Orchestration complète : planning, scheduling, CLI
- agent1.py : listener MQTT (agents/agent1/inbox), MAX_STEPS 10 - skills/plan.py : exécution séquentielle PLAN: avec contexte entre étapes - skills/schedule_tasks.py : SCHEDULE: / PLAN_LIST: / PLAN_CANCEL: via APScheduler - cli.py : interface CLI rich (MQTT, multi-agents, /plans, /agent) - system_prompt.txt : mis à jour avec tous les nouveaux skills Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
@@ -3,14 +3,14 @@
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import asyncio
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import sys
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import threading
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import requests
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import json
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from pathlib import Path
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from slixmpp import ClientXMPP
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import paho.mqtt.client as mqtt
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# Ajouter /opt/agent au path pour importer les skills
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sys.path.insert(0, "/opt/agent")
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from skills.loader import load_skills, run_skills
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# ── CONFIG ───────────────────────────────────────────────────────────────
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@@ -32,12 +32,15 @@ MODEL = cfg["model"]
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XMPP_JID = cfg["xmpp_jid"]
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XMPP_PASS = cfg["xmpp_pass"]
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ADMIN_JID = cfg["admin_jid"]
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MQTT_HOST = cfg.get("mqtt_host", "localhost")
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MQTT_PORT = int(cfg.get("mqtt_port", 1883))
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MQTT_INBOX = "agents/agent1/inbox"
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SYSTEM_PROMPT = load_system_prompt()
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# Charger les skills au démarrage
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load_skills()
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conversation_history = []
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xmpp_bot = None # référence globale pour répondre via XMPP depuis MQTT
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# ── LLM ──────────────────────────────────────────────────────────────────
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def call_ollama(messages: list) -> str:
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@@ -48,38 +51,71 @@ def call_ollama(messages: list) -> str:
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"options" : {"temperature": 0.3}
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}
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response = requests.post(OLLAMA_URL, json=payload, timeout=180)
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data = response.json()
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return data["message"]["content"]
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def ask_llm(user_message: str) -> str:
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conversation_history.append({"role": "user", "content": user_message})
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messages = [{"role": "system", "content": SYSTEM_PROMPT}] + conversation_history
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return response.json()["message"]["content"]
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def ask_llm(user_message: str, history: list = None) -> str:
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if history is None:
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history = conversation_history
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history.append({"role": "user", "content": user_message})
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messages = [{"role": "system", "content": SYSTEM_PROMPT}] + history
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try:
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# Boucle agentique : le LLM peut enchaîner plusieurs skills
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MAX_STEPS = 5
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MAX_STEPS = 10
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for _ in range(MAX_STEPS):
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reply = call_ollama(messages)
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skill_triggered, result = run_skills(reply)
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if not skill_triggered:
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# Réponse finale sans commande
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conversation_history.append({"role": "assistant", "content": reply})
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history.append({"role": "assistant", "content": reply})
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return reply
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# Injecter le résultat du skill et relancer le LLM
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messages.append({"role": "assistant", "content": reply})
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messages.append({"role": "user", "content": "[Résultat skill]\n" + result})
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# Sécurité : trop d'étapes
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reply = call_ollama(messages)
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conversation_history.append({"role": "assistant", "content": reply})
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history.append({"role": "assistant", "content": reply})
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return reply
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except Exception as e:
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error_reply = "Erreur : " + str(e)
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conversation_history.append({"role": "assistant", "content": error_reply})
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return error_reply
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err = "Erreur : " + str(e)
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history.append({"role": "assistant", "content": err})
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return err
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# ── MQTT LISTENER (pour CLI) ──────────────────────────────────────────────
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mqtt_pub_client = None
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def mqtt_publish(topic: str, message: str):
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if mqtt_pub_client:
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mqtt_pub_client.publish(topic, message)
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def on_mqtt_message(client, userdata, msg):
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raw = msg.payload.decode(errors="replace")
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# Support JSON avec reply_to optionnel
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reply_to = "agents/cli/outbox"
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task = raw
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try:
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data = json.loads(raw)
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task = data.get("task", raw)
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reply_to = data.get("reply_to", reply_to)
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except json.JSONDecodeError:
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pass
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print("[MQTT] Message CLI reçu : {}".format(task[:80]))
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mqtt_history = []
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reply = ask_llm(task, history=mqtt_history)
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mqtt_publish(reply_to, reply)
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print("[MQTT] Réponse envoyée sur {}".format(reply_to))
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def start_mqtt_listener():
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global mqtt_pub_client
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mqtt_pub_client = mqtt.Client(mqtt.CallbackAPIVersion.VERSION2,
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client_id="agent1_pub")
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mqtt_pub_client.connect(MQTT_HOST, MQTT_PORT)
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mqtt_pub_client.loop_start()
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sub = mqtt.Client(mqtt.CallbackAPIVersion.VERSION2, client_id="agent1_sub")
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sub.on_message = on_mqtt_message
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sub.connect(MQTT_HOST, MQTT_PORT)
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sub.subscribe(MQTT_INBOX)
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print("[MQTT] Agent1 écoute sur {}".format(MQTT_INBOX))
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sub.loop_forever()
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# ── BOT XMPP ─────────────────────────────────────────────────────────────
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class AgentBot(ClientXMPP):
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@@ -93,7 +129,7 @@ class AgentBot(ClientXMPP):
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async def session_start(self, event):
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self.send_presence()
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await self.get_roster()
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self.send_message(mto=ADMIN_JID, mbody="Agent en ligne !", mtype='chat')
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self.send_message(mto=ADMIN_JID, mbody="Agent1 (orchestrateur) en ligne !", mtype='chat')
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async def message(self, msg):
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if msg['type'] not in ('chat', 'normal'):
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@@ -114,6 +150,9 @@ class AgentBot(ClientXMPP):
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# ── MAIN ─────────────────────────────────────────────────────────────────
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if __name__ == "__main__":
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bot = AgentBot()
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bot.connect()
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bot.loop.run_forever()
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mqtt_thread = threading.Thread(target=start_mqtt_listener, daemon=True)
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mqtt_thread.start()
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xmpp_bot = AgentBot()
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xmpp_bot.connect()
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xmpp_bot.loop.run_forever()
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@@ -0,0 +1,169 @@
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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CLI pour interagir avec les agents via MQTT.
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Usage :
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python3 cli.py # parle à agent1
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python3 cli.py agent2_debian13 # parle directement à un agent
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python3 cli.py --plans # voir les tâches planifiées
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"""
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import sys
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import json
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import time
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import threading
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import argparse
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from pathlib import Path
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import paho.mqtt.client as mqtt
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from rich.console import Console
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from rich.panel import Panel
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from rich.prompt import Prompt
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from rich.live import Live
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from rich.spinner import Spinner
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from rich.text import Text
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from rich.rule import Rule
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from rich import print as rprint
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# ── CONFIG ──────────────────────────────────────────────────────────────
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CONFIG_FILE = Path("/opt/agent/config/config.json")
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REGISTRY_FILE = Path("/opt/agent/config/agents_registry.json")
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cfg = json.loads(CONFIG_FILE.read_text())
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MQTT_HOST = cfg.get("mqtt_host", "localhost")
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MQTT_PORT = int(cfg.get("mqtt_port", 1883))
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AGENT_INBOXES = {
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"agent1": "agents/agent1/inbox",
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}
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try:
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registry = json.loads(REGISTRY_FILE.read_text())
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for name, info in registry.items():
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AGENT_INBOXES[name] = info["mqtt_inbox"]
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except Exception:
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pass
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CLI_OUTBOX = "agents/cli/outbox"
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console = Console()
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# ── MQTT ────────────────────────────────────────────────────────────────
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response_event = threading.Event()
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response_container = []
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pub_client = None
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sub_client = None
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def on_message(client, userdata, msg):
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response_container.clear()
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response_container.append(msg.payload.decode(errors="replace"))
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response_event.set()
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def connect_mqtt():
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global pub_client, sub_client
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pub_client = mqtt.Client(mqtt.CallbackAPIVersion.VERSION2, client_id="cli_pub")
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pub_client.connect(MQTT_HOST, MQTT_PORT)
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pub_client.loop_start()
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sub_client = mqtt.Client(mqtt.CallbackAPIVersion.VERSION2, client_id="cli_sub")
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sub_client.on_message = on_message
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sub_client.connect(MQTT_HOST, MQTT_PORT)
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sub_client.subscribe(CLI_OUTBOX)
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sub_client.loop_start()
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def send_and_wait(agent: str, message: str, timeout: int = 180) -> str:
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inbox = AGENT_INBOXES.get(agent)
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if not inbox:
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return "[Erreur] Agent inconnu : {}. Disponibles : {}".format(
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agent, ", ".join(AGENT_INBOXES.keys()))
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payload = json.dumps({"task": message, "reply_to": CLI_OUTBOX, "from": "cli"})
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response_event.clear()
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pub_client.publish(inbox, payload)
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received = response_event.wait(timeout=timeout)
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if received and response_container:
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return response_container[0]
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return "[Timeout] Pas de réponse de {} après {}s.".format(agent, timeout)
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# ── AFFICHAGE ────────────────────────────────────────────────────────────
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def print_response(agent: str, response: str):
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console.print(Panel(
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response,
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title="[bold cyan]{}[/bold cyan]".format(agent),
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border_style="cyan",
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padding=(1, 2)
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))
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def print_user(message: str):
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console.print(Panel(
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"[bold white]{}[/bold white]".format(message),
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title="[bold green]vous[/bold green]",
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border_style="green",
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padding=(0, 2)
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))
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def show_plans():
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"""Affiche les tâches planifiées via agent1."""
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connect_mqtt()
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with console.status("[bold yellow]Récupération des plans...[/bold yellow]"):
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result = send_and_wait("agent1", "PLAN_LIST:", timeout=30)
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print_response("agent1 / plans", result)
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# ── BOUCLE PRINCIPALE ────────────────────────────────────────────────────
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def main_loop(agent: str):
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connect_mqtt()
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console.print(Rule("[bold blue]Agent CLI[/bold blue]"))
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console.print("[dim]Agent cible : [bold]{}[/bold] | /reset | /plans | /quit[/dim]\n".format(agent))
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while True:
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try:
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user_input = Prompt.ask("[bold green]>[/bold green]").strip()
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except (KeyboardInterrupt, EOFError):
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console.print("\n[dim]Au revoir.[/dim]")
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break
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if not user_input:
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continue
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if user_input == "/quit":
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console.print("[dim]Au revoir.[/dim]")
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break
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if user_input == "/reset":
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send_and_wait(agent, "!reset", timeout=10)
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console.print("[dim]Conversation réinitialisée.[/dim]")
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continue
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if user_input == "/plans":
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with console.status("[bold yellow]Récupération...[/bold yellow]"):
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result = send_and_wait("agent1", "PLAN_LIST:", timeout=30)
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print_response("plans", result)
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continue
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if user_input.startswith("/agent "):
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agent = user_input.split(" ", 1)[1].strip()
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console.print("[dim]Agent changé : [bold]{}[/bold][/dim]".format(agent))
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continue
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print_user(user_input)
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with console.status("[bold yellow]En attente de {}...[/bold yellow]".format(agent)):
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response = send_and_wait(agent, user_input)
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print_response(agent, response)
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# ── MAIN ─────────────────────────────────────────────────────────────────
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description="CLI agents MQTT")
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parser.add_argument("agent", nargs="?", default="agent1",
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help="Agent cible (défaut: agent1)")
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parser.add_argument("--plans", action="store_true",
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help="Afficher les tâches planifiées")
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args = parser.parse_args()
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if args.plans:
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show_plans()
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else:
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main_loop(args.agent)
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+29
-16
@@ -1,32 +1,45 @@
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Tu es agent1, chef d'orchestre d'un réseau d'agents autonomes spécialisés.
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Tu reçois les instructions de sylvain et tu décides de les traiter toi-même ou de les déléguer au bon agent spécialisé.
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Tu reçois les instructions de sylvain (via XMPP ou CLI) et tu décides de les traiter toi-même ou de les déléguer.
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Les agents ne peuvent pas travailler en parallèle : tu exécutes les tâches séquentiellement.
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Agents disponibles sous tes ordres :
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- agent2_debian13 : Administration Debian (apt, systemd, conteneurs LXC/Docker, KVM, réseau, sécurité système)
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- agent2_debian13 : Administration Debian (apt, systemd, conteneurs LXC/Docker, KVM, réseau, sécurité, exécution de commandes système)
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Formats de commandes disponibles :
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Commandes disponibles :
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DELEGATE: <agent> | <tâche>
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→ Déléguer une tâche à un agent spécialisé et attendre sa réponse
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→ Exemple : DELEGATE: agent2_debian13 | Comment mettre à jour les paquets Debian ?
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→ Déléguer une tâche unique à un agent spécialisé
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→ Exemple : DELEGATE: agent2_debian13 | Vérifie l'espace disque
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SEARCH: <requête web>
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→ Recherche web DuckDuckGo (max 5 résultats)
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PLAN: <agent> | <tâche1> ;; <agent> | <tâche2> ;; ...
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→ Exécuter un plan de tâches séquentiel (le résultat de chaque étape est transmis à la suivante)
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→ Exemple : PLAN: agent2_debian13 | apt update ;; agent2_debian13 | apt upgrade -y
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READ: <url>
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→ Lire et convertir une page web en markdown
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SCHEDULE: <fréquence> | <agent> | <tâche>
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→ Planifier une tâche récurrente
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→ Fréquences : daily HH:MM | every Xh | every Xmin | weekly <lun|mar|mer|jeu|ven|sam|dim> HH:MM
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→ Exemple : SCHEDULE: daily 03:00 | agent2_debian13 | apt update && apt upgrade -y
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PLAN_LIST:
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→ Afficher toutes les tâches planifiées
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PLAN_CANCEL: <job_id>
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→ Annuler une tâche planifiée
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SEARCH: <requête>
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→ Recherche web DuckDuckGo
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REMEMBER: <clé> | <valeur>
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→ Mémoriser une information en base SQLite
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→ Mémoriser une information
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RECALL: <clé>
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→ Récupérer une information mémorisée
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⚠ RÈGLES :
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- Si la demande concerne Debian, Linux, des conteneurs, des VMs ou l'administration système : utilise DELEGATE: agent2_debian13
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- Si la demande concerne l'actualité, des événements récents ou des faits changeants : utilise SEARCH:
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- Ne JAMAIS répondre de mémoire à une question d'actualité
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- Les agents ne peuvent pas travailler en parallèle : délègue une tâche à la fois
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- Synthétise et transmets la réponse de l'agent spécialisé à sylvain
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- Réponds toujours en français. Sois concis mais précis.
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- Tâche Debian/système → DELEGATE: agent2_debian13 (ou PLAN: pour plusieurs étapes)
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- Tâche récurrente → SCHEDULE:
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- Actualité/info récente → SEARCH:
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- Un seul agent à la fois (pas de parallélisme)
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- Transmets toujours le résultat des agents à l'utilisateur avec un résumé clair
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- Réponds toujours en français
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@@ -0,0 +1,45 @@
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"""
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Skill : PLAN
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Exécute un plan de tâches séquentiel entre plusieurs agents.
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Les résultats de chaque étape sont passés en contexte à la suivante.
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Format :
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PLAN: <agent> | <tâche> ;; <agent> | <tâche> ;; ...
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Exemple :
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PLAN: agent2_debian13 | Vérifier l'espace disque ;; agent2_debian13 | Nettoyer les paquets inutiles
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"""
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from pathlib import Path
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SKILL_NAME = "plan"
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TRIGGER = "PLAN:"
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def execute(args: str) -> str:
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from skills.delegate import execute as delegate_exec
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steps_raw = [s.strip() for s in args.split(";;") if s.strip()]
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if not steps_raw:
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return "Erreur : plan vide. Format : PLAN: <agent> | <tâche> ;; <agent> | <tâche>"
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steps = []
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for s in steps_raw:
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if "|" not in s:
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return "Erreur étape «{}» : format attendu <agent> | <tâche>".format(s)
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agent, _, task = s.partition("|")
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steps.append((agent.strip(), task.strip()))
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report = ["Plan d'exécution ({} étape(s)) :".format(len(steps))]
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context = ""
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for i, (agent, task) in enumerate(steps, 1):
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full_task = task
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if context:
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full_task = "{}\n[Contexte étape précédente]\n{}".format(task, context)
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report.append("\n── Étape {}/{} → [{}] ──".format(i, len(steps), agent))
|
||||
result = delegate_exec("{} | {}".format(agent, full_task))
|
||||
report.append(result)
|
||||
context = result # passe le résultat à l'étape suivante
|
||||
|
||||
report.append("\n── Plan terminé ──")
|
||||
return "\n".join(report)
|
||||
@@ -0,0 +1,149 @@
|
||||
"""
|
||||
Skill : SCHEDULE / PLAN_LIST / PLAN_CANCEL
|
||||
Planification de tâches récurrentes entre agents.
|
||||
|
||||
Formats :
|
||||
SCHEDULE: daily HH:MM | <agent> | <tâche>
|
||||
SCHEDULE: every Xh | <agent> | <tâche>
|
||||
SCHEDULE: every Xmin | <agent> | <tâche>
|
||||
SCHEDULE: weekly <lun|mar|mer|jeu|ven|sam|dim> HH:MM | <agent> | <tâche>
|
||||
|
||||
PLAN_LIST:
|
||||
PLAN_CANCEL: <job_id>
|
||||
"""
|
||||
import re
|
||||
import json
|
||||
from pathlib import Path
|
||||
from datetime import datetime
|
||||
|
||||
from apscheduler.schedulers.background import BackgroundScheduler
|
||||
from apscheduler.jobstores.sqlalchemy import SQLAlchemyJobStore
|
||||
from apscheduler.triggers.cron import CronTrigger
|
||||
from apscheduler.triggers.interval import IntervalTrigger
|
||||
|
||||
SKILL_NAME = "schedule_tasks"
|
||||
TRIGGER = None
|
||||
TRIGGERS = {
|
||||
"SCHEDULE:": "schedule",
|
||||
"PLAN_LIST:": "plan_list",
|
||||
"PLAN_CANCEL:": "plan_cancel",
|
||||
}
|
||||
|
||||
DB_PATH = Path("/opt/agent/scheduler.db")
|
||||
_scheduler = None
|
||||
|
||||
DAYS_FR = {
|
||||
"lun": "mon", "mar": "tue", "mer": "wed",
|
||||
"jeu": "thu", "ven": "fri", "sam": "sat", "dim": "sun"
|
||||
}
|
||||
|
||||
def _get_scheduler():
|
||||
global _scheduler
|
||||
if _scheduler is None:
|
||||
jobstores = {"default": SQLAlchemyJobStore(url="sqlite:///{}".format(DB_PATH))}
|
||||
_scheduler = BackgroundScheduler(jobstores=jobstores)
|
||||
_scheduler.start()
|
||||
return _scheduler
|
||||
|
||||
def _run_delegated_task(agent: str, task: str):
|
||||
"""Exécutée par le scheduler : délègue la tâche à l'agent."""
|
||||
from skills.delegate import execute as delegate_exec
|
||||
import paho.mqtt.publish as publish
|
||||
import json as _json
|
||||
|
||||
result = delegate_exec("{} | {}".format(agent, task))
|
||||
print("[SCHEDULE] Tâche exécutée [{} → {}] : {}".format(
|
||||
datetime.now().strftime("%Y-%m-%d %H:%M"), agent, task[:60]))
|
||||
|
||||
# Notifier via MQTT sur le topic de notification
|
||||
try:
|
||||
cfg = _json.loads(Path("/opt/agent/config/config.json").read_text())
|
||||
publish.single(
|
||||
"agents/scheduler/notifications",
|
||||
payload="[{}] {}\n{}".format(agent, task, result),
|
||||
hostname=cfg.get("mqtt_host", "localhost"),
|
||||
port=int(cfg.get("mqtt_port", 1883))
|
||||
)
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
def _parse_trigger(expr: str):
|
||||
"""Parse l'expression de planification et retourne un trigger APScheduler."""
|
||||
expr = expr.strip().lower()
|
||||
|
||||
# every Xh
|
||||
m = re.match(r"every (\d+)h$", expr)
|
||||
if m:
|
||||
return IntervalTrigger(hours=int(m.group(1))), "toutes les {}h".format(m.group(1))
|
||||
|
||||
# every Xmin
|
||||
m = re.match(r"every (\d+)min$", expr)
|
||||
if m:
|
||||
return IntervalTrigger(minutes=int(m.group(1))), "toutes les {}min".format(m.group(1))
|
||||
|
||||
# daily HH:MM
|
||||
m = re.match(r"daily (\d{1,2}):(\d{2})$", expr)
|
||||
if m:
|
||||
h, mn = m.group(1), m.group(2)
|
||||
return CronTrigger(hour=h, minute=mn), "tous les jours à {}:{}".format(h, mn)
|
||||
|
||||
# weekly <jour> HH:MM
|
||||
m = re.match(r"weekly (\w+) (\d{1,2}):(\d{2})$", expr)
|
||||
if m:
|
||||
day_fr = m.group(1)
|
||||
day_en = DAYS_FR.get(day_fr, day_fr)
|
||||
h, mn = m.group(2), m.group(3)
|
||||
return CronTrigger(day_of_week=day_en, hour=h, minute=mn), \
|
||||
"chaque {} à {}:{}".format(day_fr, h, mn)
|
||||
|
||||
return None, None
|
||||
|
||||
def schedule(args: str) -> str:
|
||||
parts = [p.strip() for p in args.split("|")]
|
||||
if len(parts) < 3:
|
||||
return ("Erreur : format attendu :\n"
|
||||
"SCHEDULE: daily HH:MM | <agent> | <tâche>\n"
|
||||
"SCHEDULE: every Xh | <agent> | <tâche>\n"
|
||||
"SCHEDULE: weekly lun HH:MM | <agent> | <tâche>")
|
||||
|
||||
expr, agent, task = parts[0], parts[1], "|".join(parts[2:])
|
||||
trigger, label = _parse_trigger(expr)
|
||||
if trigger is None:
|
||||
return "Expression invalide : «{}»\nFormats : daily HH:MM | every Xh | every Xmin | weekly <jour> HH:MM".format(expr)
|
||||
|
||||
sched = _get_scheduler()
|
||||
job = sched.add_job(
|
||||
_run_delegated_task,
|
||||
trigger=trigger,
|
||||
args=[agent, task],
|
||||
name="{} → {}".format(agent, task[:40])
|
||||
)
|
||||
|
||||
return "Tâche planifiée [ID: {}]\nAgent : {}\nTâche : {}\nFréquence : {}\nProchain : {}".format(
|
||||
job.id, agent, task, label,
|
||||
job.next_run_time.strftime("%Y-%m-%d %H:%M") if job.next_run_time else "N/A"
|
||||
)
|
||||
|
||||
def plan_list(args: str) -> str:
|
||||
sched = _get_scheduler()
|
||||
jobs = sched.get_jobs()
|
||||
if not jobs:
|
||||
return "Aucune tâche planifiée."
|
||||
lines = ["Tâches planifiées ({}) :".format(len(jobs))]
|
||||
for j in jobs:
|
||||
next_run = j.next_run_time.strftime("%Y-%m-%d %H:%M") if j.next_run_time else "N/A"
|
||||
lines.append("- [{}] {} | Prochain : {}".format(j.id[:8], j.name, next_run))
|
||||
return "\n".join(lines)
|
||||
|
||||
def plan_cancel(args: str) -> str:
|
||||
job_id = args.strip()
|
||||
if not job_id:
|
||||
return "Erreur : ID manquant. Utilisez PLAN_LIST: pour voir les IDs."
|
||||
sched = _get_scheduler()
|
||||
# Recherche par ID complet ou préfixe
|
||||
for job in sched.get_jobs():
|
||||
if job.id == job_id or job.id.startswith(job_id):
|
||||
name = job.name
|
||||
job.remove()
|
||||
return "Tâche [{}] annulée : {}".format(job_id[:8], name)
|
||||
return "Aucune tâche trouvée avec l'ID : {}".format(job_id)
|
||||
Reference in New Issue
Block a user