快乐，然后继续下一个生日快乐！🥰 + +7. 愿你眼神清澈永藏诗歌，手掌温热布满星河。 + +8. 我会在每个有意义的时辰，远隔山海与你共祝。愿你付出甘之如饴，愿你所得归于欢喜。 + +9. 生日快乐🎂愿你﹣-不熬夜不失眠不焦虑，不长痘不脱发不生病，荡尽不平，理想长鸣。 + +10. 生日快乐🎂愿你﹣-柴米油盐，腌渍诗与远方。锅碗瓢盆，盛满琳琅爱意。酸甜苦辣，料理无味时日。亲亲吾爱，可抵山水万难。 + +11. 生日快乐🎂愿你﹣-不管世界怎么糟糕你都不会被打扰，你的路途繁花似锦，你是永远快乐的小姑娘。 + +12. 银河便利店在贩卖星球，我用身上所有的浪漫，买下了一颗最亮的恒星，在你对着蛋糕许愿的时候，向你眼里发射无尽的星光。 + +13. 默念你的名，愿你前途云蒸霞蔚，灿若星河。愿你度过的叫吉时，得到的叫如愿。 + +14. 往后余生暴瘦是你，有钱是你，拥有一切美好的还是你，承蒙相遇，三生有幸，亲爱的，生日快乐！ + +15. 愿你在新的一岁里，喜乐安平，热烈坦荡！愿你面对生活万境，无惧无畏，仍做自己！ + +16. 生辰吉乐！愿你在新的一年里，岁岁安康，万事如意！愿你面对未来荆棘时，剑斩荆棘，稳当自如！ + +17. 愿你能像向阳花般在你的世界闪闪发光，做自己的小太阳！ + +18. 生日快乐！愿你有自持而节制的华丽，层出不穷的新鲜，愈炼愈飞的魔性，永远虔诚的天真。 + +19. 你生日了🎂这个时候生日的人是未来之星🌟是国家栋梁🏠是都市小说的商业大鳄💎是吾日三省吾身的自律者💪是相亲节目里的心动嘉宾💓是自然界的丛林之王👑是世间所有丑与恶的唾弃者🔥是世间所有美与好的创作者❗❗ + +20. 我该祝你什么呢，想祝你平顺，可漫漫长路并非皆是坦途。想祝你快乐，但未来之途并非都是欢欣，失意低谷在所难免。那就祝你勇敢且坚强，乐观且豁达吧！ + + +1. 2024 让我们有有趣趣的，去做可可爱爱的人，去做勇勇敢敢的事，实现心心念念的梦 + +2. 愿你风驰电掣，如龙腾空，奔向梦想的彼岸。愿你龙战于野，身负鳞甲，不惧风雨！ + +3. 新的一年，祝您龙行蘿蘿，前程關關。 + +4. 愿新年，胜旧年。欢愉且胜意，万事皆可期。 + +5. 新年，旧年，有你皆甜。山河共赴，新岁同欢。咔！兔年杀青！龙年！奔赴下一场山海！ + +6. 旧岁千般皆如意，新年万事定称心。 + +7. 愿新的一年，卡里不缺钱，晚上不失眠。 + +8. 长路漫漫，终有归途。这路遥马急的人间，你我平安喜乐就好。🚗🌈 + +9. 希望你的新年，全糖去冰。 🍧🌟 + +10. 发月常新，美好常在。纵使人潮汹涌，光阴似箭，愿所有的驰骋最终都奔向团圆。🌌👨‍👩‍👧‍👦 + +11. 所求皆如愿，所行化坦途。多喜乐，长安宁。旧年好，新年更好。新年快乐！(˶╹ꇴ╹˶)🧨🎇 + +12. 辞慕尔尔，烟火年年。日子滚烫，人间可爱。✨🎉 + +13. 家人闲坐，灯火可亲，新年伊始，喜乐安宁。 🏡✨ + +14. 星光璀璨，愿新年的生活同样夺目，让幸福如同星星一般闪耀✨ + +15. 🌠 时光流转，愿你在新年找到属于自己的蓝天，生活是彩虹梦幻的不尽旅程🌈 + +16. 新年，愿生活充满奇迹，每一天都有惊叹的时刻，探险充满奇迹的精彩⚜ + +17. 新曦初绽，春节将至，祝君岁岁皆如意，生活如诗，岁月似画。 + +18. 春佳节伊始，愿你的日子如诗如画，温馨而美好。🌈愿你心中的梦想如龙腾四海，逐浪前行。🌊 + +19. 新的一年，愿你万事顺遂，所爱如山。从此眼底是绮丽，周遭是晴朗，嘴角是笑意，耳畔是阜盛烟火。 + +20. 心之所向、行之所往、不慌不忙；烟火起、照人间、喜悦无边，举杯敬此年，唯愿：年年岁岁常康健，岁岁年年常相见。 diff --git a/tianji/utils/knowledge_tool.py b/tianji/utils/knowledge_tool.py index 28bc30f..9fca673 100644 --- a/tianji/utils/knowledge_tool.py +++ b/tianji/utils/knowledge_tool.py @@ -1,9 +1,13 @@ +from __future__ import annotations + from langchain.embeddings.openai import OpenAIEmbeddings from langchain.text_splitter import CharacterTextSplitter from langchain.vectorstores import Chroma from langchain.document_loaders import TextLoader +from langchain.embeddings.base import Embeddings +from langchain.pydantic_v1 import BaseModel, root_validator +from typing import Dict, List, Optional import os -from zhipuai import ZhipuAI from dotenv import load_dotenv load_dotenv() @@ -17,7 +21,6 @@ def get_docs_list_query_openai( k_num=5, ): embeddings = OpenAIEmbeddings() - print("-----", os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) loader_file_path = os.path.join( os.path.dirname(os.path.dirname(os.path.abspath(__file__))), loader_file_path ) @@ -43,20 +46,113 @@ def get_docs_list_query_openai( return knowledge -# ZhipuAI -class ZhipuAIEmbeddings: - def __init__(self, api_key=None): - self.client = ZhipuAI(api_key=api_key) +class ZhipuAIEmbeddings(BaseModel, Embeddings): + """`Zhipuai Embeddings` embedding models.""" + + zhipuai_api_key: Optional[str] = None + """Zhipuai application apikey""" + + @root_validator() + def validate_environment(cls, values: Dict) -> Dict: + """ + Validate whether zhipuai_api_key in the environment variables or + configuration file are available or not. + + Args: + + values: a dictionary containing configuration information, must include the + fields of zhipuai_api_key + Returns: + + a dictionary containing configuration information. If zhipuai_api_key + are not provided in the environment variables or configuration + file, the original values will be returned; otherwise, values containing + zhipuai_api_key will be returned. + Raises: + + ValueError: zhipuai package not found, please install it with `pip install + zhipuai` + """ + # values["zhipuai_api_key"] = get_from_dict_or_env( + # values, + # "zhipuai_api_key", + # "ZHIPUAI_API_KEY", + # ) + + try: + import zhipuai + + # zhipuai.api_key = values["zhipuai_api_key"] + values["client"] = zhipuai.ZhipuAI() + + except ImportError: + raise ValueError( + "Zhipuai package not found, please install it with " + "`pip install zhipuai`" + ) + return values + + def _embed(self, texts: str) -> List[float]: + # send request + try: + resp = self.client.embeddings.create( + model="embedding-2", # 填写需要调用的模型名称 + input=texts, + ) + except Exception as e: + raise ValueError(f"Error raised by inference endpoint: {e}") + + # if resp["code"] != 200: + # raise ValueError( + # "Error raised by inference API HTTP code: %s, %s" + # % (resp["code"], resp["msg"]) + # ) + embeddings = resp.data[0].embedding + + return embeddings + + def embed_query(self, text: str) -> List[float]: + """ + Embedding a text. + + Args: + + Text (str): A text to be embedded. + + Return: + + List [float]: An embedding list of input text, which is a list of floating-point values. + """ + resp = self.embed_documents([text]) + return resp[0] + + def embed_documents(self, texts: List[str]) -> List[List[float]]: + """ + Embeds a list of text documents. + + Args: + texts (List[str]): A list of text documents to embed. + + Returns: + List[List[float]]: A list of embeddings for each document in the input list. + Each embedding is represented as a list of float values. + """ + return [self._embed(text) for text in texts] + + async def aembed_documents(self, texts: List[str]) -> List[List[float]]: + """Asynchronous Embed search docs.""" + raise NotImplementedError( + "Please use `embed_documents`. Official does not support asynchronous requests" + ) - def __call__(self, texts): - response = self.client.embeddings.create( - model="embedding-2", - input=texts, + async def aembed_query(self, text: str) -> List[float]: + """Asynchronous Embed query text.""" + raise NotImplementedError( + "Please use `aembed_query`. Official does not support asynchronous requests" ) - return response["embeddings"] -def get_docs_list_query_zhipu( +def get_docs_list_query_zhipuai( query_str, loader_file_path="knowledges/knowledges.txt", persist_directory="",