diff --git a/swarms/structs/corporate_swarm.py b/swarms/structs/corporate_swarm.py index 67ef84b3..fa1c95f9 100644 --- a/swarms/structs/corporate_swarm.py +++ b/swarms/structs/corporate_swarm.py @@ -1,153 +1,320 @@ """ -CorporateSwarm - Autonomous Corporate Governance System - -A sophisticated multi-agent orchestration system that simulates a complete corporate -structure with board governance, executive leadership, departmental operations, and -democratic decision-making processes. Built on the foundation of EuroSwarm Parliament -with corporate-specific enhancements. - -This module provides a comprehensive corporate simulation including: -- Board of Directors with democratic voting -- Executive leadership team coordination -- Departmental swarm management -- Financial oversight and reporting -- Strategic decision-making processes -- Compliance and governance frameworks - -Classes: - CorporateMember: Represents individual corporate stakeholders - CorporateProposal: Represents business proposals and decisions - CorporateDepartment: Represents corporate departments - CorporateVote: Represents voting sessions and results - CorporateSwarm: Main corporate orchestration system +CorporateSwarm - Advanced Autonomous Corporate Governance System + +Multi-agent orchestration system for corporate governance with board oversight, +executive leadership, ESG frameworks, risk management, and democratic decision-making. + +Features: ESG scoring, risk assessment, stakeholder engagement, regulatory compliance, +AI ethics governance, crisis management, and innovation oversight. """ +# Standard library imports +import asyncio import json +import os import time +import traceback import uuid +from abc import ABC, abstractmethod +from concurrent.futures import ThreadPoolExecutor from dataclasses import dataclass, field from enum import Enum +from functools import lru_cache from typing import Any, Dict, List, Optional, Union +# Third-party imports from loguru import logger from pydantic import BaseModel, Field +# Swarms imports from swarms.structs.agent import Agent from swarms.structs.conversation import Conversation from swarms.structs.hybrid_hiearchical_peer_swarm import HybridHierarchicalClusterSwarm from swarms.structs.swarm_router import SwarmRouter -from swarms.utils.history_output_formatter import history_output_formatter +from swarms.utils.loguru_logger import initialize_logger +from swarms.utils.output_types import OutputType + +# ============================================================================ +# CONSTANTS AND CONFIGURATION +# ============================================================================ + +# Initialize centralized logger +CORPORATE_LOGGER = initialize_logger(log_folder="corporate_swarm") + +# Default configuration values +DEFAULT_BOARD_SIZE = 6 +DEFAULT_EXECUTIVE_TEAM_SIZE = 4 +DEFAULT_DECISION_THRESHOLD = 0.6 +DEFAULT_BUDGET_LIMIT = 200.0 +DEFAULT_BATCH_SIZE = 25 +DEFAULT_MEETING_DURATION = 600 + +# Risk assessment constants +RISK_LEVELS = {"low": 0.3, "medium": 0.6, "high": 0.8, "critical": 1.0} +RISK_CATEGORIES = ["operational", "financial", "strategic", "compliance", "cybersecurity", "reputation", "environmental", "regulatory"] + +# Stakeholder types +STAKEHOLDER_TYPES = ["investor", "customer", "employee", "community", "supplier", "regulator"] + +# Compliance frameworks +COMPLIANCE_FRAMEWORKS = { + "SOX": ("financial", ["Internal controls", "Financial reporting", "Audit requirements"]), + "GDPR": ("data_privacy", ["Data protection", "Privacy rights", "Consent management"]), + "ISO 27001": ("cybersecurity", ["Information security", "Risk management", "Security controls"]), + "ESG": ("sustainability", ["Environmental reporting", "Social responsibility", "Governance standards"]), + "HIPAA": ("healthcare", ["Patient privacy", "Data security", "Compliance monitoring"]) +} + + +# ============================================================================ +# CORPORATE SWARM CONFIGURATION +# ============================================================================ + + +class CorporateConfigModel(BaseModel): + """Configuration model for CorporateSwarm with corporate structure and governance settings.""" + + # Corporate structure + default_board_size: int = Field( + default=6, + ge=3, + le=15, + description="Default number of board members when creating a new board.", + ) + + default_executive_team_size: int = Field( + default=4, + ge=2, + le=10, + description="Default number of executive team members.", + ) + + # Governance settings + decision_threshold: float = Field( + default=0.6, + ge=0.0, + le=1.0, + description="Threshold for majority decisions (0.0-1.0).", + ) + + enable_democratic_discussion: bool = Field( + default=True, + description="Enable democratic discussion features.", + ) + + enable_departmental_work: bool = Field( + default=True, + description="Enable departmental collaboration.", + ) + + enable_financial_oversight: bool = Field( + default=True, + description="Enable financial oversight features.", + ) + + # Model settings + default_corporate_model: str = Field( + default="gpt-4o-mini", + description="Default model for corporate member agents.", + ) + + # Logging and monitoring + verbose_logging: bool = Field( + default=False, + description="Enable verbose logging for corporate operations.", + ) + + # Performance settings + max_corporate_meeting_duration: int = Field( + default=600, + ge=60, + le=3600, + description="Maximum duration for corporate meetings in seconds.", + ) + + budget_limit: float = Field( + default=200.0, + ge=0.0, + description="Maximum budget in dollars for corporate operations.", + ) + + batch_size: int = Field( + default=25, + ge=1, + le=100, + description="Number of members to process in batches.", + ) + + enable_lazy_loading: bool = Field( + default=True, + description="Enable lazy loading of member agents.", + ) + + enable_caching: bool = Field( + default=True, + description="Enable response caching.", + ) + + +@dataclass +class CorporateConfig: + """Configuration manager for CorporateSwarm.""" + + config_file_path: Optional[str] = None + config_data: Optional[Dict[str, Any]] = None + config: CorporateConfigModel = field(init=False) + + def __post_init__(self) -> None: + self._load_config() + + def _load_config(self) -> None: + """Load configuration with priority: explicit data > file > defaults.""" + try: + self.config = CorporateConfigModel() + if self.config_file_path and os.path.exists(self.config_file_path): + self._load_from_file() + if self.config_data: + self._load_from_dict(self.config_data) + except Exception as e: + CORPORATE_LOGGER.error(f"Configuration loading failed: {e}") + raise + + def _load_from_file(self) -> None: + """Load configuration from YAML file.""" + try: + import yaml + with open(self.config_file_path, "r") as f: + self._load_from_dict(yaml.safe_load(f)) + CORPORATE_LOGGER.info(f"Loaded config from: {self.config_file_path}") + except Exception as e: + CORPORATE_LOGGER.warning(f"File loading failed {self.config_file_path}: {e}") + raise + + def _load_from_dict(self, config_dict: Dict[str, Any]) -> None: + """Load configuration from dictionary with validation.""" + for key, value in config_dict.items(): + if hasattr(self.config, key): + try: + setattr(self.config, key, value) + except (ValueError, TypeError) as e: + CORPORATE_LOGGER.warning(f"Config {key} failed: {e}") + raise ValueError(f"Invalid configuration value for {key}: {e}") + + def get_config(self) -> CorporateConfigModel: + return self.config + + def update_config(self, updates: Dict[str, Any]) -> None: + try: + self._load_from_dict(updates) + except ValueError as e: + CORPORATE_LOGGER.error(f"Config update failed: {e}") + raise + + def validate_config(self) -> List[str]: + """Validate configuration and return error list.""" + errors = [] + try: + self.config.model_validate(self.config.model_dump()) + except Exception as e: + errors.append(f"Configuration validation failed: {e}") + + if self.config.decision_threshold < 0.5: + errors.append("Decision threshold should be at least 0.5") + if self.config.default_board_size < 3: + errors.append("Board size should be at least 3") + + return errors + + +# Global configuration cache +_corporate_config: Optional[CorporateConfig] = None + +@lru_cache(maxsize=1) +def get_corporate_config(config_file_path: Optional[str] = None) -> CorporateConfig: + """Get global CorporateSwarm configuration instance.""" + global _corporate_config + if _corporate_config is None: + _corporate_config = CorporateConfig(config_file_path=config_file_path) + return _corporate_config + + +# ============================================================================ +# CORPORATE SWARM DATA MODELS +# ============================================================================ + + +class BaseCorporateAgent(ABC): + """Base class for corporate agents.""" + + @abstractmethod + def run(self, task: str, **kwargs) -> Any: + """Synchronous execution method.""" + pass + + @abstractmethod + async def arun(self, task: str, **kwargs) -> Any: + """Asynchronous execution method.""" + pass + + def __call__(self, task: str, **kwargs) -> Any: + """Callable interface.""" + return self.run(task, **kwargs) class CorporateRole(str, Enum): """Corporate roles and positions.""" - CEO = "ceo" - CFO = "cfo" - CTO = "cto" - COO = "coo" - BOARD_CHAIR = "board_chair" - BOARD_VICE_CHAIR = "board_vice_chair" - BOARD_MEMBER = "board_member" - INDEPENDENT_DIRECTOR = "independent_director" - EXECUTIVE_DIRECTOR = "executive_director" - NON_EXECUTIVE_DIRECTOR = "non_executive_director" - COMMITTEE_CHAIR = "committee_chair" - COMMITTEE_MEMBER = "committee_member" - DEPARTMENT_HEAD = "department_head" - MANAGER = "manager" - EMPLOYEE = "employee" - INVESTOR = "investor" - ADVISOR = "advisor" - AUDITOR = "auditor" - SECRETARY = "secretary" + CEO, CFO, CTO, COO = "ceo", "cfo", "cto", "coo" + BOARD_CHAIR, BOARD_VICE_CHAIR, BOARD_MEMBER = "board_chair", "board_vice_chair", "board_member" + INDEPENDENT_DIRECTOR, EXECUTIVE_DIRECTOR, NON_EXECUTIVE_DIRECTOR = "independent_director", "executive_director", "non_executive_director" + COMMITTEE_CHAIR, COMMITTEE_MEMBER = "committee_chair", "committee_member" + DEPARTMENT_HEAD, MANAGER, EMPLOYEE = "department_head", "manager", "employee" + INVESTOR, ADVISOR, AUDITOR, SECRETARY = "investor", "advisor", "auditor", "secretary" class DepartmentType(str, Enum): """Corporate department types.""" - FINANCE = "finance" - OPERATIONS = "operations" - MARKETING = "marketing" - HUMAN_RESOURCES = "human_resources" - LEGAL = "legal" - TECHNOLOGY = "technology" - RESEARCH_DEVELOPMENT = "research_development" - SALES = "sales" - CUSTOMER_SERVICE = "customer_service" - COMPLIANCE = "compliance" + FINANCE, OPERATIONS, MARKETING, HUMAN_RESOURCES = "finance", "operations", "marketing", "human_resources" + LEGAL, TECHNOLOGY, RESEARCH_DEVELOPMENT = "legal", "technology", "research_development" + SALES, CUSTOMER_SERVICE, COMPLIANCE = "sales", "customer_service", "compliance" class ProposalType(str, Enum): """Types of corporate proposals.""" - STRATEGIC_INITIATIVE = "strategic_initiative" - BUDGET_ALLOCATION = "budget_allocation" - HIRING_DECISION = "hiring_decision" - PRODUCT_LAUNCH = "product_launch" - PARTNERSHIP = "partnership" - MERGER_ACQUISITION = "merger_acquisition" - POLICY_CHANGE = "policy_change" - INVESTMENT = "investment" - OPERATIONAL_CHANGE = "operational_change" - COMPLIANCE_UPDATE = "compliance_update" - BOARD_RESOLUTION = "board_resolution" - EXECUTIVE_COMPENSATION = "executive_compensation" - DIVIDEND_DECLARATION = "dividend_declaration" - SHARE_ISSUANCE = "share_issuance" - AUDIT_APPOINTMENT = "audit_appointment" - RISK_MANAGEMENT = "risk_management" - SUCCESSION_PLANNING = "succession_planning" + STRATEGIC_INITIATIVE, BUDGET_ALLOCATION, HIRING_DECISION = "strategic_initiative", "budget_allocation", "hiring_decision" + PRODUCT_LAUNCH, PARTNERSHIP, MERGER_ACQUISITION = "product_launch", "partnership", "merger_acquisition" + POLICY_CHANGE, INVESTMENT, OPERATIONAL_CHANGE = "policy_change", "investment", "operational_change" + COMPLIANCE_UPDATE, BOARD_RESOLUTION, EXECUTIVE_COMPENSATION = "compliance_update", "board_resolution", "executive_compensation" + DIVIDEND_DECLARATION, SHARE_ISSUANCE, AUDIT_APPOINTMENT = "dividend_declaration", "share_issuance", "audit_appointment" + RISK_MANAGEMENT, SUCCESSION_PLANNING = "risk_management", "succession_planning" class VoteResult(str, Enum): """Voting result outcomes.""" - APPROVED = "approved" - REJECTED = "rejected" - TABLED = "tabled" - FAILED = "failed" - UNANIMOUS = "unanimous" - MAJORITY = "majority" - MINORITY = "minority" - ABSTAINED = "abstained" + APPROVED, REJECTED, TABLED, FAILED = "approved", "rejected", "tabled", "failed" + UNANIMOUS, MAJORITY, MINORITY, ABSTAINED = "unanimous", "majority", "minority", "abstained" class BoardCommitteeType(str, Enum): """Types of board committees.""" - AUDIT = "audit" - COMPENSATION = "compensation" - NOMINATING = "nominating" - GOVERNANCE = "governance" - RISK = "risk" - TECHNOLOGY = "technology" - STRATEGIC = "strategic" - FINANCE = "finance" - COMPLIANCE = "compliance" + AUDIT, COMPENSATION, NOMINATING, GOVERNANCE = "audit", "compensation", "nominating", "governance" + RISK, TECHNOLOGY, STRATEGIC, FINANCE = "risk", "technology", "strategic", "finance" + COMPLIANCE, ESG, SUSTAINABILITY, CYBERSECURITY = "compliance", "esg", "sustainability", "cybersecurity" + INNOVATION, STAKEHOLDER, CRISIS_MANAGEMENT = "innovation", "stakeholder", "crisis_management" + AI_ETHICS, DATA_PRIVACY = "ai_ethics", "data_privacy" class MeetingType(str, Enum): """Types of board meetings.""" - REGULAR_BOARD = "regular_board" - SPECIAL_BOARD = "special_board" - ANNUAL_GENERAL = "annual_general" - COMMITTEE_MEETING = "committee_meeting" - EXECUTIVE_SESSION = "executive_session" - EMERGENCY_MEETING = "emergency_meeting" + REGULAR_BOARD, SPECIAL_BOARD, ANNUAL_GENERAL = "regular_board", "special_board", "annual_general" + COMMITTEE_MEETING, EXECUTIVE_SESSION, EMERGENCY_MEETING = "committee_meeting", "executive_session", "emergency_meeting" + ESG_REVIEW, RISK_ASSESSMENT, CRISIS_RESPONSE = "esg_review", "risk_assessment", "crisis_response" + STAKEHOLDER_ENGAGEMENT, INNOVATION_REVIEW, COMPLIANCE_AUDIT = "stakeholder_engagement", "innovation_review", "compliance_audit" + SUSTAINABILITY_REPORTING, AI_ETHICS_REVIEW = "sustainability_reporting", "ai_ethics_review" @dataclass class BoardCommittee: - """ - Represents a board committee with specific governance responsibilities. - - Attributes: - committee_id: Unique identifier for the committee - name: Name of the committee - committee_type: Type of board committee - chair: Committee chair member ID - members: List of committee member IDs - responsibilities: Committee responsibilities and scope - meeting_schedule: Regular meeting schedule - quorum_required: Minimum members required for quorum - metadata: Additional committee information - """ + """Board committee with governance responsibilities.""" committee_id: str = field(default_factory=lambda: str(uuid.uuid4())) name: str = "" committee_type: BoardCommitteeType = BoardCommitteeType.GOVERNANCE @@ -161,21 +328,7 @@ class BoardCommittee: @dataclass class BoardMeeting: - """ - Represents a board meeting with agenda and minutes. - - Attributes: - meeting_id: Unique identifier for the meeting - meeting_type: Type of board meeting - date: Meeting date and time - location: Meeting location (physical or virtual) - attendees: List of attendee member IDs - agenda: Meeting agenda items - minutes: Meeting minutes and decisions - quorum_met: Whether quorum was met - resolutions: Board resolutions passed - metadata: Additional meeting information - """ + """Board meeting with agenda and minutes.""" meeting_id: str = field(default_factory=lambda: str(uuid.uuid4())) meeting_type: MeetingType = MeetingType.REGULAR_BOARD date: float = field(default_factory=time.time) @@ -188,86 +341,42 @@ class BoardMeeting: metadata: Dict[str, Any] = field(default_factory=dict) -@dataclass -class CorporateMember: - """ - Represents a corporate stakeholder with specific role and responsibilities. - - Attributes: - member_id: Unique identifier for the member - name: Full name of the member - role: Corporate role and position - department: Department affiliation - expertise_areas: Areas of professional expertise - voting_weight: Weight of vote in corporate decisions - board_committees: List of board committees the member serves on - independence_status: Whether the member is independent - term_start: When the member's term started - term_end: When the member's term ends - compensation: Member compensation information - agent: AI agent representing this member - metadata: Additional member information - """ - member_id: str = field(default_factory=lambda: str(uuid.uuid4())) - name: str = "" - role: CorporateRole = CorporateRole.EMPLOYEE - department: DepartmentType = DepartmentType.OPERATIONS - expertise_areas: List[str] = field(default_factory=list) - voting_weight: float = 1.0 - board_committees: List[str] = field(default_factory=list) - independence_status: bool = False - term_start: float = field(default_factory=time.time) - term_end: Optional[float] = None - compensation: Dict[str, Any] = field(default_factory=dict) - agent: Optional[Agent] = None - metadata: Dict[str, Any] = field(default_factory=dict) +class CorporateMember(BaseModel): + """Corporate stakeholder with role, expertise, and governance responsibilities.""" + + member_id: str = Field(default_factory=lambda: str(uuid.uuid4())) + name: str = Field(default="") + role: CorporateRole = Field(default=CorporateRole.EMPLOYEE) + department: DepartmentType = Field(default=DepartmentType.OPERATIONS) + expertise_areas: List[str] = Field(default_factory=list) + voting_weight: float = Field(default=1.0, ge=0.0, le=5.0) + board_committees: List[str] = Field(default_factory=list) + independence_status: bool = Field(default=False) + term_start: float = Field(default_factory=time.time) + term_end: Optional[float] = Field(default=None) + compensation: Dict[str, Any] = Field(default_factory=dict) + agent: Optional[Agent] = Field(default=None) + metadata: Dict[str, Any] = Field(default_factory=dict) -@dataclass -class CorporateProposal: - """ - Represents a corporate proposal requiring decision-making. - - Attributes: - proposal_id: Unique identifier for the proposal - title: Title of the proposal - description: Detailed description of the proposal - proposal_type: Type of corporate proposal - sponsor: Member who sponsored the proposal - department: Department responsible for implementation - budget_impact: Financial impact of the proposal - timeline: Implementation timeline - status: Current status of the proposal - metadata: Additional proposal information - """ - proposal_id: str = field(default_factory=lambda: str(uuid.uuid4())) - title: str = "" - description: str = "" - proposal_type: ProposalType = ProposalType.STRATEGIC_INITIATIVE - sponsor: str = "" - department: DepartmentType = DepartmentType.OPERATIONS - budget_impact: float = 0.0 - timeline: str = "" - status: str = "pending" - metadata: Dict[str, Any] = field(default_factory=dict) +class CorporateProposal(BaseModel): + """Corporate proposal requiring decision-making with financial impact.""" + + proposal_id: str = Field(default_factory=lambda: str(uuid.uuid4())) + title: str = Field(default="") + description: str = Field(default="") + proposal_type: ProposalType = Field(default=ProposalType.STRATEGIC_INITIATIVE) + sponsor: str = Field(default="") + department: DepartmentType = Field(default=DepartmentType.OPERATIONS) + budget_impact: float = Field(default=0.0, ge=0.0) + timeline: str = Field(default="") + status: str = Field(default="pending") + metadata: Dict[str, Any] = Field(default_factory=dict) @dataclass class CorporateDepartment: - """ - Represents a corporate department with specific functions. - - Attributes: - department_id: Unique identifier for the department - name: Name of the department - department_type: Type of department - head: Department head member - members: List of department members - budget: Department budget allocation - objectives: Department objectives and goals - current_projects: Active projects in the department - metadata: Additional department information - """ + """Corporate department with specific functions and budget.""" department_id: str = field(default_factory=lambda: str(uuid.uuid4())) name: str = "" department_type: DepartmentType = DepartmentType.OPERATIONS @@ -279,99 +388,107 @@ class CorporateDepartment: metadata: Dict[str, Any] = field(default_factory=dict) -@dataclass -class CorporateVote: - """ - Represents a corporate voting session and results. - - Attributes: - vote_id: Unique identifier for the vote - proposal: Proposal being voted on - participants: Members participating in the vote - individual_votes: Individual member votes and reasoning - political_group_analysis: Analysis by corporate groups - result: Final voting result - timestamp: When the vote was conducted - metadata: Additional voting information - """ - vote_id: str = field(default_factory=lambda: str(uuid.uuid4())) - proposal: CorporateProposal = field(default_factory=CorporateProposal) - participants: List[str] = field(default_factory=list) - individual_votes: Dict[str, Dict[str, Any]] = field(default_factory=dict) - political_group_analysis: Dict[str, Any] = field(default_factory=dict) - result: VoteResult = VoteResult.FAILED - timestamp: float = field(default_factory=time.time) - metadata: Dict[str, Any] = field(default_factory=dict) +class CorporateVote(BaseModel): + """Corporate voting session with individual votes and analysis.""" + + vote_id: str = Field(default_factory=lambda: str(uuid.uuid4())) + proposal: CorporateProposal = Field(default_factory=CorporateProposal) + participants: List[str] = Field(default_factory=list) + individual_votes: Dict[str, Dict[str, Any]] = Field(default_factory=dict) + political_group_analysis: Dict[str, Any] = Field(default_factory=dict) + result: VoteResult = Field(default=VoteResult.FAILED) + timestamp: float = Field(default_factory=time.time) + metadata: Dict[str, Any] = Field(default_factory=dict) + + +class ESGScore(BaseModel): + """Environmental, Social, and Governance scoring model.""" + + environmental_score: float = Field(default=0.0, ge=0.0, le=100.0) + social_score: float = Field(default=0.0, ge=0.0, le=100.0) + governance_score: float = Field(default=0.0, ge=0.0, le=100.0) + overall_score: float = Field(default=0.0, ge=0.0, le=100.0) + carbon_footprint: float = Field(default=0.0, ge=0.0) + diversity_index: float = Field(default=0.0, ge=0.0, le=1.0) + stakeholder_satisfaction: float = Field(default=0.0, ge=0.0, le=100.0) + sustainability_goals: List[str] = Field(default_factory=list) + last_updated: float = Field(default_factory=time.time) -class CorporateSwarm: - """ - A comprehensive corporate governance system with democratic decision-making. - - This class orchestrates a complete corporate structure including board governance, - executive leadership, departmental operations, and strategic decision-making. - Built on the foundation of EuroSwarm Parliament with corporate-specific enhancements. - - Attributes: - name: Name of the corporate entity - description: Description of the corporate structure - members: Dictionary of corporate members - departments: Dictionary of corporate departments - proposals: List of active proposals - votes: List of voting sessions - board_members: List of board of directors members - executive_team: List of executive leadership - max_loops: Maximum number of decision-making loops - enable_democratic_discussion: Enable democratic discussion features - enable_departmental_work: Enable departmental collaboration - enable_financial_oversight: Enable financial oversight features - verbose: Enable detailed logging - conversation: Conversation history tracker - democratic_swarm: Democratic decision-making swarm - """ +class RiskAssessment(BaseModel): + """Comprehensive risk assessment model for corporate governance.""" + + risk_id: str = Field(default_factory=lambda: str(uuid.uuid4())) + risk_category: str = Field(default="operational") + risk_level: str = Field(default="medium") + probability: float = Field(default=0.5, ge=0.0, le=1.0) + impact: float = Field(default=0.5, ge=0.0, le=1.0) + risk_score: float = Field(default=0.25, ge=0.0, le=1.0) + mitigation_strategies: List[str] = Field(default_factory=list) + owner: str = Field(default="") + status: str = Field(default="active") + last_reviewed: float = Field(default_factory=time.time) + + +class StakeholderEngagement(BaseModel): + """Stakeholder engagement and management model.""" + + stakeholder_id: str = Field(default_factory=lambda: str(uuid.uuid4())) + stakeholder_type: str = Field(default="investor") + name: str = Field(default="") + influence_level: str = Field(default="medium") + interest_level: str = Field(default="medium") + engagement_frequency: str = Field(default="quarterly") + satisfaction_score: float = Field(default=0.0, ge=0.0, le=100.0) + concerns: List[str] = Field(default_factory=list) + last_engagement: float = Field(default_factory=time.time) + + +class ComplianceFramework(BaseModel): + """Regulatory compliance and audit framework model.""" + + compliance_id: str = Field(default_factory=lambda: str(uuid.uuid4())) + regulation_name: str = Field(default="") + regulation_type: str = Field(default="financial") + compliance_status: str = Field(default="compliant") + compliance_score: float = Field(default=100.0, ge=0.0, le=100.0) + requirements: List[str] = Field(default_factory=list) + controls: List[str] = Field(default_factory=list) + audit_findings: List[str] = Field(default_factory=list) + next_audit_date: float = Field(default_factory=lambda: time.time() + (365 * 24 * 60 * 60)) + responsible_officer: str = Field(default="") + + +class CorporateSwarm(BaseCorporateAgent): + """Autonomous corporate governance system with democratic decision-making.""" def __init__( self, name: str = "CorporateSwarm", description: str = "A comprehensive corporate governance system with democratic decision-making", max_loops: int = 1, - enable_democratic_discussion: bool = True, - enable_departmental_work: bool = True, - enable_financial_oversight: bool = True, - enable_lazy_loading: bool = True, - enable_caching: bool = True, - batch_size: int = 25, - budget_limit: float = 200.0, + output_type: OutputType = "dict-all-except-first", + corporate_model_name: str = "gpt-4o-mini", verbose: bool = False, - ): - """ - Initialize the CorporateSwarm with corporate governance capabilities. - - Args: - name: Name of the corporate entity - description: Description of the corporate structure - max_loops: Maximum number of decision-making loops - enable_democratic_discussion: Enable democratic discussion features - enable_departmental_work: Enable departmental collaboration - enable_financial_oversight: Enable financial oversight features - enable_lazy_loading: Enable lazy loading of member agents - enable_caching: Enable response caching - batch_size: Number of members to process in batches - budget_limit: Maximum budget in dollars - verbose: Enable detailed logging - """ + config_file_path: Optional[str] = None, + config_data: Optional[Dict[str, Any]] = None, + *args: Any, + **kwargs: Any, + ) -> None: + """Initialize CorporateSwarm with corporate governance capabilities.""" self.name = name self.description = description self.max_loops = max_loops - self.enable_democratic_discussion = enable_democratic_discussion - self.enable_departmental_work = enable_departmental_work - self.enable_financial_oversight = enable_financial_oversight - self.enable_lazy_loading = enable_lazy_loading - self.enable_caching = enable_caching - self.batch_size = batch_size - self.budget_limit = budget_limit + self.output_type = output_type + self.corporate_model_name = corporate_model_name self.verbose = verbose + # Load configuration + self.config = CorporateConfig( + config_file_path=config_file_path, + config_data=config_data + ).get_config() + # Initialize corporate structure self.members: Dict[str, CorporateMember] = {} self.departments: Dict[str, CorporateDepartment] = {} @@ -384,25 +501,209 @@ class CorporateSwarm: self.independent_directors: List[str] = [] self.executive_directors: List[str] = [] + # Advanced governance frameworks + self.esg_scores: Dict[str, ESGScore] = {} + self.risk_assessments: Dict[str, RiskAssessment] = {} + self.stakeholder_engagements: Dict[str, StakeholderEngagement] = {} + self.compliance_frameworks: Dict[str, ComplianceFramework] = {} + self.crisis_management_plans: Dict[str, Dict[str, Any]] = {} + self.innovation_pipeline: List[Dict[str, Any]] = [] + self.audit_trails: List[Dict[str, Any]] = [] + self.performance_metrics: Dict[str, Any] = {} + self.sustainability_targets: Dict[str, Any] = {} + self.ai_ethics_framework: Dict[str, Any] = {} + # Initialize conversation and democratic systems - self.conversation = Conversation() + self.conversation = Conversation(time_enabled=False) self.democratic_swarm = None # Cost tracking - self.cost_tracker = CostTracker(budget_limit) + self.cost_tracker = CostTracker(self.config.budget_limit) + + # Performance settings + self.max_workers = os.cpu_count() + + # Initialize the corporate swarm + self._init_corporate_swarm() + + def _init_corporate_swarm(self) -> None: + """Initialize CorporateSwarm structure and perform reliability checks.""" + try: + if self.verbose: + CORPORATE_LOGGER.info( + f"Initializing CorporateSwarm: {self.name}" + ) + CORPORATE_LOGGER.info( + f"Configuration - Max loops: {self.max_loops}" + ) + + # Perform reliability checks + self._perform_reliability_checks() + + # Initialize default corporate structure + self._initialize_default_structure() + + # Initialize democratic swarm if enabled + if self.config.enable_democratic_discussion: + self._initialize_democratic_swarm() + + if self.verbose: + CORPORATE_LOGGER.success( + f"CorporateSwarm initialized successfully: {self.name}" + ) + + except Exception as e: + CORPORATE_LOGGER.error(f"Failed to initialize CorporateSwarm: {str(e)}") + raise + + def _perform_reliability_checks(self) -> None: + """Validate critical requirements and configuration parameters.""" + try: + if self.verbose: + CORPORATE_LOGGER.info( + f"Running reliability checks for CorporateSwarm: {self.name}" + ) + + if self.max_loops <= 0: + raise ValueError( + "Max loops must be greater than 0. Please set a valid number of loops." + ) + + if ( + self.config.decision_threshold < 0.0 + or self.config.decision_threshold > 1.0 + ): + raise ValueError( + "Decision threshold must be between 0.0 and 1.0." + ) + + if self.config.budget_limit < 0: + raise ValueError( + "Budget limit must be non-negative." + ) + + if self.verbose: + CORPORATE_LOGGER.success( + f"Reliability checks passed for CorporateSwarm: {self.name}" + ) + + except Exception as e: + CORPORATE_LOGGER.error(f"Failed reliability checks: {str(e)}") + raise + + @classmethod + def create_simple_corporation( + cls, + name: str = "SimpleCorp", + num_board_members: int = 5, + num_executives: int = 4, + verbose: bool = False + ) -> "CorporateSwarm": + """Create a simple corporation with basic structure.""" + return cls( + name=name, + max_loops=1, + enable_democratic_discussion=True, + enable_departmental_work=True, + enable_financial_oversight=True, + verbose=verbose + ) + + def run( + self, + task: str, + **kwargs + ) -> Union[str, Dict[str, Any]]: + """ + Main execution method - processes corporate tasks through democratic decision-making. + + Implements intelligent task routing and performance optimization via concurrency. + Args: + task: The corporate task or proposal to process + **kwargs: Additional parameters for task processing + + Returns: + Union[str, Dict[str, Any]]: Task results or decision outcomes + + Example: + >>> corporate = CorporateSwarm() + >>> result = corporate.run("Should we invest in AI technology?") + >>> print(result['vote_result']) + """ + if self.verbose: + CORPORATE_LOGGER.info(f"CorporateSwarm processing task: {task[:100]}...") + + # Check budget before starting + if not self.cost_tracker.check_budget(): + CORPORATE_LOGGER.warning(f"Budget limit exceeded for task: {task[:50]}...") + return { + "status": "failed", + "reason": "Budget limit exceeded", + "task": task + } + + try: + # Determine task type and route accordingly with performance optimization + task_lower = task.lower() + + if any(keyword in task_lower for keyword in ["proposal", "vote", "decision"]): + return self._process_proposal_task(task, **kwargs) + elif any(keyword in task_lower for keyword in ["meeting", "board", "committee"]): + return self._process_meeting_task(task, **kwargs) + elif any(keyword in task_lower for keyword in ["strategic", "planning", "initiative"]): + return self._process_strategic_task(task, **kwargs) + else: + return self._process_general_task(task, **kwargs) + + except Exception as e: + CORPORATE_LOGGER.error(f"Error processing task '{task[:50]}...': {str(e)}") + return { + "status": "error", + "error": str(e), + "task": task + } + + async def arun( + self, + task: str, + **kwargs + ) -> Union[str, Dict[str, Any]]: + """ + Asynchronous version of run method with concurrency optimization. + + Args: + task: The corporate task or proposal to process + **kwargs: Additional parameters for task processing + + Returns: + Union[str, Dict[str, Any]]: Task results or decision outcomes + """ if self.verbose: - logger.info(f"Initializing CorporateSwarm: {self.name}") - logger.debug(f"CorporateSwarm parameters: max_loops={max_loops}, " - f"democratic_discussion={enable_democratic_discussion}, " - f"departmental_work={enable_departmental_work}") + logger.info(f"CorporateSwarm async processing task: {task[:100]}...") - # Initialize default corporate structure - self._initialize_default_structure() + # Check budget before starting + if not self.cost_tracker.check_budget(): + logger.warning(f"Budget limit exceeded for async task: {task[:50]}...") + return { + "status": "failed", + "reason": "Budget limit exceeded", + "task": task + } - # Initialize democratic swarm if enabled - if self.enable_democratic_discussion: - self._initialize_democratic_swarm() + try: + # Run in thread pool for I/O bound operations + loop = asyncio.get_event_loop() + result = await loop.run_in_executor(None, self.run, task, **kwargs) + return result + + except Exception as e: + logger.error(f"Error in async processing task '{task[:50]}...': {str(e)}") + return { + "status": "error", + "error": str(e), + "task": task + } def _initialize_default_structure(self) -> None: """Initialize default corporate structure with key positions.""" @@ -503,6 +804,14 @@ class CorporateSwarm: (BoardCommitteeType.NOMINATING, "Nominating Committee", ["board_nominations", "governance_policies", "director_evaluations"]), (BoardCommitteeType.RISK, "Risk Committee", ["risk_management", "cybersecurity", "operational_risk"]), (BoardCommitteeType.TECHNOLOGY, "Technology Committee", ["technology_strategy", "digital_transformation", "innovation"]), + (BoardCommitteeType.ESG, "ESG Committee", ["environmental_sustainability", "social_responsibility", "governance_oversight"]), + (BoardCommitteeType.SUSTAINABILITY, "Sustainability Committee", ["carbon_neutrality", "renewable_energy", "sustainable_practices"]), + (BoardCommitteeType.CYBERSECURITY, "Cybersecurity Committee", ["cyber_risk_management", "data_protection", "incident_response"]), + (BoardCommitteeType.INNOVATION, "Innovation Committee", ["r_and_d_strategy", "digital_transformation", "emerging_technologies"]), + (BoardCommitteeType.STAKEHOLDER, "Stakeholder Committee", ["stakeholder_engagement", "community_relations", "investor_relations"]), + (BoardCommitteeType.CRISIS_MANAGEMENT, "Crisis Management Committee", ["crisis_response", "business_continuity", "reputation_management"]), + (BoardCommitteeType.AI_ETHICS, "AI Ethics Committee", ["ai_governance", "algorithmic_fairness", "responsible_ai"]), + (BoardCommitteeType.DATA_PRIVACY, "Data Privacy Committee", ["data_protection", "privacy_compliance", "gdpr_oversight"]), ] for committee_type, name, responsibilities in committee_configs: @@ -694,22 +1003,7 @@ When participating in corporate decisions, always provide: timeline: str = "", **kwargs ) -> str: - """ - Create a new corporate proposal. - - Args: - title: Title of the proposal - description: Detailed description of the proposal - proposal_type: Type of corporate proposal - sponsor_id: ID of the member sponsoring the proposal - department: Department responsible for implementation - budget_impact: Financial impact of the proposal - timeline: Implementation timeline - **kwargs: Additional proposal attributes - - Returns: - str: Proposal ID of the created proposal - """ + """Create a new corporate proposal.""" if sponsor_id not in self.members: raise ValueError(f"Sponsor {sponsor_id} not found in corporate members") @@ -736,16 +1030,7 @@ When participating in corporate decisions, always provide: proposal_id: str, participants: List[str] = None ) -> CorporateVote: - """ - Conduct a democratic vote on a corporate proposal. - - Args: - proposal_id: ID of the proposal to vote on - participants: List of member IDs to participate in the vote - - Returns: - CorporateVote: Vote results and analysis - """ + """Conduct a democratic vote on a corporate proposal.""" # Find the proposal proposal = None for p in self.proposals: @@ -1031,16 +1316,7 @@ Your voting weight: {member.voting_weight} meeting_id: str, discussion_topics: List[str] = None ) -> BoardMeeting: - """ - Conduct a board meeting with discussion and decisions. - - Args: - meeting_id: ID of the meeting to conduct - discussion_topics: List of topics to discuss - - Returns: - BoardMeeting: Updated meeting with minutes and resolutions - """ + """Conduct a board meeting with discussion and decisions.""" # Find the meeting meeting = None for m in self.board_meetings: @@ -1107,17 +1383,7 @@ Your voting weight: {member.voting_weight} meeting_type: MeetingType = MeetingType.COMMITTEE_MEETING, agenda: List[str] = None ) -> Dict[str, Any]: - """ - Conduct a committee meeting with real API calls. - - Args: - committee_id: ID of the committee - meeting_type: Type of meeting - agenda: List of agenda items - - Returns: - Dict[str, Any]: Committee meeting results with issues discussed and recommendations - """ + """Conduct a committee meeting with real API calls.""" if committee_id not in self.board_committees: raise ValueError(f"Committee {committee_id} not found") @@ -1222,12 +1488,7 @@ Your voting weight: {member.voting_weight} } def evaluate_board_performance(self) -> Dict[str, Any]: - """ - Evaluate board performance and governance effectiveness. - - Returns: - Dict[str, Any]: Board performance metrics and analysis - """ + """Evaluate board performance and governance effectiveness.""" if self.verbose: logger.info("Evaluating board performance") @@ -1280,6 +1541,504 @@ Your voting weight: {member.voting_weight} return performance_metrics + def calculate_esg_score(self) -> ESGScore: + """Calculate comprehensive ESG (Environmental, Social, Governance) score.""" + if self.verbose: + CORPORATE_LOGGER.info("Calculating ESG score for corporate governance") + + # Calculate environmental score + environmental_score = self._calculate_environmental_score() + + # Calculate social score + social_score = self._calculate_social_score() + + # Calculate governance score + governance_score = self._calculate_governance_score() + + # Calculate overall score + overall_score = (environmental_score + social_score + governance_score) / 3 + + # Calculate diversity index + diversity_index = self._calculate_diversity_index() + + # Calculate stakeholder satisfaction + stakeholder_satisfaction = self._calculate_stakeholder_satisfaction() + + esg_score = ESGScore( + environmental_score=environmental_score, + social_score=social_score, + governance_score=governance_score, + overall_score=overall_score, + carbon_footprint=self._calculate_carbon_footprint(), + diversity_index=diversity_index, + stakeholder_satisfaction=stakeholder_satisfaction, + sustainability_goals=self._get_sustainability_goals() + ) + + # Store ESG score + self.esg_scores[str(time.time())] = esg_score + + return esg_score + + def _calculate_environmental_score(self) -> float: + """Calculate environmental performance score.""" + # Base score from sustainability practices + base_score = 70.0 + + # Adjust based on sustainability targets + if self.sustainability_targets: + target_achievement = len([t for t in self.sustainability_targets.values() if t.get('achieved', False)]) + total_targets = len(self.sustainability_targets) + if total_targets > 0: + base_score += (target_achievement / total_targets) * 30 + + return min(100.0, base_score) + + def _calculate_social_score(self) -> float: + """Calculate social performance score.""" + # Base score from stakeholder engagement + base_score = 75.0 + + # Adjust based on stakeholder satisfaction + if self.stakeholder_engagements: + avg_satisfaction = sum(s.satisfaction_score for s in self.stakeholder_engagements.values()) / len(self.stakeholder_engagements) + base_score = avg_satisfaction + + return min(100.0, base_score) + + def _calculate_governance_score(self) -> float: + """Calculate governance performance score.""" + # Base score from board performance + base_score = 80.0 + + # Adjust based on board performance metrics + if hasattr(self, 'performance_metrics') and self.performance_metrics: + governance_metrics = self.performance_metrics.get('governance', {}) + if governance_metrics: + base_score = governance_metrics.get('governance_score', base_score) + + return min(100.0, base_score) + + def _calculate_diversity_index(self) -> float: + """Calculate board diversity index.""" + if not self.board_members: + return 0.0 + + # Simple diversity calculation based on different expertise areas + unique_expertise = set() + for member_id in self.board_members: + if member_id in self.members: + unique_expertise.update(self.members[member_id].expertise_areas) + + # Normalize to 0-1 scale + max_possible_diversity = 10 # Assume max 10 different expertise areas + diversity_index = min(1.0, len(unique_expertise) / max_possible_diversity) + + return diversity_index + + def _calculate_stakeholder_satisfaction(self) -> float: + """Calculate overall stakeholder satisfaction score.""" + if not self.stakeholder_engagements: + return 75.0 # Default score + + avg_satisfaction = sum(s.satisfaction_score for s in self.stakeholder_engagements.values()) / len(self.stakeholder_engagements) + return avg_satisfaction + + def _calculate_carbon_footprint(self) -> float: + """Calculate corporate carbon footprint.""" + # Simplified carbon footprint calculation + base_footprint = 100.0 # Base metric tons CO2 equivalent + + # Adjust based on sustainability practices + if self.sustainability_targets: + carbon_reduction = len([t for t in self.sustainability_targets.values() if 'carbon' in t.get('type', '').lower()]) + base_footprint -= carbon_reduction * 10 + + return max(0.0, base_footprint) + + def _get_sustainability_goals(self) -> List[str]: + """Get current sustainability goals.""" + if not self.sustainability_targets: + return ["Carbon neutrality by 2030", "100% renewable energy", "Zero waste to landfill"] + + return [goal.get('description', '') for goal in self.sustainability_targets.values()] + + def conduct_risk_assessment(self, risk_category: str = "comprehensive") -> Dict[str, RiskAssessment]: + """Conduct comprehensive risk assessment across all corporate areas.""" + if self.verbose: + CORPORATE_LOGGER.info(f"Conducting {risk_category} risk assessment") + + risk_categories = [ + "operational", "financial", "strategic", "compliance", + "cybersecurity", "reputation", "environmental", "regulatory" + ] + + assessments = {} + + for category in risk_categories: + if risk_category == "comprehensive" or risk_category == category: + assessment = self._assess_risk_category(category) + assessments[category] = assessment + self.risk_assessments[assessment.risk_id] = assessment + + return assessments + + def _assess_risk_category(self, category: str) -> RiskAssessment: + """Assess risk for a specific category.""" + # Simplified risk assessment logic + risk_levels = {"operational": 0.3, "financial": 0.4, "strategic": 0.5, "compliance": 0.2} + probabilities = {"operational": 0.6, "financial": 0.4, "strategic": 0.3, "compliance": 0.7} + + probability = probabilities.get(category, 0.5) + impact = risk_levels.get(category, 0.4) + risk_score = probability * impact + + risk_level = "low" if risk_score < 0.3 else "medium" if risk_score < 0.6 else "high" + + return RiskAssessment( + risk_category=category, + risk_level=risk_level, + probability=probability, + impact=impact, + risk_score=risk_score, + mitigation_strategies=self._get_mitigation_strategies(category), + owner=self._get_risk_owner(category) + ) + + def _get_mitigation_strategies(self, category: str) -> List[str]: + """Get mitigation strategies for risk category.""" + strategies = { + "operational": ["Process optimization", "Backup systems", "Training programs"], + "financial": ["Diversification", "Hedging strategies", "Cash reserves"], + "strategic": ["Market research", "Competitive analysis", "Scenario planning"], + "compliance": ["Regular audits", "Training programs", "Compliance monitoring"], + "cybersecurity": ["Security protocols", "Incident response", "Regular updates"], + "reputation": ["Crisis management", "Stakeholder communication", "Brand monitoring"], + "environmental": ["Sustainability initiatives", "Environmental monitoring", "Green practices"], + "regulatory": ["Legal compliance", "Regulatory monitoring", "Policy updates"] + } + return strategies.get(category, ["General risk mitigation", "Monitoring", "Response planning"]) + + def _get_risk_owner(self, category: str) -> str: + """Get risk owner for category.""" + owners = { + "operational": "COO", + "financial": "CFO", + "strategic": "CEO", + "compliance": "General Counsel", + "cybersecurity": "CTO", + "reputation": "CEO", + "environmental": "Sustainability Officer", + "regulatory": "Compliance Officer" + } + return owners.get(category, "Board of Directors") + + def manage_stakeholder_engagement(self, stakeholder_type: str = "all") -> Dict[str, StakeholderEngagement]: + """ + Manage comprehensive stakeholder engagement across all stakeholder groups. + + Args: + stakeholder_type: Type of stakeholders to engage with + + Returns: + Dict[str, StakeholderEngagement]: Stakeholder engagement records + """ + if self.verbose: + CORPORATE_LOGGER.info(f"Managing stakeholder engagement for {stakeholder_type}") + + stakeholder_types = ["investor", "customer", "employee", "community", "supplier", "regulator"] + engagements = {} + + for stype in stakeholder_types: + if stakeholder_type == "all" or stakeholder_type == stype: + engagement = self._create_stakeholder_engagement(stype) + engagements[stype] = engagement + self.stakeholder_engagements[engagement.stakeholder_id] = engagement + + return engagements + + def _create_stakeholder_engagement(self, stakeholder_type: str) -> StakeholderEngagement: + """Create stakeholder engagement record.""" + # Simplified stakeholder engagement logic + satisfaction_scores = { + "investor": 85.0, + "customer": 80.0, + "employee": 75.0, + "community": 70.0, + "supplier": 78.0, + "regulator": 90.0 + } + + return StakeholderEngagement( + stakeholder_type=stakeholder_type, + name=f"{stakeholder_type.title()} Group", + influence_level="high" if stakeholder_type in ["investor", "regulator"] else "medium", + interest_level="high" if stakeholder_type in ["investor", "customer"] else "medium", + satisfaction_score=satisfaction_scores.get(stakeholder_type, 75.0), + concerns=self._get_stakeholder_concerns(stakeholder_type) + ) + + def _get_stakeholder_concerns(self, stakeholder_type: str) -> List[str]: + """Get common concerns for stakeholder type.""" + concerns = { + "investor": ["ROI", "Risk management", "Growth prospects"], + "customer": ["Product quality", "Customer service", "Pricing"], + "employee": ["Work-life balance", "Career development", "Compensation"], + "community": ["Environmental impact", "Local employment", "Community support"], + "supplier": ["Payment terms", "Partnership stability", "Fair treatment"], + "regulator": ["Compliance", "Transparency", "Risk management"] + } + return concerns.get(stakeholder_type, ["General concerns", "Communication", "Transparency"]) + + def establish_compliance_framework(self, regulation_type: str = "comprehensive") -> Dict[str, ComplianceFramework]: + """Establish comprehensive compliance framework for regulatory adherence.""" + if self.verbose: + CORPORATE_LOGGER.info(f"Establishing compliance framework for {regulation_type}") + + regulations = [ + ("SOX", "financial", ["Internal controls", "Financial reporting", "Audit requirements"]), + ("GDPR", "data_privacy", ["Data protection", "Privacy rights", "Consent management"]), + ("ISO 27001", "cybersecurity", ["Information security", "Risk management", "Security controls"]), + ("ESG", "sustainability", ["Environmental reporting", "Social responsibility", "Governance standards"]), + ("HIPAA", "healthcare", ["Patient privacy", "Data security", "Compliance monitoring"]) + ] + + frameworks = {} + + for reg_name, reg_type, requirements in regulations: + if regulation_type == "comprehensive" or regulation_type == reg_type: + framework = ComplianceFramework( + regulation_name=reg_name, + regulation_type=reg_type, + requirements=requirements, + controls=self._get_compliance_controls(reg_type), + responsible_officer=self._get_compliance_officer(reg_type) + ) + frameworks[reg_name] = framework + self.compliance_frameworks[framework.compliance_id] = framework + + return frameworks + + def _get_compliance_controls(self, regulation_type: str) -> List[str]: + """Get compliance controls for regulation type.""" + controls = { + "financial": ["Internal audit", "Financial controls", "Reporting systems"], + "data_privacy": ["Data encryption", "Access controls", "Privacy policies"], + "cybersecurity": ["Security monitoring", "Incident response", "Access management"], + "sustainability": ["Environmental monitoring", "Sustainability reporting", "Goal tracking"], + "healthcare": ["Patient data protection", "Access controls", "Audit trails"] + } + return controls.get(regulation_type, ["General controls", "Monitoring", "Reporting"]) + + def _get_compliance_officer(self, regulation_type: str) -> str: + """Get compliance officer for regulation type.""" + officers = { + "financial": "CFO", + "data_privacy": "Data Protection Officer", + "cybersecurity": "CISO", + "sustainability": "Sustainability Officer", + "healthcare": "Compliance Officer" + } + return officers.get(regulation_type, "Compliance Officer") + + def _process_proposal_task(self, task: str, **kwargs) -> Dict[str, Any]: + """ + Process proposal-related tasks with performance optimization. + + Args: + task: The proposal task to process + **kwargs: Additional parameters for proposal creation + + Returns: + Dict[str, Any]: Proposal processing results + """ + if self.verbose: + logger.info("Processing proposal task with democratic voting") + + try: + # Create a proposal from the task + proposal_id = self.create_proposal( + title=f"Task Proposal: {task[:50]}...", + description=task, + proposal_type=ProposalType.STRATEGIC_INITIATIVE, + sponsor_id=self.executive_team[0] if self.executive_team else self.board_members[0], + department=DepartmentType.OPERATIONS, + **kwargs + ) + + # Conduct democratic vote with error handling + vote = self.conduct_corporate_vote(proposal_id) + + return { + "status": "completed", + "proposal_id": proposal_id, + "vote_result": vote.result.value, + "participants": len(vote.participants), + "task": task, + "timestamp": time.time() + } + + except Exception as e: + logger.error(f"Error processing proposal task: {str(e)}") + return { + "status": "error", + "error": str(e), + "task": task + } + + def _process_meeting_task(self, task: str, **kwargs) -> Dict[str, Any]: + """Process meeting-related tasks with board governance.""" + if self.verbose: + logger.info("Processing meeting task with board governance") + + try: + # Schedule and conduct a board meeting + meeting_id = self.schedule_board_meeting( + meeting_type=MeetingType.REGULAR_BOARD, + agenda=[task], + **kwargs + ) + + meeting = self.conduct_board_meeting( + meeting_id=meeting_id, + discussion_topics=[task] + ) + + return { + "status": "completed", + "meeting_id": meeting_id, + "resolutions": meeting.resolutions, + "minutes": meeting.minutes, + "task": task, + "timestamp": time.time() + } + + except Exception as e: + logger.error(f"Error processing meeting task: {str(e)}") + return { + "status": "error", + "error": str(e), + "task": task + } + + def _process_strategic_task(self, task: str, **kwargs) -> Dict[str, Any]: + """ + Process strategic planning tasks with comprehensive analysis. + + Args: + task: The strategic task to process + **kwargs: Additional parameters for strategic planning + + Returns: + Dict[str, Any]: Strategic planning results + """ + if self.verbose: + logger.info("Processing strategic task with comprehensive analysis") + + try: + # Run a corporate session for strategic planning + session_results = self.run_corporate_session( + session_type="strategic_planning", + agenda_items=[task], + **kwargs + ) + + return { + "status": "completed", + "session_type": session_results["session_type"], + "decisions": session_results["decisions"], + "task": task, + "timestamp": time.time() + } + + except Exception as e: + logger.error(f"Error processing strategic task: {str(e)}") + return { + "status": "error", + "error": str(e), + "task": task + } + + def _process_general_task(self, task: str, **kwargs) -> Union[str, Dict[str, Any]]: + """Process general corporate tasks using democratic swarm with performance optimization.""" + if self.verbose: + logger.info("Processing general task through democratic swarm") + + if self.democratic_swarm is not None: + try: + result = self.democratic_swarm.run(task) + + # Handle different result types with robust parsing + parsed_result = self._parse_swarm_result(result) + + return { + "status": "completed", + "result": parsed_result, + "task": task, + "timestamp": time.time() + } + + except Exception as e: + logger.error(f"Democratic swarm encountered issue: {e}") + return { + "status": "error", + "error": str(e), + "task": task + } + else: + # Fallback to simple task processing + logger.warning("Democratic swarm not available, using fallback processing") + return { + "status": "completed", + "result": f"Task processed: {task}", + "task": task, + "timestamp": time.time() + } + + def _parse_swarm_result(self, result: Any) -> Dict[str, Any]: + """Parse swarm result with robust error handling.""" + try: + if isinstance(result, list): + if result and len(result) > 0: + first_item = result[0] + if isinstance(first_item, dict) and 'function' in first_item: + function_data = first_item.get('function', {}) + if 'arguments' in function_data: + try: + args_str = function_data['arguments'] + if isinstance(args_str, str): + parsed_args = json.loads(args_str) + return parsed_args + else: + return args_str + except (json.JSONDecodeError, TypeError): + return function_data.get('arguments', {}) + else: + return function_data + else: + return { + 'result': 'processed', + 'data': result, + 'type': 'list_response' + } + else: + return {'result': 'empty_response', 'type': 'list_response'} + elif isinstance(result, dict): + return result + else: + return { + 'result': 'processed', + 'data': str(result), + 'type': 'string_response' + } + except Exception as e: + logger.warning(f"Error parsing swarm result: {e}") + return { + 'result': 'parse_error', + 'error': str(e), + 'raw_data': str(result) + } + def _analyze_vote_results( self, individual_votes: Dict[str, Dict[str, Any]], @@ -1323,16 +2082,7 @@ Your voting weight: {member.voting_weight} session_type: str = "board_meeting", agenda_items: List[str] = None ) -> Dict[str, Any]: - """ - Run a corporate governance session. - - Args: - session_type: Type of corporate session - agenda_items: List of agenda items to discuss - - Returns: - Dict[str, Any]: Session results and outcomes - """ + """Run a corporate governance session.""" if not agenda_items: agenda_items = ["Strategic planning", "Budget review", "Operational updates"] @@ -1377,15 +2127,22 @@ Your voting weight: {member.voting_weight} return session_results def get_corporate_status(self) -> Dict[str, Any]: - """ - Get current corporate status and metrics. - - Returns: - Dict[str, Any]: Corporate status information - """ + """Get current corporate status and metrics including advanced governance frameworks.""" # Get board performance metrics board_performance = self.evaluate_board_performance() + # Calculate ESG score + esg_score = self.calculate_esg_score() + + # Get risk assessment summary + risk_summary = self._get_risk_summary() + + # Get stakeholder engagement summary + stakeholder_summary = self._get_stakeholder_summary() + + # Get compliance status + compliance_status = self._get_compliance_status() + return { "name": self.name, "description": self.description, @@ -1432,8 +2189,174 @@ Your voting weight: {member.voting_weight} for meeting in self.board_meetings[-3:] # Last 3 meetings ], "performance_metrics": board_performance + }, + "esg_governance": { + "overall_score": esg_score.overall_score, + "environmental_score": esg_score.environmental_score, + "social_score": esg_score.social_score, + "governance_score": esg_score.governance_score, + "carbon_footprint": esg_score.carbon_footprint, + "diversity_index": esg_score.diversity_index, + "stakeholder_satisfaction": esg_score.stakeholder_satisfaction, + "sustainability_goals": esg_score.sustainability_goals + }, + "risk_management": risk_summary, + "stakeholder_engagement": stakeholder_summary, + "compliance_framework": compliance_status, + "advanced_governance": { + "total_risk_assessments": len(self.risk_assessments), + "total_stakeholder_engagements": len(self.stakeholder_engagements), + "total_compliance_frameworks": len(self.compliance_frameworks), + "crisis_management_plans": len(self.crisis_management_plans), + "innovation_pipeline_items": len(self.innovation_pipeline), + "audit_trail_entries": len(self.audit_trails) } } + + def _get_risk_summary(self) -> Dict[str, Any]: + """Get risk management summary.""" + if not self.risk_assessments: + return {"status": "No risk assessments conducted", "total_risks": 0} + + high_risks = [r for r in self.risk_assessments.values() if r.risk_level == "high"] + medium_risks = [r for r in self.risk_assessments.values() if r.risk_level == "medium"] + low_risks = [r for r in self.risk_assessments.values() if r.risk_level == "low"] + + return { + "total_risks": len(self.risk_assessments), + "high_risks": len(high_risks), + "medium_risks": len(medium_risks), + "low_risks": len(low_risks), + "risk_categories": list(set(r.risk_category for r in self.risk_assessments.values())), + "average_risk_score": sum(r.risk_score for r in self.risk_assessments.values()) / len(self.risk_assessments) + } + + def _get_stakeholder_summary(self) -> Dict[str, Any]: + """Get stakeholder engagement summary.""" + if not self.stakeholder_engagements: + return {"status": "No stakeholder engagements recorded", "total_stakeholders": 0} + + stakeholder_types = list(set(s.stakeholder_type for s in self.stakeholder_engagements.values())) + avg_satisfaction = sum(s.satisfaction_score for s in self.stakeholder_engagements.values()) / len(self.stakeholder_engagements) + + return { + "total_stakeholders": len(self.stakeholder_engagements), + "stakeholder_types": stakeholder_types, + "average_satisfaction": avg_satisfaction, + "high_influence_stakeholders": len([s for s in self.stakeholder_engagements.values() if s.influence_level == "high"]), + "high_interest_stakeholders": len([s for s in self.stakeholder_engagements.values() if s.interest_level == "high"]) + } + + def _get_compliance_status(self) -> Dict[str, Any]: + """Get compliance framework status.""" + if not self.compliance_frameworks: + return {"status": "No compliance frameworks established", "total_frameworks": 0} + + compliant_frameworks = [f for f in self.compliance_frameworks.values() if f.compliance_status == "compliant"] + non_compliant_frameworks = [f for f in self.compliance_frameworks.values() if f.compliance_status == "non_compliant"] + + return { + "total_frameworks": len(self.compliance_frameworks), + "compliant_frameworks": len(compliant_frameworks), + "non_compliant_frameworks": len(non_compliant_frameworks), + "compliance_rate": len(compliant_frameworks) / len(self.compliance_frameworks) * 100, + "regulation_types": list(set(f.regulation_type for f in self.compliance_frameworks.values())), + "average_compliance_score": sum(f.compliance_score for f in self.compliance_frameworks.values()) / len(self.compliance_frameworks) + } + + def conduct_comprehensive_governance_review(self) -> Dict[str, Any]: + """Conduct a comprehensive governance review across all frameworks.""" + if self.verbose: + CORPORATE_LOGGER.info("Conducting comprehensive governance review") + + # Calculate ESG score + esg_score = self.calculate_esg_score() + + # Conduct risk assessment + risk_assessments = self.conduct_risk_assessment("comprehensive") + + # Manage stakeholder engagement + stakeholder_engagements = self.manage_stakeholder_engagement("all") + + # Establish compliance framework + compliance_frameworks = self.establish_compliance_framework("comprehensive") + + # Evaluate board performance + board_performance = self.evaluate_board_performance() + + # Get corporate status + corporate_status = self.get_corporate_status() + + return { + "review_timestamp": time.time(), + "esg_analysis": { + "overall_score": esg_score.overall_score, + "environmental_score": esg_score.environmental_score, + "social_score": esg_score.social_score, + "governance_score": esg_score.governance_score, + "carbon_footprint": esg_score.carbon_footprint, + "diversity_index": esg_score.diversity_index, + "stakeholder_satisfaction": esg_score.stakeholder_satisfaction + }, + "risk_analysis": { + "total_risks": len(risk_assessments), + "high_risk_categories": [cat for cat, risk in risk_assessments.items() if risk.risk_level == "high"], + "average_risk_score": sum(risk.risk_score for risk in risk_assessments.values()) / len(risk_assessments) if risk_assessments else 0 + }, + "stakeholder_analysis": { + "total_stakeholders": len(stakeholder_engagements), + "average_satisfaction": sum(eng.satisfaction_score for eng in stakeholder_engagements.values()) / len(stakeholder_engagements) if stakeholder_engagements else 0, + "stakeholder_types": list(stakeholder_engagements.keys()) + }, + "compliance_analysis": { + "total_frameworks": len(compliance_frameworks), + "compliance_rate": len([f for f in compliance_frameworks.values() if f.compliance_status == "compliant"]) / len(compliance_frameworks) * 100 if compliance_frameworks else 0, + "regulation_types": list(set(f.regulation_type for f in compliance_frameworks.values())) + }, + "board_performance": board_performance, + "corporate_status": corporate_status, + "governance_recommendations": self._generate_governance_recommendations(esg_score, risk_assessments, stakeholder_engagements, compliance_frameworks) + } + + def _generate_governance_recommendations( + self, + esg_score: ESGScore, + risk_assessments: Dict[str, RiskAssessment], + stakeholder_engagements: Dict[str, StakeholderEngagement], + compliance_frameworks: Dict[str, ComplianceFramework] + ) -> List[str]: + """Generate governance recommendations based on analysis.""" + recommendations = [] + + # ESG recommendations + if esg_score.overall_score < 70: + recommendations.append("Improve overall ESG performance through enhanced sustainability initiatives") + if esg_score.environmental_score < 70: + recommendations.append("Implement stronger environmental sustainability programs") + if esg_score.social_score < 70: + recommendations.append("Enhance social responsibility and stakeholder engagement") + if esg_score.governance_score < 70: + recommendations.append("Strengthen corporate governance practices and board oversight") + + # Risk recommendations + high_risks = [risk for risk in risk_assessments.values() if risk.risk_level == "high"] + if high_risks: + recommendations.append(f"Address {len(high_risks)} high-risk areas with immediate mitigation strategies") + + # Stakeholder recommendations + low_satisfaction_stakeholders = [eng for eng in stakeholder_engagements.values() if eng.satisfaction_score < 70] + if low_satisfaction_stakeholders: + recommendations.append("Improve stakeholder satisfaction through enhanced engagement programs") + + # Compliance recommendations + non_compliant = [f for f in compliance_frameworks.values() if f.compliance_status == "non_compliant"] + if non_compliant: + recommendations.append(f"Address {len(non_compliant)} non-compliant regulatory frameworks") + + if not recommendations: + recommendations.append("Maintain current governance excellence and continue monitoring") + + return recommendations class CostTracker: