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# encoding:utf-8 |
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import json |
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import time |
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from typing import List, Tuple |
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import openai |
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import openai.error |
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import broadscope_bailian |
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from broadscope_bailian import ChatQaMessage |
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from bot.bot import Bot |
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from bot.baidu.baidu_wenxin_session import BaiduWenxinSession |
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from bot.session_manager import SessionManager |
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from bridge.context import ContextType |
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from bridge.reply import Reply, ReplyType |
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from common.log import logger |
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from config import conf, load_config |
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class TongyiQwenBot(Bot): |
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def __init__(self): |
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super().__init__() |
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self.access_key_id = conf().get("tongyi_access_key_id") |
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self.access_key_secret = conf().get("tongyi_access_key_secret") |
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self.agent_key = conf().get("tongyi_agent_key") |
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self.app_id = conf().get("tongyi_app_id") |
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self.node_id = conf().get("tongyi_node_id") |
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self.api_key_client = broadscope_bailian.AccessTokenClient(access_key_id=self.access_key_id, access_key_secret=self.access_key_secret) |
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self.api_key_expired_time = self.set_api_key() |
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self.sessions = SessionManager(BaiduWenxinSession, model=conf().get("model") or "tongyi") |
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self.temperature = conf().get("temperature", 0.2) # 值在[0,1]之间,越大表示回复越具有不确定性 |
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self.top_p = conf().get("top_p", 1) |
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def reply(self, query, context=None): |
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# acquire reply content |
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if context.type == ContextType.TEXT: |
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logger.info("[TONGYI] query={}".format(query)) |
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session_id = context["session_id"] |
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reply = None |
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clear_memory_commands = conf().get("clear_memory_commands", ["#清除记忆"]) |
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if query in clear_memory_commands: |
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self.sessions.clear_session(session_id) |
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reply = Reply(ReplyType.INFO, "记忆已清除") |
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elif query == "#清除所有": |
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self.sessions.clear_all_session() |
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reply = Reply(ReplyType.INFO, "所有人记忆已清除") |
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elif query == "#更新配置": |
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load_config() |
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reply = Reply(ReplyType.INFO, "配置已更新") |
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if reply: |
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return reply |
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session = self.sessions.session_query(query, session_id) |
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logger.debug("[TONGYI] session query={}".format(session.messages)) |
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reply_content = self.reply_text(session) |
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logger.debug( |
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"[TONGYI] new_query={}, session_id={}, reply_cont={}, completion_tokens={}".format( |
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session.messages, |
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session_id, |
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reply_content["content"], |
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reply_content["completion_tokens"], |
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) |
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) |
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if reply_content["completion_tokens"] == 0 and len(reply_content["content"]) > 0: |
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reply = Reply(ReplyType.ERROR, reply_content["content"]) |
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elif reply_content["completion_tokens"] > 0: |
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self.sessions.session_reply(reply_content["content"], session_id, reply_content["total_tokens"]) |
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reply = Reply(ReplyType.TEXT, reply_content["content"]) |
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else: |
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reply = Reply(ReplyType.ERROR, reply_content["content"]) |
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logger.debug("[TONGYI] reply {} used 0 tokens.".format(reply_content)) |
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return reply |
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else: |
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reply = Reply(ReplyType.ERROR, "Bot不支持处理{}类型的消息".format(context.type)) |
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return reply |
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def reply_text(self, session: BaiduWenxinSession, retry_count=0) -> dict: |
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""" |
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call bailian's ChatCompletion to get the answer |
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:param session: a conversation session |
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:param retry_count: retry count |
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:return: {} |
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""" |
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try: |
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prompt, history = self.convert_messages_format(session.messages) |
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self.update_api_key_if_expired() |
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# NOTE 阿里百炼的call()函数参数比较奇怪, top_k参数表示top_p, top_p参数表示temperature, 可以参考文档 https://help.aliyun.com/document_detail/2587502.htm |
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response = broadscope_bailian.Completions().call(app_id=self.app_id, prompt=prompt, history=history, top_k=self.top_p, top_p=self.temperature) |
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completion_content = self.get_completion_content(response, self.node_id) |
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completion_tokens, total_tokens = self.calc_tokens(session.messages, completion_content) |
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return { |
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"total_tokens": total_tokens, |
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"completion_tokens": completion_tokens, |
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"content": completion_content, |
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} |
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except Exception as e: |
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need_retry = retry_count < 2 |
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result = {"completion_tokens": 0, "content": "我现在有点累了,等会再来吧"} |
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if isinstance(e, openai.error.RateLimitError): |
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logger.warn("[TONGYI] RateLimitError: {}".format(e)) |
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result["content"] = "提问太快啦,请休息一下再问我吧" |
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if need_retry: |
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time.sleep(20) |
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elif isinstance(e, openai.error.Timeout): |
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logger.warn("[TONGYI] Timeout: {}".format(e)) |
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result["content"] = "我没有收到你的消息" |
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if need_retry: |
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time.sleep(5) |
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elif isinstance(e, openai.error.APIError): |
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logger.warn("[TONGYI] Bad Gateway: {}".format(e)) |
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result["content"] = "请再问我一次" |
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if need_retry: |
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time.sleep(10) |
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elif isinstance(e, openai.error.APIConnectionError): |
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logger.warn("[TONGYI] APIConnectionError: {}".format(e)) |
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need_retry = False |
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result["content"] = "我连接不到你的网络" |
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else: |
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logger.exception("[TONGYI] Exception: {}".format(e)) |
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need_retry = False |
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self.sessions.clear_session(session.session_id) |
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if need_retry: |
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logger.warn("[TONGYI] 第{}次重试".format(retry_count + 1)) |
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return self.reply_text(session, retry_count + 1) |
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else: |
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return result |
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def set_api_key(self): |
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api_key, expired_time = self.api_key_client.create_token(agent_key=self.agent_key) |
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broadscope_bailian.api_key = api_key |
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return expired_time |
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def update_api_key_if_expired(self): |
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if time.time() > self.api_key_expired_time: |
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self.api_key_expired_time = self.set_api_key() |
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def convert_messages_format(self, messages) -> Tuple[str, List[ChatQaMessage]]: |
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history = [] |
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user_content = '' |
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assistant_content = '' |
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for message in messages: |
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role = message.get('role') |
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if role == 'user': |
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user_content += message.get('content') |
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elif role == 'assistant': |
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assistant_content = message.get('content') |
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history.append(ChatQaMessage(user_content, assistant_content)) |
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user_content = '' |
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assistant_content = '' |
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if user_content == '': |
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raise Exception('no user message') |
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return user_content, history |
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def get_completion_content(self, response, node_id): |
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text = response['Data']['Text'] |
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if node_id == '': |
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return text |
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# TODO: 当使用流程编排创建大模型应用时,响应结构如下,最终结果在['finalResult'][node_id]['response']['text']中,暂时先这么写 |
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# { |
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# 'Success': True, |
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# 'Code': None, |
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# 'Message': None, |
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# 'Data': { |
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# 'ResponseId': '9822f38dbacf4c9b8daf5ca03a2daf15', |
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# 'SessionId': 'session_id', |
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# 'Text': '{"finalResult":{"LLM_T7islK":{"params":{"modelId":"qwen-plus-v1","prompt":"${systemVars.query}${bizVars.Text}"},"response":{"text":"作为一个AI语言模型,我没有年龄,因为我没有生日。\n我只是一个程序,没有生命和身体。"}}}}', |
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# 'Thoughts': [], |
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# 'Debug': {}, |
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# 'DocReferences': [] |
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# }, |
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# 'RequestId': '8e11d31551ce4c3f83f49e6e0dd998b0', |
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# 'Failed': None |
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# } |
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text_dict = json.loads(text) |
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completion_content = text_dict['finalResult'][node_id]['response']['text'] |
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return completion_content |
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def calc_tokens(self, messages, completion_content): |
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completion_tokens = len(completion_content) |
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prompt_tokens = 0 |
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for message in messages: |
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prompt_tokens += len(message["content"]) |
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return completion_tokens, prompt_tokens + completion_tokens |