feat(agent): add learn action flow and grounding guards

core/execution/input_handler.py

@@ -171,13 +171,17 @@ def handle_detected_pattern(pattern: Dict[str, Any]) -> bool:
                 screenshot = sct.grab(monitor)
                 screen = Image.frombytes('RGB', screenshot.size, screenshot.bgra, 'raw', 'BGRX')
 
-            # EasyOCR (rapide, bonne qualité GUI) avec fallback docTR.
-            # gpu=True : harmonisé avec dialog_handler.py et title_verifier.py.
-            # Coût VRAM ~0.5 GB, sous le budget RTX 5070 (cf. deploy/VRAM_BUDGET.md).
+            # EasyOCR (bonne qualité GUI) avec fallback docTR. Par défaut CPU :
+            # le replay server réserve la VRAM à Ollama.
             words = []
             try:
                 import easyocr
-                _reader = easyocr.Reader(['fr', 'en'], gpu=True, verbose=False)
+                from core.llm.ocr_extractor import easyocr_gpu_enabled
+                _reader = easyocr.Reader(
+                    ['fr', 'en'],
+                    gpu=easyocr_gpu_enabled(default=False),
+                    verbose=False,
+                )
                 results = _reader.readtext(np.array(screen))
                 for (bbox_pts, text, conf) in results:
                     if not text or len(text.strip()) < 1:

core/grounding/dialog_handler.py

@@ -248,8 +248,10 @@ class DialogHandler:
 
         try:
             import easyocr
+            from core.llm.ocr_extractor import easyocr_gpu_enabled
+            gpu = easyocr_gpu_enabled(default=False)
             self._easyocr_reader = easyocr.Reader(
-                ['fr', 'en'], gpu=True, verbose=False
+                ['fr', 'en'], gpu=gpu, verbose=False
             )
             return self._easyocr_reader
         except ImportError:

core/grounding/fast_detector.py

@@ -144,19 +144,21 @@ class FastDetector:
     _easyocr_reader = None  # Singleton EasyOCR (chargé une fois)
 
     def _ocr_extract(self, image) -> List[Dict[str, Any]]:
-        """Extrait les mots visibles via EasyOCR (GPU, ~500ms).
+        """Extrait les mots visibles via EasyOCR.
 
         Fallback sur docTR si EasyOCR non disponible.
         """
         try:
             import numpy as np
             import easyocr
+            from core.llm.ocr_extractor import easyocr_gpu_enabled
 
             # Singleton : charger le reader une seule fois
             if FastDetector._easyocr_reader is None:
-                print(f"🔍 [FAST/ocr] Chargement EasyOCR (GPU)...")
+                gpu = easyocr_gpu_enabled(default=False)
+                print(f"🔍 [FAST/ocr] Chargement EasyOCR ({'GPU' if gpu else 'CPU'})...")
                 FastDetector._easyocr_reader = easyocr.Reader(
-                    ['fr', 'en'], gpu=True, verbose=False
+                    ['fr', 'en'], gpu=gpu, verbose=False
                 )
 
             results = FastDetector._easyocr_reader.readtext(np.array(image))

core/grounding/title_verifier.py

@@ -148,10 +148,16 @@ class TitleVerifier:
         try:
             import easyocr
             import numpy as np
+            from core.llm.ocr_extractor import easyocr_gpu_enabled
 
             if TitleVerifier._easyocr_reader is None:
+                gpu = easyocr_gpu_enabled(default=False)
                 TitleVerifier._easyocr_reader = easyocr.Reader(
-                    ['fr', 'en'], gpu=True, verbose=False
+                    ['fr', 'en'], gpu=gpu, verbose=False
+                )
+                logger.info(
+                    "TitleVerifier EasyOCR initialisé (fr+en, %s)",
+                    "GPU" if gpu else "CPU",
                 )
 
             def _easyocr_extract_text(img):