feat(agent): add learn action flow and grounding guards
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@@ -137,11 +137,31 @@ class AutonomousPlanner:
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logger.info(f"AutonomousPlanner initialized (LLM: {self.llm_model}, available: {self.llm_available}, visual: {self._owl_detector is not None}, vlm: {self._vlm_client is not None})")
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def _init_visual_detection(self):
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"""Initialise le détecteur visuel OWL-v2."""
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"""Initialise le détecteur visuel OWL-v2.
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Désactivé par défaut depuis 2026-05-25 (C1b) : OWL-v2 chargeait sur
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CUDA au boot et retenait ~600 MiB VRAM même en cas d'OOM silencieux,
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fausssant les benchs perf et contribuant à l'offload Ollama VLM.
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Comme `autonomous_planner` est largement non-wired au runtime actif
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(cf. mémoire projet : HTTP 410 dépréciés), le défaut est skip.
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Activation : `AGENT_CHAT_ENABLE_OWL=1` (env var).
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Device : `AGENT_CHAT_OWL_DEVICE=cuda|cpu` (override l'auto-détect).
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"""
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if os.environ.get("AGENT_CHAT_ENABLE_OWL", "0").strip() not in ("1", "true", "yes"):
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logger.info(
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"OWL-v2 visual detector skipped at boot "
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"(AGENT_CHAT_ENABLE_OWL!=1, économie ~600 MiB VRAM)"
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)
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return
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if VISUAL_DETECTION_AVAILABLE and OwlDetector:
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try:
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self._owl_detector = OwlDetector(confidence_threshold=0.1)
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logger.info("OWL-v2 visual detector initialized")
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device = os.environ.get("AGENT_CHAT_OWL_DEVICE", "").strip() or None
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self._owl_detector = OwlDetector(
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confidence_threshold=0.1,
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device=device,
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)
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logger.info(f"OWL-v2 visual detector initialized (device={device or 'auto'})")
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except Exception as e:
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logger.warning(f"Could not initialize OWL detector: {e}")
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self._owl_detector = None
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