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@@ -1,7 +1,7 @@
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### 前置确认
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1. 运行于国内网络环境,未开代理
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2. python 已安装:版本在 3.7 ~ 3.10 之间,依赖已安装
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1. 网络能够访问openai接口 [#351](https://github.com/zhayujie/chatgpt-on-wechat/issues/351)
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2. python 已安装:版本在 3.7 ~ 3.10 之间,依赖已安装
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3. 在已有 issue 中未搜索到类似问题
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4. [FAQS](https://github.com/zhayujie/chatgpt-on-wechat/wiki/FAQs) 中无类似问题
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@@ -13,9 +13,9 @@
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# 更新日志
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>**2023.03.02:** 接入[ChatGPT API](https://platform.openai.com/docs/guides/chat) (gpt-3.5-turbo),默认使用该模型进行对话,需升级openai依赖 (`pip3 install --upgrade openai`)
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>**2023.03.02:** 接入[ChatGPT API](https://platform.openai.com/docs/guides/chat) (gpt-3.5-turbo),默认使用该模型进行对话,需升级openai依赖 (`pip3 install --upgrade openai`)。网络问题参考 [#351](https://github.com/zhayujie/chatgpt-on-wechat/issues/351)
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>**2023.02.20:** 增加 [python-wechaty](https://github.com/wechaty/python-wechaty) 支持,Pad协议相对稳定,不易封号,但Token收费,可申请七天体验Token (使用参考[#244](https://github.com/zhayujie/chatgpt-on-wechat/pull/244),contributed by [ZQ7](https://github.com/ZQ7))
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>**2023.02.20:** 增加 [python-wechaty](https://github.com/wechaty/python-wechaty) 作为可选渠道,使用Pad协议相对稳定,但Token收费 (使用参考[#244](https://github.com/zhayujie/chatgpt-on-wechat/pull/244),contributed by [ZQ7](https://github.com/ZQ7))
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>**2023.02.09:** 扫码登录存在封号风险,请谨慎使用,参考[#58](https://github.com/AutumnWhj/ChatGPT-wechat-bot/issues/158)
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@@ -48,7 +48,7 @@
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### 1. OpenAI账号注册
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前往 [OpenAI注册页面](https://beta.openai.com/signup) 创建账号,参考这篇 [教程](https://freepac.siterubix.com/chatgpt%e6%b3%a8%e5%86%8c%e6%95%99%e7%a8%8b%ef%bc%88%e5%ae%8c%e6%95%b4%e6%8c%87%e5%8d%97%ef%bc%89/) 可以通过虚拟手机号来接收验证码。创建完账号则前往 [API管理页面](https://beta.openai.com/account/api-keys) 创建一个 API Key 并保存下来,后面需要在项目中配置这个key。
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前往 [OpenAI注册页面](https://beta.openai.com/signup) 创建账号,参考这篇 [教程](https://www.pythonthree.com/register-openai-chatgpt/) 可以通过虚拟手机号来接收验证码。创建完账号则前往 [API管理页面](https://beta.openai.com/account/api-keys) 创建一个 API Key 并保存下来,后面需要在项目中配置这个key。
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> 项目中使用的对话模型是 davinci,计费方式是约每 750 字 (包含请求和回复) 消耗 $0.02,图片生成是每张消耗 $0.016,账号创建有免费的 $18 额度,使用完可以更换邮箱重新注册。
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@@ -89,6 +89,7 @@ cp config-template.json config.json
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# config.json文件内容示例
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{
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"open_ai_api_key": "YOUR API KEY", # 填入上面创建的 OpenAI API KEY
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"proxy": "127.0.0.1:7890", # 代理客户端的ip和端口
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"single_chat_prefix": ["bot", "@bot"], # 私聊时文本需要包含该前缀才能触发机器人回复
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"single_chat_reply_prefix": "[bot] ", # 私聊时自动回复的前缀,用于区分真人
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"group_chat_prefix": ["@bot"], # 群聊时包含该前缀则会触发机器人回复
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@@ -113,6 +114,7 @@ cp config-template.json config.json
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**3.其他配置**
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+ `proxy`:由于目前 `openai` 接口国内无法访问,需配置代理客户端的地址,详情参考 [#351](https://github.com/zhayujie/chatgpt-on-wechat/issues/351)
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+ 对于图像生成,在满足个人或群组触发条件外,还需要额外的关键词前缀来触发,对应配置 `image_create_prefix `
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+ 关于OpenAI对话及图片接口的参数配置(内容自由度、回复字数限制、图片大小等),可以参考 [对话接口](https://beta.openai.com/docs/api-reference/completions) 和 [图像接口](https://beta.openai.com/docs/api-reference/completions) 文档直接在 [代码](https://github.com/zhayujie/chatgpt-on-wechat/blob/master/bot/openai/open_ai_bot.py) `bot/openai/open_ai_bot.py` 中进行调整。
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+ `conversation_max_tokens`:表示能够记忆的上下文最大字数(一问一答为一组对话,如果累积的对话字数超出限制,就会优先移除最早的一组对话)
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@@ -140,6 +142,7 @@ touch nohup.out # 首次运行需要新建日
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nohup python3 app.py & tail -f nohup.out # 在后台运行程序并通过日志输出二维码
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```
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扫码登录后程序即可运行于服务器后台,此时可通过 `ctrl+c` 关闭日志,不会影响后台程序的运行。使用 `ps -ef | grep app.py | grep -v grep` 命令可查看运行于后台的进程,如果想要重新启动程序可以先 `kill` 掉对应的进程。日志关闭后如果想要再次打开只需输入 `tail -f nohup.out`。
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scripts/目录有相应的脚本可以调用
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> **注意:** 如果 扫码后手机提示登录验证需要等待5s,而终端的二维码再次刷新并提示 `Log in time out, reloading QR code`,此时需参考此 [issue](https://github.com/zhayujie/chatgpt-on-wechat/issues/8) 修改一行代码即可解决。
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+66
-14
@@ -3,15 +3,22 @@
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from bot.bot import Bot
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from config import conf
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from common.log import logger
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from common.expired_dict import ExpiredDict
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import openai
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import time
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user_session = dict()
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if conf().get('expires_in_seconds'):
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user_session = ExpiredDict(conf().get('expires_in_seconds'))
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else:
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user_session = dict()
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# OpenAI对话模型API (可用)
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class ChatGPTBot(Bot):
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def __init__(self):
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openai.api_key = conf().get('open_ai_api_key')
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proxy = conf().get('proxy')
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if proxy:
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openai.proxy = proxy
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def reply(self, query, context=None):
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# acquire reply content
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@@ -21,6 +28,9 @@ class ChatGPTBot(Bot):
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if query == '#清除记忆':
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Session.clear_session(from_user_id)
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return '记忆已清除'
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elif query == '#清除所有':
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Session.clear_all_session()
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return '所有人记忆已清除'
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new_query = Session.build_session_query(query, from_user_id)
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logger.debug("[OPEN_AI] session query={}".format(new_query))
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@@ -30,29 +40,36 @@ class ChatGPTBot(Bot):
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# return self.reply_text_stream(query, new_query, from_user_id)
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reply_content = self.reply_text(new_query, from_user_id, 0)
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logger.debug("[OPEN_AI] new_query={}, user={}, reply_cont={}".format(new_query, from_user_id, reply_content))
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if reply_content:
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Session.save_session(query, reply_content, from_user_id)
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return reply_content
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logger.debug("[OPEN_AI] new_query={}, user={}, reply_cont={}".format(new_query, from_user_id, reply_content["content"]))
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if reply_content["completion_tokens"] > 0:
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Session.save_session(reply_content["content"], from_user_id, reply_content["total_tokens"])
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return reply_content["content"]
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elif context.get('type', None) == 'IMAGE_CREATE':
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return self.create_img(query, 0)
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def reply_text(self, query, user_id, retry_count=0):
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def reply_text(self, query, user_id, retry_count=0) ->dict:
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'''
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call openai's ChatCompletion to get the answer
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:param query: query content
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:param user_id: from user id
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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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response = openai.ChatCompletion.create(
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model="gpt-3.5-turbo", # 对话模型的名称
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messages=query,
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temperature=0.9, # 值在[0,1]之间,越大表示回复越具有不确定性
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max_tokens=1200, # 回复最大的字符数
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#max_tokens=4096, # 回复最大的字符数
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top_p=1,
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frequency_penalty=0.0, # [-2,2]之间,该值越大则更倾向于产生不同的内容
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presence_penalty=0.0, # [-2,2]之间,该值越大则更倾向于产生不同的内容
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)
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# res_content = response.choices[0]['text'].strip().replace('<|endoftext|>', '')
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logger.info(response.choices[0]['message']['content'])
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# log.info("[OPEN_AI] reply={}".format(res_content))
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return response.choices[0]['message']['content']
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logger.info("[ChatGPT] reply={}, total_tokens={}".format(response.choices[0]['message']['content'], response["usage"]["total_tokens"]))
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return {"total_tokens": response["usage"]["total_tokens"],
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"completion_tokens": response["usage"]["completion_tokens"],
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"content": response.choices[0]['message']['content']}
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except openai.error.RateLimitError as e:
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# rate limit exception
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logger.warn(e)
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@@ -61,12 +78,21 @@ class ChatGPTBot(Bot):
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logger.warn("[OPEN_AI] RateLimit exceed, 第{}次重试".format(retry_count+1))
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return self.reply_text(query, user_id, retry_count+1)
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else:
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return "提问太快啦,请休息一下再问我吧"
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return {"completion_tokens": 0, "content": "提问太快啦,请休息一下再问我吧"}
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except openai.error.APIConnectionError as e:
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# api connection exception
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logger.warn(e)
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logger.warn("[OPEN_AI] APIConnection failed")
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return {"completion_tokens": 0, "content":"我连接不到你的网络"}
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except openai.error.Timeout as e:
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logger.warn(e)
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logger.warn("[OPEN_AI] Timeout")
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return {"completion_tokens": 0, "content":"我没有收到你的消息"}
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except Exception as e:
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# unknown exception
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logger.exception(e)
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Session.clear_session(user_id)
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return "请再问我一次吧"
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return {"completion_tokens": 0, "content": "请再问我一次吧"}
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def create_img(self, query, retry_count=0):
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try:
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@@ -117,14 +143,40 @@ class Session(object):
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return session
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@staticmethod
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def save_session(query, answer, user_id):
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def save_session(answer, user_id, total_tokens):
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max_tokens = conf().get("conversation_max_tokens")
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if not max_tokens:
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# default 3000
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max_tokens = 1000
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max_tokens=int(max_tokens)
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session = user_session.get(user_id)
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if session:
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# append conversation
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gpt_item = {'role': 'assistant', 'content': answer}
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session.append(gpt_item)
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# discard exceed limit conversation
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Session.discard_exceed_conversation(session, max_tokens, total_tokens)
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@staticmethod
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def discard_exceed_conversation(session, max_tokens, total_tokens):
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dec_tokens = int(total_tokens)
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# logger.info("prompt tokens used={},max_tokens={}".format(used_tokens,max_tokens))
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while dec_tokens > max_tokens:
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# pop first conversation
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if len(session) > 3:
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session.pop(1)
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session.pop(1)
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else:
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break
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dec_tokens = dec_tokens - max_tokens
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@staticmethod
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def clear_session(user_id):
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user_session[user_id] = []
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@staticmethod
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def clear_all_session():
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user_session.clear()
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@@ -46,6 +46,9 @@ class WechatChannel(Channel):
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other_user_id = msg['User']['UserName'] # 对手方id
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content = msg['Text']
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match_prefix = self.check_prefix(content, conf().get('single_chat_prefix'))
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if "」\n- - - - - - - - - - - - - - -" in content:
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logger.debug("[WX]reference query skipped")
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return
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if from_user_id == other_user_id and match_prefix is not None:
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# 好友向自己发送消息
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if match_prefix != '':
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@@ -87,7 +90,9 @@ class WechatChannel(Channel):
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content = context_special_list[1]
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elif len(content_list) == 2:
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content = content_list[1]
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if "」\n- - - - - - - - - - - - - - -" in content:
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logger.debug("[WX]reference query skipped")
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return ""
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config = conf()
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match_prefix = (msg['IsAt'] and not config.get("group_at_off", False)) or self.check_prefix(origin_content, config.get('group_chat_prefix')) \
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or self.check_contain(origin_content, config.get('group_chat_keyword'))
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@@ -0,0 +1,23 @@
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from datetime import datetime, timedelta
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class ExpiredDict(dict):
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def __init__(self, expires_in_seconds):
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super().__init__()
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self.expires_in_seconds = expires_in_seconds
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def __getitem__(self, key):
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value, expiry_time = super().__getitem__(key)
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if datetime.now() > expiry_time:
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del self[key]
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raise KeyError("expired {}".format(key))
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self.__setitem__(key, value)
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return value
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def __setitem__(self, key, value):
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expiry_time = datetime.now() + timedelta(seconds=self.expires_in_seconds)
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super().__setitem__(key, (value, expiry_time))
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def get(self, key, default=None):
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try:
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return self[key]
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except KeyError:
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return default
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@@ -1,11 +1,12 @@
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{
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"open_ai_api_key": "YOUR API KEY",
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"wechaty_puppet_service_token": "WECHATY PUPPET SERVICE TOKEN",
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"proxy": "",
|
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"single_chat_prefix": ["bot", "@bot"],
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"single_chat_reply_prefix": "[bot] ",
|
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"group_chat_prefix": ["@bot"],
|
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"group_name_white_list": ["ChatGPT测试群", "ChatGPT测试群2"],
|
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"image_create_prefix": ["画", "看", "找"],
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"conversation_max_tokens": 1000,
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"character_desc": "你是ChatGPT, 一个由OpenAI训练的大型语言模型, 你旨在回答并解决人们的任何问题,并且可以使用多种语言与人交流。"
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"character_desc": "你是ChatGPT, 一个由OpenAI训练的大型语言模型, 你旨在回答并解决人们的任何问题,并且可以使用多种语言与人交流。",
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"expires_in_seconds": 3600
|
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}
|
||||
|
||||
Reference in New Issue
Block a user