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fix #I6WHKN [app_chatgpt]敏感语处理有问题,要修 置顶
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@@ -40,7 +40,7 @@ GPT-3 A set of models that can understand and generate natural language
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# begin gpt 参数
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# 1. stop:表示聊天机器人停止生成回复的条件,可以是一段文本或者一个列表,当聊天机器人生成的回复中包含了这个条件,就会停止继续生成回复。
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# 2. temperature:控制回复的“新颖度”,值越高,聊天机器人生成的回复越不确定和随机,值越低,聊天机器人生成的回复会更加可预测和常规化。
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# 3. top_p:与temperature有些类似,也是控制回复的“新颖度”。不同的是,top_p控制的是回复中概率最高的几个可能性的累计概率之和,值越小,生成的回复越保守,值越大,生成的回复越新颖。
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# 3. top_p:言语连贯性,与temperature有些类似,也是控制回复的“新颖度”。不同的是,top_p控制的是回复中概率最高的几个可能性的累计概率之和,值越小,生成的回复越保守,值越大,生成的回复越新颖。
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# 4. frequency_penalty:用于控制聊天机器人回复中出现频率过高的词汇的惩罚程度。聊天机器人会尝试避免在回复中使用频率较高的词汇,以提高回复的多样性和新颖度。
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# 5. presence_penalty:与frequency_penalty相对,用于控制聊天机器人回复中出现频率较低的词汇的惩罚程度。聊天机器人会尝试在回复中使用频率较低的词汇,以提高回复的多样性和新颖度。
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max_tokens = fields.Integer('Max response', default=600,
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@@ -50,7 +50,7 @@ GPT-3 A set of models that can understand and generate natural language
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(including system message, examples, message history, and user query) and the model's response.
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One token is roughly 4 characters for typical English text.
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""")
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temperature = fields.Float(string='Temperature', default=0.9,
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temperature = fields.Float(string='Temperature', default=0.8,
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help="""
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Controls randomness. Lowering the temperature means that the model will produce
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more repetitive and deterministic responses.
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@@ -104,39 +104,47 @@ GPT-3 A set of models that can understand and generate natural language
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def action_disconnect(self):
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requests.delete('https://chatgpt.com/v1/disconnect')
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def get_ai(self, data, author_id=False, answer_id=False, param={}):
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# 通用方法
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# author_id: 请求的 partner_id 对象
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# answer_id: 回答的 partner_id 对象
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# kwargs,dict 形式的可变参数
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self.ensure_one()
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# 前置勾子,一般返回 False,有问题返回响应内容
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res_pre = self.get_ai_pre(data, author_id, answer_id, param)
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if res_pre:
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return res_pre
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if hasattr(self, 'get_%s' % self.provider):
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res = getattr(self, 'get_%s' % self.provider)(data, author_id, answer_id, param)
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else:
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res = _('No robot provider found')
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# 后置勾子,返回处理后的内容,用于处理敏感词等
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res_post = self.get_ai_post(res, author_id, answer_id, param)
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return res_post
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def get_ai_pre(self, data, author_id=False, answer_id=False, param={}):
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if self.is_filtering:
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search = WordsSearch()
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search.SetKeywords([])
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content = data[0]['content']
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if isinstance(data, list):
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content = data[len(data)-1]['content']
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else:
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content = data
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sensi = search.FindFirst(content)
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if sensi is not None:
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_logger.error('==========敏感词:%s' % sensi['Keyword'])
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return _('温馨提示:您发送的内容含有敏感词,请修改内容后再向我发送。')
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else:
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return False
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def get_ai(self, data, author_id=False, answer_id=False, param={}):
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# 通用方法
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# author_id: 请求的 partner_id 对象
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# answer_id: 回答的 partner_id 对象
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# param,dict 形式的参数
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# 调整输出为2个参数:res_post详细内容,is_ai是否ai的响应
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self.ensure_one()
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# 前置勾子,一般返回 False,有问题返回响应内容,用于处理敏感词等
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res_pre = self.get_ai_pre(data, author_id, answer_id, param)
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if res_pre:
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# 有错误内容,则返回上级内容及 is_ai为假
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return res_pre, False
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if not hasattr(self, 'get_%s' % self.provider):
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res = _('No robot provider found')
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return res, False
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res = getattr(self, 'get_%s' % self.provider)(data, author_id, answer_id, param)
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# 后置勾子,返回处理后的内容
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res_post, is_ai = self.get_ai_post(res, author_id, answer_id, param)
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return res_post, is_ai
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def get_ai_post(self, res, author_id=False, answer_id=False, param={}):
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if res and author_id and isinstance(res, openai.openai_object.OpenAIObject) or isinstance(res, list):
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# 返回是个对象,那么就是ai
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usage = json.loads(json.dumps(res['usage']))
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content = json.loads(json.dumps(res['choices'][0]['message']['content']))
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data = content.replace(' .', '.').strip()
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@@ -169,9 +177,10 @@ GPT-3 A set of models that can understand and generate natural language
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'first_ask_time': ask_date
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})
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ai_use.write(vals)
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return data, True
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else:
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data = res
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return data
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# 直接返回错误语句,那么就是非ai
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return res, False
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def get_ai_system(self, content=None):
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# 获取基础ai角色设定, role system
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@@ -221,7 +230,7 @@ GPT-3 A set of models that can understand and generate natural language
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# 处理传参,传过来的优先于 robot 默认的
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max_tokens = param.get('max_tokens') or self.max_tokens or 600,
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temperature = param.get('temperature') or self.temperature or 0.9,
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temperature = param.get('temperature') or self.temperature or 0.8,
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top_p = param.get('top_p') or self.top_p or 0.6,
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frequency_penalty = param.get('frequency_penalty') or self.frequency_penalty or 0.5,
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presence_penalty = param.get('presence_penalty') or self.presence_penalty or 0.5,
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@@ -250,7 +259,7 @@ GPT-3 A set of models that can understand and generate natural language
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model=self.ai_model,
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messages=messages,
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n=1,
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temperature=self.temperature or 0.9,
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temperature=self.temperature or 0.8,
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max_tokens=self.max_tokens or 600,
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top_p=self.top_p or 0.6,
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frequency_penalty=self.frequency_penalty or 0.5,
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@@ -276,7 +285,7 @@ GPT-3 A set of models that can understand and generate natural language
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pdata = {
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"model": self.ai_model,
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"prompt": data,
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"temperature": 0.9,
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"temperature": 0.8,
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"max_tokens": max_tokens,
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"top_p": 1,
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"frequency_penalty": 0.0,
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@@ -311,9 +320,9 @@ GPT-3 A set of models that can understand and generate natural language
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else:
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messages = [{"role": "user", "content": data}]
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# 处理传参,传过来的优先于 robot 默认的
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# todo: 处理传参,传过来的优先于 robot 默认的,当前有问题,无法做tuple转换
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max_tokens = param.get('max_tokens') or self.max_tokens or 600,
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temperature = param.get('temperature') or self.temperature or 0.9,
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temperature = param.get('temperature') or self.temperature or 0.8,
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top_p = param.get('top_p') or self.top_p or 0.6,
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frequency_penalty = param.get('frequency_penalty') or self.frequency_penalty or 0.5,
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presence_penalty = param.get('presence_penalty') or self.presence_penalty or 0.5,
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@@ -330,7 +339,7 @@ GPT-3 A set of models that can understand and generate natural language
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messages=messages,
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# 返回的回答数量
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n=1,
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temperature=self.temperature or 0.9,
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temperature=self.temperature or 0.8,
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max_tokens=self.max_tokens or 600,
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top_p=self.top_p or 0.6,
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frequency_penalty=self.frequency_penalty or 0.5,
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@@ -10567,7 +10567,6 @@ fuck兴奋剂
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禽獸
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明慧网
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jiejie
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的
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嫩穴
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床上激情自拍图
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6。4
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@@ -13533,7 +13532,6 @@ re xue ying hao
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烂
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淫荡老师
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小姨子的小嫩屄
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create
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亚洲激情BT
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省长的儿媳妇
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苹果日报
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@@ -14077,7 +14075,6 @@ gong fu
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89年的鬥爭
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台湾十八电影
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小淫虫电影
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CREATE
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外阴
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外??挂
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毛爷爷复活
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@@ -63,7 +63,7 @@ class Channel(models.Model):
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answer_id = user_id.partner_id
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# todo: 只有个人配置的群聊才给配置
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param = self.get_ai_config(ai)
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res = ai.get_ai(messages, author_id, answer_id, param)
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res, is_ai = ai.get_ai(messages, author_id, answer_id, param)
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if res:
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res = res.replace('\n', '<br/>')
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channel.with_user(user_id).message_post(body=res, message_type='comment', subtype_xmlid='mail.mt_comment', parent_id=message.id)
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@@ -144,22 +144,18 @@ class Channel(models.Model):
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if not msg:
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return rdata
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# api_key = self.env['ir.config_parameter'].sudo().get_param('app_chatgpt.openapi_api_key')
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api_key = ''
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if ai:
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# ai处理,不要自问自答
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if ai and answer_id != message.author_id:
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api_key = ai.openapi_api_key
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if not api_key:
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_logger.warning(_("ChatGPT Robot【%s】have not set open api key."))
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return rdata
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try:
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openapi_context_timeout = int(self.env['ir.config_parameter'].sudo().get_param('app_chatgpt.openapi_context_timeout')) or 60
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except:
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openapi_context_timeout = 60
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sync_config = self.env['ir.config_parameter'].sudo().get_param('app_chatgpt.openai_sync_config')
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openai.api_key = api_key
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# print(msg_vals)
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# print(msg_vals.get('record_name', ''))
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# print('self.channel_type :',self.channel_type)
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if ai:
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try:
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openapi_context_timeout = int(self.env['ir.config_parameter'].sudo().get_param('app_chatgpt.openapi_context_timeout')) or 60
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except:
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openapi_context_timeout = 60
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sync_config = self.env['ir.config_parameter'].sudo().get_param('app_chatgpt.openai_sync_config')
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openai.api_key = api_key
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# 非4版本,取0次。其它取3 次历史
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chat_count = 0 if '4' in ai.ai_model else 3
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if author_id != answer_id.id and self.channel_type == 'chat':
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