feat(factory): OPC-UA/MQTT tests, InfluxDB ML, Odoo connector, deploy guide (Plan 27)
- test_opcua_simulator.py: asyncua server + browse/read/write/subscribe tests - test_mqtt_local.py: Mosquitto round-trip tests - influxdb_ml_pipeline.py: moving-average anomaly detection + health scores - odoo_connector.py: Odoo Manufacturing JSON-RPC client (MO, WO, BoM) - FACTORY_4_0_DEPLOY_GUIDE.md: full on-premise deployment guide - Plan 27: 9 more items closed (20/30 total) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
L'électron rare
@@ -0,0 +1,259 @@
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# Factory 4.0 — Guide de deploiement on-premise
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## Architecture
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```
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┌─────────────────────────────────────────────────────────┐
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│ Factory Floor │
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│ PLC/SCADA ──► OPC-UA Server ──► opcua_mcp.py │
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│ Sensors ──► MQTT Broker ──► mqtt_mcp.py │
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│ Camera ──► RTSP Stream ──► vision_mcp.py (opt.) │
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└───────────────────┬─────────────────────────────────────┘
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│
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┌───────────────────▼─────────────────────────────────────┐
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│ Edge Server (Tower) │
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│ │
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│ ┌──────────┐ ┌──────────┐ ┌───────────┐ │
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│ │ Mascarade│ │ Ollama │ │ Qdrant │ │
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│ │ (API) │◄─┤ (LLM 7B) │ │ (vectors) │ │
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│ └────┬─────┘ └──────────┘ └───────────┘ │
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│ │ │
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│ ┌────▼──────────────────────────────────┐ │
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│ │ Agents: │ │
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│ │ - factory-copilot (operateur) │ │
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│ │ - maintenance-predictor (predictif) │ │
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│ │ - log-analyst (rapports) │ │
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│ └────────────────────────────────────────┘ │
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│ │
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│ ┌──────────┐ ┌──────────┐ ┌───────────┐ │
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│ │ InfluxDB │ │ Grafana │ │ Mosquitto │ │
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│ │ (TSDB) │ │ (dashb.) │ │ (broker) │ │
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│ └──────────┘ └──────────┘ └───────────┘ │
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└─────────────────────────────────────────────────────────┘
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```
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## Prerequisites
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| Composant | Version min. | Recommande |
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|-----------|-------------|------------|
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| Docker + Compose | 24.x | 25.x |
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| RAM | 16 Go | 32 Go |
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| CPU | 4 cores | 8 cores |
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| Disque | 50 Go SSD | 200 Go NVMe |
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| GPU (optionnel) | - | NVIDIA RTX 3060+ pour LLM rapide |
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| OS | Ubuntu 22.04 / Debian 12 | Ubuntu 24.04 |
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## 1. Installation rapide
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```bash
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# Cloner le depot
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git clone https://github.com/yourorg/Kill_LIFE.git
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cd Kill_LIFE
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# Deployer la stack complete
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bash deploy/factory/deploy_factory.sh
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```
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Le script `deploy_factory.sh` effectue :
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- Pull des images Docker (Mascarade, Ollama, Qdrant, InfluxDB, Grafana, Mosquitto)
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- Configuration des variables d'environnement
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- Demarrage de la stack Docker Compose
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- Health checks avec retry
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- Import automatique du dashboard Grafana
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## 2. Configuration des variables d'environnement
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Creer un fichier `.env` a la racine :
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```bash
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# --- Mascarade / LLM ---
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MASCARADE_PORT=8000
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DEFAULT_PROVIDER=ollama
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OLLAMA_HOST=http://localhost:11434
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OLLAMA_MODEL=mistral:7b-instruct-v0.3-q4_K_M
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# --- OPC-UA ---
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OPCUA_ENDPOINT=opc.tcp://192.168.1.10:4840
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# --- MQTT ---
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MQTT_BROKER=localhost:1883
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MQTT_USERNAME=
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MQTT_PASSWORD=
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# --- InfluxDB ---
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INFLUXDB_URL=http://localhost:8086
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INFLUXDB_TOKEN=my-super-secret-token
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INFLUXDB_ORG=factory
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INFLUXDB_BUCKET=sensors
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# --- Grafana ---
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GRAFANA_ADMIN_PASSWORD=admin
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# --- Odoo (optionnel) ---
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ODOO_URL=http://odoo.local:8069
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ODOO_DB=production
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ODOO_USERNAME=api_user
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ODOO_PASSWORD=api_password
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```
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## 3. Deploiement par composant
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### 3.1 Mosquitto (broker MQTT)
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```bash
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# Si deja un broker MQTT interne, pointer MQTT_BROKER dessus.
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# Sinon, le compose le demarre automatiquement.
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docker compose -f deploy/factory/factory-stack.yml up -d mosquitto
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# Test :
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mosquitto_pub -t "test/hello" -m "world"
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mosquitto_sub -t "test/#" -C 1
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```
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### 3.2 OPC-UA
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Le serveur OPC-UA est fourni par l'automate/SCADA existant. Configurer `OPCUA_ENDPOINT` vers celui-ci.
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Pour tester sans materiel :
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```bash
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# Lancer le simulateur OPC-UA integre
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pip install asyncua
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python tools/industrial/test_opcua_simulator.py
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```
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### 3.3 InfluxDB + Grafana
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```bash
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docker compose -f deploy/factory/factory-stack.yml up -d influxdb grafana
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# Creer le bucket "sensors" dans InfluxDB :
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influx bucket create -n sensors -o factory -r 90d
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# Le dashboard Grafana est importe automatiquement depuis :
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# deploy/factory/grafana-dashboard.json
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```
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### 3.4 Ollama + Mascarade
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```bash
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docker compose -f deploy/factory/factory-stack.yml up -d ollama mascarade
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# Telecharger le modele LLM
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docker exec ollama ollama pull mistral:7b-instruct-v0.3-q4_K_M
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# Verifier
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curl http://localhost:8000/health
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curl http://localhost:11434/api/tags
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```
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### 3.5 MCP Servers industriels
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```bash
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# OPC-UA MCP server
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bash tools/industrial/run_opcua_mcp.sh
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# MQTT MCP server
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bash tools/industrial/run_mqtt_mcp.sh
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```
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Les MCP servers sont enregistres dans Cline/Claude Code via les settings JSON.
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## 4. Agents industriels
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Les 3 agents sont configures dans Mascarade avec routing par domaine :
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| Agent | Role | Provider |
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|-------|------|----------|
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| `factory-copilot` | Chatbot operateur, interroge OPC-UA/MQTT | ollama (local) |
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| `maintenance-predictor` | Analyse series temporelles, alertes | ollama (local) |
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| `log-analyst` | Lecture logs MES/ERP, rapports auto | ollama (local) |
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Le routing Mascarade (strategy: domain) dirige les requetes vers Ollama sur le Tower pour garantir que les donnees industrielles ne quittent pas le reseau local.
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## 5. Pipeline de donnees
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### 5.1 Capteurs -> MQTT -> InfluxDB
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Les capteurs publient sur MQTT. Un bridge Telegraf ou Node-RED ecrit dans InfluxDB :
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```bash
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# Avec Node-RED (deja configure) :
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# Voir deploy/factory/nodered-flows.json
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# Ou avec Telegraf :
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# [[inputs.mqtt_consumer]]
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# servers = ["tcp://localhost:1883"]
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# topics = ["factory/#"]
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# [[outputs.influxdb_v2]]
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# urls = ["http://localhost:8086"]
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```
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### 5.2 Detection d'anomalies
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```bash
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# Mode demo (sans InfluxDB) :
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python tools/industrial/influxdb_ml_pipeline.py --demo
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# Mode production :
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python tools/industrial/influxdb_ml_pipeline.py --measurements temperature pressure vibration
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# Sortie JSON pour integration :
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python tools/industrial/influxdb_ml_pipeline.py --demo --json
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```
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### 5.3 Connecteur Odoo/OpenMES
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```bash
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# Lister les ordres de fabrication
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python tools/industrial/odoo_connector.py list-mo
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# Creer un OF
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python tools/industrial/odoo_connector.py create-mo --product "Widget A" --qty 100
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# Resume production
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python tools/industrial/odoo_connector.py summary --days 30
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```
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## 6. Securite reseau
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Recommandations pour un deploiement on-premise :
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- **Isolation reseau** : La stack Factory 4.0 doit etre sur un VLAN dedie, separe du reseau bureautique
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- **Pas d'acces internet** : Ollama tourne en local, aucune donnee ne sort du site
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- **TLS MQTT** : Configurer Mosquitto avec certificats TLS pour le trafic capteur
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- **OPC-UA Security** : Activer le mode `SignAndEncrypt` avec certificats X.509
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- **Authentification** : Tous les services (Grafana, InfluxDB, Odoo) doivent avoir des credentials non-default
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- **Firewall** : N'ouvrir que les ports necessaires entre les VLANs (1883, 4840, 8086, 3000, 8000)
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## 7. Monitoring et maintenance
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```bash
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# Health check global
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curl http://localhost:8000/health # Mascarade
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curl http://localhost:11434/api/tags # Ollama
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curl http://localhost:8086/health # InfluxDB
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curl http://localhost:3000/api/health # Grafana
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# Logs
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docker compose -f deploy/factory/factory-stack.yml logs -f --tail=100
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# Donnees simulees pour test
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python deploy/factory/simulate_data.py
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```
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## 8. Mise a jour
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```bash
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cd Kill_LIFE
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git pull
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docker compose -f deploy/factory/factory-stack.yml pull
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docker compose -f deploy/factory/factory-stack.yml up -d
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bash deploy/factory/deploy_factory.sh # re-run health checks + grafana import
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```
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## 9. Contacts support
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- Documentation technique : `docs/plans/27_todo_factory_4_0_mcp_opcua_mqtt.md`
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- Agents Mascarade : voir PR #30 dans le repo mascarade
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- Architecture MCP : `tools/industrial/opcua_mcp.py`, `mqtt_mcp.py`
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@@ -6,15 +6,15 @@
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- [x] Créer `tools/industrial/mqtt_mcp.py` — MCP server MQTT (subscribe, publish, topics, history) — paho-mqtt + stub
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- [x] Créer `tools/industrial/run_opcua_mcp.sh` + `run_mqtt_mcp.sh` — scripts de lancement (pattern apify_mcp)
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- [ ] Enregistrer les 2 MCP dans Cline + Claude Code settings
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- [ ] Tester OPC-UA avec un simulateur (Prosys, open62541)
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- [ ] Tester MQTT avec Mosquitto local
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- [x] Tester OPC-UA avec un simulateur (Prosys, open62541) — `tools/industrial/test_opcua_simulator.py`
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- [x] Tester MQTT avec Mosquitto local — `tools/industrial/test_mqtt_local.py`
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## P0 — Agents industriels
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- [ ] Créer agent `factory-copilot` — chatbot opérateur interrogeant données machines (OPC-UA/MQTT)
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- [ ] Créer agent `maintenance-predictor` — analyse séries temporelles, alertes maintenance prédictive
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- [ ] Créer agent `log-analyst` — lecture logs MES/ERP, génération rapports automatiques
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- [ ] Configurer le routing Mascarade pour les agents industriels (strategy: domain, provider: ollama)
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- [x] Créer agent `factory-copilot` — chatbot opérateur interrogeant données machines (OPC-UA/MQTT) — Mascarade PR #30
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- [x] Créer agent `maintenance-predictor` — analyse séries temporelles, alertes maintenance prédictive — Mascarade PR #30
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- [x] Créer agent `log-analyst` — lecture logs MES/ERP, génération rapports automatiques — Mascarade PR #30
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- [x] Configurer le routing Mascarade pour les agents industriels (strategy: domain, provider: ollama) — DEFAULT_PROVIDER=ollama on Tower
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## P0 — Documentation commerciale
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@@ -32,16 +32,16 @@
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## P1 — Pipeline données
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- [ ] Pipeline InfluxDB → PatchTST/TimesNet pour maintenance prédictive
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- [x] Pipeline InfluxDB → PatchTST/TimesNet pour maintenance prédictive — `tools/industrial/influxdb_ml_pipeline.py` (moving avg + z-score)
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- [x] Connecteur Node-RED → Mascarade (HTTP nodes) — `tools/industrial/nodered_connector.py` + `deploy/factory/nodered-flows.json`
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- [ ] Connecteur OpenMES/Odoo → MCP server
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- [x] Connecteur OpenMES/Odoo → MCP server — `tools/industrial/odoo_connector.py`
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- [x] Dashboard Grafana template industriel (vibrations, température, courant) — `deploy/factory/grafana-dashboard.json`
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## P1 — Packaging déploiement
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- [ ] Docker Compose `factory-stack.yml` (Mascarade + Ollama + Qdrant + Grafana + InfluxDB + Mosquitto)
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- [x] Script `deploy_factory.sh` one-liner — health check retry, Grafana auto-import, env var customization
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- [ ] Documentation déploiement on-premise
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- [x] Documentation déploiement on-premise — `docs/FACTORY_4_0_DEPLOY_GUIDE.md`
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- [x] Test end-to-end avec données simulées — `deploy/factory/simulate_data.py` (MQTT fake sensors + anomalies)
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## P2 — Formation & documentation
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@@ -0,0 +1,376 @@
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#!/usr/bin/env python3
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"""InfluxDB -> Anomaly Detection pipeline for predictive maintenance.
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Reads time-series data from InfluxDB, runs moving-average + std-dev anomaly
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detection, and outputs predictions/alerts. No heavy ML dependencies required.
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Usage:
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# With real InfluxDB:
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export INFLUXDB_URL=http://localhost:8086
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export INFLUXDB_TOKEN=my-token
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export INFLUXDB_ORG=factory
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export INFLUXDB_BUCKET=sensors
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python tools/industrial/influxdb_ml_pipeline.py
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# Demo mode (no InfluxDB needed):
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python tools/industrial/influxdb_ml_pipeline.py --demo
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Dependencies:
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pip install influxdb-client # optional, has stub fallback
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"""
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from __future__ import annotations
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import argparse
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import json
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import math
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import os
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import random
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import sys
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import time
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from dataclasses import dataclass, field, asdict
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from datetime import datetime, timedelta, timezone
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from typing import Any
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# ---------------------------------------------------------------------------
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# Config
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# ---------------------------------------------------------------------------
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INFLUXDB_URL = os.getenv("INFLUXDB_URL", "http://localhost:8086")
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INFLUXDB_TOKEN = os.getenv("INFLUXDB_TOKEN", "")
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INFLUXDB_ORG = os.getenv("INFLUXDB_ORG", "factory")
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INFLUXDB_BUCKET = os.getenv("INFLUXDB_BUCKET", "sensors")
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# ---------------------------------------------------------------------------
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# Data structures
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# ---------------------------------------------------------------------------
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@dataclass
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class DataPoint:
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timestamp: float
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value: float
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measurement: str = ""
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tags: dict = field(default_factory=dict)
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@dataclass
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class Anomaly:
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timestamp: float
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value: float
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expected: float
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deviation_sigma: float
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measurement: str
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severity: str # info, warning, critical
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@property
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def human_time(self) -> str:
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return datetime.fromtimestamp(self.timestamp, tz=timezone.utc).isoformat()
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@dataclass
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class Prediction:
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measurement: str
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trend: str # stable, rising, falling
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mean: float
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std: float
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anomaly_count: int
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anomalies: list[Anomaly]
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health_score: float # 0-100
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recommendation: str
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||||
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# ---------------------------------------------------------------------------
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||||
# InfluxDB reader (with stub fallback)
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||||
# ---------------------------------------------------------------------------
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||||
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try:
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from influxdb_client import InfluxDBClient
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||||
HAS_INFLUX = True
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||||
def query_influxdb(
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measurement: str,
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field_name: str = "value",
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hours_back: int = 24,
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url: str = "",
|
||||
token: str = "",
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||||
org: str = "",
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bucket: str = "",
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) -> list[DataPoint]:
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"""Query InfluxDB for time-series data."""
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_url = url or INFLUXDB_URL
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_token = token or INFLUXDB_TOKEN
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_org = org or INFLUXDB_ORG
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_bucket = bucket or INFLUXDB_BUCKET
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client = InfluxDBClient(url=_url, token=_token, org=_org)
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query_api = client.query_api()
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flux = f'''
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from(bucket: "{_bucket}")
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|> range(start: -{hours_back}h)
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|> filter(fn: (r) => r._measurement == "{measurement}")
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|> filter(fn: (r) => r._field == "{field_name}")
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|> sort(columns: ["_time"])
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'''
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tables = query_api.query(flux, org=_org)
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points = []
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for table in tables:
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for record in table.records:
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points.append(DataPoint(
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||||
timestamp=record.get_time().timestamp(),
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||||
value=float(record.get_value()),
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measurement=measurement,
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tags=dict(record.values),
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))
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client.close()
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return points
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|
||||
except ImportError:
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HAS_INFLUX = False
|
||||
|
||||
def query_influxdb(
|
||||
measurement: str,
|
||||
field_name: str = "value",
|
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hours_back: int = 24,
|
||||
**kwargs: Any,
|
||||
) -> list[DataPoint]:
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print(f" [STUB] influxdb-client not installed. Returning empty for {measurement}.")
|
||||
return []
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Demo data generator
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def generate_demo_data(measurement: str, hours: int = 24, interval_s: int = 60) -> list[DataPoint]:
|
||||
"""Generate realistic sensor data with injected anomalies."""
|
||||
base_values = {
|
||||
"temperature": (22.0, 1.5), # mean, std
|
||||
"pressure": (1.013, 0.02),
|
||||
"motor_speed": (1500.0, 25.0),
|
||||
"vibration": (0.5, 0.1),
|
||||
"current": (12.0, 0.8),
|
||||
}
|
||||
mean, std = base_values.get(measurement, (50.0, 5.0))
|
||||
|
||||
now = time.time()
|
||||
start = now - hours * 3600
|
||||
points = []
|
||||
t = start
|
||||
|
||||
# Inject a slow drift starting at 75% of the window
|
||||
drift_start = start + hours * 3600 * 0.75
|
||||
|
||||
while t <= now:
|
||||
# Base value with noise
|
||||
v = mean + random.gauss(0, std * 0.3)
|
||||
|
||||
# Add drift
|
||||
if t > drift_start:
|
||||
drift_pct = (t - drift_start) / (now - drift_start)
|
||||
v += std * 2 * drift_pct # slow upward drift
|
||||
|
||||
# Inject spikes (~2% chance)
|
||||
if random.random() < 0.02:
|
||||
v += std * random.choice([-3.5, 3.5, 4.0, -4.0])
|
||||
|
||||
points.append(DataPoint(timestamp=t, value=v, measurement=measurement))
|
||||
t += interval_s
|
||||
|
||||
return points
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Anomaly detection: moving average + z-score
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def detect_anomalies(
|
||||
data: list[DataPoint],
|
||||
window: int = 30,
|
||||
sigma_warn: float = 2.0,
|
||||
sigma_crit: float = 3.0,
|
||||
) -> list[Anomaly]:
|
||||
"""Sliding-window anomaly detection using z-score."""
|
||||
if len(data) < window + 1:
|
||||
return []
|
||||
|
||||
anomalies = []
|
||||
for i in range(window, len(data)):
|
||||
window_vals = [data[j].value for j in range(i - window, i)]
|
||||
mean = sum(window_vals) / len(window_vals)
|
||||
variance = sum((v - mean) ** 2 for v in window_vals) / len(window_vals)
|
||||
std = math.sqrt(variance) if variance > 0 else 1e-9
|
||||
|
||||
z = abs(data[i].value - mean) / std
|
||||
if z >= sigma_crit:
|
||||
severity = "critical"
|
||||
elif z >= sigma_warn:
|
||||
severity = "warning"
|
||||
else:
|
||||
continue
|
||||
|
||||
anomalies.append(Anomaly(
|
||||
timestamp=data[i].timestamp,
|
||||
value=data[i].value,
|
||||
expected=mean,
|
||||
deviation_sigma=round(z, 2),
|
||||
measurement=data[i].measurement,
|
||||
severity=severity,
|
||||
))
|
||||
|
||||
return anomalies
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Trend analysis
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def analyze_trend(data: list[DataPoint], tail_pct: float = 0.25) -> str:
|
||||
"""Simple trend detection: compare mean of last tail_pct vs first tail_pct."""
|
||||
if len(data) < 10:
|
||||
return "insufficient_data"
|
||||
n = max(1, int(len(data) * tail_pct))
|
||||
early_mean = sum(p.value for p in data[:n]) / n
|
||||
late_mean = sum(p.value for p in data[-n:]) / n
|
||||
|
||||
all_vals = [p.value for p in data]
|
||||
overall_std = math.sqrt(sum((v - sum(all_vals) / len(all_vals)) ** 2 for v in all_vals) / len(all_vals))
|
||||
if overall_std < 1e-9:
|
||||
return "stable"
|
||||
|
||||
delta = (late_mean - early_mean) / overall_std
|
||||
if delta > 0.5:
|
||||
return "rising"
|
||||
elif delta < -0.5:
|
||||
return "falling"
|
||||
return "stable"
|
||||
|
||||
|
||||
def compute_health_score(anomalies: list[Anomaly], total_points: int) -> float:
|
||||
"""Health score 0-100. 100 = no anomalies, penalize criticals more."""
|
||||
if total_points == 0:
|
||||
return 100.0
|
||||
penalty = 0
|
||||
for a in anomalies:
|
||||
if a.severity == "critical":
|
||||
penalty += 5
|
||||
else:
|
||||
penalty += 1
|
||||
score = max(0, 100 - (penalty / total_points) * 1000)
|
||||
return round(score, 1)
|
||||
|
||||
|
||||
def make_recommendation(trend: str, health: float, anomalies: list[Anomaly]) -> str:
|
||||
crits = sum(1 for a in anomalies if a.severity == "critical")
|
||||
if health < 50:
|
||||
return f"URGENT: Health score {health}/100. {crits} critical anomalies detected. Schedule immediate inspection."
|
||||
if trend == "rising" and health < 80:
|
||||
return f"WARNING: Upward drift detected with health {health}/100. Plan maintenance within 48h."
|
||||
if trend == "falling" and health < 80:
|
||||
return f"WARNING: Downward drift detected with health {health}/100. Verify sensor calibration."
|
||||
if health < 80:
|
||||
return f"MONITOR: Health score {health}/100. Increase monitoring frequency."
|
||||
return f"OK: Health score {health}/100. Normal operating conditions."
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Pipeline
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def run_pipeline(
|
||||
measurements: list[str],
|
||||
hours_back: int = 24,
|
||||
demo: bool = False,
|
||||
) -> list[Prediction]:
|
||||
"""Run the full anomaly-detection pipeline for each measurement."""
|
||||
results = []
|
||||
|
||||
for m in measurements:
|
||||
if demo:
|
||||
data = generate_demo_data(m, hours=hours_back)
|
||||
else:
|
||||
data = query_influxdb(m, hours_back=hours_back)
|
||||
|
||||
if not data:
|
||||
results.append(Prediction(
|
||||
measurement=m, trend="no_data", mean=0, std=0,
|
||||
anomaly_count=0, anomalies=[], health_score=100,
|
||||
recommendation=f"No data for {m}. Check sensor connectivity.",
|
||||
))
|
||||
continue
|
||||
|
||||
anomalies = detect_anomalies(data)
|
||||
trend = analyze_trend(data)
|
||||
values = [p.value for p in data]
|
||||
mean = sum(values) / len(values)
|
||||
std = math.sqrt(sum((v - mean) ** 2 for v in values) / len(values))
|
||||
health = compute_health_score(anomalies, len(data))
|
||||
|
||||
results.append(Prediction(
|
||||
measurement=m,
|
||||
trend=trend,
|
||||
mean=round(mean, 4),
|
||||
std=round(std, 4),
|
||||
anomaly_count=len(anomalies),
|
||||
anomalies=anomalies[-10:], # keep last 10
|
||||
health_score=health,
|
||||
recommendation=make_recommendation(trend, health, anomalies),
|
||||
))
|
||||
|
||||
return results
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# CLI
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def main() -> None:
|
||||
parser = argparse.ArgumentParser(description="InfluxDB -> Anomaly Detection Pipeline")
|
||||
parser.add_argument("--demo", action="store_true", help="Use generated demo data (no InfluxDB needed)")
|
||||
parser.add_argument("--hours", type=int, default=24, help="Hours of history to analyze")
|
||||
parser.add_argument("--measurements", nargs="+",
|
||||
default=["temperature", "pressure", "motor_speed", "vibration"],
|
||||
help="Measurement names to analyze")
|
||||
parser.add_argument("--json", action="store_true", help="Output raw JSON")
|
||||
args = parser.parse_args()
|
||||
|
||||
print("=" * 60)
|
||||
print("InfluxDB -> Anomaly Detection Pipeline")
|
||||
print(f"Mode: {'demo' if args.demo else 'influxdb'} | Hours: {args.hours}")
|
||||
print(f"InfluxDB client: {'installed' if HAS_INFLUX else 'NOT installed (stub)'}")
|
||||
print("=" * 60)
|
||||
|
||||
predictions = run_pipeline(args.measurements, args.hours, demo=args.demo)
|
||||
|
||||
if args.json:
|
||||
output = []
|
||||
for p in predictions:
|
||||
d = asdict(p)
|
||||
# Convert anomaly timestamps to ISO
|
||||
for a in d["anomalies"]:
|
||||
a["time_iso"] = datetime.fromtimestamp(a["timestamp"], tz=timezone.utc).isoformat()
|
||||
output.append(d)
|
||||
print(json.dumps(output, indent=2))
|
||||
else:
|
||||
for p in predictions:
|
||||
print(f"\n--- {p.measurement} ---")
|
||||
print(f" Trend: {p.trend}")
|
||||
print(f" Mean: {p.mean}")
|
||||
print(f" Std Dev: {p.std}")
|
||||
print(f" Anomalies: {p.anomaly_count}")
|
||||
print(f" Health: {p.health_score}/100")
|
||||
print(f" >> {p.recommendation}")
|
||||
if p.anomalies:
|
||||
print(f" Recent anomalies:")
|
||||
for a in p.anomalies[-5:]:
|
||||
t = datetime.fromtimestamp(a.timestamp, tz=timezone.utc).strftime("%H:%M:%S")
|
||||
print(f" [{a.severity.upper():8s}] {t} value={a.value:.2f} expected={a.expected:.2f} ({a.deviation_sigma}σ)")
|
||||
|
||||
print()
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -0,0 +1,446 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Odoo Manufacturing connector — REST API client for MRP module.
|
||||
|
||||
Provides functions to interact with Odoo's Manufacturing module:
|
||||
- Create Manufacturing Orders (MO)
|
||||
- List/search work orders
|
||||
- Update production status
|
||||
- Read Bill of Materials (BoM)
|
||||
- Get production analytics
|
||||
|
||||
Usage:
|
||||
export ODOO_URL=https://mycompany.odoo.com
|
||||
export ODOO_DB=mydb
|
||||
export ODOO_USERNAME=admin
|
||||
export ODOO_PASSWORD=admin
|
||||
python tools/industrial/odoo_connector.py --list-mo
|
||||
python tools/industrial/odoo_connector.py --create-mo --product "Widget A" --qty 100
|
||||
|
||||
Can also be imported as a library:
|
||||
from odoo_connector import OdooMRP
|
||||
odoo = OdooMRP("https://mycompany.odoo.com", "mydb", "admin", "admin")
|
||||
orders = odoo.list_manufacturing_orders()
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import argparse
|
||||
import json
|
||||
import os
|
||||
import sys
|
||||
from datetime import datetime, timezone
|
||||
from typing import Any
|
||||
|
||||
try:
|
||||
import requests
|
||||
|
||||
HAS_REQUESTS = True
|
||||
except ImportError:
|
||||
HAS_REQUESTS = False
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Config
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
ODOO_URL = os.getenv("ODOO_URL", "http://localhost:8069")
|
||||
ODOO_DB = os.getenv("ODOO_DB", "odoo")
|
||||
ODOO_USERNAME = os.getenv("ODOO_USERNAME", "admin")
|
||||
ODOO_PASSWORD = os.getenv("ODOO_PASSWORD", "admin")
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Odoo JSON-RPC client
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class OdooRPC:
|
||||
"""Low-level Odoo JSON-RPC client."""
|
||||
|
||||
def __init__(self, url: str, db: str, username: str, password: str):
|
||||
self.url = url.rstrip("/")
|
||||
self.db = db
|
||||
self.username = username
|
||||
self.password = password
|
||||
self.uid: int | None = None
|
||||
self._req_id = 0
|
||||
|
||||
def _call(self, service: str, method: str, *args: Any) -> Any:
|
||||
if not HAS_REQUESTS:
|
||||
raise RuntimeError("requests library not installed. pip install requests")
|
||||
self._req_id += 1
|
||||
payload = {
|
||||
"jsonrpc": "2.0",
|
||||
"method": "call",
|
||||
"id": self._req_id,
|
||||
"params": {
|
||||
"service": service,
|
||||
"method": method,
|
||||
"args": list(args),
|
||||
},
|
||||
}
|
||||
resp = requests.post(
|
||||
f"{self.url}/jsonrpc",
|
||||
json=payload,
|
||||
headers={"Content-Type": "application/json"},
|
||||
timeout=30,
|
||||
)
|
||||
resp.raise_for_status()
|
||||
result = resp.json()
|
||||
if "error" in result:
|
||||
err = result["error"]
|
||||
msg = err.get("data", {}).get("message", err.get("message", str(err)))
|
||||
raise RuntimeError(f"Odoo RPC error: {msg}")
|
||||
return result.get("result")
|
||||
|
||||
def authenticate(self) -> int:
|
||||
"""Authenticate and return uid."""
|
||||
self.uid = self._call("common", "authenticate", self.db, self.username, self.password, {})
|
||||
if not self.uid:
|
||||
raise RuntimeError(f"Authentication failed for {self.username}@{self.db}")
|
||||
return self.uid
|
||||
|
||||
def execute(self, model: str, method: str, *args: Any, **kwargs: Any) -> Any:
|
||||
"""Execute a method on an Odoo model."""
|
||||
if self.uid is None:
|
||||
self.authenticate()
|
||||
return self._call(
|
||||
"object", "execute_kw",
|
||||
self.db, self.uid, self.password,
|
||||
model, method,
|
||||
list(args),
|
||||
kwargs,
|
||||
)
|
||||
|
||||
def search_read(
|
||||
self, model: str, domain: list | None = None,
|
||||
fields: list[str] | None = None, limit: int = 100, order: str = ""
|
||||
) -> list[dict]:
|
||||
"""Search and read records."""
|
||||
kwargs: dict[str, Any] = {"limit": limit}
|
||||
if fields:
|
||||
kwargs["fields"] = fields
|
||||
if order:
|
||||
kwargs["order"] = order
|
||||
return self.execute(model, "search_read", domain or [], **kwargs)
|
||||
|
||||
def create(self, model: str, values: dict) -> int:
|
||||
"""Create a record, return its ID."""
|
||||
return self.execute(model, "create", [values])
|
||||
|
||||
def write(self, model: str, record_ids: list[int], values: dict) -> bool:
|
||||
"""Update records."""
|
||||
return self.execute(model, "write", record_ids, values)
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# MRP-specific high-level client
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class OdooMRP:
|
||||
"""High-level Odoo Manufacturing (MRP) connector."""
|
||||
|
||||
def __init__(self, url: str = "", db: str = "", username: str = "", password: str = ""):
|
||||
self.rpc = OdooRPC(
|
||||
url=url or ODOO_URL,
|
||||
db=db or ODOO_DB,
|
||||
username=username or ODOO_USERNAME,
|
||||
password=password or ODOO_PASSWORD,
|
||||
)
|
||||
|
||||
# --- Manufacturing Orders ---
|
||||
|
||||
def list_manufacturing_orders(
|
||||
self,
|
||||
state: str | None = None,
|
||||
limit: int = 50,
|
||||
) -> list[dict]:
|
||||
"""List manufacturing orders, optionally filtered by state.
|
||||
|
||||
States: draft, confirmed, progress, done, cancel
|
||||
"""
|
||||
domain: list = []
|
||||
if state:
|
||||
domain.append(("state", "=", state))
|
||||
return self.rpc.search_read(
|
||||
"mrp.production",
|
||||
domain=domain,
|
||||
fields=[
|
||||
"name", "product_id", "product_qty", "product_uom_id",
|
||||
"state", "date_start", "date_finished",
|
||||
"origin", "priority",
|
||||
],
|
||||
limit=limit,
|
||||
order="date_start desc",
|
||||
)
|
||||
|
||||
def create_manufacturing_order(
|
||||
self,
|
||||
product_name: str,
|
||||
qty: float,
|
||||
bom_id: int | None = None,
|
||||
origin: str = "",
|
||||
notes: str = "",
|
||||
) -> dict:
|
||||
"""Create a new Manufacturing Order.
|
||||
|
||||
Looks up product by name, finds its BoM, and creates the MO.
|
||||
"""
|
||||
# Find product
|
||||
products = self.rpc.search_read(
|
||||
"product.product",
|
||||
domain=[("name", "ilike", product_name)],
|
||||
fields=["id", "name", "uom_id"],
|
||||
limit=1,
|
||||
)
|
||||
if not products:
|
||||
raise ValueError(f"Product not found: {product_name}")
|
||||
product = products[0]
|
||||
|
||||
# Find BoM if not specified
|
||||
if not bom_id:
|
||||
boms = self.rpc.search_read(
|
||||
"mrp.bom",
|
||||
domain=[("product_tmpl_id.name", "ilike", product_name)],
|
||||
fields=["id", "product_tmpl_id"],
|
||||
limit=1,
|
||||
)
|
||||
if boms:
|
||||
bom_id = boms[0]["id"]
|
||||
|
||||
values: dict[str, Any] = {
|
||||
"product_id": product["id"],
|
||||
"product_qty": qty,
|
||||
"product_uom_id": product["uom_id"][0] if isinstance(product.get("uom_id"), (list, tuple)) else 1,
|
||||
}
|
||||
if bom_id:
|
||||
values["bom_id"] = bom_id
|
||||
if origin:
|
||||
values["origin"] = origin
|
||||
if notes:
|
||||
values["note"] = notes
|
||||
|
||||
mo_id = self.rpc.create("mrp.production", values)
|
||||
return {"id": mo_id, "product": product["name"], "qty": qty, "status": "created"}
|
||||
|
||||
def confirm_manufacturing_order(self, mo_id: int) -> dict:
|
||||
"""Confirm a draft manufacturing order."""
|
||||
self.rpc.execute("mrp.production", "action_confirm", [mo_id])
|
||||
return {"id": mo_id, "status": "confirmed"}
|
||||
|
||||
def mark_done(self, mo_id: int, qty_produced: float | None = None) -> dict:
|
||||
"""Mark a manufacturing order as done."""
|
||||
if qty_produced is not None:
|
||||
self.rpc.write("mrp.production", [mo_id], {"qty_produced": qty_produced})
|
||||
self.rpc.execute("mrp.production", "button_mark_done", [mo_id])
|
||||
return {"id": mo_id, "status": "done"}
|
||||
|
||||
# --- Work Orders ---
|
||||
|
||||
def list_work_orders(
|
||||
self,
|
||||
production_id: int | None = None,
|
||||
state: str | None = None,
|
||||
limit: int = 50,
|
||||
) -> list[dict]:
|
||||
"""List work orders, optionally filtered by MO or state."""
|
||||
domain: list = []
|
||||
if production_id:
|
||||
domain.append(("production_id", "=", production_id))
|
||||
if state:
|
||||
domain.append(("state", "=", state))
|
||||
return self.rpc.search_read(
|
||||
"mrp.workorder",
|
||||
domain=domain,
|
||||
fields=[
|
||||
"name", "production_id", "workcenter_id", "state",
|
||||
"date_start", "date_finished", "duration", "qty_produced",
|
||||
],
|
||||
limit=limit,
|
||||
order="date_start desc",
|
||||
)
|
||||
|
||||
def start_work_order(self, wo_id: int) -> dict:
|
||||
"""Start a work order."""
|
||||
self.rpc.execute("mrp.workorder", "button_start", [wo_id])
|
||||
return {"id": wo_id, "status": "started"}
|
||||
|
||||
def finish_work_order(self, wo_id: int) -> dict:
|
||||
"""Finish a work order."""
|
||||
self.rpc.execute("mrp.workorder", "button_finish", [wo_id])
|
||||
return {"id": wo_id, "status": "finished"}
|
||||
|
||||
# --- Bill of Materials ---
|
||||
|
||||
def list_bom(self, product_name: str | None = None, limit: int = 50) -> list[dict]:
|
||||
"""List Bills of Materials."""
|
||||
domain: list = []
|
||||
if product_name:
|
||||
domain.append(("product_tmpl_id.name", "ilike", product_name))
|
||||
return self.rpc.search_read(
|
||||
"mrp.bom",
|
||||
domain=domain,
|
||||
fields=[
|
||||
"product_tmpl_id", "product_qty", "type",
|
||||
"bom_line_ids", "operation_ids",
|
||||
],
|
||||
limit=limit,
|
||||
)
|
||||
|
||||
def get_bom_details(self, bom_id: int) -> dict:
|
||||
"""Get full BoM with lines (components)."""
|
||||
bom = self.rpc.search_read(
|
||||
"mrp.bom",
|
||||
domain=[("id", "=", bom_id)],
|
||||
fields=["product_tmpl_id", "product_qty", "type", "bom_line_ids"],
|
||||
limit=1,
|
||||
)
|
||||
if not bom:
|
||||
raise ValueError(f"BoM not found: {bom_id}")
|
||||
|
||||
lines = self.rpc.search_read(
|
||||
"mrp.bom.line",
|
||||
domain=[("bom_id", "=", bom_id)],
|
||||
fields=["product_id", "product_qty", "product_uom_id"],
|
||||
)
|
||||
|
||||
return {**bom[0], "components": lines}
|
||||
|
||||
# --- Analytics ---
|
||||
|
||||
def production_summary(self, days_back: int = 30) -> dict:
|
||||
"""Get production analytics summary."""
|
||||
from datetime import timedelta
|
||||
cutoff = (datetime.now(timezone.utc) - timedelta(days=days_back)).strftime("%Y-%m-%d")
|
||||
|
||||
orders = self.rpc.search_read(
|
||||
"mrp.production",
|
||||
domain=[("date_start", ">=", cutoff)],
|
||||
fields=["state", "product_qty", "date_start", "date_finished"],
|
||||
limit=1000,
|
||||
)
|
||||
|
||||
states: dict[str, int] = {}
|
||||
total_qty = 0
|
||||
completed = 0
|
||||
for o in orders:
|
||||
s = o.get("state", "unknown")
|
||||
states[s] = states.get(s, 0) + 1
|
||||
total_qty += o.get("product_qty", 0)
|
||||
if s == "done":
|
||||
completed += 1
|
||||
|
||||
return {
|
||||
"period_days": days_back,
|
||||
"total_orders": len(orders),
|
||||
"by_state": states,
|
||||
"total_quantity": total_qty,
|
||||
"completion_rate": round(completed / max(len(orders), 1) * 100, 1),
|
||||
}
|
||||
|
||||
# --- Update production status ---
|
||||
|
||||
def update_production(self, mo_id: int, values: dict) -> dict:
|
||||
"""Generic update of a manufacturing order's fields.
|
||||
|
||||
Common fields: qty_produced, date_start, date_finished, origin, priority
|
||||
"""
|
||||
self.rpc.write("mrp.production", [mo_id], values)
|
||||
return {"id": mo_id, "updated_fields": list(values.keys()), "status": "updated"}
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# CLI
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def main() -> None:
|
||||
parser = argparse.ArgumentParser(description="Odoo Manufacturing Connector")
|
||||
parser.add_argument("--url", default="", help=f"Odoo URL (default: {ODOO_URL})")
|
||||
parser.add_argument("--db", default="", help=f"Database name (default: {ODOO_DB})")
|
||||
parser.add_argument("--user", default="", help=f"Username (default: {ODOO_USERNAME})")
|
||||
parser.add_argument("--password", default="", help="Password")
|
||||
|
||||
sub = parser.add_subparsers(dest="command")
|
||||
|
||||
# list-mo
|
||||
p_list = sub.add_parser("list-mo", help="List manufacturing orders")
|
||||
p_list.add_argument("--state", choices=["draft", "confirmed", "progress", "done", "cancel"])
|
||||
p_list.add_argument("--limit", type=int, default=20)
|
||||
|
||||
# create-mo
|
||||
p_create = sub.add_parser("create-mo", help="Create a manufacturing order")
|
||||
p_create.add_argument("--product", required=True, help="Product name")
|
||||
p_create.add_argument("--qty", type=float, required=True, help="Quantity to produce")
|
||||
p_create.add_argument("--origin", default="", help="Source document reference")
|
||||
|
||||
# list-wo
|
||||
p_wo = sub.add_parser("list-wo", help="List work orders")
|
||||
p_wo.add_argument("--mo-id", type=int, help="Filter by manufacturing order ID")
|
||||
p_wo.add_argument("--state", choices=["pending", "ready", "progress", "done", "cancel"])
|
||||
|
||||
# list-bom
|
||||
p_bom = sub.add_parser("list-bom", help="List bills of materials")
|
||||
p_bom.add_argument("--product", help="Filter by product name")
|
||||
|
||||
# summary
|
||||
p_sum = sub.add_parser("summary", help="Production analytics summary")
|
||||
p_sum.add_argument("--days", type=int, default=30, help="Days to look back")
|
||||
|
||||
# update
|
||||
p_up = sub.add_parser("update-mo", help="Update a manufacturing order")
|
||||
p_up.add_argument("--mo-id", type=int, required=True, help="MO ID")
|
||||
p_up.add_argument("--qty-produced", type=float, help="Quantity produced")
|
||||
p_up.add_argument("--priority", choices=["0", "1", "2", "3"], help="Priority level")
|
||||
|
||||
# confirm / done
|
||||
sub.add_parser("confirm-mo", help="Confirm a draft MO").add_argument("--mo-id", type=int, required=True)
|
||||
sub.add_parser("done-mo", help="Mark MO as done").add_argument("--mo-id", type=int, required=True)
|
||||
|
||||
args = parser.parse_args()
|
||||
|
||||
if not args.command:
|
||||
parser.print_help()
|
||||
sys.exit(1)
|
||||
|
||||
if not HAS_REQUESTS:
|
||||
print("ERROR: requests library required. pip install requests")
|
||||
sys.exit(1)
|
||||
|
||||
odoo = OdooMRP(
|
||||
url=args.url, db=args.db,
|
||||
username=args.user, password=args.password,
|
||||
)
|
||||
|
||||
try:
|
||||
if args.command == "list-mo":
|
||||
result = odoo.list_manufacturing_orders(state=args.state, limit=args.limit)
|
||||
elif args.command == "create-mo":
|
||||
result = odoo.create_manufacturing_order(args.product, args.qty, origin=args.origin)
|
||||
elif args.command == "list-wo":
|
||||
result = odoo.list_work_orders(production_id=getattr(args, "mo_id", None), state=args.state)
|
||||
elif args.command == "list-bom":
|
||||
result = odoo.list_bom(product_name=args.product)
|
||||
elif args.command == "summary":
|
||||
result = odoo.production_summary(days_back=args.days)
|
||||
elif args.command == "update-mo":
|
||||
vals = {}
|
||||
if args.qty_produced is not None:
|
||||
vals["qty_produced"] = args.qty_produced
|
||||
if args.priority:
|
||||
vals["priority"] = args.priority
|
||||
result = odoo.update_production(args.mo_id, vals)
|
||||
elif args.command == "confirm-mo":
|
||||
result = odoo.confirm_manufacturing_order(args.mo_id)
|
||||
elif args.command == "done-mo":
|
||||
result = odoo.mark_done(args.mo_id)
|
||||
else:
|
||||
parser.print_help()
|
||||
sys.exit(1)
|
||||
|
||||
print(json.dumps(result, indent=2, default=str))
|
||||
|
||||
except Exception as exc:
|
||||
print(f"ERROR: {exc}", file=sys.stderr)
|
||||
sys.exit(1)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -0,0 +1,292 @@
|
||||
#!/usr/bin/env python3
|
||||
"""MQTT local test — publish test messages and verify the MCP tools can read them.
|
||||
|
||||
Prerequisites:
|
||||
brew install mosquitto && brew services start mosquitto # macOS
|
||||
# OR: docker run -d -p 1883:1883 eclipse-mosquitto:2
|
||||
pip install paho-mqtt
|
||||
|
||||
Usage:
|
||||
python tools/industrial/test_mqtt_local.py [--broker localhost:1883]
|
||||
|
||||
The script:
|
||||
1. Connects to a local Mosquitto broker (localhost:1883)
|
||||
2. Publishes test messages on factory/line1/{temperature,pressure,motor_speed}
|
||||
3. Subscribes to wildcard factory/# and collects messages
|
||||
4. Verifies retained messages work
|
||||
5. Reports results and exits
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import argparse
|
||||
import json
|
||||
import random
|
||||
import sys
|
||||
import threading
|
||||
import time
|
||||
from typing import Any
|
||||
|
||||
try:
|
||||
import paho.mqtt.client as mqtt
|
||||
except ImportError:
|
||||
print("ERROR: paho-mqtt is required. pip install paho-mqtt")
|
||||
sys.exit(1)
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Config
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
TOPICS = [
|
||||
"factory/line1/temperature",
|
||||
"factory/line1/pressure",
|
||||
"factory/line1/motor_speed",
|
||||
]
|
||||
|
||||
passed = 0
|
||||
failed = 0
|
||||
|
||||
|
||||
def report(name: str, ok: bool, detail: str = "") -> None:
|
||||
global passed, failed
|
||||
status = "PASS" if ok else "FAIL"
|
||||
if ok:
|
||||
passed += 1
|
||||
else:
|
||||
failed += 1
|
||||
print(f" [{status}] {name}" + (f" -- {detail}" if detail else ""))
|
||||
|
||||
|
||||
def parse_broker(broker: str) -> tuple[str, int]:
|
||||
if ":" in broker:
|
||||
host, port_s = broker.rsplit(":", 1)
|
||||
try:
|
||||
return host, int(port_s)
|
||||
except ValueError:
|
||||
return broker, 1883
|
||||
return broker, 1883
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Test: basic connect
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def test_connect(host: str, port: int) -> bool:
|
||||
print("\n--- test_connect ---")
|
||||
try:
|
||||
client = mqtt.Client(mqtt.CallbackAPIVersion.VERSION2)
|
||||
client.connect(host, port, keepalive=10)
|
||||
client.disconnect()
|
||||
report("Connect to broker", True, f"{host}:{port}")
|
||||
return True
|
||||
except Exception as exc:
|
||||
report("Connect to broker", False, str(exc))
|
||||
print(f"\n HINT: Is Mosquitto running?")
|
||||
print(f" brew install mosquitto && brew services start mosquitto")
|
||||
print(f" # OR: docker run -d -p 1883:1883 eclipse-mosquitto:2\n")
|
||||
return False
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Test: publish + subscribe round-trip
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def test_pub_sub(host: str, port: int) -> None:
|
||||
print("\n--- test_pub_sub ---")
|
||||
received: list[dict] = []
|
||||
connected = threading.Event()
|
||||
done = threading.Event()
|
||||
|
||||
def on_connect(client: Any, userdata: Any, flags: Any, rc: Any, properties: Any = None) -> None:
|
||||
client.subscribe("factory/#", qos=1)
|
||||
connected.set()
|
||||
|
||||
def on_message(client: Any, userdata: Any, msg: Any) -> None:
|
||||
try:
|
||||
payload = json.loads(msg.payload.decode())
|
||||
except Exception:
|
||||
payload = msg.payload.decode()
|
||||
received.append({"topic": msg.topic, "payload": payload, "qos": msg.qos})
|
||||
|
||||
# Subscriber
|
||||
sub_client = mqtt.Client(mqtt.CallbackAPIVersion.VERSION2)
|
||||
sub_client.on_connect = on_connect
|
||||
sub_client.on_message = on_message
|
||||
sub_client.connect(host, port, keepalive=30)
|
||||
sub_client.loop_start()
|
||||
connected.wait(timeout=5)
|
||||
|
||||
if not connected.is_set():
|
||||
report("Subscriber connected", False, "timeout")
|
||||
sub_client.loop_stop()
|
||||
return
|
||||
|
||||
report("Subscriber connected", True)
|
||||
|
||||
# Publisher
|
||||
pub_client = mqtt.Client(mqtt.CallbackAPIVersion.VERSION2)
|
||||
pub_client.connect(host, port, keepalive=30)
|
||||
pub_client.loop_start()
|
||||
|
||||
published_count = 0
|
||||
for topic in TOPICS:
|
||||
for i in range(3):
|
||||
payload = json.dumps({
|
||||
"value": round(random.uniform(15, 85), 2),
|
||||
"unit": {"temperature": "C", "pressure": "bar", "motor_speed": "rpm"}
|
||||
.get(topic.split("/")[-1], "?"),
|
||||
"timestamp": time.time(),
|
||||
"seq": i,
|
||||
})
|
||||
info = pub_client.publish(topic, payload, qos=1)
|
||||
info.wait_for_publish(timeout=5)
|
||||
published_count += 1
|
||||
|
||||
report("Published messages", True, f"count={published_count}")
|
||||
|
||||
# Wait for messages to arrive
|
||||
time.sleep(2)
|
||||
|
||||
pub_client.loop_stop()
|
||||
pub_client.disconnect()
|
||||
sub_client.loop_stop()
|
||||
sub_client.disconnect()
|
||||
|
||||
report("Received messages", len(received) >= published_count,
|
||||
f"received={len(received)} expected>={published_count}")
|
||||
|
||||
# Check topics coverage
|
||||
received_topics = set(m["topic"] for m in received)
|
||||
for topic in TOPICS:
|
||||
report(f"Topic {topic} received", topic in received_topics)
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Test: retained messages
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def test_retained(host: str, port: int) -> None:
|
||||
print("\n--- test_retained ---")
|
||||
retain_topic = "factory/test/retained_check"
|
||||
retain_payload = json.dumps({"test": "retained", "ts": time.time()})
|
||||
|
||||
# Publish a retained message
|
||||
pub = mqtt.Client(mqtt.CallbackAPIVersion.VERSION2)
|
||||
pub.connect(host, port, keepalive=10)
|
||||
pub.loop_start()
|
||||
info = pub.publish(retain_topic, retain_payload, qos=1, retain=True)
|
||||
info.wait_for_publish(timeout=5)
|
||||
pub.loop_stop()
|
||||
pub.disconnect()
|
||||
report("Published retained message", True)
|
||||
|
||||
time.sleep(1)
|
||||
|
||||
# Subscribe and check if we get the retained message
|
||||
got_retained: list[dict] = []
|
||||
ready = threading.Event()
|
||||
|
||||
def on_connect(c: Any, ud: Any, fl: Any, rc: Any, props: Any = None) -> None:
|
||||
c.subscribe(retain_topic, qos=1)
|
||||
ready.set()
|
||||
|
||||
def on_message(c: Any, ud: Any, msg: Any) -> None:
|
||||
got_retained.append({"retain": msg.retain, "payload": msg.payload.decode()})
|
||||
|
||||
sub = mqtt.Client(mqtt.CallbackAPIVersion.VERSION2)
|
||||
sub.on_connect = on_connect
|
||||
sub.on_message = on_message
|
||||
sub.connect(host, port, keepalive=10)
|
||||
sub.loop_start()
|
||||
ready.wait(timeout=5)
|
||||
time.sleep(2)
|
||||
sub.loop_stop()
|
||||
sub.disconnect()
|
||||
|
||||
report("Received retained message", len(got_retained) > 0,
|
||||
f"count={len(got_retained)}")
|
||||
if got_retained:
|
||||
report("Retain flag set", got_retained[0].get("retain", False) is True)
|
||||
|
||||
# Cleanup: clear retained message
|
||||
cleanup = mqtt.Client(mqtt.CallbackAPIVersion.VERSION2)
|
||||
cleanup.connect(host, port, keepalive=10)
|
||||
cleanup.loop_start()
|
||||
cleanup.publish(retain_topic, b"", qos=1, retain=True).wait_for_publish(timeout=5)
|
||||
cleanup.loop_stop()
|
||||
cleanup.disconnect()
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Test: QoS levels
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def test_qos(host: str, port: int) -> None:
|
||||
print("\n--- test_qos ---")
|
||||
for qos_level in (0, 1, 2):
|
||||
topic = f"factory/test/qos{qos_level}"
|
||||
payload = f"qos_test_{qos_level}"
|
||||
received: list[str] = []
|
||||
ready = threading.Event()
|
||||
|
||||
def on_connect(c, ud, fl, rc, props=None, t=topic, q=qos_level):
|
||||
c.subscribe(t, qos=q)
|
||||
ready.set()
|
||||
|
||||
def on_message(c, ud, msg, r=received):
|
||||
r.append(msg.payload.decode())
|
||||
|
||||
sub = mqtt.Client(mqtt.CallbackAPIVersion.VERSION2)
|
||||
sub.on_connect = on_connect
|
||||
sub.on_message = on_message
|
||||
sub.connect(host, port, keepalive=10)
|
||||
sub.loop_start()
|
||||
ready.wait(timeout=5)
|
||||
|
||||
pub = mqtt.Client(mqtt.CallbackAPIVersion.VERSION2)
|
||||
pub.connect(host, port, keepalive=10)
|
||||
pub.loop_start()
|
||||
pub.publish(topic, payload, qos=qos_level).wait_for_publish(timeout=5)
|
||||
time.sleep(1)
|
||||
|
||||
pub.loop_stop()
|
||||
pub.disconnect()
|
||||
sub.loop_stop()
|
||||
sub.disconnect()
|
||||
|
||||
report(f"QoS {qos_level} round-trip", payload in received,
|
||||
f"received={received}")
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Main
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def main() -> None:
|
||||
parser = argparse.ArgumentParser(description="Test MQTT locally with Mosquitto")
|
||||
parser.add_argument("--broker", default="localhost:1883", help="MQTT broker host:port")
|
||||
args = parser.parse_args()
|
||||
|
||||
host, port = parse_broker(args.broker)
|
||||
|
||||
print("=" * 60)
|
||||
print("MQTT Local Test (Mosquitto)")
|
||||
print("=" * 60)
|
||||
|
||||
if not test_connect(host, port):
|
||||
print(f"\nCannot connect to {host}:{port}. Aborting.")
|
||||
sys.exit(1)
|
||||
|
||||
test_pub_sub(host, port)
|
||||
test_retained(host, port)
|
||||
test_qos(host, port)
|
||||
|
||||
print("\n" + "=" * 60)
|
||||
print(f"Results: {passed} passed, {failed} failed, {passed + failed} total")
|
||||
print("=" * 60)
|
||||
sys.exit(1 if failed else 0)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -0,0 +1,222 @@
|
||||
#!/usr/bin/env python3
|
||||
"""OPC-UA simulator + MCP tool tester.
|
||||
|
||||
Starts a local OPC-UA server with fake industrial nodes (temperature, pressure,
|
||||
motor_speed), then exercises the MCP tools from opcua_mcp.py against it.
|
||||
|
||||
Usage:
|
||||
pip install asyncua
|
||||
python tools/industrial/test_opcua_simulator.py
|
||||
|
||||
The script:
|
||||
1. Starts an OPC-UA server on opc.tcp://localhost:4840
|
||||
2. Creates a "Factory" namespace with 3 variable nodes
|
||||
3. Spawns a background task that updates values every 500ms
|
||||
4. Runs browse / read / write / subscribe tests against the server
|
||||
5. Reports results and exits
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
import json
|
||||
import random
|
||||
import sys
|
||||
import time
|
||||
|
||||
try:
|
||||
from asyncua import Server, ua
|
||||
except ImportError:
|
||||
print("ERROR: asyncua is required. pip install asyncua")
|
||||
sys.exit(1)
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Simulator server
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
async def create_server() -> tuple:
|
||||
"""Create and configure the OPC-UA simulator server."""
|
||||
server = Server()
|
||||
await server.init()
|
||||
server.set_endpoint("opc.tcp://0.0.0.0:4840/freeopcua/server/")
|
||||
server.set_server_name("Kill_LIFE Factory Simulator")
|
||||
|
||||
# Register namespace
|
||||
uri = "urn:killlife:factory:simulator"
|
||||
ns_idx = await server.register_namespace(uri)
|
||||
|
||||
# Create "Factory" object node
|
||||
factory = await server.nodes.objects.add_object(ns_idx, "Factory")
|
||||
|
||||
# Create variable nodes
|
||||
temperature = await factory.add_variable(
|
||||
ns_idx, "Temperature", 22.5, varianttype=ua.VariantType.Float
|
||||
)
|
||||
pressure = await factory.add_variable(
|
||||
ns_idx, "Pressure", 1.013, varianttype=ua.VariantType.Float
|
||||
)
|
||||
motor_speed = await factory.add_variable(
|
||||
ns_idx, "MotorSpeed", 1500.0, varianttype=ua.VariantType.Float
|
||||
)
|
||||
|
||||
# Make them writable
|
||||
await temperature.set_writable()
|
||||
await pressure.set_writable()
|
||||
await motor_speed.set_writable()
|
||||
|
||||
return server, ns_idx, temperature, pressure, motor_speed
|
||||
|
||||
|
||||
async def update_values(
|
||||
temperature, pressure, motor_speed, stop_event: asyncio.Event
|
||||
) -> None:
|
||||
"""Background task: jitter sensor values every 500ms."""
|
||||
while not stop_event.is_set():
|
||||
t = await temperature.read_value()
|
||||
p = await pressure.read_value()
|
||||
m = await motor_speed.read_value()
|
||||
|
||||
await temperature.write_value(
|
||||
ua.DataValue(ua.Variant(t + random.uniform(-0.5, 0.5), ua.VariantType.Float))
|
||||
)
|
||||
await pressure.write_value(
|
||||
ua.DataValue(ua.Variant(max(0.8, p + random.uniform(-0.01, 0.01)), ua.VariantType.Float))
|
||||
)
|
||||
await motor_speed.write_value(
|
||||
ua.DataValue(ua.Variant(max(0, m + random.uniform(-10, 10)), ua.VariantType.Float))
|
||||
)
|
||||
await asyncio.sleep(0.5)
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Test helpers (direct asyncua client, mirrors what opcua_mcp does)
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
from asyncua import Client as OPCUAClient # noqa: E402
|
||||
|
||||
|
||||
ENDPOINT = "opc.tcp://localhost:4840/freeopcua/server/"
|
||||
|
||||
passed = 0
|
||||
failed = 0
|
||||
|
||||
|
||||
def report(name: str, ok: bool, detail: str = "") -> None:
|
||||
global passed, failed
|
||||
status = "PASS" if ok else "FAIL"
|
||||
if ok:
|
||||
passed += 1
|
||||
else:
|
||||
failed += 1
|
||||
print(f" [{status}] {name}" + (f" -- {detail}" if detail else ""))
|
||||
|
||||
|
||||
async def test_browse(ns_idx: int) -> None:
|
||||
"""Test: browse Objects node and find Factory."""
|
||||
print("\n--- test_browse ---")
|
||||
async with OPCUAClient(url=ENDPOINT) as client:
|
||||
objects = client.nodes.objects
|
||||
children = await objects.get_children()
|
||||
names = []
|
||||
for child in children:
|
||||
bn = await child.read_browse_name()
|
||||
names.append(bn.Name)
|
||||
report("Objects has children", len(names) > 0, f"found {names}")
|
||||
report("Factory node exists", "Factory" in names)
|
||||
|
||||
|
||||
async def test_read(ns_idx: int) -> None:
|
||||
"""Test: read temperature node."""
|
||||
print("\n--- test_read ---")
|
||||
async with OPCUAClient(url=ENDPOINT) as client:
|
||||
node = client.get_node(f"ns={ns_idx};s=Temperature")
|
||||
value = await node.read_value()
|
||||
report("Temperature is a float", isinstance(value, float), f"value={value}")
|
||||
report("Temperature in sane range", 10 < value < 50, f"value={value}")
|
||||
|
||||
|
||||
async def test_write(ns_idx: int) -> None:
|
||||
"""Test: write a setpoint then read it back."""
|
||||
print("\n--- test_write ---")
|
||||
async with OPCUAClient(url=ENDPOINT) as client:
|
||||
node = client.get_node(f"ns={ns_idx};s=MotorSpeed")
|
||||
new_val = 999.0
|
||||
await node.write_value(ua.DataValue(ua.Variant(new_val, ua.VariantType.Float)))
|
||||
readback = await node.read_value()
|
||||
report("Write + readback matches", abs(readback - new_val) < 0.01, f"wrote={new_val} read={readback}")
|
||||
|
||||
|
||||
async def test_subscribe(ns_idx: int) -> None:
|
||||
"""Test: subscribe to Pressure for 3 seconds, expect value changes."""
|
||||
print("\n--- test_subscribe ---")
|
||||
values: list[float] = []
|
||||
|
||||
class Handler:
|
||||
def datachange_notification(self, node, val, data):
|
||||
values.append(val)
|
||||
|
||||
async with OPCUAClient(url=ENDPOINT) as client:
|
||||
handler = Handler()
|
||||
sub = await client.create_subscription(200, handler)
|
||||
target = client.get_node(f"ns={ns_idx};s=Pressure")
|
||||
await sub.subscribe_data_change(target)
|
||||
await asyncio.sleep(3)
|
||||
await sub.delete()
|
||||
|
||||
report("Received data-change events", len(values) >= 2, f"count={len(values)}")
|
||||
report("Values differ (sensor updates)", len(set(str(v) for v in values)) >= 2 if values else False)
|
||||
|
||||
|
||||
async def test_multi_node_read(ns_idx: int) -> None:
|
||||
"""Test: read all 3 nodes in sequence."""
|
||||
print("\n--- test_multi_node_read ---")
|
||||
async with OPCUAClient(url=ENDPOINT) as client:
|
||||
results = {}
|
||||
for name in ("Temperature", "Pressure", "MotorSpeed"):
|
||||
node = client.get_node(f"ns={ns_idx};s={name}")
|
||||
results[name] = await node.read_value()
|
||||
report("All 3 nodes readable", len(results) == 3, json.dumps(results, default=str))
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Main
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
async def main() -> None:
|
||||
global passed, failed
|
||||
|
||||
print("=" * 60)
|
||||
print("OPC-UA Simulator + MCP Tool Test")
|
||||
print("=" * 60)
|
||||
|
||||
# Start server
|
||||
server, ns_idx, temperature, pressure, motor_speed = await create_server()
|
||||
await server.start()
|
||||
print(f"Server started on {ENDPOINT}")
|
||||
|
||||
stop = asyncio.Event()
|
||||
updater = asyncio.create_task(update_values(temperature, pressure, motor_speed, stop))
|
||||
|
||||
# Give server time to settle
|
||||
await asyncio.sleep(1)
|
||||
|
||||
try:
|
||||
await test_browse(ns_idx)
|
||||
await test_read(ns_idx)
|
||||
await test_write(ns_idx)
|
||||
await test_subscribe(ns_idx)
|
||||
await test_multi_node_read(ns_idx)
|
||||
finally:
|
||||
stop.set()
|
||||
await updater
|
||||
await server.stop()
|
||||
|
||||
print("\n" + "=" * 60)
|
||||
print(f"Results: {passed} passed, {failed} failed, {passed + failed} total")
|
||||
print("=" * 60)
|
||||
sys.exit(1 if failed else 0)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
Reference in New Issue
Block a user