mirror of
https://github.com/guohuadeng/app-odoo.git
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162 lines
7.1 KiB
Python
162 lines
7.1 KiB
Python
# -*- coding: utf-8 -*-
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import requests,json
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import openai
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from odoo import api, fields, models, _
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from odoo.exceptions import UserError
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from .lib.WordsSearch import WordsSearch
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import logging
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_logger = logging.getLogger(__name__)
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class AiRobot(models.Model):
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_name = 'ai.robot'
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_description = 'Gpt Robot'
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_order = 'sequence, name'
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name = fields.Char(string='Name', translate=True, required=True)
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provider = fields.Selection(string="AI Provider", selection=[('openai', 'OpenAI'), ('azure', 'Azure')], required=True, default='openai')
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ai_model = fields.Selection(string="AI Model", selection=[
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('gpt-4', 'Chatgpt 4'),
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('gpt-3.5-turbo', 'Chatgpt 3.5 Turbo'),
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('gpt-3.5-turbo-0301', 'Chatgpt 3.5 Turbo on 20230301'),
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('text-davinci-003', 'Chatgpt 3 Davinci'),
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('code-davinci-002', 'Chatgpt 2 Code Optimized'),
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('text-davinci-002', 'Chatgpt 2 Davinci'),
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('dall-e2', 'Dall-E Image'),
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], required=True, default='gpt-3.5-turbo',
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help="""
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GPT-4: Can understand Image, generate natural language or code.
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GPT-3.5: A set of models that improve on GPT-3 and can understand as well as generate natural language or code
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DALL·E: A model that can generate and edit images given a natural language prompt
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Whisper: A model that can convert audio into text
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Embeddings: A set of models that can convert text into a numerical form
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CodexLimited: A set of models that can understand and generate code, including translating natural language to code
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Moderation: A fine-tuned model that can detect whether text may be sensitive or unsafe
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GPT-3 A set of models that can understand and generate natural language
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""")
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openapi_api_key = fields.Char(string="API Key", help="Provide the API key here")
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temperature = fields.Float(string='Temperature', default=0.9)
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max_length = fields.Integer('Max Length', default=300)
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endpoint = fields.Char('End Point', default='https://api.openai.com/v1/chat/completions')
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engine = fields.Char('Engine', help='If use Azure, Please input the Model deployment name.')
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api_version = fields.Char('API Version', default='2022-12-01')
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sequence = fields.Integer('Sequence', help="Determine the display order", default=10)
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sensitive_words = fields.Text('Sensitive Words', help='Sensitive word filtering. Separate keywords with a carriage return.')
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is_filtering = fields.Boolean('Filter Sensitive Words', default=False)
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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, partner_name='odoo', *args):
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# 通用方法
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self.ensure_one()
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if hasattr(self, 'get_%s' % self.provider):
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return getattr(self, 'get_%s' % self.provider)(data, partner_name, *args)
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else:
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return _('No robot provider found')
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def get_openai(self, data, partner_name='odoo', *args):
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self.ensure_one()
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headers = {"Content-Type": "application/json", "Authorization": f"Bearer {self.openapi_api_key}"}
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R_TIMEOUT = 300
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o_url = self.endpoint or "https://api.openai.com/v1/chat/completions"
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# 以下处理 open ai
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# 获取模型信息
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# list_model = requests.get("https://api.openai.com/v1/models", headers=headers)
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# model_info = requests.get("https://api.openai.com/v1/models/%s" % ai_model, headers=headers)
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if self.ai_model == 'dall-e2':
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# todo: 处理 图像引擎，主要是返回参数到聊天中
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# image_url = response['data'][0]['url']
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# https://platform.openai.com/docs/guides/images/introduction
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pdata = {
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"prompt": data,
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"n": 3,
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"size": "1024x1024",
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}
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return '建设中'
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elif self.ai_model in ['gpt-3.5-turbo', 'gpt-3.5-turbo-0301']:
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pdata = {
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"model": self.ai_model,
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"messages": [{"role": "user", "content": data}],
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"temperature": 0.9,
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"max_tokens": self.max_length or 1000,
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"top_p": 1,
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"frequency_penalty": 0.0,
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"presence_penalty": 0.6,
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"user": partner_name,
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"stop": ["Human:", "AI:"]
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}
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_logger.warning('=====================open input pdata: %s' % pdata)
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response = requests.post(o_url, data=json.dumps(pdata), headers=headers, timeout=R_TIMEOUT)
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res = response.json()
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if 'choices' in res:
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# for rec in res:
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# res = rec['message']['content']
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res = '\n'.join([x['message']['content'] for x in res['choices']])
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res = self.filter_sensitive_words(res)
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return res
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else:
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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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"max_tokens": self.max_length or 1000,
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"top_p": 1,
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"frequency_penalty": 0.0,
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"presence_penalty": 0.6,
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"user": partner_name,
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"stop": ["Human:", "AI:"]
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}
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response = requests.post(o_url, data=json.dumps(pdata), headers=headers, timeout=R_TIMEOUT)
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res = response.json()
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if 'choices' in res:
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res = '\n'.join([x['text'] for x in res['choices']])
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res = self.filter_sensitive_words(res)
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return res
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return "获取结果超时，请重新跟我聊聊。"
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def get_azure(self, data, partner_name='odoo', *args):
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self.ensure_one()
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# only for azure
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openai.api_type = self.provider
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if not self.endpoint:
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raise UserError(_("Please Set your AI robot's endpoint first."))
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openai.api_base = self.endpoint
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if not self.api_version:
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raise UserError(_("Please Set your AI robot's API Version first."))
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openai.api_version = self.api_version
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openai.api_key = self.openapi_api_key
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response = openai.Completion.create(
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engine=self.engine,
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prompt=data,
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temperature=self.temperature or 0.9,
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max_tokens=self.max_length or 600,
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top_p=0.5,
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frequency_penalty=0,
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presence_penalty=0, stop=["Human:", "AI:"])
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_logger.warning('=====================azure input data: %s' % data)
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if 'choices' in response:
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res = response['choices'][0]['text'].replace(' .', '.').strip()
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res = self.filter_sensitive_words(res)
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return res
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@api.onchange('provider')
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def _onchange_provider(self):
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if self.provider == 'openai':
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self.endpoint = 'https://api.openai.com/v1/chat/completions'
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elif self.provider == 'azure':
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self.endpoint = 'https://odoo.openai.azure.com'
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def filter_sensitive_words(self, data):
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if self.is_filtering:
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search = WordsSearch()
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s = self.sensitive_words
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search.SetKeywords(s.split('\n'))
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result = search.Replace(text=data)
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return result
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