fix #I6WHKN [app_chatgpt]敏感语处理有问题，要修 置顶

app_chatgpt/models/ai_robot.py

@@ -40,7 +40,7 @@ GPT-3	A set of models that can understand and generate natural language
     # begin gpt 参数
     # 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。
     # 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。
-    # 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。
+    # 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。
     # 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。
     # 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。
     max_tokens = fields.Integer('Max response', default=600,
@@ -50,7 +50,7 @@ GPT-3	A set of models that can understand and generate natural language
                                 (including system message, examples, message history, and user query) and the model's response.
                                 One token is roughly 4 characters for typical English text.
                                 """)
-    temperature = fields.Float(string='Temperature', default=0.9,
+    temperature = fields.Float(string='Temperature', default=0.8,
                                help="""
                                Controls randomness. Lowering the temperature means that the model will produce
                                more repetitive and deterministic responses.
@@ -105,38 +105,46 @@ GPT-3	A set of models that can understand and generate natural language
     def action_disconnect(self):
         requests.delete('https://chatgpt.com/v1/disconnect')
 
-    def get_ai(self, data, author_id=False, answer_id=False, param={}):
-        #     通用方法
-        # author_id: 请求的 partner_id 对象
-        # answer_id: 回答的 partner_id 对象
-        # kwargs，dict 形式的可变参数
-        self.ensure_one()
-        # 前置勾子，一般返回 False，有问题返回响应内容
-        res_pre = self.get_ai_pre(data, author_id, answer_id, param)
-        if res_pre:
-            return res_pre
-        if hasattr(self, 'get_%s' % self.provider):
-            res = getattr(self, 'get_%s' % self.provider)(data, author_id, answer_id, param)
-        else:
-            res = _('No robot provider found')
-        
-        # 后置勾子，返回处理后的内容，用于处理敏感词等
-        res_post = self.get_ai_post(res, author_id, answer_id,  param)
-        return res_post
-
     def get_ai_pre(self, data, author_id=False, answer_id=False, param={}):
         if self.is_filtering:
             search = WordsSearch()
             search.SetKeywords([])
-            content = data[0]['content']
+            if isinstance(data, list):
+                content = data[len(data)-1]['content']
+            else:
+                content = data
             sensi = search.FindFirst(content)
             if sensi is not None:
+                _logger.error('==========敏感词：%s' % sensi['Keyword'])
                 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。')
         else:
             return False
 
+    def get_ai(self, data, author_id=False, answer_id=False, param={}):
+        #     通用方法
+        # author_id: 请求的 partner_id 对象
+        # answer_id: 回答的 partner_id 对象
+        # param，dict 形式的参数
+        # 调整输出为2个参数：res_post详细内容，is_ai是否ai的响应
+        
+        self.ensure_one()
+        # 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
+        res_pre = self.get_ai_pre(data, author_id, answer_id, param)
+        if res_pre:
+            # 有错误内容，则返回上级内容及 is_ai为假
+            return res_pre, False
+        if not hasattr(self, 'get_%s' % self.provider):
+            res = _('No robot provider found')
+            return res, False
+        
+        res = getattr(self, 'get_%s' % self.provider)(data, author_id, answer_id, param)
+        # 后置勾子，返回处理后的内容
+        res_post, is_ai = self.get_ai_post(res, author_id, answer_id,  param)
+        return res_post, is_ai
+    
     def get_ai_post(self, res, author_id=False, answer_id=False, param={}):
         if res and author_id and isinstance(res, openai.openai_object.OpenAIObject) or isinstance(res, list):
+            # 返回是个对象，那么就是ai
             usage = json.loads(json.dumps(res['usage']))
             content = json.loads(json.dumps(res['choices'][0]['message']['content']))
             data = content.replace(' .', '.').strip()
@@ -169,9 +177,10 @@ GPT-3	A set of models that can understand and generate natural language
                             'first_ask_time': ask_date
                         })
                     ai_use.write(vals)
+            return data, True
         else:
-            data = res
+            # 直接返回错误语句，那么就是非ai
-        return data
+            return res, False
     
     def get_ai_system(self, content=None):
         # 获取基础ai角色设定, role system
@@ -221,7 +230,7 @@ GPT-3	A set of models that can understand and generate natural language
 
         # 处理传参，传过来的优先于 robot 默认的
         max_tokens = param.get('max_tokens') or self.max_tokens or 600,
-        temperature = param.get('temperature') or self.temperature or 0.9,
+        temperature = param.get('temperature') or self.temperature or 0.8,
         top_p = param.get('top_p') or self.top_p or 0.6,
         frequency_penalty = param.get('frequency_penalty') or self.frequency_penalty or 0.5,
         presence_penalty = param.get('presence_penalty') or self.presence_penalty or 0.5,
@@ -250,7 +259,7 @@ GPT-3	A set of models that can understand and generate natural language
                 model=self.ai_model,
                 messages=messages,
                 n=1,
-                temperature=self.temperature or 0.9,
+                temperature=self.temperature or 0.8,
                 max_tokens=self.max_tokens or 600,
                 top_p=self.top_p or 0.6,
                 frequency_penalty=self.frequency_penalty or 0.5,
@@ -276,7 +285,7 @@ GPT-3	A set of models that can understand and generate natural language
             pdata = {
                 "model": self.ai_model,
                 "prompt": data,
-                "temperature": 0.9,
+                "temperature": 0.8,
                 "max_tokens": max_tokens,
                 "top_p": 1,
                 "frequency_penalty": 0.0,
@@ -311,9 +320,9 @@ GPT-3	A set of models that can understand and generate natural language
         else:
             messages = [{"role": "user", "content": data}]
 
-        # 处理传参，传过来的优先于 robot 默认的
+        # 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
         max_tokens = param.get('max_tokens') or self.max_tokens or 600,
-        temperature = param.get('temperature') or self.temperature or 0.9,
+        temperature = param.get('temperature') or self.temperature or 0.8,
         top_p = param.get('top_p') or self.top_p or 0.6,
         frequency_penalty = param.get('frequency_penalty') or self.frequency_penalty or 0.5,
         presence_penalty = param.get('presence_penalty') or self.presence_penalty or 0.5,
@@ -330,7 +339,7 @@ GPT-3	A set of models that can understand and generate natural language
             messages=messages,
             # 返回的回答数量
             n=1,
-            temperature=self.temperature or 0.9,
+            temperature=self.temperature or 0.8,
             max_tokens=self.max_tokens or 600,
             top_p=self.top_p or 0.6,
             frequency_penalty=self.frequency_penalty or 0.5,

app_chatgpt/models/lib/sensi_words.txt

@@ -10567,7 +10567,6 @@ fuck兴奋剂
 禽獸
 明慧网
 jiejie
-的
 嫩穴
 床上激情自拍图
 6。4
@@ -13533,7 +13532,6 @@ re xue ying hao
 烂
 淫荡老师
 小姨子的小嫩屄
-create
 亚洲激情BT
 省长的儿媳妇
 苹果日报
@@ -14077,7 +14075,6 @@ gong fu
 89年的鬥爭
 台湾十八电影
 小淫虫电影
-CREATE
 外阴
 外？？挂
 毛爷爷复活

app_chatgpt/models/mail_channel.py

@@ -63,7 +63,7 @@ class Channel(models.Model):
         answer_id = user_id.partner_id
         # todo: 只有个人配置的群聊才给配置
         param = self.get_ai_config(ai)
-        res = ai.get_ai(messages, author_id, answer_id, param)
+        res, is_ai = ai.get_ai(messages, author_id, answer_id, param)
         if res:
             res = res.replace('\n', '<br/>')
             channel.with_user(user_id).message_post(body=res, message_type='comment', subtype_xmlid='mail.mt_comment', parent_id=message.id)
@@ -144,8 +144,8 @@ class Channel(models.Model):
         if not msg:
             return rdata
         # api_key = self.env['ir.config_parameter'].sudo().get_param('app_chatgpt.openapi_api_key')
-        api_key = ''
+        # ai处理，不要自问自答
-        if ai:
+        if ai and answer_id != message.author_id:
             api_key = ai.openapi_api_key
             if not api_key:
                 _logger.warning(_("ChatGPT Robot【%s】have not set open api key."))
@@ -156,10 +156,6 @@ class Channel(models.Model):
                 openapi_context_timeout = 60
             sync_config = self.env['ir.config_parameter'].sudo().get_param('app_chatgpt.openai_sync_config')
             openai.api_key = api_key
-        # print(msg_vals)
-        # print(msg_vals.get('record_name', ''))
-        # print('self.channel_type :',self.channel_type)
-        if ai:
             # 非4版本，取0次。其它取3 次历史
             chat_count = 0 if '4' in ai.ai_model else 3
             if author_id != answer_id.id and self.channel_type == 'chat':