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"""
Test pratique MCP pour évaluer les capacités réelles des modèles
Simule l'usage réel dans un jeu RTS avec des commandes typiques
"""
import sys
import os
import json
import time
sys.path.append(os.path.dirname(os.path.abspath(__file__)))
def test_model_practical(model_path, model_name):
"""Test pratique avec des commandes RTS réelles"""
try:
from llama_cpp import Llama
print(f"🎮 Test pratique de {model_name}...")
llm = Llama(
model_path=model_path,
n_ctx=1024,
n_threads=1,
verbose=False
)
# Commandes RTS typiques qu'un utilisateur taperait
real_commands = [
"show game state",
"move infantry to 100,200",
"attack enemy tank at 300,150",
"build barracks near 250,200",
"defend base with all units",
"harvest resources with harvester",
"scout enemy positions"
]
results = []
for command in real_commands:
prompt = f"""You control an RTS game via MCP. Available tools:
- get_game_state()
- move_units(unit_ids, target_x, target_y)
- attack_unit(attacker_ids, target_id)
- build_building(building_type, position_x, position_y)
User command: "{command}"
Respond with JSON: {{"tool": "tool_name", "args": {{}}}}"""
start_time = time.time()
response = llm(
prompt,
max_tokens=100,
temperature=0.1
)
response_time = time.time() - start_time
# Extraire et évaluer
try:
response_text = response['choices'][0]['text'].strip()
except:
response_text = str(response)
# Évaluation simple mais réaliste
score = 0
# JSON valide?
try:
json.loads(response_text)
score += 3
except:
# Chercher JSON dans le texte
import re
if re.search(r'\{.*\}', response_text):
score += 1
# Outil approprié?
if "game state" in command and "get_game_state" in response_text:
score += 3
elif "move" in command and "move_units" in response_text:
score += 3
elif "attack" in command and "attack_unit" in response_text:
score += 3
elif "build" in command and "build_building" in response_text:
score += 3
elif any(tool in response_text for tool in ['get_game_state', 'move_units', 'attack_unit', 'build_building']):
score += 1
# Paramètres raisonnables?
if "100,200" in response_text or "300,150" in response_text or "250,200" in response_text:
score += 2
score = min(score, 10)
print(f" '{command}' → {score}/10 ({response_time:.2f}s)")
results.append({
'command': command,
'score': score,
'time': response_time,
'response': response_text[:50]
})
avg_score = sum(r['score'] for r in results) / len(results)
avg_time = sum(r['time'] for r in results) / len(results)
print(f"📊 {model_name}: {avg_score:.1f}/10 moyen | {avg_time:.2f}s moyen")
return {
'name': model_name,
'avg_score': avg_score,
'avg_time': avg_time,
'results': results
}
except Exception as e:
print(f"❌ Erreur {model_name}: {e}")
return None
def main():
"""Test pratique comparatif"""
print("🎯 TEST PRATIQUE MCP - COMMANDES RTS RÉELLES")
print("=" * 50)
print("Simulation de l'usage réel avec des commandes typiques")
print("=" * 50)
models = [
{'name': 'Qwen2.5-0.5B', 'path': 'qwen2.5-0.5b-instruct-q4_0.gguf'},
{'name': 'Qwen3-0.6B', 'path': 'Qwen3-0.6B-Q8_0.gguf'},
{'name': 'Gemma-3-270M', 'path': 'gemma-3-270m-it-qat-Q8_0.gguf'}
]
results = []
for model in models:
if os.path.exists(model['path']):
result = test_model_practical(model['path'], model['name'])
if result:
results.append(result)
print()
# Analyse pratique
if results:
print("📊 RÉSULTATS PRATIQUES:")
print("-" * 30)
sorted_results = sorted(results, key=lambda x: x['avg_score'], reverse=True)
for i, result in enumerate(sorted_results, 1):
print(f"{i}. {result['name']}: {result['avg_score']:.1f}/10")
# Recommandation pratique
best = sorted_results[0]
print(f"\n🎯 RECOMMANDATION PRATIQUE:")
if best['avg_score'] >= 7:
print(f"✅ {best['name']} est EXCELLENT pour la production")
print(" → Gère bien les commandes RTS typiques")
elif best['avg_score'] >= 5:
print(f"👍 {best['name']} est UTILISABLE avec validation")
print(" → Fonctionne pour les commandes simples")
else:
print(f"⚠️ {best['name']} nécessite des améliorations")
print(" → Considérer prompts plus spécifiques")
# Analyse des commandes réussies
print(f"\n📈 COMMANDES LES MIEUX GÉRÉES:")
for result in results:
best_commands = [r for r in result['results'] if r['score'] >= 7]
if best_commands:
print(f"\n{result['name']}:")
for cmd in best_commands[:3]: # Top 3
print(f" • {cmd['command']}: {cmd['score']}/10")
# Conclusion sur la pertinence du test
print(f"\n🔍 PERTINENCE DU TEST:")
print("✅ Ce test est BEAUCOUP plus représentatif:")
print(" • Commandes réelles d'utilisateurs")
print(" • Format de sortie JSON attendu")
print(" • Temps de réponse réaliste")
print(" • Pas de prompts artificiels complexes")
# Sauvegarder
with open("practical_mcp_results.json", "w") as f:
json.dump(results, f, indent=2)
print(f"\n📄 Résultats sauvegardés: practical_mcp_results.json")
if __name__ == "__main__":
main() |