agent2/agent2.py

#!/usr/bin/env python3
# -*- coding: utf-8 -*-

import asyncio
import sys
import requests
import json
from pathlib import Path
from slixmpp import ClientXMPP

# Ajouter /opt/agent2 au path pour importer les skills
sys.path.insert(0, "/opt/agent2")

from skills.loader import load_skills, run_skills

# ── CONFIG ───────────────────────────────────────────────────────────────
CONFIG_DIR  = Path("/opt/agent2/config")
CONFIG_FILE = CONFIG_DIR / "config.json"
PROMPT_FILE = CONFIG_DIR / "system_prompt.txt"

def load_config():
    with open(CONFIG_FILE, "r", encoding="utf-8") as f:
        return json.load(f)

def load_system_prompt():
    with open(PROMPT_FILE, "r", encoding="utf-8") as f:
        return f.read()

cfg           = load_config()
OLLAMA_URL    = cfg["ollama_url"]
MODEL         = cfg["model"]
XMPP_JID      = cfg["xmpp_jid"]
XMPP_PASS     = cfg["xmpp_pass"]
ADMIN_JID     = cfg["admin_jid"]
SYSTEM_PROMPT = load_system_prompt()

# Charger les skills au démarrage
load_skills()

conversation_history = []

# ── LLM ──────────────────────────────────────────────────────────────────
def call_ollama(messages: list) -> str:
    payload = {
        "model"   : MODEL,
        "messages": messages,
        "stream"  : False,
        "options" : {"temperature": 0.3}
    }
    response = requests.post(OLLAMA_URL, json=payload, timeout=180)
    data     = response.json()
    return data["message"]["content"]

def ask_llm(user_message: str) -> str:
    conversation_history.append({"role": "user", "content": user_message})
    messages = [{"role": "system", "content": SYSTEM_PROMPT}] + conversation_history

    try:
        # Boucle agentique : le LLM peut enchaîner plusieurs skills
        MAX_STEPS = 5
        for _ in range(MAX_STEPS):
            reply = call_ollama(messages)
            skill_triggered, result = run_skills(reply)

            if not skill_triggered:
                # Réponse finale sans commande
                conversation_history.append({"role": "assistant", "content": reply})
                return reply

            # Injecter le résultat du skill et relancer le LLM
            messages.append({"role": "assistant", "content": reply})
            messages.append({"role": "user",      "content": "[Résultat skill]\n" + result})

        # Sécurité : trop d'étapes
        reply = call_ollama(messages)
        conversation_history.append({"role": "assistant", "content": reply})
        return reply

    except Exception as e:
        error_reply = "Erreur : " + str(e)
        conversation_history.append({"role": "assistant", "content": error_reply})
        return error_reply

# ── BOT XMPP ─────────────────────────────────────────────────────────────
class AgentBot(ClientXMPP):
    def __init__(self):
        ClientXMPP.__init__(self, XMPP_JID, XMPP_PASS)
        self.add_event_handler("session_start", self.session_start)
        self.add_event_handler("message",       self.message)
        self.register_plugin('xep_0030')
        self.register_plugin('xep_0199')

    async def session_start(self, event):
        self.send_presence()
        await self.get_roster()
        self.send_message(mto=ADMIN_JID, mbody="Agent en ligne !", mtype='chat')

    async def message(self, msg):
        if msg['type'] not in ('chat', 'normal'):
            return
        if str(msg['from']).split('/')[0] != ADMIN_JID:
            return

        user_input = msg['body'].strip()

        if user_input == "!reset":
            conversation_history.clear()
            self.send_message(mto=ADMIN_JID, mbody="Conversation reinitialisee.", mtype='chat')
            return

        loop  = asyncio.get_event_loop()
        reply = await loop.run_in_executor(None, ask_llm, user_input)
        self.send_message(mto=ADMIN_JID, mbody=reply, mtype='chat')

# ── MAIN ─────────────────────────────────────────────────────────────────
if __name__ == "__main__":
    bot = AgentBot()
    bot.connect()
    bot.loop.run_forever()