prepare #I6SC9C 处理azure私聊，app_chatgpt优化，指定用户时增加使用情况 置顶

处理azure 私聊

app_chatgpt/data/ai_robot_data.xml

@@ -23,6 +23,7 @@
         <field name="provider">azure</field>
         <field name="endpoint">https://my.openai.azure.com</field>
         <field name="engine">gpt35</field>
+        <field name="api_version">2023-03-15-preview</field>
         <field name="sequence">8</field>
     </record>
     <record id="chatgpt4_azure" model="ai.robot">
@@ -30,6 +31,7 @@
         <field name="provider">azure</field>
         <field name="endpoint">https://my.openai.azure.com</field>
         <field name="engine">gpt4</field>
+        <field name="api_version">2023-03-15-preview</field>
         <field name="sequence">9</field>
     </record>
 </odoo>

app_chatgpt/i18n/zh_CN.po

@@ -1399,7 +1399,7 @@ msgid "Mahjong red dragon"
 msgstr ""
 
 #. module: app_chatgpt
-#: model:ir.model.fields,field_description:app_chatgpt.field_ai_robot__max_length
+#: model:ir.model.fields,field_description:app_chatgpt.field_ai_robot__max_tokens
 msgid "Max Length"
 msgstr ""
 

app_chatgpt/models/ai_robot.py

@@ -37,8 +37,63 @@ Moderation: A fine-tuned model that can detect whether text may be sensitive or
 GPT-3	A set of models that can understand and generate natural language
                              """)
     openapi_api_key = fields.Char(string="API Key", help="Provide the API key here")
-    temperature = fields.Float(string='Temperature', default=0.9)
+    # begin gpt 参数
-    max_length = fields.Integer('Max Length', default=300)
+    # 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。
+    # 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,
+                                help="""
+                                Set a limit on the number of tokens per model response.
+                                The API supports a maximum of 4000 tokens shared between the prompt
+                                (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,
+                               help="""
+                               Controls randomness. Lowering the temperature means that the model will produce
+                               more repetitive and deterministic responses.
+                               Increasing the temperature will result in more unexpected or creative responses.
+                               Try adjusting temperature or Top P but not both.
+                                    """)
+    top_p = fields.Float('Top probabilities', default=0.6,
+                         help="""
+                         Similar to temperature, this controls randomness but uses a different method.
+                         Lowering Top P will narrow the model’s token selection to likelier tokens.
+                         Increasing Top P will let the model choose from tokens with both high and low likelihood.
+                         Try adjusting temperature or Top P but not both
+                         """)
+    # 避免使用常用词
+    frequency_penalty = fields.Float('Frequency penalty', default=0.5,
+                                     help="""
+                                     Reduce the chance of repeating a token proportionally based on how often it has appeared in the text so far.
+                                     This decreases the likelihood of repeating the exact same text in a response.
+                                     """)
+    # 避免使用生僻词
+    presence_penalty = fields.Float('Presence penalty', default=0.2,
+                                    help="""
+                                    Reduce the chance of repeating any token that has appeared in the text at all so far.
+                                    This increases the likelihood of introducing new topics in a response.
+                                    """)
+    # 停止回复的关键词
+    stop = fields.Char('Stop sequences',
+                       help="""
+                       Use , to separate the stop key word.
+                       Make responses stop at a desired point, such as the end of a sentence or list.
+                       Specify up to four sequences where the model will stop generating further tokens in a response.
+                       The returned text will not contain the stop sequence.
+                       """)
+    # 角色设定
+    sys_content = fields.Char('System message',
+                              help="""
+                              Give the model instructions about how it should behave and any context it should reference when generating a response.
+                              You can describe the assistant’s personality,
+                              tell it what it should and shouldn’t answer, and tell it how to format responses.
+                              There’s no token limit for this section, but it will be included with every API call,
+                              so it counts against the overall token limit.
+                              """)
+    # end gpt 参数
     endpoint = fields.Char('End Point', default='https://api.openai.com/v1/chat/completions')
     engine = fields.Char('Engine', help='If use Azure, Please input the Model deployment name.')
     api_version = fields.Char('API Version', default='2022-12-01')
@@ -50,32 +105,39 @@ 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, sender_id=False, answer_id=False, **kwargs):
+    def get_ai(self, data, author_id=False, answer_id=False, **kwargs):
         #     通用方法
-        # sender_id: 请求的 partner_id 对象
+        # 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, sender_id, answer_id, **kwargs)
+        res_pre = self.get_ai_pre(data, author_id, answer_id, **kwargs)
         if res_pre:
             return res_pre
         if hasattr(self, 'get_%s' % self.provider):
-            res = getattr(self, 'get_%s' % self.provider)(data, sender_id, answer_id, **kwargs)
+            res = getattr(self, 'get_%s' % self.provider)(data, author_id, answer_id, **kwargs)
         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, sender_id, answer_id, **kwargs)
+        res_post = self.get_ai_post(res, author_id, answer_id, **kwargs)
         return res_post
 
-    def get_ai_pre(self, data, sender_id=False, answer_id=False, **kwargs):
+    def get_ai_pre(self, data, author_id=False, answer_id=False, **kwargs):
         return False
     
-    def get_ai_post(self, res, sender_id=False, answer_id=False, **kwargs):
+    def get_ai_post(self, res, author_id=False, answer_id=False, **kwargs):
-        res = self.filter_sensitive_words(res)
+        # res = self.filter_sensitive_words(res)
         return res
     
+    def get_ai_system(self, content=None):
+        # 获取基础ai角色设定, role system
+        sys_content = content or self.sys_content
+        if sys_content:
+            return {"role": "system", "content": sys_content}
+        return {}
+    
     def get_ai_model_info(self):
         self.ensure_one()
         headers = {"Content-Type": "application/json", "Authorization": f"Bearer {self.openapi_api_key}"}
@@ -109,19 +171,63 @@ GPT-3	A set of models that can understand and generate natural language
             r_text = 'No response.'
         raise UserError(r_text)
 
-    def get_openai(self, data, sender_id, answer_id, *args):
+    def get_openai(self, data, author_id, answer_id, **kwargs):
         self.ensure_one()
         headers = {"Content-Type": "application/json", "Authorization": f"Bearer {self.openapi_api_key}"}
         R_TIMEOUT = self.ai_timeout or 120
         o_url = self.endpoint or "https://api.openai.com/v1/chat/completions"
-        partner_name = 'odoo'
+
-        # if sender_id:
+        if self.stop:
-        #     partner_name = sender_id.name
+            stop = self.stop.split(',')
+        else:
+            stop = ["Human:", "AI:"]
         # 以下处理 open ai
-        #     获取模型信息
+        if self.ai_model in ['gpt-3.5-turbo', 'gpt-3.5-turbo-0301']:
-        # list_model = requests.get("https://api.openai.com/v1/models", headers=headers)
+            messages = [{"role": "user", "content": data}]
-        # model_info = requests.get("https://api.openai.com/v1/models/%s" % ai_model, headers=headers)
+            # Ai角色设定
-        if self.ai_model == 'dall-e2':
+            sys_content = self.get_ai_system(kwargs.get('sys_content'))
+            if sys_content:
+                messages.insert(sys_content)
+            pdata = {
+                "model": self.ai_model,
+                "messages": messages,
+                "temperature": self.temperature or 0.9,
+                "max_tokens": self.max_tokens or 1000,
+                "top_p": self.top_p or 0.6,
+                "frequency_penalty": self.frequency_penalty or 0.5,
+                "presence_penalty": self.presence_penalty or 0.2,
+                "stop": stop
+            }
+            _logger.warning('=====================open input pdata: %s' % pdata)
+            response = requests.post(o_url, data=json.dumps(pdata), headers=headers, timeout=R_TIMEOUT)
+            try:
+                # todo: 将 res 总结果给 self.get_ai_post，再取实际内容 return，将 tokens 计算写在 post 方法中
+                res = response.json()
+                if 'usage' in res:
+                    usage = res['usage']
+                    prompt_tokens = usage['prompt_tokens']
+                    completion_tokens = usage['completion_tokens']
+                    total_tokens = usage['total_tokens']
+                    vals = {
+                        'human_prompt_tokens': author_id.human_prompt_tokens + prompt_tokens,
+                        'ai_completion_tokens': author_id.ai_completion_tokens + completion_tokens,
+                        'tokens_total': author_id.tokens_total + total_tokens,
+                        'used_number': author_id.used_number + 1,
+                    }
+                    if not author_id.first_ask_time:
+                        ask_date = response.headers.get("Date")
+                        vals.update({
+                            'first_ask_time': ask_date
+                        })
+                    author_id.write(vals)
+                if 'choices' in res:
+                    # for rec in res:
+                    #     res = rec['message']['content']
+                    res = '\n'.join([x['message']['content'] for x in res['choices']])
+                    return res
+            except Exception as e:
+                _logger.warning("Get Response Json failed: %s", e)
+        elif self.ai_model == 'dall-e2':
             # todo: 处理 图像引擎，主要是返回参数到聊天中
             # image_url = response['data'][0]['url']
             # https://platform.openai.com/docs/guides/images/introduction
@@ -131,56 +237,15 @@ GPT-3	A set of models that can understand and generate natural language
                 "size": "1024x1024",
             }
             return '建设中'
-        elif self.ai_model in ['gpt-3.5-turbo', 'gpt-3.5-turbo-0301']:
-            pdata = {
-                "model": self.ai_model,
-                "messages": [{"role": "user", "content": data}],
-                "temperature": 0.9,
-                "max_tokens": self.max_length or 1000,
-                "top_p": 1,
-                "frequency_penalty": 0.0,
-                "presence_penalty": 0.6,
-                "user": partner_name,
-                "stop": ["Human:", "AI:"]
-            }
-            _logger.warning('=====================open input pdata: %s' % pdata)
-            response = requests.post(o_url, data=json.dumps(pdata), headers=headers, timeout=R_TIMEOUT)
-            try:
-                res = response.json()
-                if 'usage' in res:
-                    usage = res['usage']
-                    prompt_tokens = usage['prompt_tokens']
-                    completion_tokens = usage['completion_tokens']
-                    total_tokens = usage['total_tokens']
-                    vals = {
-                        'human_prompt_tokens': sender_id.human_prompt_tokens + prompt_tokens,
-                        'ai_completion_tokens': sender_id.ai_completion_tokens + completion_tokens,
-                        'tokens_total': sender_id.tokens_total + total_tokens,
-                        'used_number': sender_id.used_number + 1,
-                    }
-                    if not sender_id.first_ask_time:
-                        ask_date = response.headers.get("Date")
-                        vals.update({
-                            'first_ask_time': ask_date
-                        })
-                    sender_id.write(vals)
-                if 'choices' in res:
-                    # for rec in res:
-                    #     res = rec['message']['content']
-                    res = '\n'.join([x['message']['content'] for x in res['choices']])
-                    return res
-            except Exception as e:
-                _logger.warning("Get Response Json failed: %s", e)
         else:
             pdata = {
                 "model": self.ai_model,
                 "prompt": data,
                 "temperature": 0.9,
-                "max_tokens": self.max_length or 1000,
+                "max_tokens": self.max_tokens or 1000,
                 "top_p": 1,
                 "frequency_penalty": 0.0,
                 "presence_penalty": 0.6,
-                "user": partner_name,
                 "stop": ["Human:", "AI:"]
             }
             response = requests.post(o_url, data=json.dumps(pdata), headers=headers, timeout=R_TIMEOUT)
@@ -189,9 +254,9 @@ GPT-3	A set of models that can understand and generate natural language
                 res = '\n'.join([x['text'] for x in res['choices']])
                 return res
     
-        return "获取结果超时，请重新跟我聊聊。"
+        return _("Response Timeout, please speak again.")
 
-    def get_azure(self, data, sender_id, answer_id, *args):
+    def get_azure(self, data, author_id, answer_id, **kwargs):
         self.ensure_one()
         # only for azure
         openai.api_type = self.provider
@@ -202,21 +267,29 @@ GPT-3	A set of models that can understand and generate natural language
             raise UserError(_("Please Set your AI robot's API Version first."))
         openai.api_version = self.api_version
         openai.api_key = self.openapi_api_key
-        pdata = {
+        if self.stop:
-            "engine": self.engine,
+            stop = self.stop.split(',')
-            "prompt": data,
+        else:
-            "temperature": self.temperature or 0.9,
+            stop = ["Human:", "AI:"]
-            "max_tokens": self.max_length or 600,
+        if isinstance(data, list):
-            "top_p": 0.5,
+            messages = data
-            "frequency_penalty": 0,
+        else:
-            "presence_penalty": 0,
+            messages = [{"role": "user", "content": data}]
-            "stop": ["Human:", "AI:"],
+        # Ai角色设定
-        }
+        sys_content = self.get_ai_system(kwargs.get('sys_content'))
-        _logger.warning('=====================azure input data: %s' % pdata)
+        if sys_content:
-        response = openai.Completion.create(pdata)
+            messages.insert(sys_content)
-        
+        response = openai.ChatCompletion.create(
+            engine=self.engine,
+            messages=messages,
+            temperature=self.temperature or 0.9,
+            max_tokens=self.max_tokens or 600,
+            top_p=self.top_p or 0.6,
+            frequency_penalty=self.frequency_penalty or 0.5,
+            presence_penalty=self.presence_penalty or 0.2,
+            stop=stop)
         if 'choices' in response:
-            res = response['choices'][0]['text'].replace(' .', '.').strip()
+            res = response['choices'][0]['message']['content'].replace(' .', '.').strip()
             return res
         else:
             _logger.warning('=====================azure output data: %s' % response)

app_chatgpt/models/lib/sensi_words.txt

@@ -977,7 +977,6 @@ GY
 有容奶大
 李总统
 操你媽
-GP
 你的逼……真紧
 GN
 GM
@@ -1412,7 +1411,6 @@ blowjobs
 耶和華
 奶大穴肥多条肉棒难满足
 瞿秋白
-gp
 dong fang chuan shuo
 saga
 藏春阁【全免费】

app_chatgpt/models/mail_channel.py

@@ -14,40 +14,41 @@ _logger = logging.getLogger(__name__)
 class Channel(models.Model):
     _inherit = 'mail.channel'
     
-    @api.model
+    def get_openai_context(self, channel_id, author_id, answer_id, minutes=30):
-    def get_openai_context(self, channel_id, partner_chatgpt, current_prompt, seconds=600):
+        # 上下文处理，要处理群的方式，以及独聊的方式
-        afterTime = fields.Datetime.now() - datetime.timedelta(seconds=seconds)
+        # azure新api 处理
+        context_history = []
+        afterTime = fields.Datetime.now() - datetime.timedelta(minutes=minutes)
         message_model = self.env['mail.message'].sudo()
-        prompt = [f"Human:{current_prompt}\nAI:", ]
+        # 处理消息： 取最新问题 + 上2次的交互，将之前的交互按时间顺序拼接
+        # 注意： ai 每一次回复都有 parent_id 来处理连续性
+        # 私聊处理
         domain = [('res_id', '=', channel_id),
                   ('model', '=', 'mail.channel'),
                   ('message_type', '!=', 'user_notification'),
-                ('parent_id', '=', False),
+                  ('parent_id', '!=', False),
-                ('date', '>=', afterTime),
+                  ('author_id', '=', answer_id.id),
-                ('author_id', '=', self.env.user.partner_id.id)]
+                  ('body', '!=', '<p>%s</p>' % _('Response Timeout, please speak again.'))]
-        messages = message_model.with_context(tz='UTC').search(domain, order="id desc", limit=15)
+        if self.channel_type in ['group', 'channel']:
-        # print('domain:',domain)
+            # 群聊增加时间限制，当前找所有人，不限制 author_id
-        # print('messages:',messages)
+            domain += [('date', '>=', afterTime)]
-        for msg in messages:
+            ai_msg_list = message_model.with_context(tz='UTC').search(domain, order="id desc", limit=2)
-            ai_msg = message_model.search([("res_id", "=", channel_id),
+            for ai_msg in ai_msg_list.sorted(key='id'):
-                                           ('model', '=', msg.model),
+                user_content = ai_msg.parent_id.body.replace("<p>", "").replace("</p>", "")
-                                           ('parent_id', '=', msg.id),
+                ai_content = ai_msg.body.replace("<p>", "").replace("</p>", "")
-                                           ('author_id', '=', partner_chatgpt),
+                context_history.append({
-                                           ('body', '!=', '<p>获取结果超时，请重新跟我聊聊。</p>')])
+                    'role': 'user',
-            if ai_msg:
+                    'content': user_content,
-                prompt.append("Human:%s\nAI:%s" % (
+                }, {
-                msg.body.replace("<p>", "").replace("</p>", ""), ai_msg.body.replace("<p>", "").replace("</p>", "")))
+                    'role': 'assistant',
-                # print(msg.body.replace("<p>", "").replace("</p>", ""))
+                    'content': ai_content,
-                # print(ai_msg.body.replace("<p>", "").replace("</p>", ""))
+                })
-            else:
+        return context_history
-                _logger.error(f"not find for id:{str(msg.id)}")
 
-        return '\n'.join(prompt[::-1])
+    def get_ai_response(self, ai, messages, channel, user_id, message):
-
+        author_id = message.create_uid.partner_id
-    def get_ai(self, ai, prompt, partner_name, channel, user_id, message):
-        sender_id = message.create_uid.partner_id
         answer_id = user_id.partner_id
-        res = ai.get_ai(prompt, sender_id, answer_id)
+        res = ai.get_ai(messages, author_id, answer_id)
         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)
@@ -55,21 +56,21 @@ class Channel(models.Model):
     def _notify_thread(self, message, msg_vals=False, **kwargs):
         rdata = super(Channel, self)._notify_thread(message, msg_vals=msg_vals, **kwargs)
         # print(f'rdata:{rdata}')
-        to_partner_id = self.env['res.partner']
+        answer_id = self.env['res.partner']
         user_id = self.env['res.users']
         author_id = msg_vals.get('author_id')
         ai = self.env['ai.robot']
         channel_type = self.channel_type
         if channel_type == 'chat':
             channel_partner_ids = self.channel_partner_ids
-            to_partner_id = channel_partner_ids - message.author_id
+            answer_id = channel_partner_ids - message.author_id
-            user_id = to_partner_id.mapped('user_ids').filtered(lambda r: r.gpt_id)[:1]
+            user_id = answer_id.mapped('user_ids').filtered(lambda r: r.gpt_id)[:1]
-            if user_id and to_partner_id.gpt_id:
+            if user_id and answer_id.gpt_id:
                 gpt_policy = user_id.gpt_policy
                 gpt_wl_users = user_id.gpt_wl_users
                 is_allow = message.create_uid.id in gpt_wl_users.ids
                 if gpt_policy == 'all' or (gpt_policy == 'limit' and is_allow):
-                    ai = to_partner_id.gpt_id
+                    ai = answer_id.gpt_id
 
         elif channel_type in ['group', 'channel']:
             # partner_ids = @ ids
@@ -82,16 +83,16 @@ class Channel(models.Model):
                     gpt_policy = user_id.gpt_policy
                     gpt_wl_users = user_id.gpt_wl_users
                     is_allow = message.create_uid.id in gpt_wl_users.ids
-                    to_partner_id = user_id.partner_id
+                    answer_id = user_id.partner_id
                     if gpt_policy == 'all' or (gpt_policy == 'limit' and is_allow):
                         ai = user_id.gpt_id
 
         chatgpt_channel_id = self.env.ref('app_chatgpt.channel_chatgpt')
 
-        prompt = msg_vals.get('body')
+        msg = msg_vals.get('body')
         # print('prompt:', prompt)
         # print('-----')
-        if not prompt:
+        if not msg:
             return rdata
         # api_key = self.env['ir.config_parameter'].sudo().get_param('app_chatgpt.openapi_api_key')
         api_key = ''
@@ -106,48 +107,36 @@ class Channel(models.Model):
             openapi_context_timeout = 600
         sync_config = self.env['ir.config_parameter'].sudo().get_param('app_chatgpt.openai_sync_config')
         openai.api_key = api_key
-        partner_name = ''
         # print(msg_vals)
         # print(msg_vals.get('record_name', ''))
         # print('self.channel_type :',self.channel_type)
         if ai:
-            if author_id != to_partner_id.id and self.channel_type == 'chat':
+            if author_id != answer_id.id and self.channel_type == 'chat':
-                _logger.info(f'私聊:author_id:{author_id},partner_chatgpt.id:{to_partner_id.id}')
+                _logger.info(f'私聊:author_id:{author_id},partner_chatgpt.id:{answer_id.id}')
                 try:
                     channel = self.env[msg_vals.get('model')].browse(msg_vals.get('res_id'))
                     # if ai_model not in ['gpt-3.5-turbo', 'gpt-3.5-turbo-0301']:
-                    prompt = self.get_openai_context(channel.id, to_partner_id.id, prompt, openapi_context_timeout)
+                    messages = [{"role": "user", "content": msg}]
-                    print(prompt)
+                    c_history = self.get_openai_context(channel.id, author_id, answer_id, openapi_context_timeout)
+                    if c_history:
+                        messages.insert(0, c_history)
                     if sync_config == 'sync':
-                        self.get_ai(ai, prompt, partner_name, channel, user_id, message)
+                        self.get_ai_response(ai, messages, channel, user_id, message)
                     else:
-                        self.with_delay().get_ai(ai, prompt, partner_name, channel, user_id, message)
+                        self.with_delay().get_ai_response(ai, messages, channel, user_id, message)
-                    # res = ai.get_ai(prompt, partner_name)
-                    # res = res.replace('\n', '<br/>')
-                    # print('res:',res)
-                    # print('channel:',channel)
-                    # channel.with_user(user_id).message_post(body=res, message_type='comment',subtype_xmlid='mail.mt_comment', parent_id=message.id)
-                    # channel.with_user(user_chatgpt).message_post(body=res, message_type='notification', subtype_xmlid='mail.mt_comment')
-                    # channel.sudo().message_post(
-                    #     body=res,
-                    #     author_id=partner_chatgpt.id,
-                    #     message_type="comment",
-                    #     subtype_xmlid="mail.mt_comment",
-                    # )
-                    # self.with_user(user_chatgpt).message_post(body=res, message_type='comment', subtype_xmlid='mail.mt_comment')
                 except Exception as e:
                     raise UserError(_(e))
-            elif author_id != to_partner_id.id and msg_vals.get('model', '') == 'mail.channel' and msg_vals.get('res_id', 0) == chatgpt_channel_id.id:
+            elif author_id != answer_id.id and msg_vals.get('model', '') == 'mail.channel' and msg_vals.get('res_id', 0) == chatgpt_channel_id.id:
-                _logger.info(f'频道群聊:author_id:{author_id},partner_chatgpt.id:{to_partner_id.id}')
+                _logger.info(f'频道群聊:author_id:{author_id},partner_chatgpt.id:{answer_id.id}')
                 try:
-                    prompt = self.get_openai_context(chatgpt_channel_id.id, to_partner_id.id, prompt, openapi_context_timeout)
+                    messages = [{"role": "user", "content": msg}]
+                    c_history = self.get_openai_context(chatgpt_channel_id.id, author_id, answer_id, openapi_context_timeout)
+                    if c_history:
+                        messages.insert(0, c_history)
                     if sync_config == 'sync':
-                        self.get_ai(ai, prompt, 'odoo', chatgpt_channel_id, user_id, message)
+                        self.get_ai_response(ai, messages, chatgpt_channel_id, user_id, message)
                     else:
-                        self.with_delay().get_ai(ai, prompt, 'odoo', chatgpt_channel_id, user_id, message)
+                        self.with_delay().get_ai(ai, messages, chatgpt_channel_id, user_id, message)
-                    # res = ai.get_ai(prompt, 'odoo')
-                    # res = res.replace('\n', '<br/>')
-                    # chatgpt_channel_id.with_user(user_id).message_post(body=res, message_type='comment', subtype_xmlid='mail.mt_comment', parent_id=message.id)
                 except Exception as e:
                     raise UserError(_(e))
 

app_chatgpt/views/ai_robot_views.xml

@@ -10,7 +10,7 @@
                 <field name="provider" optional="hide"/>
                 <field name="ai_model" optional="show"/>
                 <field name="openapi_api_key" password="True"/>
-                <field name="max_length" optional="show"/>
+                <field name="max_tokens" optional="show"/>
                 <field name="temperature"/>
             </tree>
         </field>
@@ -26,12 +26,19 @@
                     <button string="Get Model Info" type="object" name="get_ai_model_info"/>
                 </header>
                 <sheet>
+                    <div class="oe_title">
+                        <label for="name"/>
+                        <h1>
+                            <field name="name" placeholder="Robot Name" required="1"/>
+                        </h1>
+                    </div>
                     <group>
                         <group>
-                            <field name="name"/>
                             <field name="openapi_api_key" password="True" required="True"/>
                             <field name="temperature"/>
-                            <field name="sequence"/>
+                            <field name="top_p"/>
+                            <field name="frequency_penalty"/>
+                            <field name="presence_penalty"/>
                         </group>
                         <group>
                             <field name="ai_model"/>
@@ -42,11 +49,12 @@
                                 <field name="provider"/>
                                 <a href="https://platform.openai.com/docs/introduction" title="OpenAI Document" class="o_doc_link" target="_blank"></a>
                             </div>
-                            <field name="max_length"/>
+                            <field name="max_tokens"/>
                             <field name="engine"/>
                             <field name="endpoint"/>
                             <field name="api_version"/>
                             <field name="ai_timeout"/>
+                            <field name="sequence"/>
                         </group>
                         <group>
                             <field name="is_filtering"/>