base init v17, 很多只改了版号，没验证

app_chatgpt/models/ai_robot.py

@@ -0,0 +1,412 @@
+# -*- coding: utf-8 -*-
+
+import openai.openai_object
+import requests, json
+import openai
+import base64
+
+from odoo import api, fields, models, modules, tools, _
+from odoo.exceptions import UserError
+
+import logging
+_logger = logging.getLogger(__name__)
+
+
+class AiRobot(models.Model):
+    _name = 'ai.robot'
+    _description = 'Ai Robot'
+    _order = 'sequence, name'
+
+    name = fields.Char(string='Name', translate=True, required=True)
+    provider = fields.Selection(string="AI Provider", selection=[('openai', 'OpenAI'), ('azure', 'Azure')],
+                                required=True, default='openai', change_default=True)
+    # update ai_robot set ai_model=set_ai_model
+    ai_model = fields.Char(string="AI Model", required=True, default='auto', help='Customize input')
+    set_ai_model = fields.Selection(string="Quick Set Model", selection=[
+        ('gpt-3.5-turbo-0613', 'gpt-3.5-turbo-0613(Default and Latest)'),
+        ('gpt-3.5-turbo-16k-0613', 'gpt-3.5-turbo-16k-0613(Big text)'),
+        ('gpt-4', 'Chatgpt 4'),
+        ('gpt-4-32k', 'Chatgpt 4 32k'),
+        ('gpt-3.5-turbo', 'Chatgpt 3.5 Turbo'),
+        ('gpt-3.5-turbo-0301', 'Chatgpt 3.5 Turbo on 20230301'),
+        ('text-davinci-003', 'Chatgpt 3 Davinci'),
+        ('code-davinci-002', 'Chatgpt 2 Code Optimized'),
+        ('text-davinci-002', 'Chatgpt 2 Davinci'),
+        ('dall-e2', 'Dall-E Image'),
+    ], default='gpt-3.5-turbo-0613',
+                                help="""
+GPT-4: Can understand Image, generate natural language or code.
+GPT-3.5: A set of models that improve on GPT-3 and can understand as well as generate natural language or code
+DALL·E: A model that can generate and edit images given a natural language prompt
+Whisper: A model that can convert audio into text
+Embeddings:	A set of models that can convert text into a numerical form
+CodexLimited: A set of models that can understand and generate code, including translating natural language to code
+Moderation: A fine-tuned model that can detect whether text may be sensitive or unsafe
+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")
+    # 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：0-2，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：0-1，语言连贯性，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：-2~2，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：-2~2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=1,
+                               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=1,
+                                     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.
+                                     """)
+    # 越大模型就趋向于生成更新的话题，惩罚已经出现过的文本
+    presence_penalty = fields.Float('Presence penalty', default=1,
+                                    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')
+    ai_timeout = fields.Integer('Timeout(seconds)', help="Connect timeout for Ai response", default=120)
+    sequence = fields.Integer('Sequence', help="Determine the display order", default=10)
+    sensitive_words = fields.Text('Sensitive Words Plus', help='Sensitive word filtering. Separate keywords with a carriage return.')
+    is_filtering = fields.Boolean('Filter Sensitive Words', default=False, help='Use base Filter in dir models/lib/sensi_words.txt')
+
+    max_send_char = fields.Integer('Max Send Char', help='Max Send Prompt Length', default=8000)
+    image_avatar = fields.Image('Avatar')
+    partner_ids = fields.One2many('res.partner', 'gpt_id', string='Partner')
+    partner_count = fields.Integer('#Partner', compute='_compute_partner_count', store=False)
+    active = fields.Boolean('Active', default=True)
+
+    def _compute_partner_count(self):
+        for rec in self:
+            rec.partner_count = len(rec.partner_ids)
+
+    def action_disconnect(self):
+        requests.delete('https://chatgpt.com/v1/disconnect')
+
+    def get_ai_pre(self, data, author_id=False, answer_id=False, param={}):
+        # hook，都正常
+        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, usage, is_ai = self.get_ai_post(res, author_id, answer_id,  param)
+        return res_post, usage, is_ai
+
+    def get_ai_origin(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, usage, is_ai = self.get_ai_post(res, author_id, answer_id, param)
+        return res
+    
+    def get_ai_post(self, res, author_id=False, answer_id=False, param={}):
+        # hook，高级版要替代
+        if res and author_id and isinstance(res, openai.openai_object.OpenAIObject) or isinstance(res, list) or isinstance(res, dict):
+            # 返回是个对象，那么就是ai
+            # if isinstance(res, dict):
+            if self.provider == 'openai':
+                # openai 格式处理
+                usage = res['usage']
+                content = res['choices'][0]['message']['content']
+                # _logger.warning('===========Ai响应:%s' % content)
+            elif self.provider == 'azure':
+                # azure 格式
+                usage = json.loads(json.dumps(res['usage']))
+                content = json.loads(json.dumps(res['choices'][0]['message']['content']))
+            else:
+                usage = False
+                content = res
+            data = content.replace(' .', '.').strip()
+            return data, usage, True
+        else:
+            # 直接返回错误语句，那么就是非ai
+            return res, False, False
+    
+    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}"}
+        R_TIMEOUT = self.ai_timeout or 120
+        o_url = "https://api.openai.com/v1/models/%s" % self.ai_model
+        if self.endpoint:
+            o_url = self.endpoint.replace("/chat/completions", "") + "/models/%s" % self.ai_model
+        
+        response = requests.get(o_url, headers=headers, timeout=R_TIMEOUT)
+        response.close()
+        if response:
+            res = response.json()
+            r_text = json.dumps(res, indent=2)
+        else:
+            r_text = 'No response.'
+        raise UserError(r_text)
+
+    def get_ai_list_model(self):
+        self.ensure_one()
+        headers = {"Content-Type": "application/json", "Authorization": f"Bearer {self.openapi_api_key}"}
+        R_TIMEOUT = self.ai_timeout or 120
+        o_url = "https://api.openai.com/v1/models"
+        if self.endpoint:
+            o_url = self.endpoint.replace("/chat/completions", "") + "/models"
+        response = requests.get(o_url, headers=headers, timeout=R_TIMEOUT)
+        response.close()
+        if response:
+            res = response.json()
+            r_text = json.dumps(res, indent=2)
+        else:
+            r_text = 'No response.'
+        raise UserError(r_text)
+
+    def get_openai(self, data, author_id, answer_id, param={}):
+        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"
+
+        # 处理传参，传过来的优先于 robot 默认的
+        max_tokens = param.get('max_tokens') if param.get('max_tokens') else self.max_tokens
+        temperature = param.get('temperature') if param.get('temperature') else self.temperature
+        top_p = param.get('top_p') if param.get('top_p') else self.top_p
+        frequency_penalty = param.get('frequency_penalty') if param.get('frequency_penalty') else self.frequency_penalty
+        presence_penalty = param.get('presence_penalty') if param.get('presence_penalty') else self.presence_penalty
+        request_timeout = param.get('request_timeout') if param.get('request_timeout') else self.ai_timeout
+        
+        if self.stop:
+            stop = self.stop.split(',')
+        else:
+            stop = ["Human:", "AI:"]
+        # 以下处理 open ai
+        if self.ai_model in ['gpt-3.5-turbo', 'gpt-3.5-turbo-0301']:
+            # 基本与 azure 同，要处理 api_base
+            openai.api_key = self.openapi_api_key
+            openai.api_base = o_url.replace('/chat/completions', '')
+            if isinstance(data, list):
+                messages = data
+            else:
+                messages = [{"role": "user", "content": data}]
+            # Ai角色设定，如果没设定则再处理
+            if messages[0].get('role') != 'system':
+                sys_content = self.get_ai_system(param.get('sys_content'))
+                if sys_content:
+                    messages.insert(0, sys_content)
+            # todo: 当前反向代理方式不通，要调整为 远程主机中接受请求，post到openai，再将结果返回给请求者
+            # response = openai.ChatCompletion.create(
+            #     model=self.ai_model,
+            #     messages=messages,
+            #     # 返回的回答数量
+            #     n=1,
+            #     max_tokens=max_tokens,
+            #     temperature=temperature,
+            #     top_p=top_p,
+            #     frequency_penalty=frequency_penalty,
+            #     presence_penalty=presence_penalty,
+            #     stop=stop,
+            #     request_timeout=request_timeout,
+            # )
+            # if 'choices' in response:
+            #     return response
+            # todo: 两种方式一样，要调整 v 服务器的二次处理 /root/toai.py
+            pdata = {
+                "model": self.ai_model,
+                "messages": messages,
+                "max_tokens": max_tokens,
+                "temperature": temperature,
+                "top_p": top_p,
+                "frequency_penalty": frequency_penalty,
+                "presence_penalty": presence_penalty,
+                "stop": stop
+            }
+            response = requests.post(o_url, data=json.dumps(pdata), headers=headers, timeout=R_TIMEOUT)
+            try:
+                res = response.json()
+                if 'choices' in res:
+                    return res
+            except Exception as e:
+                _logger.warning("Get Response Json failed: %s", e)
+            else:
+                _logger.warning('=====================Openai output data: %s' % response.json())
+        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
+            pdata = {
+                "prompt": data,
+                "n": 3,
+                "size": "1024x1024",
+            }
+            return '建设中'
+        else:
+            pdata = {
+                "model": self.ai_model,
+                "prompt": data,
+                "temperature": 1,
+                "max_tokens": max_tokens,
+                "top_p": 0.6,
+                "frequency_penalty": 0.1,
+                "presence_penalty": 0.1,
+                "stop": stop
+            }
+            response = openai.ChatCompletion.create(
+                model=self.ai_model,
+                messages=data
+            )
+            # response = requests.post(o_url, data=json.dumps(pdata), headers=headers, timeout=R_TIMEOUT)
+            if 'choices' in response:
+                return response
+            else:
+                _logger.warning('=====================openai output data: %s' % response.json())
+    
+        return _("Response Timeout, please speak again.")
+
+    def get_azure(self, data, author_id, answer_id, param={}):
+        self.ensure_one()
+        # only for azure
+        openai.api_type = self.provider
+        if not self.endpoint:
+            raise UserError(_("Please Set your AI robot's endpoint first."))
+        openai.api_base = self.endpoint
+        if not self.api_version:
+            raise UserError(_("Please Set your AI robot's API Version first."))
+        openai.api_version = self.api_version
+        openai.api_key = self.openapi_api_key
+        if self.stop:
+            stop = self.stop.split(',')
+        else:
+            stop = ["Human:", "AI:"]
+        if isinstance(data, list):
+            messages = data
+        else:
+            messages = [{"role": "user", "content": data}]
+
+        # 处理传参，传过来的优先于 robot 默认的
+        max_tokens = param.get('max_tokens') if param.get('max_tokens') else self.max_tokens
+        temperature = param.get('temperature') if param.get('temperature') else self.temperature
+        top_p = param.get('top_p') if param.get('top_p') else self.top_p
+        frequency_penalty = param.get('frequency_penalty') if param.get('frequency_penalty') else self.frequency_penalty
+        presence_penalty = param.get('presence_penalty') if param.get('presence_penalty') else self.presence_penalty
+        request_timeout= param.get('request_timeout') if param.get('request_timeout') else self.ai_timeout
+
+        # Ai角色设定，如果没设定则再处理
+        if messages[0].get('role') != 'system':
+            sys_content = self.get_ai_system(param.get('sys_content'))
+            if sys_content:
+                messages.insert(0, sys_content)
+        #         暂时不变
+        response = openai.ChatCompletion.create(
+            engine=self.engine,
+            messages=messages,
+            # 返回的回答数量
+            n=1,
+            max_tokens=max_tokens,
+            temperature=temperature,
+            top_p=top_p,
+            frequency_penalty=frequency_penalty,
+            presence_penalty=presence_penalty,
+            stop=None,
+            request_timeout=request_timeout,
+        )
+        if 'choices' in response:
+            return response
+        else:
+            _logger.warning('=====================azure output data: %s' % response.json())
+        return _("Response Timeout, please speak again.")
+
+    @api.onchange('provider')
+    def _onchange_provider(self):
+        if self.provider == 'openai':
+            self.endpoint = 'https://api.openai.com/v1/chat/completions'
+        elif self.provider == 'azure':
+            self.endpoint = 'https://odoo.openai.azure.com'
+            
+        if self.provider:
+            # 取头像
+            module_path = modules.get_module_path('app_chatgpt', display_warning=False)
+            if module_path:
+                path = modules.check_resource_path(module_path, ('static/description/src/%s.png' % self.provider))
+                if path:
+                    image_file = tools.file_open(path, 'rb')
+                    self.image_avatar = base64.b64encode(image_file.read())
+            
+    @api.onchange('set_ai_model')
+    def _onchange_set_ai_model(self):
+        if self.set_ai_model:
+            self.ai_model = self.set_ai_model
+        else:
+            self.ai_model = None