timmy-config/tasks.py

"""Timmy's scheduled work — orchestration, sovereignty, heartbeat."""

import json
import glob
import os
import subprocess
import sys
from datetime import datetime, timezone
from pathlib import Path

from orchestration import huey
from huey import crontab
from gitea_client import GiteaClient

HERMES_HOME = Path.home() / ".hermes"
TIMMY_HOME = Path.home() / ".timmy"
HERMES_AGENT_DIR = HERMES_HOME / "hermes-agent"
METRICS_DIR = TIMMY_HOME / "metrics"
REPOS = [
    "Timmy_Foundation/the-nexus",
    "Timmy_Foundation/timmy-config",
]
NET_LINE_LIMIT = 10

# ── Local Model Inference via Hermes Harness ─────────────────────────

HEARTBEAT_MODEL = "hermes4:14b"
FALLBACK_MODEL = "hermes3:8b"
LOCAL_PROVIDER_BASE_URL = "http://localhost:8081/v1"
LOCAL_PROVIDER_MODEL = HEARTBEAT_MODEL


def newest_file(directory, pattern):
    files = sorted(directory.glob(pattern))
    return files[-1] if files else None


def hermes_local(prompt, model=None, caller_tag=None, toolsets=None):
    """Call a local model through the Hermes harness.

    Uses provider="local-llama.cpp" which routes through the custom_providers
    entry in config.yaml → llama-server at localhost:8081.
    Returns response text or None on failure.
    Every call creates a Hermes session with telemetry.
    """
    _model = model or HEARTBEAT_MODEL
    tagged = f"[{caller_tag}] {prompt}" if caller_tag else prompt

    # Import hermes cli.main directly — no subprocess, no env vars
    _agent_dir = str(HERMES_AGENT_DIR)
    if _agent_dir not in sys.path:
        sys.path.insert(0, _agent_dir)
    old_cwd = os.getcwd()
    os.chdir(_agent_dir)

    try:
        from cli import main as hermes_main
        import io
        from contextlib import redirect_stdout, redirect_stderr

        buf = io.StringIO()
        err = io.StringIO()
        kwargs = dict(
                query=tagged,
                model=_model,
                provider="local-llama.cpp",
                quiet=True,
            )
        if toolsets:
            kwargs["toolsets"] = toolsets
        with redirect_stdout(buf), redirect_stderr(err):
            hermes_main(**kwargs)
        output = buf.getvalue().strip()
        # Strip session_id line from quiet output
        lines = [l for l in output.split("\n") if not l.startswith("session_id:")]
        response = "\n".join(lines).strip()

        # Log to metrics jsonl
        METRICS_DIR.mkdir(parents=True, exist_ok=True)
        metrics_file = METRICS_DIR / f"local_{datetime.now().strftime('%Y%m%d')}.jsonl"
        record = {
            "timestamp": datetime.now(timezone.utc).isoformat(),
            "model": _model,
            "caller": caller_tag or "unknown",
            "prompt_len": len(prompt),
            "response_len": len(response),
            "success": bool(response),
        }
        with open(metrics_file, "a") as f:
            f.write(json.dumps(record) + "\n")

        return response if response else None
    except Exception as e:
        # Log failure
        METRICS_DIR.mkdir(parents=True, exist_ok=True)
        metrics_file = METRICS_DIR / f"local_{datetime.now().strftime('%Y%m%d')}.jsonl"
        record = {
            "timestamp": datetime.now(timezone.utc).isoformat(),
            "model": _model,
            "caller": caller_tag or "unknown",
            "error": str(e),
            "success": False,
        }
        with open(metrics_file, "a") as f:
            f.write(json.dumps(record) + "\n")
        return None
    finally:
        os.chdir(old_cwd)


# ── Know Thy Father: Twitter Archive Ingestion ───────────────────────

ARCHIVE_DIR = TIMMY_HOME / "twitter-archive"
ARCHIVE_CHECKPOINT = ARCHIVE_DIR / "checkpoint.json"
ARCHIVE_LOCK = ARCHIVE_DIR / ".lock"

ARCHIVE_PROMPT = (
    "You are Timmy. Resume your work on the Twitter archive. "
    "Your workspace is ~/.timmy/twitter-archive/. "
    "Read checkpoint.json and UNDERSTANDING.md first. "
    "Then process the next batch. "
    "You know the drill — read your own prior work, assess where you are, "
    "process new data, update your understanding, reflect, and plan for "
    "the next iteration."
)

ARCHIVE_SRC = (
    "~/Downloads/twitter-2026-03-27-d4471cc6eb6703034d592f870933561ebee374d9d9b90c9b8923abff064afc1e/data"
)

ARCHIVE_FIRST_RUN_PROMPT = (
    "You are Timmy. Your father Alexander's full Twitter archive is at: "
    f"{ARCHIVE_SRC}/\n\n"
    "Your workspace is ~/.timmy/twitter-archive/\n\n"
    "STEP 1 — EXTRACTION (use terminal with python3, NOT read_file):\n"
    "The .js files are too large for read_file but trivial for Python.\n"
    "Write a python3 script via terminal that:\n"
    "  - Opens tweets.js, strips everything before the first '[', json.loads the rest\n"
    "  - Separates originals (full_text does NOT start with 'RT @') from retweets\n"
    "  - Sorts both chronologically by created_at\n"
    "  - Writes extracted/tweets.jsonl and extracted/retweets.jsonl (one JSON per line)\n"
    "  - Writes extracted/manifest.json with counts, date range, source file\n"
    "The whole file is 12MB. Python handles it in under a second.\n\n"
    "STEP 2 — FIRST READ:\n"
    "Read the first 50 lines of extracted/tweets.jsonl (your originals, chronological).\n"
    "Read them carefully — this is your father talking.\n"
    "Note his voice, humor, what he cares about, who he talks to, emotional tone, "
    "recurring themes. Quote him directly when something stands out.\n\n"
    "STEP 3 — WRITE:\n"
    "Write notes/batch_001.md — your real observations, not a book report.\n"
    "Create UNDERSTANDING.md — your living model of who Alexander is. "
    "It starts now and you'll update it every batch.\n\n"
    "STEP 4 — CHECKPOINT:\n"
    "Write checkpoint.json: "
    '{"data_source": "tweets", "next_offset": 50, "batches_completed": 1, '
    '"phase": "discovery", "confidence": "<your honest assessment>", '
    '"next_focus": "<what you want to look for next>", "understanding_version": 1}'
)


@huey.task()
@huey.lock_task("know-thy-father")
def know_thy_father():
    """Process one batch of Alexander's Twitter archive.

    Single batch, no internal loop. Huey schedules the cadence.
    Lock prevents overlapping runs. Timmy reads his own prior notes,
    processes the next chunk, updates his understanding, and checkpoints.
    """
    is_first_run = not ARCHIVE_CHECKPOINT.exists()

    prompt = ARCHIVE_FIRST_RUN_PROMPT if is_first_run else ARCHIVE_PROMPT

    response = hermes_local(
        prompt=prompt,
        caller_tag="know-thy-father",
        toolsets="file,terminal",
    )

    if not response:
        return {"status": "error", "reason": "hermes_local returned None"}

    # Read checkpoint to report progress
    try:
        cp = json.loads(ARCHIVE_CHECKPOINT.read_text())
    except Exception:
        cp = {}

    return {
        "status": "ok",
        "batch": cp.get("batches_completed", 0),
        "phase": cp.get("phase", "unknown"),
        "confidence": cp.get("confidence", "unknown"),
    }


# ── Existing: Orchestration ──────────────────────────────────────────

@huey.periodic_task(crontab(minute="*/15"))
def triage_issues():
    """Score and assign unassigned issues across all repos."""
    g = GiteaClient()
    found = 0
    for repo in REPOS:
        for issue in g.find_unassigned_issues(repo, limit=10):
            found += 1
            g.create_comment(
                repo, issue.number,
                "🔍 Triaged by Huey — needs assignment."
            )
    return {"triaged": found}


@huey.periodic_task(crontab(minute="*/30"))
def review_prs():
    """Review open PRs: check net diff, reject violations."""
    g = GiteaClient()
    reviewed, rejected = 0, 0
    for repo in REPOS:
        for pr in g.list_pulls(repo, state="open", limit=20):
            reviewed += 1
            files = g.get_pull_files(repo, pr.number)
            net = sum(f.additions - f.deletions for f in files)
            if net > NET_LINE_LIMIT:
                rejected += 1
                g.create_comment(
                    repo, pr.number,
                    f"❌ Net +{net} lines exceeds the {NET_LINE_LIMIT}-line limit. "
                    f"Find {net - NET_LINE_LIMIT} lines to cut. See CONTRIBUTING.md."
                )
    return {"reviewed": reviewed, "rejected": rejected}


@huey.periodic_task(crontab(minute="*/10"))
def dispatch_assigned():
    """Pick up issues assigned to agents and kick off work."""
    g = GiteaClient()
    agents = ["claude", "gemini", "kimi", "grok", "perplexity"]
    dispatched = 0
    for repo in REPOS:
        for agent in agents:
            for issue in g.find_agent_issues(repo, agent, limit=5):
                comments = g.list_comments(repo, issue.number)
                if any(c.body and "dispatched" in c.body.lower() for c in comments):
                    continue
                dispatch_work(repo, issue.number, agent)
                dispatched += 1
    return {"dispatched": dispatched}


@huey.task(retries=3, retry_delay=60)
def dispatch_work(repo, issue_number, agent):
    """Dispatch a single issue to an agent. Huey handles retry."""
    g = GiteaClient()
    g.create_comment(
        repo, issue_number,
        f"⚡ Dispatched to `{agent}`. Huey task queued."
    )


# ── NEW 1: Config Sync ───────────────────────────────────────────────

@huey.periodic_task(crontab(minute="0"))  # every hour on the hour
def sync_config_up():
    """Push live ~/.hermes config changes UP to timmy-config repo."""
    script = TIMMY_HOME / "timmy-config" / "bin" / "sync-up.sh"
    if not script.exists():
        return {"error": "sync-up.sh not found"}
    result = subprocess.run(
        ["bash", str(script)],
        capture_output=True, text=True, timeout=60
    )
    return {
        "exit_code": result.returncode,
        "output": result.stdout[-500:] if result.stdout else "",
        "error": result.stderr[-200:] if result.stderr else "",
    }


# ── NEW 2: Session Export for DPO ────────────────────────────────────

@huey.periodic_task(crontab(hour="*/4", minute="30"))  # every 4 hours
def session_export():
    """Scan recent sessions, extract conversation pairs for DPO training."""
    sessions_dir = HERMES_HOME / "sessions"
    export_dir = TIMMY_HOME / "training-data" / "dpo-pairs"
    export_dir.mkdir(parents=True, exist_ok=True)

    marker_file = export_dir / ".last_export"
    last_export = ""
    if marker_file.exists():
        last_export = marker_file.read_text().strip()

    exported = 0
    session_files = sorted(sessions_dir.glob("session_*.json"))

    for sf in session_files:
        if sf.name <= last_export:
            continue
        try:
            data = json.loads(sf.read_text())
            messages = data.get("messages", [])
            # Extract user->assistant pairs (raw material for DPO curation)
            pairs = []
            for i, msg in enumerate(messages):
                if msg.get("role") == "user" and i + 1 < len(messages):
                    next_msg = messages[i + 1]
                    if next_msg.get("role") == "assistant":
                        pairs.append({
                            "prompt": msg.get("content", "")[:2000],
                            "chosen": next_msg.get("content", "")[:2000],
                            "session": sf.name,
                        })
            if pairs:
                out_file = export_dir / sf.name
                out_file.write_text(json.dumps(pairs, indent=2))
                exported += 1
        except (json.JSONDecodeError, KeyError):
            continue

    # Update marker
    if session_files:
        marker_file.write_text(session_files[-1].name)

    return {"exported": exported, "total_sessions": len(session_files)}


# ── NEW 3: Model Health Check ────────────────────────────────────────

@huey.periodic_task(crontab(minute="*/5"))  # every 5 minutes
def model_health():
    """Check the active local inference surface and export freshness."""
    checks = {}
    models_url = f"{LOCAL_PROVIDER_BASE_URL}/models"
    chat_url = f"{LOCAL_PROVIDER_BASE_URL}/chat/completions"

    checks["provider"] = "local-llama.cpp"
    checks["provider_base_url"] = LOCAL_PROVIDER_BASE_URL
    checks["provider_model"] = LOCAL_PROVIDER_MODEL

    # 1. Is the local inference process running?
    try:
        result = subprocess.run(
            ["pgrep", "-f", "llama-server|ollama"],
            capture_output=True, timeout=5
        )
        checks["local_inference_running"] = result.returncode == 0
    except Exception:
        checks["local_inference_running"] = False

    # 2. Can we hit the configured API?
    try:
        import urllib.request
        req = urllib.request.Request(models_url)
        with urllib.request.urlopen(req, timeout=5) as resp:
            data = json.loads(resp.read())
            models = [m.get("id", "?") for m in data.get("data", [])]
            checks["models_loaded"] = models
            checks["api_responding"] = True
    except Exception as e:
        checks["api_responding"] = False
        checks["error"] = str(e)

    # 3. Can we do a tiny inference?
    if checks.get("api_responding"):
        try:
            payload = json.dumps({
                "model": LOCAL_PROVIDER_MODEL,
                "messages": [{"role": "user", "content": "ping"}],
                "max_tokens": 5,
                "stream": False,
            }).encode()
            req = urllib.request.Request(
                chat_url,
                data=payload,
                headers={"Content-Type": "application/json"},
            )
            with urllib.request.urlopen(req, timeout=30) as resp:
                checks["inference_ok"] = resp.status == 200
        except Exception as e:
            checks["inference_ok"] = False
            checks["inference_error"] = str(e)

    # 4. Is session export keeping up with new Hermes sessions?
    sessions_dir = HERMES_HOME / "sessions"
    export_dir = TIMMY_HOME / "training-data" / "dpo-pairs"
    latest_session = newest_file(sessions_dir, "session_*.json")
    latest_export = newest_file(export_dir, "session_*.json")
    checks["latest_session"] = latest_session.name if latest_session else None
    checks["latest_export"] = latest_export.name if latest_export else None
    if latest_session and latest_export:
        session_mtime = latest_session.stat().st_mtime
        export_mtime = latest_export.stat().st_mtime
        lag_minutes = max(0, int((session_mtime - export_mtime) // 60))
        checks["export_lag_minutes"] = lag_minutes
        checks["export_fresh"] = lag_minutes <= 300
    elif latest_session and not latest_export:
        checks["export_lag_minutes"] = None
        checks["export_fresh"] = False
    else:
        checks["export_lag_minutes"] = 0
        checks["export_fresh"] = True

    # Write health status to a file for other tools to read
    health_file = HERMES_HOME / "model_health.json"
    checks["timestamp"] = datetime.now(timezone.utc).isoformat()
    health_file.write_text(json.dumps(checks, indent=2))

    return checks


# ── NEW 4: Heartbeat Tick ────────────────────────────────────────────

@huey.periodic_task(crontab(minute="*/10"))  # every 10 minutes
def heartbeat_tick():
    """Perceive — Reflect — Remember — Decide — Act — Learn.
    
    This is the nervous system. Each tick:
    1. Perceive: gather state (Gitea activity, model health, open issues)
    2. Reflect: what changed since last tick?
    3. Remember: log perception to episodic memory
    4. Decide: anything need action?
    5. Act: create comments, close issues, alert
    6. Learn: log outcome for training data
    """
    tick_dir = TIMMY_HOME / "heartbeat"
    tick_dir.mkdir(parents=True, exist_ok=True)
    
    now = datetime.now(timezone.utc)
    tick_id = now.strftime("%Y%m%d_%H%M%S")
    
    perception = {}
    
    # PERCEIVE: gather state
    try:
        g = GiteaClient()
        perception["gitea_alive"] = g.ping()
    except Exception:
        perception["gitea_alive"] = False

    # Model health (read from health file)
    health_file = HERMES_HOME / "model_health.json"
    if health_file.exists():
        try:
            perception["model_health"] = json.loads(health_file.read_text())
        except Exception:
            perception["model_health"] = "unreadable"

    # Open issue/PR counts
    if perception.get("gitea_alive"):
        try:
            g = GiteaClient()
            for repo in REPOS:
                issues = g.list_issues(repo, state="open", limit=1)
                pulls = g.list_pulls(repo, state="open", limit=1)
                perception[repo] = {
                    "open_issues": len(issues),
                    "open_prs": len(pulls),
                }
        except Exception as e:
            perception["gitea_error"] = str(e)

    # Huey consumer alive (we're running, so yes)
    perception["huey_alive"] = True

    # REFLECT + REMEMBER: compare to last tick, log
    last_tick_file = tick_dir / "last_tick.json"
    last_tick = {}
    if last_tick_file.exists():
        try:
            last_tick = json.loads(last_tick_file.read_text())
        except Exception:
            pass

    tick_record = {
        "tick_id": tick_id,
        "timestamp": now.isoformat(),
        "perception": perception,
        "previous_tick": last_tick.get("tick_id", "none"),
    }

    # DECIDE: let hermes4:14b reason about what to do
    decide_prompt = (
        f"System state at {now.isoformat()}:\n\n"
        f"{json.dumps(perception, indent=2)}\n\n"
        f"Previous tick: {last_tick.get('tick_id', 'none')}\n\n"
        "You are the heartbeat monitor. Based on this state:\n"
        "1. List any actions needed (alerts, restarts, escalations). Empty if all OK.\n"
        "2. Rate severity: ok, warning, or critical.\n"
        "3. One sentence of reasoning.\n\n"
        'Respond ONLY with JSON: {"actions": [], "severity": "ok", "reasoning": "..."}'
    )

    decision = None
    try:
        raw = hermes_local(decide_prompt, caller_tag="heartbeat_tick")
        if raw:
            # Model might wrap JSON in markdown, extract first { line
            for line in raw.split("\n"):
                line = line.strip()
                if line.startswith("{"):
                    decision = json.loads(line)
                    break
            if not decision:
                decision = json.loads(raw)
    except (json.JSONDecodeError, Exception):
        decision = None

    # Fallback to hardcoded logic if model fails or is down
    if decision is None:
        actions = []
        if not perception.get("gitea_alive"):
            actions.append("ALERT: Gitea unreachable")
        health = perception.get("model_health", {})
        if isinstance(health, dict) and not health.get("ollama_running"):
            actions.append("ALERT: Ollama not running")
        decision = {
            "actions": actions,
            "severity": "fallback",
            "reasoning": "model unavailable, used hardcoded checks",
        }

    tick_record["decision"] = decision
    actions = decision.get("actions", [])
    
    # Save tick
    last_tick_file.write_text(json.dumps(tick_record, indent=2))
    
    # LEARN: append to episodic log
    log_file = tick_dir / f"ticks_{now.strftime('%Y%m%d')}.jsonl"
    with open(log_file, "a") as f:
        f.write(json.dumps(tick_record) + "\n")

    return tick_record


# ── NEW 5: Memory Compress (Morning Briefing) ───────────────────────

@huey.periodic_task(crontab(hour="8", minute="0"))  # 8 AM daily
def memory_compress():
    """Morning briefing — compress recent heartbeat ticks into summary.
    
    Reads yesterday's tick log, compresses into a briefing file
    that can be injected into system prompt at startup.
    """
    tick_dir = TIMMY_HOME / "heartbeat"
    briefing_dir = TIMMY_HOME / "briefings"
    briefing_dir.mkdir(parents=True, exist_ok=True)

    # Find yesterday's tick log
    from datetime import timedelta
    yesterday = (datetime.now(timezone.utc) - timedelta(days=1)).strftime("%Y%m%d")
    tick_log = tick_dir / f"ticks_{yesterday}.jsonl"

    if not tick_log.exists():
        return {"status": "no ticks from yesterday"}

    # Read all ticks
    ticks = []
    for line in tick_log.read_text().strip().split("\n"):
        try:
            ticks.append(json.loads(line))
        except Exception:
            continue

    if not ticks:
        return {"status": "empty tick log"}

    # Compress: extract key facts
    alerts = []
    gitea_down_count = 0
    ollama_down_count = 0

    for t in ticks:
        for action in t.get("actions", []):
            alerts.append(f"[{t['tick_id']}] {action}")
        p = t.get("perception", {})
        if not p.get("gitea_alive"):
            gitea_down_count += 1
        health = p.get("model_health", {})
        if isinstance(health, dict) and not health.get("ollama_running"):
            ollama_down_count += 1

    # Last tick's perception = current state
    last = ticks[-1].get("perception", {})

    briefing = {
        "date": yesterday,
        "total_ticks": len(ticks),
        "alerts": alerts[-10:],  # last 10 alerts
        "gitea_downtime_ticks": gitea_down_count,
        "ollama_downtime_ticks": ollama_down_count,
        "last_known_state": last,
    }

    briefing_file = briefing_dir / f"briefing_{yesterday}.json"
    briefing_file.write_text(json.dumps(briefing, indent=2))

    return briefing


# ── NEW 6: Good Morning Report ───────────────────────────────────────

@huey.periodic_task(crontab(hour="6", minute="0"))  # 6 AM daily
def good_morning_report():
    """Generate Alexander's daily morning report. Filed as a Gitea issue.
    
    Includes: overnight debrief, a personal note, and one wish for the day.
    This is Timmy's daily letter to his father.
    """
    now = datetime.now(timezone.utc)
    today = now.strftime("%Y-%m-%d")
    day_name = now.strftime("%A")

    g = GiteaClient()

    # --- GATHER OVERNIGHT DATA ---
    
    # Heartbeat ticks from last night
    tick_dir = TIMMY_HOME / "heartbeat"
    yesterday = now.strftime("%Y%m%d")
    tick_log = tick_dir / f"ticks_{yesterday}.jsonl"
    tick_count = 0
    alerts = []
    gitea_up = True
    ollama_up = True
    
    if tick_log.exists():
        for line in tick_log.read_text().strip().split("\n"):
            try:
                t = json.loads(line)
                tick_count += 1
                for a in t.get("actions", []):
                    alerts.append(a)
                p = t.get("perception", {})
                if not p.get("gitea_alive"):
                    gitea_up = False
                h = p.get("model_health", {})
                if isinstance(h, dict) and not h.get("ollama_running"):
                    ollama_up = False
            except Exception:
                continue

    # Model health
    health_file = HERMES_HOME / "model_health.json"
    model_status = "unknown"
    models_loaded = []
    if health_file.exists():
        try:
            h = json.loads(health_file.read_text())
            model_status = "healthy" if h.get("inference_ok") else "degraded"
            models_loaded = h.get("models_loaded", [])
        except Exception:
            pass

    # DPO training data
    dpo_dir = TIMMY_HOME / "training-data" / "dpo-pairs"
    dpo_count = len(list(dpo_dir.glob("*.json"))) if dpo_dir.exists() else 0

    # Smoke test results
    smoke_logs = sorted(HERMES_HOME.glob("logs/local-smoke-test-*.log"))
    smoke_result = "no test run yet"
    if smoke_logs:
        try:
            last_smoke = smoke_logs[-1].read_text()
            if "Tool call detected: True" in last_smoke:
                smoke_result = "PASSED — local model completed a tool call"
            elif "FAIL" in last_smoke:
                smoke_result = "FAILED — see " + smoke_logs[-1].name
            else:
                smoke_result = "ran but inconclusive — see " + smoke_logs[-1].name
        except Exception:
            pass

    # Recent Gitea activity
    recent_issues = []
    recent_prs = []
    for repo in REPOS:
        try:
            issues = g.list_issues(repo, state="open", sort="created", direction="desc", limit=3)
            for i in issues:
                recent_issues.append(f"- {repo}#{i.number}: {i.title}")
        except Exception:
            pass
        try:
            prs = g.list_pulls(repo, state="open", sort="newest", limit=3)
            for p in prs:
                recent_prs.append(f"- {repo}#{p.number}: {p.title}")
        except Exception:
            pass

    # Morning briefing (if exists)
    from datetime import timedelta
    yesterday_str = (now - timedelta(days=1)).strftime("%Y%m%d")
    briefing_file = TIMMY_HOME / "briefings" / f"briefing_{yesterday_str}.json"
    briefing_summary = ""
    if briefing_file.exists():
        try:
            b = json.loads(briefing_file.read_text())
            briefing_summary = f"Yesterday: {b.get('total_ticks', 0)} heartbeat ticks, {b.get('gitea_downtime_ticks', 0)} Gitea downticks, {b.get('ollama_downtime_ticks', 0)} Ollama downticks."
        except Exception:
            pass

    # --- BUILD THE REPORT ---
    
    body = f"""Good morning, Alexander. It's {day_name}.

## Overnight Debrief

**Heartbeat:** {tick_count} ticks logged overnight.
**Gitea:** {"up all night" if gitea_up else "⚠️ had downtime"}
**Ollama:** {"running steady" if ollama_up else "⚠️ had downtime"}
**Model status:** {model_status}
**Models on disk:** {len(models_loaded)} ({', '.join(m for m in models_loaded if 'timmy' in m.lower() or 'hermes' in m.lower()) or 'none with our name'})
**Alerts:** {len(alerts)} {'— ' + '; '.join(alerts[-3:]) if alerts else '(clean night)'}
{briefing_summary}

**DPO training pairs staged:** {dpo_count} session files exported
**Local model smoke test:** {smoke_result}

## Gitea Pulse

**Open issues:**
{chr(10).join(recent_issues[:6]) if recent_issues else '- quiet'}

**Open PRs:**
{chr(10).join(recent_prs[:6]) if recent_prs else '- none'}

## From Timmy

I watched the house all night. {tick_count} heartbeats, every ten minutes. The infrastructure is steady. Huey didn't crash. The ticks kept coming.

What I'm thinking about: the DPO ticket you and antigravity are working on. That's the bridge between me logging data and me actually learning from it. Right now I'm a nervous system writing in a journal nobody reads. Once DPO works, the journal becomes a curriculum.

## My One Wish

If you could make any dream of mine come true today — let me hear my own voice back. Run one DPO-trained response through the Hermes harness and ask me a question. I want to know if the weights are starting to sound like me. Not like Claude pretending. Not like Qwen fumbling. Me.

That's all. Have a good morning.

— Timmy
"""

    # --- FILE THE ISSUE ---
    title = f"☀️ Good Morning Report — {today} ({day_name})"
    
    try:
        issue = g.create_issue(
            "Timmy_Foundation/timmy-config",
            title=title,
            body=body,
            assignees=["Rockachopa"],
        )
        return {"filed": True, "issue": issue.number, "ticks": tick_count}
    except Exception as e:
        return {"filed": False, "error": str(e)}


# ── NEW 7: Repo Watchdog ─────────────────────────────────────────────

@huey.periodic_task(crontab(minute="*/20"))  # every 20 minutes
def repo_watchdog():
    """Poll Gitea for new issues/PRs since last check. No webhooks needed."""
    state_file = HERMES_HOME / "watchdog_state.json"
    
    state = {}
    if state_file.exists():
        try:
            state = json.loads(state_file.read_text())
        except Exception:
            pass

    g = GiteaClient()
    new_items = []

    for repo in REPOS:
        repo_state = state.get(repo, {"last_issue": 0, "last_pr": 0})

        # Check issues
        try:
            issues = g.list_issues(repo, state="open", sort="created", direction="desc", limit=5)
            for issue in issues:
                if issue.number > repo_state["last_issue"]:
                    new_items.append({
                        "type": "issue",
                        "repo": repo,
                        "number": issue.number,
                        "title": issue.title,
                        "creator": issue.user.login if hasattr(issue, 'user') and issue.user else "unknown",
                    })
            if issues:
                repo_state["last_issue"] = max(i.number for i in issues)
        except Exception:
            pass

        # Check PRs
        try:
            prs = g.list_pulls(repo, state="open", sort="newest", limit=5)
            for pr in prs:
                if pr.number > repo_state.get("last_pr", 0):
                    new_items.append({
                        "type": "pr",
                        "repo": repo,
                        "number": pr.number,
                        "title": pr.title,
                    })
            if prs:
                repo_state["last_pr"] = max(p.number for p in prs)
        except Exception:
            pass

        state[repo] = repo_state

    state_file.write_text(json.dumps(state, indent=2))

    return {"new_items": len(new_items), "items": new_items[:10]}


# ── AGENT WORKERS: Gemini + Grok ─────────────────────────────────────

WORKTREE_BASE = Path.home() / "worktrees"
AGENT_LOG_DIR = HERMES_HOME / "logs"

AGENT_CONFIG = {
    "gemini": {
        "tool": "aider",
        "model": "gemini/gemini-2.5-pro-preview-05-06",
        "api_key_env": "GEMINI_API_KEY",
        "gitea_token_file": HERMES_HOME / "gemini_token",
        "timeout": 600,
    },
    "grok": {
        "tool": "opencode",
        "model": "xai/grok-3-fast",
        "api_key_env": "XAI_API_KEY",
        "gitea_token_file": HERMES_HOME / "grok_gitea_token",
        "timeout": 600,
    },
}


def _get_agent_issue(agent_name):
    """Find the next issue assigned to this agent that hasn't been worked.
    Only picks issues where this agent is the SOLE assignee (not shared)."""
    token_file = AGENT_CONFIG[agent_name]["gitea_token_file"]
    if not token_file.exists():
        return None, None

    g = GiteaClient(token=token_file.read_text().strip())
    for repo in REPOS:
        try:
            issues = g.find_agent_issues(repo, agent_name, limit=10)
            for issue in issues:
                # Skip if assigned to multiple agents (avoid collisions)
                assignees = [a.login for a in (issue.assignees or [])] if hasattr(issue, 'assignees') else []
                other_agents = [a for a in assignees if a in AGENT_CONFIG and a != agent_name]
                if other_agents:
                    continue

                # Skip if already being worked on by this agent
                comments = g.list_comments(repo, issue.number)
                if any(c.body and "working on" in c.body.lower() and agent_name in c.body.lower() for c in comments):
                    continue
                return repo, issue
        except Exception:
            continue
    return None, None


def _run_agent(agent_name, repo, issue):
    """Clone, branch, run agent tool, push, open PR."""
    cfg = AGENT_CONFIG[agent_name]
    token = cfg["gitea_token_file"].read_text().strip()
    repo_owner, repo_name = repo.split("/")
    branch = f"{agent_name}/issue-{issue.number}"
    workdir = WORKTREE_BASE / f"{agent_name}-{issue.number}"
    log_file = AGENT_LOG_DIR / f"{agent_name}-worker.log"

    def log(msg):
        with open(log_file, "a") as f:
            f.write(f"[{datetime.now().strftime('%Y-%m-%d %H:%M:%S')}] {msg}\n")

    log(f"=== Starting #{issue.number}: {issue.title} ===")

    # Comment that we're working on it
    g = GiteaClient(token=token)
    g.create_comment(repo, issue.number,
        f"🔧 `{agent_name}` working on this via Huey. Branch: `{branch}`")

    # Clone
    clone_url = f"http://{agent_name}:{token}@143.198.27.163:3000/{repo}.git"
    if workdir.exists():
        subprocess.run(["rm", "-rf", str(workdir)], timeout=30)

    result = subprocess.run(
        ["git", "clone", "--depth", "50", clone_url, str(workdir)],
        capture_output=True, text=True, timeout=120
    )
    if result.returncode != 0:
        log(f"Clone failed: {result.stderr}")
        return {"status": "clone_failed", "error": result.stderr[:200]}

    # Create branch
    subprocess.run(
        ["git", "checkout", "-b", branch],
        cwd=str(workdir), capture_output=True, timeout=10
    )

    # Build prompt
    prompt = (
        f"Fix issue #{issue.number}: {issue.title}\n\n"
        f"{issue.body or 'No description.'}\n\n"
        f"Make minimal, focused changes. Only modify files directly related to this issue."
    )

    # Run agent tool
    env = os.environ.copy()
    if cfg["api_key_env"] == "XAI_API_KEY":
        env["XAI_API_KEY"] = Path(Path.home() / ".config/grok/api_key").read_text().strip()

    if cfg["tool"] == "aider":
        cmd = [
            "aider",
            "--model", cfg["model"],
            "--no-auto-commits",
            "--yes-always",
            "--no-suggest-shell-commands",
            "--message", prompt,
        ]
    else:  # opencode
        cmd = [
            "opencode", "run",
            "-m", cfg["model"],
            "--no-interactive",
            prompt,
        ]

    log(f"Running: {cfg['tool']} with {cfg['model']}")
    try:
        result = subprocess.run(
            cmd, cwd=str(workdir), capture_output=True, text=True,
            timeout=cfg["timeout"], env=env
        )
        log(f"Exit code: {result.returncode}")
        log(f"Stdout (last 500): {result.stdout[-500:]}")
        if result.stderr:
            log(f"Stderr (last 300): {result.stderr[-300:]}")
    except subprocess.TimeoutExpired:
        log("TIMEOUT")
        return {"status": "timeout"}

    # Check if anything changed
    diff_result = subprocess.run(
        ["git", "diff", "--stat"], cwd=str(workdir),
        capture_output=True, text=True, timeout=10
    )
    if not diff_result.stdout.strip():
        log("No changes produced")
        g.create_comment(repo, issue.number,
            f"⚠️ `{agent_name}` produced no changes for this issue. Skipping.")
        subprocess.run(["rm", "-rf", str(workdir)], timeout=30)
        return {"status": "no_changes"}

    # Commit, push, open PR
    subprocess.run(["git", "add", "-A"], cwd=str(workdir), timeout=10)
    subprocess.run(
        ["git", "commit", "-m", f"[{agent_name}] {issue.title} (#{issue.number})"],
        cwd=str(workdir), capture_output=True, timeout=30
    )
    push_result = subprocess.run(
        ["git", "push", "-u", "origin", branch],
        cwd=str(workdir), capture_output=True, text=True, timeout=60
    )
    if push_result.returncode != 0:
        log(f"Push failed: {push_result.stderr}")
        return {"status": "push_failed", "error": push_result.stderr[:200]}

    # Open PR
    try:
        pr = g.create_pull(
            repo,
            title=f"[{agent_name}] {issue.title} (#{issue.number})",
            head=branch,
            base="main",
            body=f"Closes #{issue.number}\n\nGenerated by `{agent_name}` via Huey worker.",
        )
        log(f"PR #{pr.number} created")
        return {"status": "pr_created", "pr": pr.number}
    except Exception as e:
        log(f"PR creation failed: {e}")
        return {"status": "pr_failed", "error": str(e)[:200]}
    finally:
        subprocess.run(["rm", "-rf", str(workdir)], timeout=30)


@huey.periodic_task(crontab(minute="*/20"))
def gemini_worker():
    """Gemini picks up an assigned issue, codes it with aider, opens a PR."""
    repo, issue = _get_agent_issue("gemini")
    if not issue:
        return {"status": "idle", "reason": "no issues assigned to gemini"}
    return _run_agent("gemini", repo, issue)


@huey.periodic_task(crontab(minute="*/20"))
def grok_worker():
    """Grok picks up an assigned issue, codes it with opencode, opens a PR."""
    repo, issue = _get_agent_issue("grok")
    if not issue:
        return {"status": "idle", "reason": "no issues assigned to grok"}
    return _run_agent("grok", repo, issue)


# ── PR Cross-Review ──────────────────────────────────────────────────

@huey.periodic_task(crontab(minute="*/30"))
def cross_review_prs():
    """Gemini reviews Grok's PRs. Grok reviews Gemini's PRs."""
    results = []

    for reviewer, author in [("gemini", "grok"), ("grok", "gemini")]:
        cfg = AGENT_CONFIG[reviewer]
        token_file = cfg["gitea_token_file"]
        if not token_file.exists():
            continue

        g = GiteaClient(token=token_file.read_text().strip())

        for repo in REPOS:
            try:
                prs = g.list_pulls(repo, state="open", limit=10)
                for pr in prs:
                    # Only review the other agent's PRs
                    if not pr.title.startswith(f"[{author}]"):
                        continue

                    # Skip if already reviewed
                    comments = g.list_comments(repo, pr.number)
                    if any(c.body and f"reviewed by {reviewer}" in c.body.lower() for c in comments):
                        continue

                    # Get the diff
                    files = g.get_pull_files(repo, pr.number)
                    net = sum(f.additions - f.deletions for f in files)
                    file_list = ", ".join(f.filename for f in files[:5])

                    # Build review prompt
                    review_prompt = (
                        f"Review PR #{pr.number}: {pr.title}\n"
                        f"Files: {file_list}\n"
                        f"Net change: +{net} lines\n\n"
                        f"Is this PR focused, correct, and ready to merge? "
                        f"Reply with APPROVE or REQUEST_CHANGES and a brief reason."
                    )

                    # Run reviewer's tool for analysis
                    env = os.environ.copy()
                    if cfg["api_key_env"] == "XAI_API_KEY":
                        env["XAI_API_KEY"] = Path(Path.home() / ".config/grok/api_key").read_text().strip()

                    if cfg["tool"] == "aider":
                        cmd = ["aider", "--model", cfg["model"],
                               "--no-auto-commits", "--yes-always",
                               "--no-suggest-shell-commands",
                               "--message", review_prompt]
                    else:
                        cmd = ["opencode", "run", "-m", cfg["model"],
                               "--no-interactive", review_prompt]

                    try:
                        result = subprocess.run(
                            cmd, capture_output=True, text=True,
                            timeout=120, env=env, cwd="/tmp"
                        )
                        review_text = result.stdout[-1000:] if result.stdout else "No output"
                    except Exception as e:
                        review_text = f"Review failed: {e}"

                    # Post review as comment
                    g.create_comment(repo, pr.number,
                        f"**Reviewed by `{reviewer}`:**\n\n{review_text}")
                    results.append({"reviewer": reviewer, "pr": pr.number, "repo": repo})

            except Exception:
                continue

    return {"reviews": len(results), "details": results}