"""
Collaborative Workflow Engine

Orchestrates collaborative workflows within agent communities,
including brainstorming, problem-solving, and knowledge synthesis.
"""

import logging
from datetime import datetime, timedelta
from typing import Dict, List, Any, Optional
import uuid
import asyncio

from .models.community_models import CollaborationSession
from .exceptions import CommunityValidationError as TaskValidationError

logger = logging.getLogger(__name__)


class CollaborativeWorkflowEngine:
    """
    Engine for orchestrating collaborative workflows within agent communities.
    """

    def __init__(self, community_manager=None, resource_manager=None, decision_engine=None):
        """
        Initialize the collaborative workflow engine.
        
        Args:
            community_manager: Reference to the community manager
            resource_manager: Reference to the resource manager
            decision_engine: Reference to the decision engine
        """
        self.community_manager = community_manager
        self.resource_manager = resource_manager
        self.decision_engine = decision_engine
        
        # Active collaborative sessions
        self.active_sessions: Dict[str, CollaborationSession] = {}
        
        # Workflow templates
        self.workflow_templates = {
            "brainstorming": self._brainstorming_workflow,
            "problem_solving": self._problem_solving_workflow,
            "knowledge_synthesis": self._knowledge_synthesis_workflow,
            "decision_making": self._decision_making_workflow,
            "resource_creation": self._resource_creation_workflow,
            "peer_review": self._peer_review_workflow,
            "consensus_building": self._consensus_building_workflow
        }
        
        logger.info("Collaborative workflow engine initialized")

    async def start_collaborative_session(
        self,
        community_id: str,
        session_leader_id: str,
        session_type: str,
        purpose: str,
        participants: List[str],
        agenda: Optional[List[str]] = None,
        duration_minutes: int = 60,
        session_config: Optional[Dict[str, Any]] = None
    ) -> str:
        """
        Start a collaborative session.
        
        Args:
            community_id: ID of the community
            session_leader_id: ID of the session leader
            session_type: Type of collaborative session
            purpose: Purpose of the session
            participants: List of participant member IDs
            agenda: Optional agenda items
            duration_minutes: Expected duration in minutes
            session_config: Optional session configuration
            
        Returns:
            Session ID
        """
        if not self.community_manager:
            raise TaskValidationError("Community manager not available")
        
        # Validate community and participants
        community = self.community_manager.communities.get(community_id)
        if not community:
            raise TaskValidationError(f"Community not found: {community_id}")
        
        # Create collaboration session
        session = CollaborationSession(
            community_id=community_id,
            participants=participants,
            session_leader=session_leader_id,
            purpose=purpose,
            session_type=session_type,
            agenda=agenda or [],
            metadata=session_config or {}
        )
        
        self.active_sessions[session.session_id] = session
        
        # Execute workflow template if available
        if session_type in self.workflow_templates:
            workflow_func = self.workflow_templates[session_type]
            await workflow_func(session)
        
        logger.info(f"Started collaborative session: {session_type} ({session.session_id})")
        return session.session_id

    async def _brainstorming_workflow(self, session: CollaborationSession) -> None:
        """
        Execute brainstorming workflow.
        
        Phases:
        1. Idea generation
        2. Idea collection and categorization
        3. Idea evaluation and ranking
        4. Action item creation
        """
        logger.info(f"Starting brainstorming workflow for session {session.session_id}")
        
        # Phase 1: Idea Generation
        await self._execute_phase(session, "idea_generation", {
            "instructions": "Generate creative ideas related to the session purpose",
            "time_limit_minutes": 15,
            "parallel_thinking": True
        })
        
        # Phase 2: Idea Collection
        await self._execute_phase(session, "idea_collection", {
            "instructions": "Collect and categorize all generated ideas",
            "time_limit_minutes": 10,
            "collaborative": True
        })
        
        # Phase 3: Idea Evaluation
        await self._execute_phase(session, "idea_evaluation", {
            "instructions": "Evaluate and rank ideas based on feasibility and impact",
            "time_limit_minutes": 15,
            "voting_enabled": True
        })
        
        # Phase 4: Action Planning
        await self._execute_phase(session, "action_planning", {
            "instructions": "Create action items for top-ranked ideas",
            "time_limit_minutes": 10,
            "assign_responsibilities": True
        })

    async def _problem_solving_workflow(self, session: CollaborationSession) -> None:
        """
        Execute problem-solving workflow.
        
        Phases:
        1. Problem definition and analysis
        2. Root cause analysis
        3. Solution brainstorming
        4. Solution evaluation and selection
        5. Implementation planning
        """
        logger.info(f"Starting problem-solving workflow for session {session.session_id}")
        
        # Phase 1: Problem Definition
        await self._execute_phase(session, "problem_definition", {
            "instructions": "Define the problem clearly and analyze its scope",
            "time_limit_minutes": 15,
            "structured_analysis": True
        })
        
        # Phase 2: Root Cause Analysis
        await self._execute_phase(session, "root_cause_analysis", {
            "instructions": "Identify root causes using systematic analysis",
            "time_limit_minutes": 20,
            "analysis_methods": ["5_whys", "fishbone", "pareto"]
        })
        
        # Phase 3: Solution Brainstorming
        await self._execute_phase(session, "solution_brainstorming", {
            "instructions": "Generate potential solutions for identified root causes",
            "time_limit_minutes": 20,
            "creative_thinking": True
        })
        
        # Phase 4: Solution Evaluation
        await self._execute_phase(session, "solution_evaluation", {
            "instructions": "Evaluate solutions based on criteria matrix",
            "time_limit_minutes": 15,
            "evaluation_criteria": ["feasibility", "impact", "cost", "timeline"]
        })
        
        # Phase 5: Implementation Planning
        await self._execute_phase(session, "implementation_planning", {
            "instructions": "Create detailed implementation plan for selected solution",
            "time_limit_minutes": 15,
            "create_timeline": True
        })

    async def _knowledge_synthesis_workflow(self, session: CollaborationSession) -> None:
        """
        Execute knowledge synthesis workflow.
        
        Phases:
        1. Knowledge gathering
        2. Information analysis
        3. Pattern identification
        4. Synthesis and integration
        5. Knowledge artifact creation
        """
        logger.info(f"Starting knowledge synthesis workflow for session {session.session_id}")
        
        # Phase 1: Knowledge Gathering
        await self._execute_phase(session, "knowledge_gathering", {
            "instructions": "Gather relevant knowledge from community resources and expertise",
            "time_limit_minutes": 20,
            "resource_search": True
        })
        
        # Phase 2: Information Analysis
        await self._execute_phase(session, "information_analysis", {
            "instructions": "Analyze gathered information for relevance and quality",
            "time_limit_minutes": 15,
            "quality_assessment": True
        })
        
        # Phase 3: Pattern Identification
        await self._execute_phase(session, "pattern_identification", {
            "instructions": "Identify patterns, themes, and connections in the information",
            "time_limit_minutes": 20,
            "pattern_analysis": True
        })
        
        # Phase 4: Synthesis
        await self._execute_phase(session, "synthesis", {
            "instructions": "Synthesize information into coherent knowledge structure",
            "time_limit_minutes": 25,
            "collaborative_editing": True
        })
        
        # Phase 5: Artifact Creation
        await self._execute_phase(session, "artifact_creation", {
            "instructions": "Create knowledge artifacts for community sharing",
            "time_limit_minutes": 15,
            "create_resources": True
        })

    async def _decision_making_workflow(self, session: CollaborationSession) -> None:
        """
        Execute decision-making workflow.
        
        Phases:
        1. Decision framing
        2. Option generation
        3. Criteria definition
        4. Option evaluation
        5. Decision and commitment
        """
        logger.info(f"Starting decision-making workflow for session {session.session_id}")
        
        # Phase 1: Decision Framing
        await self._execute_phase(session, "decision_framing", {
            "instructions": "Frame the decision clearly with context and constraints",
            "time_limit_minutes": 15,
            "structured_framing": True
        })
        
        # Phase 2: Option Generation
        await self._execute_phase(session, "option_generation", {
            "instructions": "Generate multiple decision options",
            "time_limit_minutes": 20,
            "creative_options": True
        })
        
        # Phase 3: Criteria Definition
        await self._execute_phase(session, "criteria_definition", {
            "instructions": "Define evaluation criteria and their weights",
            "time_limit_minutes": 10,
            "criteria_weighting": True
        })
        
        # Phase 4: Option Evaluation
        await self._execute_phase(session, "option_evaluation", {
            "instructions": "Evaluate options against defined criteria",
            "time_limit_minutes": 20,
            "systematic_evaluation": True
        })
        
        # Phase 5: Decision Making
        await self._execute_phase(session, "decision_making", {
            "instructions": "Make final decision and create commitment plan",
            "time_limit_minutes": 15,
            "consensus_building": True,
            "create_decision": True
        })

    async def _resource_creation_workflow(self, session: CollaborationSession) -> None:
        """Execute resource creation workflow."""
        logger.info(f"Starting resource creation workflow for session {session.session_id}")
        
        # Phase 1: Resource Planning
        await self._execute_phase(session, "resource_planning", {
            "instructions": "Plan the resource to be created",
            "time_limit_minutes": 15
        })
        
        # Phase 2: Collaborative Creation
        await self._execute_phase(session, "collaborative_creation", {
            "instructions": "Collaboratively create the resource",
            "time_limit_minutes": 30,
            "collaborative_editing": True
        })
        
        # Phase 3: Review and Refinement
        await self._execute_phase(session, "review_refinement", {
            "instructions": "Review and refine the created resource",
            "time_limit_minutes": 15,
            "peer_review": True
        })

    async def _peer_review_workflow(self, session: CollaborationSession) -> None:
        """
        Execute peer review workflow.
        
        Phases:
        1. Reviewer assignment
        2. Individual review
        3. Review collection and synthesis
        4. Feedback integration
        5. Final approval
        """
        logger.info(f"Starting peer review workflow for session {session.session_id}")
        
        # Phase 1: Reviewer Assignment
        await self._execute_phase(session, "reviewer_assignment", {
            "instructions": "Assign reviewers based on expertise and availability",
            "time_limit_minutes": 5,
            "min_reviewers": 2,
            "max_reviewers": 5
        })
        
        # Phase 2: Individual Review
        await self._execute_phase(session, "individual_review", {
            "instructions": "Conduct independent review of the material",
            "time_limit_minutes": 30,
            "review_criteria": ["accuracy", "completeness", "clarity", "quality"],
            "parallel_reviews": True
        })
        
        # Phase 3: Review Collection
        await self._execute_phase(session, "review_collection", {
            "instructions": "Collect and synthesize all review feedback",
            "time_limit_minutes": 15,
            "identify_conflicts": True,
            "aggregate_scores": True
        })
        
        # Phase 4: Feedback Integration
        await self._execute_phase(session, "feedback_integration", {
            "instructions": "Integrate reviewer feedback into the material",
            "time_limit_minutes": 20,
            "collaborative_editing": True,
            "track_changes": True
        })
        
        # Phase 5: Final Approval
        await self._execute_phase(session, "final_approval", {
            "instructions": "Reviewers provide final approval or request changes",
            "time_limit_minutes": 10,
            "require_consensus": True,
            "approval_threshold": 0.8
        })

    async def _consensus_building_workflow(self, session: CollaborationSession) -> None:
        """
        Execute consensus building workflow.
        
        Phases:
        1. Issue presentation and clarification
        2. Discussion round 1 - Position sharing
        3. Common ground identification
        4. Proposal refinement
        5. Convergence check and agreement
        """
        logger.info(f"Starting consensus building workflow for session {session.session_id}")
        
        # Phase 1: Issue Presentation
        await self._execute_phase(session, "issue_presentation", {
            "instructions": "Present the issue clearly and allow clarification questions",
            "time_limit_minutes": 15,
            "clarification_enabled": True
        })
        
        # Phase 2: Position Sharing
        await self._execute_phase(session, "position_sharing", {
            "instructions": "Each member shares their position and rationale",
            "time_limit_minutes": 20,
            "equal_participation": True,
            "capture_positions": True
        })
        
        # Phase 3: Common Ground Identification
        await self._execute_phase(session, "common_ground_identification", {
            "instructions": "Identify areas of agreement and shared values",
            "time_limit_minutes": 15,
            "find_overlaps": True,
            "identify_blockers": True
        })
        
        # Phase 4: Proposal Refinement
        await self._execute_phase(session, "proposal_refinement", {
            "instructions": "Refine proposals to address concerns and maximize agreement",
            "time_limit_minutes": 25,
            "iterative_refinement": True,
            "test_proposals": True
        })
        
        # Phase 5: Convergence Check
        await self._execute_phase(session, "convergence_check", {
            "instructions": "Check for consensus and finalize agreement",
            "time_limit_minutes": 15,
            "consensus_threshold": 0.9,
            "allow_dissent": True,
            "document_agreement": True
        })

    async def _execute_phase(
        self,
        session: CollaborationSession,
        phase_name: str,
        phase_config: Dict[str, Any]
    ) -> None:
        """
        Execute a workflow phase.
        
        Args:
            session: Collaboration session
            phase_name: Name of the phase
            phase_config: Phase configuration
        """
        logger.info(f"Executing phase '{phase_name}' for session {session.session_id}")
        
        # Record phase execution
        phase_result = {
            "phase_name": phase_name,
            "started_at": datetime.utcnow().isoformat(),
            "config": phase_config,
            "participants": session.participants,
            "outputs": []
        }
        
        # Simulate phase execution (in real implementation, this would coordinate agent activities)
        time_limit = phase_config.get("time_limit_minutes", 10)
        await asyncio.sleep(1)  # Simulate processing time
        
        phase_result["completed_at"] = datetime.utcnow().isoformat()
        phase_result["status"] = "completed"
        
        # Store phase result in session metadata
        if "phases" not in session.metadata:
            session.metadata["phases"] = []
        session.metadata["phases"].append(phase_result)
        
        logger.info(f"Completed phase '{phase_name}' for session {session.session_id}")

    async def end_session(self, session_id: str) -> Dict[str, Any]:
        """
        End a collaborative session and generate summary.
        
        Args:
            session_id: ID of the session to end
            
        Returns:
            Session summary
        """
        if session_id not in self.active_sessions:
            raise TaskValidationError(f"Session not found: {session_id}")
        
        session = self.active_sessions[session_id]
        session.status = "completed"
        session.ended_at = datetime.utcnow()
        
        # Generate session summary
        summary = {
            "session_id": session_id,
            "session_type": session.session_type,
            "purpose": session.purpose,
            "participants": session.participants,
            "duration_minutes": (session.ended_at - session.started_at).total_seconds() / 60,
            "outcomes": session.action_items,
            "resources_created": session.resources_created,
            "decisions_made": session.decisions_made,
            "phases_completed": len(session.metadata.get("phases", [])),
            "status": session.status
        }
        
        # Remove from active sessions
        del self.active_sessions[session_id]
        
        logger.info(f"Ended collaborative session {session_id}")
        return summary
