Dmmsys Professional AI Agent - Enterprise AI Platform for Odoo CE
by Dmmsys guoyihot@outlook.com 124358678@qq.com http://www.dmmsys.com$ 323.12
| Availability |
Odoo Online
Odoo.sh
On Premise
|
| Odoo Apps Dependencies |
Discuss (mail)
|
| Community Apps Dependencies | Show |
| Lines of code | 12975 |
| Technical Name |
dmmsys_professional_ai_agent |
| License | OPL-1 |
| Website | http://www.dmmsys.com |
| Versions | 17.0 18.0 |
| Availability |
Odoo Online
Odoo.sh
On Premise
|
| Odoo Apps Dependencies |
Discuss (mail)
|
| Community Apps Dependencies | Show |
| Lines of code | 12975 |
| Technical Name |
dmmsys_professional_ai_agent |
| License | OPL-1 |
| Website | http://www.dmmsys.com |
| Versions | 17.0 18.0 |
Dmmsys Professional AI Agent
Enterprise AI platform for Odoo Community Edition. An alternative to Odoo Enterprise AI capabilities, designed specifically for Community Edition users. Build knowledge bases from documents and web pages. Every AI action is logged for audit compliance. Set monthly budgets to control AI costs. Describe your process in plain language, AI builds the workflow. Multiple AI agents collaborate on complex tasks.
Dmmsys Professional AI Agent — 企业级 AI 平台
企业级 AI 平台，专为 Odoo 社区版打造。用文档和网页构建知识库。每一次 AI 操作都有记录，满足审计要求。设置月度预算，控制 AI 使用成本。用大白话描述流程，AI 自动生成工作流。多个 AI 协同完成复杂任务。
What You Can Do
Enterprise AI capabilities for everyday workAsk Questions, Get Answers
Talk to your business data like talking to a colleagueIntent-Driven Process Execution
Describe what you need — "Check inventory levels", "Start month-end closing", "Review pending approvals" — AI interprets intent and orchestrates the corresponding business process automatically.
Build Knowledge Base
Upload documents (PDF, Word, Excel) or link web pages. AI searches your knowledge base to answer employee questions.
Business Data Operations
AI can search, read, update, and create business records through configured tools — enabling automated handling of routine tasks across any registered model.
Govern & Control
Audit, budget, and monitor every AI actionFull Audit Trail
Every AI action — who, when, what — is logged. Meet compliance requirements for ISO and internal audits.
Cost Control
Set monthly budgets per department or per user. Track token usage and costs for every AI call. Get alerts when approaching limits.
Privacy Protection
Auto-mask sensitive data like ID numbers, phone numbers, and bank cards before sending to LLM. Keep customer data safe.
能帮你做什么
企业级 AI 能力，赋能日常工作提问就有答案
像跟同事聊天一样，跟数据对话意图驱动流程执行
描述你的意图——"检查库存量""开始月结""审批待办事项"——AI 理解意图后自动编排对应业务流程执行。
构建知识库
上传文档（PDF、Word、Excel）或链接网页。AI 从知识库里搜索答案。
业务数据操作
通过配置好的工具，AI 可以查询、读取、更新、创建业务记录。让日常重复操作实现自动化处理。
管控与合规
每一次 AI 操作都可审计、可管控全链路审计
每一次 AI 操作——谁、什么时候、干了什么——都有记录。满足 ISO 和内部审计要求。
成本管控
按部门或按用户设置月度预算。追踪每次 AI 调用的 token 用量和费用。接近上限时自动告警。
隐私保护
发送给大模型前自动脱敏身份证号、手机号、银行卡号。保护客户数据安全。
Automation & Collaboration
Turn complex processes into one-click automationAI-Powered Workflows
Describe your process, AI builds itGenerate Workflows from Plain Language
"When a sales order exceeds $10,000, send to manager for approval, then notify finance." AI reads your goal and creates the approval workflow automatically.
Multi-Step Task Automation
Set up a sequence of actions — search, read, update, create, approve. AI executes in order, automatically retrying if something fails.
Scheduled & Triggered Jobs
Run monthly closing, inventory checks, or report generation automatically on schedule. Routine tasks can be configured to execute at specified intervals.
AI Team Collaboration
Multiple AI agents working togetherCross-Agent Collaboration
A sales AI can call inventory AI to check stock, then call finance AI to calculate pricing. Multiple AI employees work as a team.
Smart Alerts
Get notified when AI failure rate spikes, costs exceed budget, or response time slows down. Proactive monitoring keeps AI services healthy.
Customizable AI Agents
Create AI agents tailored to your business domains — each with configurable knowledge sources, tools, role profiles, and access permissions to match specific operational needs.
自动化与协同
复杂流程，一键自动完成AI 驱动的工作流
用大白话描述，AI 帮你建大白话生成审批流
"销售订单超过1万，发给经理审批，然后通知财务。"AI 读懂你的目标，自动生成审批流程。
多步骤任务自动化
设置一串动作——查、读、改、建、批。AI 按顺序执行，失败了自动重试。
定时与触发任务
月结、库存盘点、报表生成可按计划自动运行。例行任务支持按指定间隔定时执行。
AI 团队协同
多个 AI 一起干活跨 Agent 协同
销售 AI 可以调用库存 AI 查货，再调用财务 AI 算价。多个 AI 组成团队工作。
智能告警
AI 失败率飙升、成本超预算、响应变慢时自动通知。主动监控确保 AI 服务健康。
可自定义的 AI 员工
根据业务需要创建数字员工，可配置知识库、工具组合、角色设定和访问权限，适配不同的业务场景需求。
For IT Managers
Technical capabilities & requirementsTechnical Capabilities
What's under the hoodAI Agent Core
Configurable agents with topic/role system. Response style control (analytical/balanced/creative). Knowledge sources (files + web pages). Restrict answers to knowledge sources only.
RAG & Vector Search
pgvector with ivfflat index. Automatic chunking and embedding. Scheduled cron for batch embedding generation.
Tool System
Universal tools (search/read/update/create). Server actions with "use_in_ai" flag auto-register as tools. JSON Schema parameter support. OpenAI function calling format conversion.
Task Orchestration
DAG-based task dependencies. Topological sorting execution. Failure retry mechanism. Task templates. Execution logs (ai.job.log).
Governance Layer
Unified AI Bus (ai.bus) with permission verification, quota check, and audit logging. Complete audit logs (ai.audit.log). LLM call logs with token/cost tracking (ai.llm.call.log). Sensitive data sanitizer (ID/phone/bank card). Alert rules (failure rate/cost/response time).
Workflow & Evaluation
AI-powered workflow generation from natural language goals. Cross-agent tool calling with target_agent_id. Evaluation suite (suite/case/result) for testing AI agents.
Integration & Requirements
Deployment and compatibilityLLM & UI
OpenAI-compatible LLM adapter (DeepSeek, Qwen, Zhipu, OpenAI, etc.). Mock client for offline testing. FAB floating button + VS Code style ChatWindow. Model/agent selector. Session persistence across refresh.
Business Integration
mail.thread patch provides _ai_chat() / _get_ai_context() for all business models. Composer rules for multi-entry points (chatter/form/list/system tray). Preset shortcut prompt buttons.
Requirements
Works with Odoo Community and Enterprise. No enterprise license required. Depends on dmmsys_workflow_engine. PostgreSQL with pgvector recommended for RAG. Python requests library required.
给 IT 管理人员
技术能力与环境要求技术能力
核心能力一览AI Agent 核心
可配置 Agent（主题+角色系统）。响应风格控制（分析型/平衡型/创造型）。知识源（文件+网页）。可限制仅从知识源回答。
RAG 与向量检索
pgvector + ivfflat 索引。自动分块与向量化。定时任务批量生成 Embedding。
工具系统
通用工具（查询/读取/更新/创建）。服务器动作勾选"use_in_ai"自动注册为工具。JSON Schema 参数支持。OpenAI function calling 格式转换。
任务编排
基于 DAG 的任务依赖。拓扑排序执行。失败重试机制。任务模板。执行日志（ai.job.log）。
治理层
统一 AI 总线（权限校验+配额检查+审计记录）。完整审计日志（ai.audit.log）。LLM 调用日志含 token/费用追踪（ai.llm.call.log）。敏感数据脱敏（身份证/手机号/银行卡）。告警规则（失败率/成本/响应时间）。
工作流与评估
从自然语言目标生成工作流。支持 target_agent_id 的跨 Agent 工具调用。评估套件用于测试 AI Agent。
集成与环境要求
部署与兼容性LLM 与 UI
兼容 OpenAI 接口的 LLM 适配器。Mock 客户端支持离线测试。FAB 浮动按钮 + VS Code 风格聊天窗口。模型/Agent 选择器。刷新后会话持久化。
业务集成
mail.thread 补丁为所有业务模型提供 _ai_chat() / _get_ai_context()。Composer 规则支持多入口（chatter/表单/列表/系统托盘）。预设快捷提示按钮。
环境要求
同时支持 Odoo 社区版和企业版。无需企业版许可。依赖 dmmsys_workflow_engine。RAG 功能建议使用 PostgreSQL + pgvector。需要 Python requests 库。完全开源（OPL-1）。
Zero-Token Prompt Buttons
4 built-in FAB Chat prompts: "Summarize this record -LLM", "Analyze this record -LLM", "Explain this record -LLM" require LLM; "Suggest next actions based on the current record state" is 0-Token. Direct Action Tool mechanism allows any prompt button to be configured as 0-Token.
零Token 提示词按钮
内置 4 个 FAB Chat 提示词："Summarize this record -LLM"、"Analyze this record -LLM"、"Explain this record -LLM" 需 LLM；"Suggest next actions based on the current record state" 为 0-Token。通过 Direct Action Tool 机制，管理员可为任意提示词按钮配置直接执行工具。
AI Agent Base Capability Comparison
Capabilities across Foundation / Foundation MCP / Professional / Enterprise editions
Module mapping by edition:
• Foundation — dmmsys_foundation_ai_agent: Basic AI agent capabilities (chat / tool / task / RAG / LLM)
• Foundation MCP — dmmsys_foundation_mcp_agent: Foundation AI capabilities plus MCP gateway for external AI integration
• Professional — dmmsys_professional_mcp_agent: Full professional-grade AI platform with audit, evaluation, workflow integration, alerts
• Enterprise — dmmsys_enterprise_ai_agent + dmmsys_enterprise_essence series: Enterprise AI with ontology, self-evolution, budget control, monitoring
| Capability | Foundation | Foundation MCP | Professional | Enterprise |
|---|---|---|---|---|
| Layer 0 — Intent Core (Foundation + MCP Gateway) | ||||
| Agent Core (chat / tool / task) | ✓ | ✓ | ✓ | ✓ |
| LLM Integration | ✓ | ✓ | ✓ | ✓ |
| RAG Knowledge Base | ✓ | ✓ | ✓ | ✓ |
| Prompt Buttons / Composer | ✓ | ✓ | ✓ | ✓ |
| Cognitive Orchestration (Intent Recognition) | ✓ | ✓ | ✓ | ✓ |
| MCP Gateway (External AI Integration) | ✗ | ✓ | ✓ | ✓ |
| Layer 1 — Governance Agent (Professional – Audit, Evaluation, Workflow, Alerts) | ||||
| Audit Log | ✗ | ✗ | ✓ | ✓ |
| Evaluation Suite (Regression Testing) | ✗ | ✗ | ✓ | ✓ |
| Process Integration (Workflow) | ✗ | ✗ | ✓ | ✓ |
| Alert Rules | ✗ | ✗ | ✓ | ✓ |
| Layer 2 — Essence AI (Enterprise – Ontology, Self-Evolution, Budget, Ticket, Monitoring) | ||||
| Heartbeat Health Monitoring | ✗ | ✗ | ✗ | ✓ |
| Budget Control | ✗ | ✗ | ✗ | ✓ |
| Ticket (Human Approval) | ✗ | ✗ | ✗ | ✓ |
| Skill Training Loop (Self-Evolution) | ✗ | ✗ | ✗ | ✓ |
| Business Ontology (Semantic Definition) | ✗ | ✗ | ✗ | ✓ (essence series) |
| Agent Delegation Log | ✗ | ✗ | ✗ | ✓ |
| Monitor Dashboard | ✗ | ✗ | ✗ | ✓ |
| Tool Scan / Call Log | ✗ | ✗ | ✗ | ✓ |
AI Agent 底座能力对照表
Foundation / Foundation MCP / Professional / Enterprise 四层底座能力对比
各层级对应的模块名称：
• Foundation — dmmsys_foundation_ai_agent：基础 AI Agent 核心能力（chat / tool / task / RAG / LLM）
• Foundation MCP — dmmsys_foundation_mcp_agent：基础 AI 能力 + MCP 网关（外部 AI 系统接入）
• Professional — dmmsys_professional_mcp_agent：专业级 AI 平台，增加审计、评估、流程集成、告警等功能
• Enterprise — dmmsys_enterprise_ai_agent + dmmsys_enterprise_essence 系列：企业级 AI，具备本体语义、自进化、预算控制、监控等能力
| 能力维度 | Foundation | Foundation MCP | Professional | Enterprise |
|---|---|---|---|---|
| 第 0 层 — Intent Core (意图驱动核心) – 基础 AI 能力 | ||||
| Agent 核心（chat/tool/task） | ✓ | ✓ | ✓ | ✓ |
| LLM 接入 | ✓ | ✓ | ✓ | ✓ |
| RAG 知识库 | ✓ | ✓ | ✓ | ✓ |
| 提示词按钮 / Composer | ✓ | ✓ | ✓ | ✓ |
| 认知编排（意图识别） | ✓ | ✓ | ✓ | ✓ |
| MCP 网关（外部 AI 接入） | ✗ | ✓ | ✓ | ✓ |
| 第 1 层 —Governance Agent (治理增强版) – 加入审计、权限、审批等治理 | ||||
| 审计日志 | ✗ | ✗ | ✓ | ✓ |
| 评估套件（回归测试） | ✗ | ✗ | ✓ | ✓ |
| 流程集成（Workflow） | ✗ | ✗ | ✓ | ✓ |
| 告警规则 | ✗ | ✗ | ✓ | ✓ |
| 第 2 层 —Essence AI (企业本体版) – 加入本体、PCF、知识图谱、自进化 | ||||
| Heartbeat 健康监控 | ✗ | ✗ | ✗ | ✓ |
| 预算控制 | ✗ | ✗ | ✗ | ✓ |
| 工单（人工审批） | ✗ | ✗ | ✗ | ✓ |
| Skill 训练闭环（自进化） | ✗ | ✗ | ✗ | ✓ |
| 业务本体（语义定义） | ✗ | ✗ | ✗ | ✓（essence 系列） |
| Agent 委派日志 | ✗ | ✗ | ✗ | ✓ |
| 监控仪表板 | ✗ | ✗ | ✗ | ✓ |
| 工具扫描 / 调用日志 | ✗ | ✗ | ✗ | ✓ |
Zero-Token Prompt Buttons
Foundation Edition ships with 4 built-in prompt buttons in the FAB Chat window:
• Summarize this record -LLM — LLM required
• Analyze this record -LLM — LLM required
• Suggest next actions based on the current record state — 0-Token (direct tool execution, no LLM)
• Explain this record -LLM — LLM required
Professional Edition includes additional business-specific prompt buttons (e.g., Return Order Assistant, Purchase Order Assistant, Production Order Assistant, Invoice Dispute Analysis, Payment Suggestion) tailored to each business model. These can also be configured as 0-Token via the same Direct Action Tool mechanism.
Beyond these built-in defaults, the module provides the Direct Action Tool mechanism
on ai.prompt.button: administrators can assign any ai.generic.tool record
to any prompt button. Clicking that button executes the backend method directly,
bypassing the LLM entirely and consuming zero tokens.
This enables deterministic business operations (e.g., checking inventory, closing a period,
releasing a work order) to run instantly without any AI cost.
Prompt buttons without a direct tool assigned continue to use the LLM as normal.
零Token 提示词按钮
Foundation 标准版在 FAB Chat 窗口中内置了 4 个通用提示词按钮，其中：
• Summarize this record -LLM（总结） — 需LLM
• Analyze this record -LLM（分析） — 需LLM
• Suggest next actions based on the current record state（建议下一步操作） — 0-Token，不调LLM
• Explain this record -LLM（解释） — 需LLM
Professional 专业版额外包含针对各业务对象的专用提示词按钮（如退货助手、采购助手、生产工单助手、发票争议分析、付款建议等），
同样可通过 Direct Action Tool 机制配置为 0-Token。
除内置默认配置外，本模块提供了 Direct Action Tool（直接执行工具）机制：
管理员可以在 ai.prompt.button 上为任意提示词按钮绑定一个 ai.generic.tool 记录。
绑定后点击该按钮将直接调用后端方法执行，完全绕过 LLM，消耗 零个 Token。
这使得确定性业务操作（如检查库存、关账、释放工单等）可以即时运行，无任何 AI 成本。
未绑定直接工具的提示词按钮则继续正常使用 LLM。
Professional Business Agents
专业业务智能体
Ready‑to‑use AI workers for core manufacturing operations开箱即用的制造业核心业务 AI 数字员工
| Agent Module 模块名称 |
Functionality 功能说明 |
Default Depends 默认底座依赖 |
|---|---|---|
| dmmsys_mrp_intelligent_scheduling APS 智能排程 | 有限产能排程（OR-Tools CP-SAT 多目标优化）、帕累托方案对比（甘特图）、动态重排、派工单 Finite capacity scheduling (OR‑Tools multi‑objective), Pareto comparison (Gantt), dynamic rescheduling, dispatch orders |
dmmsys_foundation_ai_agent |
| dmmsys_mrp_decision_agent 生产排产 AI 决策 | 物料可用性/产能检查、重排建议、批量下达审批 Material availability & capacity checks, rescheduling suggestions, batch release approval |
dmmsys_professional_mcp_agent |
| dmmsys_monthly_closing_agent 财务月结 AI 数字员工 | 自动化月结流程（采购/销售/库存/生产/总账/资产六大模块的顺序检查、自动修复、期间锁定） Automated month-end closing: sequential check, auto‑fix, period lock for purchasing, sales, inventory, production, general ledger, fixed assets |
dmmsys_enterprise_ai_agent |
| dmmsys_professional_change_agent PLM 工程变更数字员工 | 变更管理四层（问题报告/变更申请/变更通知/变更任务）的 AI 检查/修复/关闭 Four‑layer change management (Issue → Request → Notice → Task) AI inspection, fixing, and closure |
dmmsys_enterprise_ai_agent |
| dmmsys_stock_replenishment_agent 自动补货 AI 决策 | 库存消耗分析、再订货点优化、自动创建采购订单 Consumption pattern analysis, reorder point optimization, automatic purchase order creation |
dmmsys_enterprise_ai_agent |
| dmmsys_stock_reservation_agent 物料预留 AI 决策 | 库存预留、缺料处理、替代料建议 Stock reservation, shortage handling, substitute material suggestions |
dmmsys_enterprise_ai_agent |
Note / 说明： All agents share identical _ai_xxx business logic. The depends only determines which AI infrastructure (audit, evolution, ontology, etc.) the agent can leverage.
所有专业 Agent 的业务逻辑代码完全相同，depends 仅决定该 Agent 可以使用哪些底层 AI 基础设施（审计、自进化、本体推理等）。
Professional Business Agents
Ready‑to‑use AI workers for core manufacturing operations| Agent Module | Functionality | Default Depends |
|---|---|---|
| dmmsys_mrp_intelligent_scheduling APS intelligent scheduling |
Finite capacity scheduling (OR‑Tools CP‑SAT multi‑objective), Pareto comparison (Gantt), dynamic rescheduling, dispatch orders | dmmsys_foundation_ai_agent |
| dmmsys_mrp_decision_agent Production scheduling AI decision |
Material availability & capacity checks, rescheduling suggestions, batch release approval | dmmsys_professional_mcp_agent |
| dmmsys_monthly_closing_agent Financial month‑end closing AI agent |
Automated month‑end closing: sequential check, auto‑fix, period lock for purchasing, sales, inventory, production, general ledger, fixed assets | dmmsys_enterprise_ai_agent |
| dmmsys_professional_change_agent PLM engineering change AI agent |
Four‑layer change management (Issue → Request → Notice → Task) AI inspection, fixing, and closure | dmmsys_enterprise_ai_agent |
| dmmsys_stock_replenishment_agent Automatic replenishment AI decision |
Consumption pattern analysis, reorder point optimization, automatic purchase order creation | dmmsys_enterprise_ai_agent |
| dmmsys_stock_reservation_agent Material reservation AI decision |
Stock reservation, shortage handling, substitute material suggestions | dmmsys_enterprise_ai_agent |
Note: All agents share identical _ai_xxx business logic. The depends only determines which AI infrastructure (audit, evolution, ontology, etc.) the agent can leverage.
Three‑Layer Base Adaptation
All professional agents can run on any base layer. Choose the right base according to your needs.
Foundation
dmmsys_foundation_ai_agent
- Agent Core + LLM + RAG
- Composer + cognitive orchestration
- Basic tool system
Basic AI capabilities
Foundation MCP
dmmsys_foundation_mcp_agent
- All Foundation capabilities
- + MCP Gateway (external AI access)
- Token authentication + IP whitelist
Foundation + MCP gateway
Professional
dmmsys_professional_mcp_agent
- All Foundation MCP capabilities
- + Full audit logs
- + Evaluation suite & regression testing
- + Workflow integration & alert rules
Professional AI platform
Enterprise
dmmsys_enterprise_ai_agent + essence series
- All Professional capabilities
- + Business ontology (
ontology.object/link/action) - + Self‑evolution (nightly pipeline)
- + Budget control & ticket approval
- + Knowledge graph & GraphRAG
Enterprise AI decision foundation
How to Switch the Base Layer
- Locate the agent module’s manifest file (
__manifest__.py). - Find the
dependslist containing the default base module name (e.g.,dmmsys_foundation_ai_agent). - Replace it with the base module name you have purchased (see cards above or the capability comparison table).
- No business code changes required (
_ai_xxxlogic is identical).
Example: To upgrade dmmsys_mrp_intelligent_scheduling to run on Professional base, change depends from 'dmmsys_foundation_ai_agent' to 'dmmsys_professional_mcp_agent'.
Important Notes
- All professional agents share identical business logic (
_ai_xxxmethods). The base layer only adds extra infrastructure capabilities. - You do not need to modify any business code when switching base layers.
- The default dependency in our distribution is always the lowest compatible base (Foundation for scheduling agents, Professional/Enterprise for others). This ensures out‑of‑the‑box functionality for all customers.
- Once you purchase a higher‑level base, simply update the
dependsin the agent’s manifest and the agent will automatically gain the advanced capabilities (audit, evolution, ontology, etc.).
专业业务智能体
开箱即用的制造业核心业务 AI 数字员工| 智能体模块 | 功能说明 | 默认底座依赖 |
|---|---|---|
| dmmsys_mrp_intelligent_scheduling APS 智能排程 |
有限产能排程（OR-Tools CP-SAT 多目标优化）、帕累托方案对比（甘特图）、动态重排、派工单 | dmmsys_foundation_ai_agent |
| dmmsys_mrp_decision_agent 生产排产 AI 决策 |
物料可用性/产能检查、重排建议、批量下达审批 | dmmsys_professional_mcp_agent |
| dmmsys_monthly_closing_agent 财务月结 AI 数字员工 |
自动化月结流程（采购/销售/库存/生产/总账/资产六大模块的顺序检查、自动修复、期间锁定） | dmmsys_enterprise_ai_agent |
| dmmsys_professional_change_agent PLM 工程变更数字员工 |
变更管理四层（问题报告/变更申请/变更通知/变更任务）的 AI 检查/修复/关闭 | dmmsys_enterprise_ai_agent |
| dmmsys_stock_replenishment_agent 自动补货 AI 决策 |
库存消耗分析、再订货点优化、自动创建采购订单 | dmmsys_enterprise_ai_agent |
| dmmsys_stock_reservation_agent 物料预留 AI 决策 |
库存预留、缺料处理、替代料建议 | dmmsys_enterprise_ai_agent |
说明： 所有专业 Agent 的业务逻辑代码（_ai_xxx）完全相同，depends 仅决定该 Agent 可以使用哪些底层 AI 基础设施（审计、自进化、本体推理等）。
三层底座适配方式
所有专业业务智能体均可在任意底座层上运行。根据需求选择最合适的底座。
Foundation
dmmsys_foundation_ai_agent
- Agent 核心 + LLM + RAG
- Composer + 认知编排
- 基础工具系统
基础 AI 能力
Foundation MCP
dmmsys_foundation_mcp_agent
- 包含 Foundation 全部能力
- + MCP 网关（外部 AI 接入）
- Token 认证 + IP 白名单
基础能力 + MCP 网关
Professional
dmmsys_professional_mcp_agent
- 包含 Foundation MCP 全部能力
- + 完整审计日志
- + 评估套件 & 回归测试
- + 流程集成 & 告警规则
专业级 AI 平台
Enterprise
dmmsys_enterprise_ai_agent + essence 系列
- 包含 Professional 全部能力
- + 业务本体 (
ontology.object/link/action) - + 自进化引擎（夜间流水线）
- + 预算控制 & 工单审批
- + 知识图谱 & GraphRAG
企业级 AI 决策底座
如何切换底座
- 找到专业 Agent 模块的 manifest 文件（
__manifest__.py）。 - 找到
depends列表，它当前包含默认底座模块名（例如dmmsys_foundation_ai_agent）。 - 将其替换为您购买的底座模块名（参考上方卡片或底座能力对照表）。
- 无需修改任何业务代码（
_ai_xxx逻辑完全相同）。
示例： 将 dmmsys_mrp_intelligent_scheduling 升级到 Professional 底座，只需将 depends 中的 'dmmsys_foundation_ai_agent' 改为 'dmmsys_professional_mcp_agent'。
重要说明
- 所有专业业务智能体的业务逻辑（
_ai_xxx方法）完全相同，底座仅提供额外的基础设施能力。 - 切换底座时，无需修改任何业务代码。
- 我们发布时默认使用最低兼容底座（排程 Agent 用 Foundation，其他用 Professional/Enterprise），确保所有客户开箱即用。
- 当您购买了更高级的底座后，只需修改 manifest 中的
depends，该 Agent 就会自动获得审计、自进化、本体等高级能力。
Version History / 版本历史
| Version | Date | Changes |
|---|---|---|
| 1.0 | 2026-06-07 |
First release. FAB Chat with 4 built-in prompt buttons (3 LLM + 1 0-Token). 首次发布。FAB Chat 内置 4 个提示词按钮（3 个需 LLM + 1 个 0-Token）。 |
Pre-built Demo Agents
The module includes several pre-configured AI agents for demonstration purposes. These agents illustrate the platform's configuration capabilities with sample topics and descriptions. Important: These are demo agents only. They require actual LLM provider setup, business data integration, and thorough testing before use in production. The module provider assumes no responsibility for the functionality or output of these demo agents in real business scenarios.
| Agent Name | Sample Scenario | Status |
|---|---|---|
| Dispute Handling Agent | Invoice dispute root cause analysis | Demo |
| Payment Suggestion Agent | Payment priority suggestions | Demo |
| Return Order Agent | Return order suggestions | Demo |
| Business Assistant | General business Q&A | Demo |
预置演示 Agent
模块内置了若干预配置的 AI Agent，用于演示平台的可配置能力和示例场景。 重要声明：这些 Agent 仅作演示用途。在实际使用前，必须完成 LLM 提供商配置、业务数据对接，并经过充分的业务验证。 模块提供商不对这些演示 Agent 在真实业务场景中的功能表现或输出结果承担任何责任。 用户应根据自身业务需求自行验证和调整。
| Agent 名称 | 示例场景 | 状态 |
|---|---|---|
| Dispute Handling Agent | 发票争议根因分析 | 演示 |
| Payment Suggestion Agent | 付款优先级建议 | 演示 |
| Return Order Agent | 退货单自动建议 | 演示 |
| Business Assistant | 通用业务问答 | 演示 |
Screenshots
No. Due to Odoo front-end changes in each version, front-end modules do not support cross-version use.
Yes. The module works with both Odoo Enterprise and Community editions.
PostgreSQL with pgvector extension is recommended for RAG features. Python requests library is required.
Product and Services
Odoo Proprietary License v1.0 This software and associated files (the "Software") may only be used (executed, modified, executed after modifications) if you have purchased a valid license from the authors, typically via Odoo Apps, or if you have received a written agreement from the authors of the Software (see the COPYRIGHT file). You may develop Odoo modules that use the Software as a library (typically by depending on it, importing it and using its resources), but without copying any source code or material from the Software. You may distribute those modules under the license of your choice, provided that this license is compatible with the terms of the Odoo Proprietary License (For example: LGPL, MIT, or proprietary licenses similar to this one). It is forbidden to publish, distribute, sublicense, or sell copies of the Software or modified copies of the Software. The above copyright notice and this permission notice must be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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