++
This commit is contained in:
jack
@@ -0,0 +1,630 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
import random
|
||||
import sys
|
||||
import uuid
|
||||
|
||||
import httpx
|
||||
|
||||
from odoo import models, fields
|
||||
from . import decode_template
|
||||
|
||||
|
||||
class AlphaIdea(models.Model):
|
||||
_name = 'alpha.idea'
|
||||
_description = 'Alpha Idea'
|
||||
_order = 'id desc'
|
||||
|
||||
name = fields.Char(string='Name', required=True, default=lambda self: str(uuid.uuid4()))
|
||||
|
||||
status = fields.Selection([
|
||||
('draft', 'Draft'),
|
||||
('fetched_data', 'Fetched Data'),
|
||||
('generated_prompt', 'Generated Prompt'),
|
||||
('posted_to_ms', 'Posted To MS'),
|
||||
('llm_received', 'LLM Received'),
|
||||
('decode_template', 'Decode Template'),
|
||||
('decoded', 'Decoded'),
|
||||
('done', 'Done'),
|
||||
('failed', 'Failed'),
|
||||
('cancel', 'Cancel')
|
||||
], string='Status', default='draft')
|
||||
|
||||
pushed = fields.Boolean(string='Pushed', default=False, readonly=True)
|
||||
|
||||
region = fields.Many2one('alpha.region.settings', string='Region', required=True)
|
||||
|
||||
universe = fields.Many2one('alpha.universe.settings', string='Universe', required=True)
|
||||
|
||||
data_type = fields.Selection([('MATRIX', 'MATRIX'), ('VECTOR', 'VECTOR')], string='Data Type', required=True, default='MATRIX')
|
||||
|
||||
delay = fields.Selection([('1', '1'), ('0', '0')], required=True, string='Delay', default='1')
|
||||
|
||||
data_sets = fields.Char(string='Data Sets', compute='_compute_data_sets')
|
||||
|
||||
meta_prompt = fields.Many2one('alpha.prompt.settings', string='Meta Prompt')
|
||||
|
||||
replace_prompt = fields.Text(string='Replace Prompt')
|
||||
|
||||
final_prompt = fields.Text(string='Final Prompt')
|
||||
|
||||
system_prompt = fields.Text(string='System Prompt')
|
||||
|
||||
user_prompt = fields.Text(string='User Prompt')
|
||||
|
||||
llm_generated_idea = fields.Text(string='LLM Generated Idea')
|
||||
|
||||
result_message = fields.Text(string='Result Message')
|
||||
|
||||
llm_settings_line_id = fields.Many2one('llm.settings.line', string='Model', default=lambda self: self._default_llm_settings_line_id())
|
||||
|
||||
def _default_llm_settings_line_id(self):
|
||||
"""默认随机选择一个模型，如果没有则返回 False"""
|
||||
llm_lines = self.env['llm.settings.line'].search([])
|
||||
if llm_lines:
|
||||
return random.choice(llm_lines).id
|
||||
return False
|
||||
|
||||
idea_template_ids = fields.One2many('alpha.idea.template', 'idea_id', string='Idea Templates')
|
||||
needed_data_set_ids = fields.One2many('alpha.needed.data.set', 'idea_id', string='Needed Data Sets')
|
||||
final_expression_ids = fields.One2many('alpha.final.expression', 'idea_id', string='Final Expressions')
|
||||
|
||||
expression_count = fields.Integer(string='Expression Count', required=True, readonly=True, default=0, compute='_compute_expression_count')
|
||||
|
||||
def _compute_data_sets(self):
|
||||
# 显示使用的数据集
|
||||
for record in self:
|
||||
record.data_sets = ''
|
||||
if record.needed_data_set_ids:
|
||||
data_sets_list = []
|
||||
for data_set_name in record.needed_data_set_ids:
|
||||
data_sets_list.append(data_set_name.name)
|
||||
|
||||
if len(data_sets_list) > 0:
|
||||
record.data_sets = ', '.join(data_sets_list)
|
||||
|
||||
def action_cancel(self):
|
||||
self.status = 'cancel'
|
||||
|
||||
def action_reset(self):
|
||||
self.status = 'fetched_data'
|
||||
|
||||
def btn_check_and_fetch_data(self):
|
||||
if not self.needed_data_set_ids:
|
||||
return {
|
||||
'type': 'ir.actions.client',
|
||||
'tag': 'display_notification',
|
||||
'params': {
|
||||
'title': 'No data',
|
||||
'message': 'No data set is needed.',
|
||||
'type': 'danger',
|
||||
'sticky': False,
|
||||
}
|
||||
}
|
||||
|
||||
# TODO: 通过 datasets_id, 查找 datasets 中, 是否存在 datasets_id 的数据, 如果不存在, 则在 datasets 模块中创建一条记录, 然后需要过去手动下载(必须)
|
||||
success = False
|
||||
for dataset in self.needed_data_set_ids:
|
||||
dataset_id = self.env['alpha.datasets'].search(
|
||||
[('datasets_id', '=', dataset.name),
|
||||
('region', '=', self.region.id),
|
||||
('universe', '=', self.universe.id),
|
||||
('delay', '=', self.delay)
|
||||
], limit=1)
|
||||
if not dataset_id:
|
||||
dataset_id = self.env['alpha.datasets'].create({
|
||||
'name': str(uuid.uuid4()),
|
||||
'datasets_id': dataset.name,
|
||||
'region': self.region.id,
|
||||
'universe': self.universe.id,
|
||||
'delay': self.delay,
|
||||
})
|
||||
|
||||
# 创建 dataset_id 的记录之后, 执行一下 dataset_id 的 btn_get_datasets 方法
|
||||
try:
|
||||
dataset_id.btn_get_datasets()
|
||||
success = True
|
||||
except Exception as e:
|
||||
self.status = 'failed'
|
||||
return {
|
||||
'type': 'ir.actions.client',
|
||||
'tag': 'display_notification',
|
||||
'params': {
|
||||
'title': 'Failed',
|
||||
'message': f'Dataset fetch failed: {str(e)}',
|
||||
'type': 'danger',
|
||||
'sticky': False,
|
||||
}
|
||||
}
|
||||
else:
|
||||
if dataset_id.line_ids:
|
||||
success = True
|
||||
else:
|
||||
return {
|
||||
'type': 'ir.actions.client',
|
||||
'tag': 'display_notification',
|
||||
'params': {
|
||||
'title': 'No data',
|
||||
'message': 'Dataset does not exist.',
|
||||
'type': 'danger',
|
||||
'sticky': False,
|
||||
}
|
||||
}
|
||||
|
||||
if success:
|
||||
self.status = 'fetched_data'
|
||||
return True
|
||||
|
||||
def btn_generate_final_prompt(self):
|
||||
if self.final_prompt:
|
||||
self.final_prompt = ''
|
||||
self.system_prompt = ''
|
||||
self.user_prompt = ''
|
||||
self.status = 'fetched_data'
|
||||
return {
|
||||
'type': 'ir.actions.client',
|
||||
'tag': 'display_notification',
|
||||
'params': {
|
||||
'title': '成功',
|
||||
'message': '已清除最终提示词',
|
||||
'type': 'success',
|
||||
'sticky': False,
|
||||
}
|
||||
}
|
||||
|
||||
if not self.meta_prompt:
|
||||
return {
|
||||
'type': 'ir.actions.client',
|
||||
'tag': 'display_notification',
|
||||
'params': {
|
||||
'title': 'No data!',
|
||||
'message': 'Please select the prompt template first.',
|
||||
'type': 'danger',
|
||||
'sticky': False,
|
||||
}
|
||||
}
|
||||
|
||||
if not self.replace_prompt:
|
||||
return {
|
||||
'type': 'ir.actions.client',
|
||||
'tag': 'display_notification',
|
||||
'params': {
|
||||
'title': 'No data!',
|
||||
'message': 'Research direction cannot be empty.',
|
||||
'type': 'danger',
|
||||
'sticky': False,
|
||||
}
|
||||
}
|
||||
|
||||
system_prompt = '''You are executing two skills in sequence:
|
||||
1) brain-data-feature-engineering
|
||||
2) brain-feature-implementation
|
||||
The following SKILL.md documents are authoritative; follow them exactly.
|
||||
'''
|
||||
|
||||
data_sets_list = []
|
||||
dataset_id = ''
|
||||
category = ''
|
||||
region = self.region.name
|
||||
delay = self.delay
|
||||
universe = self.universe.name
|
||||
|
||||
for dataset in self.needed_data_set_ids:
|
||||
datasets_id = self.env['alpha.datasets'].search(
|
||||
[('datasets_id', '=', dataset.name)], limit=1)
|
||||
for datasets_line in datasets_id.line_ids:
|
||||
data_sets_list.append({
|
||||
'id': datasets_line.data_field_name,
|
||||
'description': datasets_line.description
|
||||
})
|
||||
|
||||
if not dataset_id:
|
||||
dataset_id = datasets_line.dataset_id
|
||||
|
||||
if not category:
|
||||
category = datasets_line.category_name
|
||||
|
||||
if not data_sets_list:
|
||||
return {
|
||||
'type': 'ir.actions.client',
|
||||
'tag': 'display_notification',
|
||||
'params': {
|
||||
'title': 'No data!',
|
||||
'message': 'No related dataset found.',
|
||||
'type': 'danger',
|
||||
'sticky': False,
|
||||
}
|
||||
}
|
||||
|
||||
field_count = len(data_sets_list)
|
||||
|
||||
operator_ids = self.env['alpha.operator.line'].search([])
|
||||
operator_list = []
|
||||
for operator in operator_ids:
|
||||
operator_list.append({
|
||||
'name': operator.name,
|
||||
'category': operator.category,
|
||||
'scope': operator.scope,
|
||||
'description': operator.description,
|
||||
'definition': operator.definition
|
||||
})
|
||||
|
||||
if not operator_list:
|
||||
return {
|
||||
'type': 'ir.actions.client',
|
||||
'tag': 'display_notification',
|
||||
'params': {
|
||||
'title': 'No data!',
|
||||
'message': 'No related Operator found.',
|
||||
'type': 'danger',
|
||||
'sticky': False,
|
||||
}
|
||||
}
|
||||
|
||||
fields_json = ','.join([str(field) for field in data_sets_list])
|
||||
|
||||
user_prompt = '''{
|
||||
"instructions": {
|
||||
"output_format": "Fill OUTPUT_TEMPLATE.md with concrete content.",
|
||||
"implementation_examples": "Each Implementation Example must be a template with {variable} placeholders. Use only placeholders from allowed_placeholders. Use suffix-only names; do not include dataset code/prefix/horizon.",
|
||||
"no_code_fences": true,
|
||||
"do_not_invent_placeholders": true
|
||||
},
|
||||
"dataset_context": {
|
||||
"dataset_id": "''' + dataset_id + '''",
|
||||
"dataset_name": null,
|
||||
"dataset_description": null,
|
||||
"category": "''' + category + '''",
|
||||
"region": "''' + region + '''",
|
||||
"delay": ''' + str(delay) + ''',
|
||||
"universe": "''' + universe + '''",
|
||||
"field_count": ''' + str(field_count) + '''
|
||||
},
|
||||
"fields": [
|
||||
''' + fields_json + '''
|
||||
]
|
||||
}
|
||||
'''
|
||||
|
||||
final_prompt = self.meta_prompt.prompt
|
||||
final_prompt = final_prompt.replace(
|
||||
'###question_driven###', self.replace_prompt)
|
||||
final_prompt = final_prompt.replace('###dataset_id###', dataset_id)
|
||||
final_prompt = final_prompt.replace('###category###', category)
|
||||
final_prompt = final_prompt.replace('###region###', region)
|
||||
final_prompt = final_prompt.replace('###delay###', str(delay))
|
||||
final_prompt = final_prompt.replace(
|
||||
'###field_count###', str(field_count))
|
||||
final_prompt = final_prompt.replace('###universe###', universe)
|
||||
final_prompt = final_prompt.replace(
|
||||
'###datasets###', str(data_sets_list))
|
||||
final_prompt = final_prompt.replace(
|
||||
'###operators###', str(operator_list))
|
||||
|
||||
if self.data_type and self.data_type.upper() == "VECTOR":
|
||||
vector_prompt = "since all the following the data is vector type data, before you do any process, you should choose a vector operator to generate its statistical feature to use, the data cannot be directly use. for example, if datafieldA and datafieldB are vector type data, you can use vec_avg(datafieldA) - vec_avg(datafieldB), where vec_avg() operator is used to generate the average of the data on a certain date. similarly, vector type operator can only be used on the vector type operator directly and cannot be nested, for example vec_avg(vec_sum(datafield)) is a false use."
|
||||
final_prompt = final_prompt.replace(
|
||||
'###vector_instruction###', vector_prompt)
|
||||
else:
|
||||
final_prompt = final_prompt.replace('###vector_instruction###', '')
|
||||
|
||||
self.system_prompt = system_prompt
|
||||
self.user_prompt = user_prompt
|
||||
self.final_prompt = final_prompt
|
||||
|
||||
self.status = 'generated_prompt'
|
||||
|
||||
return {
|
||||
'type': 'ir.actions.client',
|
||||
'tag': 'display_notification',
|
||||
'params': {
|
||||
'title': '成功',
|
||||
'message': f'已生成提示模板，包含 {field_count} 个数据字段',
|
||||
'type': 'success',
|
||||
'sticky': False,
|
||||
}
|
||||
}
|
||||
|
||||
def post_to_ms(self):
|
||||
if not all([self.final_prompt, self.user_prompt, self.system_prompt]):
|
||||
return {
|
||||
'type': 'ir.actions.client',
|
||||
'tag': 'display_notification',
|
||||
'params': {
|
||||
'title': 'Error',
|
||||
'message': 'Please generate a prompt template.',
|
||||
'type': 'danger',
|
||||
'sticky': False,
|
||||
}
|
||||
}
|
||||
|
||||
if not self.llm_settings_line_id:
|
||||
return {
|
||||
'type': 'ir.actions.client',
|
||||
'tag': 'display_notification',
|
||||
'params': {
|
||||
'title': 'Error',
|
||||
'message': 'Please select a model.',
|
||||
'type': 'danger',
|
||||
'sticky': False,
|
||||
}
|
||||
}
|
||||
|
||||
model_name = self.llm_settings_line_id.model_name
|
||||
base_url = self.llm_settings_line_id.llm_setting_id.base_url
|
||||
api_key = self.llm_settings_line_id.llm_setting_id.api_key
|
||||
|
||||
# 获取当前 record_id
|
||||
record_id = self.id
|
||||
|
||||
# 获取 Odoo 回调地址
|
||||
base_url_odoo = self.env['ir.config_parameter'].sudo().get_param('web.base.url')
|
||||
callback_url = f"{base_url_odoo}/api/alpha-idea/result"
|
||||
|
||||
# 组装完整 prompt
|
||||
full_prompt = f"{self.system_prompt}\n\n{self.user_prompt}\n\n{self.final_prompt}"
|
||||
|
||||
# 获取微服务配置
|
||||
ms_config = self.get_ms_config()
|
||||
ms_url = ms_config.get('url', '')
|
||||
if not ms_url:
|
||||
return {
|
||||
'type': 'ir.actions.client',
|
||||
'tag': 'display_notification',
|
||||
'params': {
|
||||
'title': 'Error',
|
||||
'message': 'Microservice address not configured.',
|
||||
'type': 'danger',
|
||||
'sticky': False
|
||||
}
|
||||
}
|
||||
|
||||
# 组装请求数据
|
||||
payload = {
|
||||
'record_id': record_id,
|
||||
'prompt': full_prompt,
|
||||
'model_name': model_name,
|
||||
'base_url': base_url,
|
||||
'api_key': api_key,
|
||||
'callback_url': callback_url,
|
||||
'system_prompt': self.system_prompt,
|
||||
'user_prompt': self.user_prompt,
|
||||
'final_prompt': self.final_prompt,
|
||||
}
|
||||
|
||||
# 发送请求到微服务
|
||||
try:
|
||||
httpx.post(f"{ms_url}:32004/api_alpha_generate_idea",
|
||||
json=payload, timeout=0.001)
|
||||
except httpx.TimeoutException:
|
||||
pass
|
||||
except Exception as e:
|
||||
self.status = 'failed'
|
||||
return {
|
||||
'type': 'ir.actions.client',
|
||||
'tag': 'display_notification',
|
||||
'params': {
|
||||
'title': 'Error',
|
||||
'message': f'Failed to send microservice:\n{e}.',
|
||||
'type': 'danger',
|
||||
'sticky': False,
|
||||
}
|
||||
}
|
||||
|
||||
self.status = 'posted_to_ms'
|
||||
|
||||
def get_ms_config(self):
|
||||
# TODO 先从 nacos 获取微服务 url
|
||||
nacos_url = ''
|
||||
|
||||
platform_info = sys.platform
|
||||
if platform_info == "darwin":
|
||||
nacos_url = 'http://192.168.31.41:30848/nacos/v1/cs/configs?dataId=microservices_dev&group=quantify'
|
||||
elif platform_info.startswith("linux"):
|
||||
nacos_url = 'http://192.168.31.41:30848/nacos/v1/cs/configs?dataId=microservices&group=quantify'
|
||||
|
||||
try:
|
||||
ms_config_resp = httpx.get(nacos_url)
|
||||
ms_config_resp.raise_for_status()
|
||||
except Exception as e:
|
||||
return {
|
||||
'type': 'ir.actions.client',
|
||||
'tag': 'display_notification',
|
||||
'params': {
|
||||
'title': 'Error',
|
||||
'message': f'Nacos request failed:\n{e}.',
|
||||
'type': 'danger',
|
||||
'sticky': False,
|
||||
}
|
||||
}
|
||||
|
||||
ms_config = ms_config_resp.json()
|
||||
|
||||
return ms_config
|
||||
|
||||
def action_set_llm_received(self):
|
||||
"""手动设置 LLM 已返回状态
|
||||
当手动录入 llm_generated_idea 后，调用此函数将状态改为 llm_received
|
||||
"""
|
||||
if self.llm_generated_idea and self.status == 'generated_prompt':
|
||||
self.status = 'llm_received'
|
||||
return True
|
||||
else:
|
||||
return {
|
||||
'type': 'ir.actions.client',
|
||||
'tag': 'display_notification',
|
||||
'params': {
|
||||
'title': 'Error',
|
||||
'message': 'llm_generated_idea 无数据或状态不是 Generated Prompt',
|
||||
'type': 'danger',
|
||||
'sticky': False,
|
||||
}
|
||||
}
|
||||
|
||||
def decode_template(self):
|
||||
if not self.llm_generated_idea or self.status != 'llm_received':
|
||||
return {
|
||||
'type': 'ir.actions.client',
|
||||
'tag': 'display_notification',
|
||||
'params': {
|
||||
'title': 'Please use llm to generate the template first.',
|
||||
'message': 'llm_generated_idea no data or status != llm_received',
|
||||
'type': 'danger',
|
||||
'sticky': False,
|
||||
}
|
||||
}
|
||||
|
||||
if self.status == 'done':
|
||||
return {
|
||||
'type': 'ir.actions.client',
|
||||
'tag': 'display_notification',
|
||||
'params': {
|
||||
'title': 'message',
|
||||
'message': 'This idea has been generated, please do not repeat the operation.',
|
||||
'type': 'danger',
|
||||
'sticky': False,
|
||||
}
|
||||
}
|
||||
|
||||
llm_template = self.llm_generated_idea
|
||||
|
||||
data_sets_list = []
|
||||
for dataset in self.needed_data_set_ids:
|
||||
datasets_id = self.env['alpha.datasets'].search(
|
||||
[('datasets_id', '=', dataset.name)], limit=1)
|
||||
for datasets_line in datasets_id.line_ids:
|
||||
data_sets_list.append({
|
||||
'id': datasets_line.data_field_name
|
||||
})
|
||||
|
||||
result_data = decode_template.process(data_sets_list, llm_template)
|
||||
|
||||
if result_data['success']:
|
||||
templates = result_data['templates']
|
||||
expressions = result_data['expressions']
|
||||
|
||||
# 如果没有解出数据，不做任何操作
|
||||
if len(templates) == 0 and len(expressions) == 0:
|
||||
return {
|
||||
'type': 'ir.actions.client',
|
||||
'tag': 'display_notification',
|
||||
'params': {
|
||||
'title': '提示',
|
||||
'message': '未解码出任何数据',
|
||||
'type': 'warning',
|
||||
'sticky': False,
|
||||
}
|
||||
}
|
||||
|
||||
# 组装模板数据
|
||||
template_data = []
|
||||
for template_item in templates:
|
||||
template_data.append({
|
||||
'template': template_item['template'],
|
||||
'original_template': template_item['original_template'],
|
||||
'idea': template_item.get('idea', ''),
|
||||
'template_line_ids': [(0, 0, {'expression': line}) for line in template_item['expressions']]
|
||||
})
|
||||
|
||||
# 保存数据
|
||||
self.write({
|
||||
'idea_template_ids': [(0, 0, data) for data in template_data],
|
||||
'final_expression_ids': [(0, 0, {'name': expression}) for expression in expressions],
|
||||
'status': 'decoded',
|
||||
})
|
||||
|
||||
return True
|
||||
else:
|
||||
return {
|
||||
'type': 'ir.actions.client',
|
||||
'tag': 'display_notification',
|
||||
'params': {
|
||||
'title': '失败',
|
||||
'message': '模板解码失败, 生成数量为 0',
|
||||
'type': 'danger',
|
||||
'sticky': False,
|
||||
}
|
||||
}
|
||||
|
||||
def combination_settings(self):
|
||||
self.ensure_one()
|
||||
if self.idea_template_ids and self.final_expression_ids:
|
||||
return {
|
||||
'type': 'ir.actions.act_window',
|
||||
'name': '组合设置',
|
||||
'res_model': 'wizard.combination.settings',
|
||||
'view_mode': 'form',
|
||||
'target': 'new',
|
||||
'context': {
|
||||
'active_model': 'alpha.idea',
|
||||
'active_id': self.id,
|
||||
},
|
||||
}
|
||||
else:
|
||||
return {
|
||||
'type': 'ir.actions.client',
|
||||
'tag': 'display_notification',
|
||||
'params': {
|
||||
'title': 'Execute the decoding template first',
|
||||
'message': 'idea_template_ids and final_expression_ids no data!',
|
||||
'type': 'danger',
|
||||
'sticky': False,
|
||||
}
|
||||
}
|
||||
|
||||
def _compute_expression_count(self):
|
||||
for record in self:
|
||||
if record.final_expression_ids:
|
||||
record.expression_count = len(record.final_expression_ids)
|
||||
else:
|
||||
record.expression_count = 0
|
||||
|
||||
|
||||
class NeededDataSet(models.Model):
|
||||
_name = 'alpha.needed.data.set'
|
||||
_description = 'Alpha Needed Data Set'
|
||||
|
||||
idea_id = fields.Many2one('alpha.idea', string='Idea', ondelete='cascade')
|
||||
|
||||
name = fields.Char(string='Name')
|
||||
|
||||
|
||||
class IdeaTemplate(models.Model):
|
||||
_name = 'alpha.idea.template'
|
||||
_description = 'Alpha Idea Template'
|
||||
|
||||
idea_id = fields.Many2one('alpha.idea', string='Idea', ondelete='cascade')
|
||||
|
||||
template_line_ids = fields.One2many(
|
||||
'alpha.idea.template.line', 'idea_id', string='Template Lines')
|
||||
|
||||
template = fields.Char(string='Template')
|
||||
|
||||
original_template = fields.Char(string='Original Template')
|
||||
|
||||
expression_count = fields.Integer(
|
||||
string='Expression Count', compute='_compute_expression_count', default=0)
|
||||
|
||||
idea = fields.Text(string='Text')
|
||||
|
||||
def _compute_expression_count(self):
|
||||
for record in self:
|
||||
record.expression_count = len(record.template_line_ids)
|
||||
|
||||
|
||||
class IdeaTemplateLine(models.Model):
|
||||
_name = 'alpha.idea.template.line'
|
||||
_description = 'Alpha Idea Template Line'
|
||||
|
||||
idea_id = fields.Many2one('alpha.idea.template',
|
||||
string='Alpha Idea Template', ondelete='cascade')
|
||||
|
||||
expression = fields.Char(string='Expression')
|
||||
|
||||
|
||||
class Final_Expression(models.Model):
|
||||
_name = 'alpha.final.expression'
|
||||
_description = 'Alpha Final Expression'
|
||||
|
||||
idea_id = fields.Many2one('alpha.idea', string='Idea', ondelete='cascade')
|
||||
|
||||
name = fields.Char(string='Name')
|
||||
Reference in New Issue
Block a user