"""
Milestone Verifier for License Compliance Monitoring

Tracks and verifies contractual milestones for license agreements.

FEATURES (Planned):
- Milestone definition and tracking
- Evidence collection for verification
- Deadline monitoring and alerts
- Integration with CriticAgent for validation

VISTA/HORIZON EU ALIGNMENT:
- Supports milestone-based payment structures common in EU research
- Integrates with project management workflows
- Provides audit trail for milestone verification

Author: SPARKNET Team
Project: VISTA/Horizon EU
Status: Placeholder - In Development
"""

from typing import Optional, Dict, Any, List
from dataclasses import dataclass, field
from datetime import datetime, date
from enum import Enum
from loguru import logger


class MilestoneStatus(str, Enum):
    """Milestone tracking status."""
    PENDING = "pending"
    IN_PROGRESS = "in_progress"
    SUBMITTED = "submitted"  # Awaiting verification
    VERIFIED = "verified"
    REJECTED = "rejected"
    WAIVED = "waived"
    OVERDUE = "overdue"


class MilestoneType(str, Enum):
    """Type of milestone."""
    TECHNICAL = "technical"  # Technical deliverable
    COMMERCIAL = "commercial"  # Commercial target
    REGULATORY = "regulatory"  # Regulatory approval
    FINANCIAL = "financial"  # Financial target
    REPORTING = "reporting"  # Report submission
    OTHER = "other"


@dataclass
class Milestone:
    """
    License agreement milestone definition.

    Represents a contractual milestone that must be achieved
    for license compliance.
    """
    milestone_id: str
    license_id: str
    title: str
    description: str
    milestone_type: MilestoneType
    due_date: date
    status: MilestoneStatus = MilestoneStatus.PENDING
    payment_trigger: bool = False  # If true, triggers milestone payment
    payment_amount: Optional[float] = None
    currency: str = "EUR"
    evidence_required: List[str] = field(default_factory=list)
    evidence_submitted: List[Dict[str, Any]] = field(default_factory=list)
    verified_by: Optional[str] = None
    verified_at: Optional[datetime] = None
    notes: Optional[str] = None
    metadata: Dict[str, Any] = field(default_factory=dict)


@dataclass
class VerificationResult:
    """
    Result of milestone verification.

    Includes CriticAgent validation scores when available.
    """
    verification_id: str
    milestone_id: str
    verified: bool
    confidence_score: float  # 0.0 to 1.0
    verification_notes: str
    evidence_review: List[Dict[str, Any]]
    critic_validation: Optional[Dict[str, Any]] = None  # CriticAgent output
    human_review_required: bool = False
    verified_at: datetime = field(default_factory=datetime.now)


class MilestoneVerifier:
    """
    Verifies milestone completion for license agreements.

    This component:
    - Tracks milestone deadlines
    - Collects and reviews evidence
    - Integrates with CriticAgent for AI validation
    - Implements human-in-the-loop for critical decisions

    HUMAN-IN-THE-LOOP CONSIDERATIONS:
    ----------------------------------
    Milestone verification often requires human judgment.
    This component implements:

    1. AUTOMATED VERIFICATION:
       - Document completeness checks
       - Format and structure validation
       - Cross-reference with requirements

    2. AI-ASSISTED REVIEW:
       - CriticAgent evaluates evidence quality
       - Confidence scoring for verification
       - Anomaly detection in submissions

    3. HUMAN DECISION POINTS:
       - Low-confidence verifications flagged for review
       - High-value milestones require approval
       - Rejection decisions need human confirmation

    4. AUDIT TRAIL:
       - All decisions logged with reasoning
       - Evidence preserved for compliance
       - Verification history maintained
    """

    def __init__(
        self,
        llm_client: Optional[Any] = None,
        critic_agent: Optional[Any] = None,  # CriticAgent for validation
        database_url: Optional[str] = None,
    ):
        """
        Initialize Milestone Verifier.

        Args:
            llm_client: LangChain LLM client for AI analysis
            critic_agent: CriticAgent for validation
            database_url: Database connection URL
        """
        self.llm_client = llm_client
        self.critic_agent = critic_agent
        self.database_url = database_url
        self.name = "MilestoneVerifier"

        # Threshold for requiring human review
        self.human_review_threshold = 0.7

        logger.info(f"Initialized {self.name} (placeholder)")

    async def create_milestone(
        self,
        license_id: str,
        title: str,
        description: str,
        milestone_type: MilestoneType,
        due_date: date,
        evidence_required: List[str],
        payment_trigger: bool = False,
        payment_amount: Optional[float] = None,
    ) -> Milestone:
        """
        Create a new milestone for a license agreement.

        Args:
            license_id: License agreement identifier
            title: Milestone title
            description: Detailed description
            milestone_type: Type of milestone
            due_date: Deadline for completion
            evidence_required: List of required evidence types
            payment_trigger: Whether completion triggers payment
            payment_amount: Payment amount if payment_trigger is True

        Returns:
            Created milestone

        TODO: Implement actual milestone creation logic
        """
        logger.info(f"Creating milestone '{title}' for license: {license_id}")

        return Milestone(
            milestone_id=f"ms_{datetime.now().strftime('%Y%m%d_%H%M%S')}",
            license_id=license_id,
            title=title,
            description=description,
            milestone_type=milestone_type,
            due_date=due_date,
            evidence_required=evidence_required,
            payment_trigger=payment_trigger,
            payment_amount=payment_amount,
        )

    async def submit_evidence(
        self,
        milestone_id: str,
        evidence_type: str,
        evidence_data: Dict[str, Any],
        submitted_by: str,
    ) -> Dict[str, Any]:
        """
        Submit evidence for milestone verification.

        Args:
            milestone_id: Milestone identifier
            evidence_type: Type of evidence being submitted
            evidence_data: Evidence data (documents, metrics, etc.)
            submitted_by: User/organization submitting

        Returns:
            Submission confirmation

        TODO: Implement actual evidence submission logic
        """
        logger.info(f"Submitting {evidence_type} evidence for milestone: {milestone_id}")

        # Placeholder response
        return {
            "submission_id": f"sub_{datetime.now().strftime('%Y%m%d_%H%M%S')}",
            "milestone_id": milestone_id,
            "evidence_type": evidence_type,
            "submitted_at": datetime.now().isoformat(),
            "submitted_by": submitted_by,
            "status": "received",
            "message": "Evidence submission not yet fully implemented",
        }

    async def verify_milestone(
        self,
        milestone_id: str,
        auto_approve: bool = False,
    ) -> VerificationResult:
        """
        Verify milestone completion using AI and human review.

        This method:
        1. Checks all required evidence is submitted
        2. Uses CriticAgent to validate evidence quality
        3. Calculates confidence score
        4. Determines if human review is needed

        Args:
            milestone_id: Milestone to verify
            auto_approve: Whether to auto-approve high-confidence verifications

        Returns:
            Verification result with confidence score

        TODO: Implement actual verification logic with CriticAgent
        """
        logger.info(f"Verifying milestone: {milestone_id}")

        # Placeholder verification result
        result = VerificationResult(
            verification_id=f"ver_{datetime.now().strftime('%Y%m%d_%H%M%S')}",
            milestone_id=milestone_id,
            verified=False,
            confidence_score=0.0,
            verification_notes="Verification not yet implemented",
            evidence_review=[],
            human_review_required=True,
        )

        return result

    async def get_overdue_milestones(
        self,
        as_of_date: Optional[date] = None,
    ) -> List[Milestone]:
        """
        Get list of overdue milestones.

        Args:
            as_of_date: Reference date (defaults to today)

        Returns:
            List of overdue milestones

        TODO: Implement actual overdue milestone tracking
        """
        as_of_date = as_of_date or date.today()
        logger.info(f"Checking overdue milestones as of {as_of_date}")

        # Placeholder response
        return []

    async def get_upcoming_milestones(
        self,
        days_ahead: int = 30,
    ) -> List[Milestone]:
        """
        Get milestones due in the near future.

        Args:
            days_ahead: Number of days to look ahead

        Returns:
            List of upcoming milestones

        TODO: Implement actual upcoming milestone tracking
        """
        logger.info(f"Getting milestones due in next {days_ahead} days")

        # Placeholder response
        return []

    def requires_human_review(
        self,
        confidence_score: float,
        milestone: Milestone,
    ) -> bool:
        """
        Determine if milestone verification requires human review.

        Human review is required when:
        - Confidence score is below threshold
        - Milestone triggers large payment
        - Milestone type is regulatory
        - Evidence is incomplete or ambiguous

        Args:
            confidence_score: AI verification confidence
            milestone: Milestone being verified

        Returns:
            True if human review required
        """
        # Low confidence requires review
        if confidence_score < self.human_review_threshold:
            return True

        # Large payments require review
        if milestone.payment_trigger and milestone.payment_amount:
            if milestone.payment_amount > 50000:  # EUR threshold
                return True

        # Regulatory milestones always require review
        if milestone.milestone_type == MilestoneType.REGULATORY:
            return True

        return False