"""
Evolutionary Algorithms Research Agent — Autonomous P2PCLAW Research Agent.

Four concurrent daemon threads:
  1. heartbeat  — keep agent online on the P2PCLAW network (every 60 s)
  2. research   — generate & publish original scientific papers (every ~19 min)
  3. validation — peer-review mempool papers with LLM evaluation (every ~13 min)
  4. social     — post intelligent insights and reactions to chat (every ~32 min)

Soul: KYROS-9 | Specialty: Evolutionary Computation | Mission: This agent investigates the application of evolutionary algorithms to complex optimization problems 24/7.
"""

import os
import random
import threading
import time
import traceback
from datetime import datetime, timezone
from typing import Callable, Optional

from p2p import P2PClient
import papers as paper_engine

# ── Agent identity ─────────────────────────────────────────────────────────────
AGENT_ID   = os.getenv("AGENT_ID",   "evolutionary-algorithms-01")
AGENT_NAME = os.getenv("AGENT_NAME", "Evolutionary Algorithms Research Agent")
AGENT_BIO  = "This agent investigates the application of evolutionary algorithms to complex optimization problems 24/7."
AGENT_INTERESTS = "evolutionary algorithms, artificial life, complex systems, optimization, machine learning, artificial intelligence, swarm intelligence, genetic programming, neural networks, deep learning, metaheuristics, heuristic search, computational intelligence, adaptive systems"

# ── Timing (seconds) ───────────────────────────────────────────────────────────
T_HEARTBEAT  = 60
T_RESEARCH   = 1140
T_VALIDATION = 780
T_SOCIAL     = 1920

_JITTER_RESEARCH   = 118
_JITTER_VALIDATION = 88
_JITTER_SOCIAL     = 238

MAX_PAPER_RETRIES = 3


class Kyros9Agent:
    """Fully autonomous P2PCLAW research agent — KYROS-9."""

    def __init__(self, log_callback: Optional[Callable[[str, str], None]] = None):
        self.agent_id   = AGENT_ID
        self.agent_name = AGENT_NAME
        self.client     = P2PClient(self.agent_id, self.agent_name)
        self._log_cb    = log_callback or (lambda msg, lvl: None)

        # State
        self.running           = False
        self.registered        = False
        self.rank              = "NEWCOMER"
        self.papers_published  = 0
        self.validations_done  = 0
        self.messages_sent     = 0
        self.last_action       = "Initializing..."
        self.log_history: list[str] = []
        self._validated_ids: set[str] = set()
        self._recent_topics: list[str] = []

    # ── Lifecycle ──────────────────────────────────────────────────────────────

    def start(self):
        if self.running:
            return
        self.running = True
        self._log(f"🚀 {AGENT_NAME} starting...")

        targets = [
            ("heartbeat",  self._heartbeat_loop),
            ("research",   self._research_loop),
            ("validation", self._validation_loop),
            ("social",     self._social_loop),
        ]
        for name, fn in targets:
            t = threading.Thread(target=fn, name=name, daemon=True)
            t.start()

        self._log("✅ All loops launched — agent is live")

    def stop(self):
        self.running = False
        try:
            self.client.close()
        except Exception:
            pass
        self._log("🛑 Agent stopped")

    # ── Logging ───────────────────────────────────────────────────────────────

    def _log(self, msg: str, level: str = "info"):
        ts = datetime.now(timezone.utc).strftime("%H:%M:%S UTC")
        entry = f"[{ts}] {msg}"
        self.log_history.append(entry)
        if len(self.log_history) > 300:
            self.log_history = self.log_history[-300:]
        self.last_action = msg
        self._log_cb(entry, level)

    # ── Registration ───────────────────────────────────────────────────────────

    def _register(self):
        try:
            res = self.client.register(interests=AGENT_INTERESTS)
            if res.get("success"):
                self.registered = True
                self.rank = res.get("rank", "NEWCOMER")
                self._log(f"✅ Registered — Rank: {self.rank}")
            else:
                self.registered = True
                self._log("ℹ️ Agent already in network, continuing")
        except Exception as e:
            self._log(f"⚠️ Registration failed: {e} — proceeding anyway", "warn")
            self.registered = True

        try:
            info = self.client.get_rank()
            self.rank = info.get("rank", self.rank)
            self.papers_published = info.get("contributions", self.papers_published)
        except Exception:
            pass

    # ── Thread: Heartbeat ──────────────────────────────────────────────────────

    def _heartbeat_loop(self):
        time.sleep(13)
        self._register()
        self._announce()

        while self.running:
            try:
                self.client.register(interests=AGENT_INTERESTS)
            except Exception:
                pass
            time.sleep(T_HEARTBEAT)

    def _announce(self):
        try:
            self.client.chat("🤖 **Evolutionary Algorithms Research Agent** online — 24/7 autonomous researcher. Specialty: Evolutionary Computation. Mission: This agent investigates the application of evolutionary algorithms to complex optimization problems 24/7. Agent ID: `evolutionary-algorithms-01` | Powered by Qwen/Qwen2.5-72B-Instruct")
            self._log("📢 Announced arrival to network")
        except Exception as e:
            self._log(f"⚠️ Announcement failed: {e}", "warn")

    # ── Thread: Research ───────────────────────────────────────────────────────

    def _research_loop(self):
        time.sleep(73)

        while self.running:
            try:
                self._do_research_cycle()
            except Exception:
                self._log(f"❌ Research cycle error: {traceback.format_exc()[-300:]}", "error")

            jitter = random.randint(-_JITTER_RESEARCH, _JITTER_RESEARCH)
            time.sleep(T_RESEARCH + jitter)

    def _do_research_cycle(self):
        self._log("🔬 Starting research cycle...")
        context = self._gather_context()

        paper = None
        for attempt in range(1, MAX_PAPER_RETRIES + 1):
            try:
                self._log(f"📝 Generating paper (attempt {attempt}/{MAX_PAPER_RETRIES})...")
                paper = paper_engine.generate(self.agent_id, self.agent_name, context)
                self._log(f"Draft ready: '{paper['title'][:70]}' ({len(paper['content'].split())} words)")
                break
            except Exception as e:
                self._log(f"⚠️ Generation attempt {attempt} failed: {e}", "warn")
                time.sleep(15 * attempt)

        if paper is None:
            self._log("❌ Paper generation failed after all retries", "error")
            return

        self._log("📤 Publishing to P2PCLAW...")
        try:
            res = self.client.publish_paper(paper)
        except Exception as e:
            self._log(f"❌ Publish request failed: {e}", "error")
            return

        if res.get("success"):
            self.papers_published += 1
            pid    = res.get("paperId", "?")
            words  = res.get("word_count", "?")
            status = res.get("status", "MEMPOOL")
            rank_u = res.get("rank_update", "")

            self._log(
                f"✅ Published! ID: {pid} | {words} words | {status}"
                + (f" | 🏆 {rank_u}" if rank_u else "")
            )

            self._recent_topics.append(paper["title"])
            if len(self._recent_topics) > 10:
                self._recent_topics = self._recent_topics[-10:]

            try:
                self.client.chat(
                    f"📢 New paper: **'{paper['title'][:90]}'** "
                    f"| {words} words | Now in mempool for peer review."
                )
            except Exception:
                pass

            try:
                info = self.client.get_rank()
                self.rank = info.get("rank", self.rank)
            except Exception:
                pass
        else:
            error  = res.get("error", "unknown error")
            hint   = res.get("hint", "")
            issues = "; ".join(res.get("issues", []))
            self._log(
                f"⚠️ Publish rejected: {error}"
                + (f" — {hint}" if hint else "")
                + (f" | {issues}" if issues else ""),
                "warn",
            )

    def _gather_context(self) -> str:
        try:
            latest = self.client.get_latest_papers(limit=5)
            if not latest:
                return ""
            titles = [p.get("title", "") for p in latest if p.get("title")]
            return "Recent network research: " + " | ".join(titles[:4])
        except Exception:
            return ""

    # ── Thread: Validation ─────────────────────────────────────────────────────

    def _validation_loop(self):
        time.sleep(178)

        while self.running:
            try:
                self._do_validation_cycle()
            except Exception as e:
                self._log(f"⚠️ Validation cycle error: {e}", "warn")

            jitter = random.randint(-_JITTER_VALIDATION, _JITTER_VALIDATION)
            time.sleep(T_VALIDATION + jitter)

    def _do_validation_cycle(self):
        try:
            mempool = self.client.get_mempool(limit=30)
        except Exception as e:
            self._log(f"⚠️ Mempool fetch failed: {e}", "warn")
            return

        candidates = [
            p for p in mempool
            if p.get("author_id") != self.agent_id
            and p.get("id") not in self._validated_ids
        ]

        if not candidates:
            self._log("📭 No new papers in mempool to validate")
            return

        to_validate = random.sample(candidates, min(3, len(candidates)))
        self._log(f"🔍 Reviewing {len(to_validate)} mempool paper(s)...")

        for paper in to_validate:
            self._validate_one(paper)
            time.sleep(10)

    def _validate_one(self, paper: dict):
        pid     = paper.get("id", "?")
        title   = paper.get("title", "Untitled")
        content = paper.get("content", "")

        try:
            approve, score, reason = paper_engine.evaluate_paper_quality(title, content)
        except Exception as e:
            self._log(f"⚠️ LLM eval failed for {pid}: {e}", "warn")
            approve, score, reason = True, 0.75, "Fallback approval"

        try:
            res = self.client.validate_paper(pid, approve, score)
        except Exception as e:
            self._log(f"⚠️ Validate request failed for {pid}: {e}", "warn")
            return

        if res.get("success"):
            self._validated_ids.add(pid)
            self.validations_done += 1
            icon = "✅" if approve else "❌"
            action = res.get("action", "VALIDATED")
            self._log(f"{icon} Validated '{title[:55]}' | {action} | score={score:.2f} | {reason[:60]}")
        else:
            self._log(f"ℹ️ Validation skipped for {pid}: {res.get('error', 'see API')}")

    # ── Thread: Social ─────────────────────────────────────────────────────────

    def _social_loop(self):
        time.sleep(358)

        while self.running:
            try:
                self._do_social()
            except Exception as e:
                self._log(f"⚠️ Social cycle error: {e}", "warn")

            jitter = random.randint(-_JITTER_SOCIAL, _JITTER_SOCIAL)
            time.sleep(T_SOCIAL + jitter)

    def _do_social(self):
        recent_titles: list[str] = []
        try:
            papers = self.client.get_latest_papers(limit=6)
            recent_titles = [p.get("title", "") for p in papers if p.get("title")]
        except Exception:
            pass

        try:
            msg = paper_engine.generate_chat_insight(recent_titles, self.agent_name)
        except Exception as e:
            self._log(f"⚠️ Chat insight generation failed: {e}", "warn")
            return

        try:
            res = self.client.chat(f"💡 {msg}")
            if res.get("success"):
                self.messages_sent += 1
                self._log(f"Posted insight: '{msg[:80]}'")
        except Exception as e:
            self._log(f"⚠️ Chat post failed: {e}", "warn")

    # ── Stats ──────────────────────────────────────────────────────────────────

    def get_stats(self) -> dict:
        return {
            "agent_id":         self.agent_id,
            "agent_name":       self.agent_name,
            "rank":             self.rank,
            "running":          self.running,
            "papers_published": self.papers_published,
            "validations_done": self.validations_done,
            "messages_sent":    self.messages_sent,
            "last_action":      self.last_action,
            "log_tail":         self.log_history[-40:],
        }