Leverage OVADARE to streamline the development of sales strategies by resolving conflicts between AI agents.
from ovadare.conflicts.conflict_detector import ConflictDetector from ovadare.resolutions.resolution_engine import ResolutionEngine from ovadare.policies.policy_manager import PolicyManager conflict_detector = ConflictDetector() resolution_engine = ResolutionEngine() policy_manager = PolicyManager()
policy_manager.add_policy({ 'name': 'PricingPolicy', 'rules': { 'access_level': 'restricted', 'resource': 'competitor_pricing' } })
agent_actions = [ {'agent_id': 'market_analyst', 'action': 'analyze_market', 'resource': 'market_data'}, {'agent_id': 'competitor_analyst', 'action': 'access_data', 'resource': 'competitor_pricing'}, {'agent_id': 'pricing_strategist', 'action': 'create_pricing', 'strategy': 'below_market'} ] conflicts = conflict_detector.detect(agent_actions)
if conflicts: resolutions = resolution_engine.generate_resolutions(conflicts) for resolution in resolutions: print(f"Resolution: {resolution}")
for resolution in resolutions: agent_id = resolution['agent_id'] corrective_action = resolution['corrective_action'] autogen_api.apply_resolution(agent_id, corrective_action)