agentic-kvc/microbench/fresh_setup/plot_kv_pool_timeline.py

#!/usr/bin/env python3
"""Plot per-instance KV-pool composition over time from MB5 snapshots.

Input: a directory of mb5_kv_snapshot_pid<PID>.jsonl files (one per
EngineCore PID) — typically MB5_LOG_DIR set during a run.

For each snapshot file, builds a stacked-area chart:
  x axis = wall-clock time since first snapshot
  y axis = KV block count (total pool size = ceiling line)
  stacked bands = per-request block usage; each request gets one
                  band colored by a hash-based palette so the eye
                  can track individual requests across the run.

Also overlays:
  - free_blocks (white area at the top)
  - 90% capacity line (red dashed)
  - waiting-queue depth (separate small subplot beneath)
"""
from __future__ import annotations

import argparse
import hashlib
import json
from collections import defaultdict
from pathlib import Path

import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
import numpy as np


def load_snapshots(path: Path) -> list[dict]:
    out = []
    with path.open() as f:
        for line in f:
            line = line.strip()
            if not line:
                continue
            try:
                out.append(json.loads(line))
            except json.JSONDecodeError:
                continue
    return out


def req_color(req_id: str) -> str:
    """Deterministic color per request_id."""
    h = hashlib.md5(req_id.encode()).hexdigest()
    return f"#{h[:6]}"


def plot_one_instance(snaps: list[dict], out: Path, title: str) -> None:
    if not snaps:
        return
    snaps = sorted(snaps, key=lambda s: s["t_unix"])
    t0 = snaps[0]["t_unix"]
    times = [s["t_unix"] - t0 for s in snaps]
    total_blocks = snaps[0]["total_blocks"]

    # Build the request × time block-count matrix
    all_req_ids: list[str] = []
    req_first_seen: dict[str, float] = {}
    for s in snaps:
        for r in s.get("running", []):
            rid = r["req_id"]
            if rid not in req_first_seen:
                req_first_seen[rid] = s["t_unix"] - t0
                all_req_ids.append(rid)
    # Sort by first-seen time so the band order follows arrival
    all_req_ids.sort(key=lambda r: req_first_seen[r])

    matrix = np.zeros((len(all_req_ids), len(times)), dtype=np.int64)
    req_to_row = {r: i for i, r in enumerate(all_req_ids)}
    for j, s in enumerate(snaps):
        for r in s.get("running", []):
            i = req_to_row[r["req_id"]]
            matrix[i, j] = r.get("n_blocks", 0)

    fig, (ax1, ax2) = plt.subplots(
        2, 1, figsize=(13, 6),
        sharex=True,
        gridspec_kw={"height_ratios": [4, 1]},
    )

    colors = [req_color(r) for r in all_req_ids]
    ax1.stackplot(times, matrix, colors=colors, linewidth=0)
    ax1.axhline(total_blocks, color="#444", lw=1.5, ls="-",
                label=f"pool total = {total_blocks} blocks")
    ax1.axhline(total_blocks * 0.9, color="#c44e52", lw=1.2, ls="--", alpha=0.7,
                label="90% capacity")
    ax1.set_ylabel("KV blocks (per-request stacked)")
    ax1.set_ylim(0, total_blocks * 1.05)
    ax1.set_title(title)
    ax1.legend(loc="upper right", fontsize=9, framealpha=0.95)
    ax1.grid(True, alpha=0.3)

    # Waiting queue depth subplot
    wait_lens = [len(s.get("waiting", [])) for s in snaps]
    ax2.fill_between(times, 0, wait_lens, color="#c44e52", alpha=0.55,
                      label="waiting requests")
    ax2.set_ylabel("queue\ndepth")
    ax2.set_xlabel("wall-clock since first snapshot (s)")
    ax2.set_ylim(0, max(max(wait_lens, default=0), 1) * 1.2 + 1)
    ax2.grid(True, alpha=0.3)
    ax2.legend(loc="upper right", fontsize=8)

    out.parent.mkdir(parents=True, exist_ok=True)
    fig.tight_layout()
    fig.savefig(out, dpi=120)
    plt.close(fig)
    print(f"wrote {out}  (n_snapshots={len(snaps)}, n_requests={len(all_req_ids)})")


def main() -> None:
    p = argparse.ArgumentParser()
    p.add_argument("--snapshot-dir", type=Path, required=True,
                   help="dir containing mb5_kv_snapshot_pid*.jsonl files")
    p.add_argument("--out-dir", type=Path, required=True)
    p.add_argument("--label", default="",
                   help="prefix for output filenames + figure title")
    args = p.parse_args()

    files = sorted(args.snapshot_dir.glob("mb5_kv_snapshot_pid*.jsonl"))
    if not files:
        print(f"[plot] no snapshot files in {args.snapshot_dir}")
        return

    for f in files:
        pid = f.stem.replace("mb5_kv_snapshot_pid", "")
        snaps = load_snapshots(f)
        if not snaps:
            print(f"[plot] {f.name}: empty")
            continue
        out = args.out_dir / f"{args.label}_pid{pid}.png"
        title = f"{args.label}  pid={pid}  (n_snap={len(snaps)})"
        plot_one_instance(snaps, out, title)


if __name__ == "__main__":
    main()