hsbg-ai/hsbg_ai/backend/ai/engine/llm_advisor.py

"""Conseiller LLM local via Ollama — enrichit les décisions heuristiques."""
import json
import httpx
import structlog
from backend.ai.engine.decision_engine import GameState, Decision, FullAdvice

log = structlog.get_logger()

SYSTEM_PROMPT = """Tu es un expert Hearthstone Battlegrounds rang Légende.
Analyse l'état de jeu et donne un conseil tactique optimal.
Réponds UNIQUEMENT avec un objet JSON valide, sans texte avant/après, sans markdown:
{"main_action":"buy|sell|freeze|upgrade|reposition|hero_power|wait","target_card":null,"priority":7,"confidence":0.8,"reasoning":"explication courte","strategy":"stratégie long terme 1 phrase","threats":"principale menace adversaire","warnings":[]}"""


class LLMAdvisor:
    """Interface avec Ollama pour les conseils LLM."""

    def __init__(self, settings):
        self.settings = settings
        self.base_url = settings.llm_base_url
        self.model = settings.llm_model
        self._client: httpx.AsyncClient | None = None
        self._available = False

    async def initialize(self):
        """Teste la disponibilité d'Ollama et du modèle."""
        self._client = httpx.AsyncClient(timeout=10)
        try:
            r = await self._client.get(f"{self.base_url}/api/tags")
            if r.status_code == 200:
                models = r.json().get("models", [])
                model_names = [m.get("name", "") for m in models]
                self._available = any(self.model in name for name in model_names)
                if self._available:
                    log.info("llm.ready", model=self.model)
                else:
                    log.warning("llm.model_not_found", model=self.model,
                               available=model_names,
                               hint=f"Exécutez: ollama pull {self.model}")
        except Exception as e:
            log.warning("llm.ollama_unreachable", url=self.base_url, error=str(e),
                       hint="Installez Ollama: curl -fsSL https://ollama.ai/install.sh | sh")
            self._available = False

    async def advise(self, state: GameState, heuristics: list[Decision]) -> FullAdvice | None:
        """Demande un conseil au LLM local."""
        if not self._available or not self._client:
            return None

        prompt = self._build_prompt(state, heuristics)

        try:
            r = await self._client.post(
                f"{self.base_url}/api/generate",
                json={
                    "model": self.model,
                    "prompt": prompt,
                    "system": SYSTEM_PROMPT,
                    "stream": False,
                    "options": {
                        "temperature": self.settings.llm_temperature,
                        "num_predict": self.settings.llm_max_tokens,
                    },
                },
                timeout=self.settings.llm_timeout,
            )
            if r.status_code == 200:
                raw = r.json().get("response", "")
                return self._parse(raw)
        except Exception as e:
            log.warning("llm.request_failed", error=str(e))
        return None

    def _build_prompt(self, state: GameState, decisions: list[Decision]) -> str:
        """Construit le prompt depuis l'état de jeu."""
        board = ", ".join(
            f"{m.get('name','?')}({m.get('attack',0)}/{m.get('health',0)})"
            + (" [DIVINE]" if m.get("has_divine") else "")
            + (" [TAUNT]" if m.get("has_taunt") else "")
            for m in state.board_minions
        ) or "vide"

        tavern = ", ".join(
            f"{m.get('name','?')}[{m.get('cost',3)}g T{m.get('tier',1)}]"
            for m in state.tavern_minions
        ) or "vide"

        top_h = decisions[0].reasoning if decisions else "aucune heuristique"

        return f"""=== ÉTAT DU JEU ===
Tour: {state.turn} | Tier taverne: {state.tavern_tier} | Or: {state.gold}g
Héros: {state.hero_id} | HP: {state.hero_hp} | Position: {state.current_placement}/{state.player_count}
Board ({len(state.board_minions)}/7): {board}
Taverne: {tavern}
Gel: {'OUI' if state.freeze else 'NON'} | Upgrade possible: {'OUI' if state.can_upgrade else 'NON'} ({state.upgrade_cost}g)
Phase: {state.phase}

=== MEILLEURE HEURISTIQUE ===
{top_h}

Analyse et donne ta recommandation JSON."""

    def _parse(self, raw: str) -> FullAdvice | None:
        """Parse la réponse JSON du LLM."""
        try:
            start = raw.find("{")
            end = raw.rfind("}") + 1
            if start == -1 or end == 0:
                return None

            data = json.loads(raw[start:end])

            main = Decision(
                action=data.get("main_action", "wait"),
                priority=min(10, max(1, int(data.get("priority", 5)))),
                confidence=min(1.0, max(0.0, float(data.get("confidence", 0.5)))),
                reasoning=data.get("reasoning", ""),
                warnings=data.get("warnings", []) or [],
            )

            return FullAdvice(
                main_decision=main,
                strategy_long_term=data.get("strategy", ""),
                threat_assessment=data.get("threats", ""),
                confidence_overall=main.confidence,
                model_used=self.model,
            )
        except (json.JSONDecodeError, ValueError, TypeError) as e:
            log.warning("llm.parse_failed", error=str(e), raw_preview=raw[:300])
            return None

    async def shutdown(self):
        if self._client:
            await self._client.aclose()