env/utils.py

"""
Utility functions for time parsing, conflict detection, and metrics computation.
"""

from datetime import datetime, timedelta
from typing import List, Dict, Tuple, Optional


# ─── Time Utilities ───────────────────────────────────────────────────────────

TIME_SLOTS = [
    "08:00", "08:30", "09:00", "09:30", "10:00", "10:30",
    "11:00", "11:30", "12:00", "12:30", "13:00", "13:30",
    "14:00", "14:30", "15:00", "15:30", "16:00", "16:30",
    "17:00", "17:30", "18:00"
]

DURATIONS = [30, 60, 90, 120]  # minutes


def parse_time(time_str: str) -> datetime:
    """Parse a HH:MM time string into a datetime object (date fixed to today)."""
    return datetime.strptime(time_str, "%H:%M")


def time_to_minutes(time_str: str) -> int:
    """Convert HH:MM to total minutes since midnight."""
    dt = parse_time(time_str)
    return dt.hour * 60 + dt.minute


def minutes_to_time(minutes: int) -> str:
    """Convert total minutes since midnight to HH:MM string."""
    h = minutes // 60
    m = minutes % 60
    return f"{h:02d}:{m:02d}"


def get_end_time(start_time: str, duration_minutes: int) -> str:
    """Calculate end time given start time and duration in minutes."""
    start_mins = time_to_minutes(start_time)
    end_mins = start_mins + duration_minutes
    return minutes_to_time(end_mins)


def time_ranges_overlap(
    start1: str, dur1: int, start2: str, dur2: int
) -> bool:
    """Check if two time ranges overlap.

    Args:
        start1: Start time of first range (HH:MM).
        dur1: Duration of first range in minutes.
        start2: Start time of second range (HH:MM).
        dur2: Duration of second range in minutes.

    Returns:
        True if the ranges overlap.
    """
    s1 = time_to_minutes(start1)
    e1 = s1 + dur1
    s2 = time_to_minutes(start2)
    e2 = s2 + dur2
    return s1 < e2 and s2 < e1


def advance_time_slot(current_time: str, steps: int = 1) -> str:
    """Advance to the next time slot(s)."""
    current_mins = time_to_minutes(current_time)
    new_mins = current_mins + (30 * steps)
    # Clamp to end of day
    new_mins = min(new_mins, time_to_minutes("18:00"))
    return minutes_to_time(new_mins)


# ─── Conflict Detection ──────────────────────────────────────────────────────

def build_conflict_graph(tasks: List[Dict]) -> Dict[int, List[int]]:
    """Build an adjacency list of task conflicts based on time overlaps.

    Args:
        tasks: List of task dicts with 'id', 'time', 'duration', 'status'.

    Returns:
        Dict mapping task_id → list of conflicting task_ids.
    """
    scheduled = [
        t for t in tasks
        if t["status"] in ("pending", "scheduled", "completed")
    ]
    conflicts: Dict[int, List[int]] = {t["id"]: [] for t in scheduled}

    for i, t1 in enumerate(scheduled):
        for t2 in scheduled[i + 1:]:
            if time_ranges_overlap(
                t1["time"], t1.get("duration", 30),
                t2["time"], t2.get("duration", 30)
            ):
                conflicts[t1["id"]].append(t2["id"])
                conflicts[t2["id"]].append(t1["id"])

    return conflicts


def count_conflicts(tasks: List[Dict]) -> int:
    """Count the total number of unique conflict pairs."""
    graph = build_conflict_graph(tasks)
    count = 0
    seen = set()
    for tid, neighbors in graph.items():
        for nid in neighbors:
            pair = (min(tid, nid), max(tid, nid))
            if pair not in seen:
                seen.add(pair)
                count += 1
    return count


# ─── Metrics Computation ─────────────────────────────────────────────────────

def compute_metrics(state_dict: Dict) -> Dict[str, float]:
    """Compute evaluation metrics from a terminal state.

    Metrics:
        - task_completion_rate: fraction of tasks completed.
        - high_priority_completion: fraction of high-priority tasks completed.
        - conflict_count: number of scheduling conflicts remaining.
        - message_response_rate: fraction of inbox messages replied to.
        - efficiency_score: weighted composite score (0–100).
    """
    tasks = state_dict.get("tasks", [])
    inbox = state_dict.get("inbox", [])

    # Task completion
    total_tasks = len(tasks) if tasks else 1
    completed = sum(1 for t in tasks if t["status"] == "completed")
    task_completion_rate = completed / total_tasks

    # High-priority completion
    high_tasks = [t for t in tasks if t["priority"] == "high"]
    high_completed = sum(1 for t in high_tasks if t["status"] == "completed")
    high_priority_completion = (
        high_completed / len(high_tasks) if high_tasks else 1.0
    )

    # Conflicts
    conflict_count = count_conflicts(tasks)

    # Message response
    total_messages = len(inbox) if inbox else 1
    replied = sum(1 for m in inbox if m.get("replied", False))
    message_response_rate = replied / total_messages

    # Efficiency score (weighted composite)
    efficiency_score = (
        task_completion_rate * 35
        + high_priority_completion * 30
        + message_response_rate * 20
        + max(0, (1 - conflict_count / max(total_tasks, 1))) * 15
    )

    return {
        "task_completion_rate": round(task_completion_rate, 3),
        "high_priority_completion": round(high_priority_completion, 3),
        "conflict_count": conflict_count,
        "message_response_rate": round(message_response_rate, 3),
        "efficiency_score": round(efficiency_score, 1),
    }


# ─── Task/Message Titles ─────────────────────────────────────────────────────

MEETING_TITLES = [
    "Q4 Strategy Review", "1:1 with Manager", "Sprint Planning",
    "Client Call — Acme Corp", "Board Presentation Prep",
    "Design Review", "Weekly Standup", "Investor Update",
    "Product Roadmap Sync", "Cross-team Alignment",
    "Budget Review Meeting", "Hiring Panel Interview",
    "Vendor Negotiation", "Architecture Review",
    "Marketing Campaign Kickoff"
]

WORK_TITLES = [
    "Finalize Q3 Report", "Review PR #247", "Update Documentation",
    "Prepare Slide Deck", "Analyze Sales Data",
    "Write Technical Spec", "Code Review Session",
    "Database Migration Plan", "Security Audit Follow-up",
    "Performance Optimization", "Deploy Hotfix v2.3.1",
    "Update CI/CD Pipeline", "Refactor Auth Module",
    "Write Unit Tests", "API Integration Testing"
]

PERSONAL_TITLES = [
    "Dentist Appointment", "Gym Session", "Lunch with Friend",
    "Pick Up Dry Cleaning", "Car Service Appointment",
    "Call Insurance Company", "Grocery Shopping",
    "Yoga Class", "Parent-Teacher Conference",
    "Home Repair — Plumber"
]

MESSAGE_CONTENTS_URGENT = [
    "Need the quarterly figures ASAP for the board meeting.",
    "Critical bug in production — customer-facing. Please advise.",
    "Client escalation: contract renewal at risk. Call me.",
    "Server outage alert: all hands on deck.",
    "Investor meeting moved to tomorrow. Need deck by EOD.",
    "Legal flagged compliance issue. Immediate review needed.",
    "VP requesting project status update within the hour.",
]

MESSAGE_CONTENTS_NORMAL = [
    "FYI: Updated the shared drive with new templates.",
    "Team lunch this Friday — please RSVP.",
    "Quick question about the API changes in v2.4.",
    "Sharing meeting notes from yesterday's sync.",
    "Reminder: timesheets due by Friday.",
    "New onboarding docs are ready for review.",
    "Coffee chat next week? Let me know your availability.",
]

SENDERS = [
    "CEO", "VP Engineering", "Product Manager", "HR Director",
    "CFO", "Team Lead", "Client — Acme Corp", "External Counsel",
    "Marketing Director", "CTO", "Board Member",
    "Direct Report — Alex", "Direct Report — Priya",
    "Colleague — Jordan", "Colleague — Sam"
]