- Frontend v4 accessible sur réseau local (192.168.1.40) - Ports ouverts: 3002 (frontend), 5001 (backend), 5004 (dashboard) - Ollama GPU fonctionnel - Self-healing interactif - Dashboard confiance Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
65 lines
1.9 KiB
Python
65 lines
1.9 KiB
Python
#!/usr/bin/env python3
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"""
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Debug: Voir ce que le VLM retourne réellement
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"""
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import sys
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from pathlib import Path
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sys.path.insert(0, str(Path(__file__).parent.parent))
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from core.detection.ollama_client import OllamaClient
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def test_vlm_response():
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"""Tester différents prompts avec le VLM"""
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client = OllamaClient(model="qwen3-vl:8b")
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screenshot_path = "rpa_vision_v3/examples/test_ui_screenshot.png"
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print("=" * 80)
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print("TEST 1: Prompt simple")
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print("=" * 80)
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prompt1 = "Describe what you see in this image."
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result1 = client.generate(prompt1, image_path=screenshot_path, temperature=0.1)
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if result1["success"]:
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print(f"✓ Réponse reçue ({len(result1['response'])} caractères)")
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print(f"\nRéponse:\n{result1['response']}\n")
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else:
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print(f"❌ Erreur: {result1['error']}")
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print("\n" + "=" * 80)
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print("TEST 2: Demander de lister les boutons")
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print("=" * 80)
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prompt2 = "List all the buttons you can see in this image. For each button, tell me its label."
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result2 = client.generate(prompt2, image_path=screenshot_path, temperature=0.1)
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if result2["success"]:
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print(f"✓ Réponse reçue ({len(result2['response'])} caractères)")
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print(f"\nRéponse:\n{result2['response']}\n")
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else:
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print(f"❌ Erreur: {result2['error']}")
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print("\n" + "=" * 80)
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print("TEST 3: Demander JSON simple")
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print("=" * 80)
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prompt3 = """List the buttons in this image as JSON.
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Format: [{"label": "button text"}]
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Return only the JSON array."""
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result3 = client.generate(prompt3, image_path=screenshot_path, temperature=0.0)
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if result3["success"]:
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print(f"✓ Réponse reçue ({len(result3['response'])} caractères)")
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print(f"\nRéponse:\n{result3['response']}\n")
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else:
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print(f"❌ Erreur: {result3['error']}")
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if __name__ == "__main__":
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test_vlm_response()
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