d49a51a5e8
The classifier was silently falling back to a clarification prompt every
time the LLM wrapped its JSON in markdown fences, prefixed it with
'json', or added surrounding prose. The bot then asked 'Could you
clarify what you need?' to every message regardless of clarity.
Now: strip code fences, slice to the first {...} block, and on parse
failure log the raw content (truncated) and treat the message as 'no
specialist agent' so the direct-answer fallback responds instead of
looping on clarification.
ActiveBlue AI
Multi-agent AI system integrated with Odoo 18 Community Edition.
Architecture
Odoo 18 (ai.activeblue.net)
└── activeblue_ai module
├── OWL2 systray brain icon + slide-in chat panel
├── Models: ab.ai.bot, ab.ai.directive, ab.ai.log, ab.ai.agent.registry
└── Controllers: /ai/chat, /ai/webhook/callback, /ai/health, /ai/approval/*
FastAPI Agent Service (192.168.2.47:8001)
├── POST /dispatch — route user message to MasterAgent
├── GET/POST /approval/* — human approval workflow
├── GET/POST /registry/* — agent registry + LLM backend overrides
├── POST /sweep — trigger proactive agent sweeps
└── GET /health — service health + Odoo/Ollama status
MasterAgent (singleton)
├── Classifies intent via LLM
├── Routes to specialist agents in parallel (asyncio.gather)
├── Manages 3-tier memory (conversation / operational / knowledge)
└── Synthesises responses
Specialist Agents (8, stateless):
finance_agent, accounting_agent, crm_agent, sales_agent,
project_agent, elearning_agent, expenses_agent, employees_agent
Privacy Modes
| Mode | Behaviour |
|---|---|
local |
Ollama only for all agents |
hybrid |
Per-agent override (DB → env → fallback) |
cloud |
Claude for non-HIPAA agents |
HIPAA-locked agents (always Ollama, no exceptions):
finance_agent, accounting_agent, employees_agent, expenses_agent
Quick Start
1. Clone and configure
git clone http://192.168.1.64:3000/tocmo0nlord/odoo-ai.git
cd odoo-ai
cp .env.example .env
# Edit .env — set POSTGRES_PASSWORD, ODOO_API_KEY, etc.
2. Run Odoo 18
docker compose -f docker-compose.odoo.yml up -d
3. Run the Agent Service
docker compose up -d
Or for development:
pip install -r requirements.txt
uvicorn agent_service.main:app --reload --port 8001
4. Run database migrations
cd agent_service/migrations
alembic upgrade head
5. Install Odoo module
In Odoo → Settings → Apps → search "ActiveBlue AI" → Install.
Environment Variables
See .env.example for the full list. Key variables:
| Variable | Description |
|---|---|
ODOO_URL |
Odoo base URL (e.g. http://ai.activeblue.net) |
ODOO_API_KEY |
Odoo user API key |
OLLAMA_URL |
Ollama API URL (e.g. http://192.168.2.47:11434) |
ANTHROPIC_API_KEY |
Required only if LLM_PRIVACY_MODE=cloud or hybrid |
LLM_PRIVACY_MODE |
local / hybrid / cloud (default: local) |
POSTGRES_PASSWORD |
Required — no default |
WEBHOOK_SECRET |
Shared secret between Odoo and agent service |
Development
Running tests
pip install pytest pytest-asyncio
pytest tests/ -v
Project structure
odoo-ai/
├── agent_service/
│ ├── agents/ # MasterAgent + 8 specialist agents + PeerBus + SweepCoordinator
│ ├── llm/ # OllamaBackend, ClaudeBackend, LLMRouter, ToolCallValidator
│ ├── memory/ # ConversationStore, OperationalStore, KnowledgeStore, MemoryManager
│ ├── tools/ # OdooClient + per-domain tools (finance, crm, sales, ...)
│ ├── routers/ # FastAPI routers (dispatch, approval, registry, sweep, health)
│ ├── prompts/ # System prompts for each agent
│ ├── migrations/ # Alembic migrations (7 tables)
│ ├── logging_utils/ # Structured JSON logging + Loki push
│ ├── config.py # pydantic-settings
│ ├── app_state.py # Global singletons
│ └── main.py # FastAPI app + lifespan startup
├── addons/
│ └── activeblue_ai/ # Odoo 18 module
│ ├── models/ # ab.ai.bot, ab.ai.directive, ab.ai.log, ab.ai.agent.registry
│ ├── controllers/ # webhook, health_proxy, approval + chat
│ ├── views/ # XML views + menus
│ ├── security/ # groups + ACL
│ ├── data/ # cron jobs
│ └── static/ # OWL2 JS + CSS + XML templates
├── research/ # Per-domain research notes
├── tests/ # pytest test suite
├── docker-compose.odoo.yml # Odoo 18 + PostgreSQL 15
├── docker-compose.yml # Agent service + PostgreSQL 15
├── Dockerfile
├── requirements.txt
└── .env.example
Agent Tool Limits
Each specialist agent is capped at 8 tools (MAX_TOOLS_PER_AGENT). The ToolCallValidator raises AgentConfigError at startup if exceeded.
Memory Architecture
| Tier | Store | TTL | Scope |
|---|---|---|---|
| Tier 1 | ab_conversation_memory |
Hard cap: 200 rows/user | Per user |
| Tier 2 | ab_operational_memory |
90 days | Per agent+scope |
| Tier 3 | ab_knowledge_store |
Permanent | Entity-keyed |
License
LGPL-3.0