Use OVADARE to streamline multi-agent workflows for analyzing industry trends.
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': 'DataAccessPolicy', 'rules': { 'resource_limit': 'unique_data_source', 'access_level': 'authorized_only' } })
agent_actions = [ {'agent_id': 'research_agent', 'action': 'fetch_data', 'resource': 'industry_publication'}, {'agent_id': 'data_analyst', 'action': 'process_data', 'resource': 'industry_publication'}, {'agent_id': 'strategy_planner', 'action': 'develop_insight', 'conflict_with': 'data_analyst'}, {'agent_id': 'report_generator', 'action': 'generate_report'} ] conflicts = conflict_detector.detect(agent_actions)
if conflicts: resolutions = resolution_engine.generate_resolutions(conflicts) for resolution in resolutions: print(f"Generated Resolution: {resolution}")
for resolution in resolutions: agent_id = resolution['agent_id'] corrective_action = resolution['corrective_action'] autogen_api.apply_resolution(agent_id, corrective_action)