Files
firmware/mcp-server/src/meshtastic_mcp/log_query.py
T
2026-07-01 19:01:27 -05:00

411 lines
13 KiB
Python

"""Read-side queries over the recorder's JSONL streams.
Pure functions over `mcp-server/.mtlog/`. Streaming JSONL reader: never
loads a whole file. Time-bound queries short-circuit as soon as `ts`
exceeds the requested end. The recorder writes monotonically, so a
forward scan is cheap; we don't need an index.
All time arguments accept:
- epoch seconds (int/float)
- relative strings: "-15m", "-2h", "-3d", "now"
- ISO-ish absolute strings: "2026-05-07T14:30:00" (naive timestamps are
treated as UTC)
Tools that return data ALWAYS cap their output (max_lines / max_points
/ max), and report whether more matched than was returned.
"""
from __future__ import annotations
import gzip
import json
import re
import statistics
import time
from datetime import datetime, timezone
from pathlib import Path
from typing import Any, Iterator
from .recorder.recorder import get_recorder
_REL_RE = re.compile(r"^\s*-\s*(\d+(?:\.\d+)?)\s*([smhd])\s*$")
_REGEX_PREVIEW_MAX = 100
_REGEX_PREVIEW_TRUNCATE = 97
def _parse_time(value: Any, *, now: float | None = None) -> float:
"""Coerce to epoch seconds. Defaults `now` to `time.time()`."""
if value is None:
return time.time()
if isinstance(value, (int, float)):
return float(value)
if not isinstance(value, str):
raise ValueError(f"invalid time: {value!r}")
s = value.strip().lower()
if s in ("", "now"):
return time.time() if now is None else now
m = _REL_RE.match(s)
if m:
n = float(m.group(1))
unit = m.group(2)
secs = n * {"s": 1, "m": 60, "h": 3600, "d": 86400}[unit]
base = time.time() if now is None else now
return base - secs
# Try ISO 8601. Accept naive (assume UTC) and Z-suffixed.
try:
if s.endswith("z"):
s = s[:-1] + "+00:00"
dt = datetime.fromisoformat(s)
if dt.tzinfo is None:
dt = dt.replace(tzinfo=timezone.utc)
return dt.timestamp()
except ValueError as e:
raise ValueError(f"unparseable time: {value!r}") from e
def _iter_jsonl(path: Path, *, since: float, until: float) -> Iterator[dict[str, Any]]:
"""Stream records in chronological order: rotated archives first
(oldest → newest by lex sort, which is chronological for our
`YYYYMMDD-HHMMSS-uuuuuu-NNNNN` archive naming), then the live file
last. The "keep last N" pop-front logic in the window queries
relies on records arriving in time order across files.
"""
files: list[Path] = []
# Gzipped archives are named "<stem>.YYYYMMDD-HHMMSS-uuuuuu-NNNNN.jsonl.gz".
for archive in sorted(path.parent.glob(f"{path.stem}.*.jsonl.gz")):
files.append(archive)
if path.exists():
files.append(path)
for f in files:
opener = gzip.open if f.suffix == ".gz" else open
try:
with opener(f, "rt", encoding="utf-8") as fh: # type: ignore[arg-type]
for line in fh:
line = line.strip()
if not line:
continue
try:
rec = json.loads(line)
except json.JSONDecodeError:
continue
ts = rec.get("ts")
if not isinstance(ts, (int, float)):
continue
if ts < since:
continue
if ts > until:
# Records are append-monotonic within a file, so
# the rest of this file is also past `until`.
# Archives can still overlap each other, so only
# short-circuit this file, not the whole scan.
break
yield rec
except (FileNotFoundError, OSError):
continue
# -- queries ------------------------------------------------------------
def logs_window(
start: Any = "-15m",
end: Any = "now",
*,
grep: str | None = None,
level: str | None = None,
tag: str | None = None,
port: str | None = None,
max_lines: int = 200,
) -> dict[str, Any]:
"""Recent firmware log lines, filtered.
`level` accepts a single level name or pipe-separated set
("WARN|ERROR|CRIT"). `grep` is a regex (Python re) over the raw
`line` field. Returns the last `max_lines` matches.
"""
s = _parse_time(start)
e = _parse_time(end)
levels = _split_set(level)
if grep:
try:
grep_re = re.compile(grep)
except re.error as exc:
preview = (
grep
if len(grep) <= _REGEX_PREVIEW_MAX
else f"{grep[:_REGEX_PREVIEW_TRUNCATE]}..."
)
raise ValueError(f"invalid grep regex {preview!r}: {exc}") from exc
else:
grep_re = None
base = get_recorder().base_dir
matched = 0
out: list[dict[str, Any]] = []
for rec in _iter_jsonl(base / "logs.jsonl", since=s, until=e):
if levels and rec.get("level") not in levels:
continue
if tag and rec.get("tag") != tag:
continue
if port and rec.get("port") != port:
continue
if grep_re and not grep_re.search(rec.get("line") or ""):
continue
matched += 1
out.append(rec)
if len(out) > max_lines:
out.pop(0) # keep the most recent N
return {
"lines": out,
"total_matched": matched,
"dropped": max(0, matched - max_lines),
"window": {"start": s, "end": e},
}
def telemetry_timeline(
window: Any = "1h",
*,
variant: str = "local",
field: str = "free_heap",
port: str | None = None,
max_points: int = 200,
) -> dict[str, Any]:
"""Timeseries of one telemetry field, downsampled.
`field` matches both the protobuf snake_case name (`free_heap`,
`heap_free_bytes`, `battery_level`) and camelCase (`freeHeap`).
Server-side bucket-mean downsamples to ≤ `max_points`. Returns
`slope_per_min` (linear regression slope, units/min) so a leak
detector can read one number.
"""
end = time.time()
if isinstance(window, (int, float)):
# Numeric `window` is a duration in seconds - "last N seconds".
# Without this branch, `_parse_time(-N)` would treat -N as an
# absolute epoch timestamp (i.e., Jan 1 1970 minus N seconds),
# producing a wildly negative `start` and matching nothing.
start = end - float(window)
elif isinstance(window, str) and not window.startswith("-"):
# Bare string like "1h" is sugar for "-1h".
start = _parse_time(f"-{window}", now=end)
else:
start = _parse_time(window, now=end)
base = get_recorder().base_dir
raw: list[tuple[float, float]] = []
field_aliases = _field_aliases(field)
for rec in _iter_jsonl(base / "telemetry.jsonl", since=start, until=end):
if rec.get("variant") != variant:
continue
if port and rec.get("port") != port:
continue
fields = rec.get("fields") or {}
value: Any = None
for alias in field_aliases:
if alias in fields:
value = fields[alias]
break
if not isinstance(value, (int, float)):
continue
raw.append((float(rec["ts"]), float(value)))
if not raw:
return {
"points": [],
"samples": 0,
"min": None,
"max": None,
"slope_per_min": None,
"window": {"start": start, "end": end, "variant": variant, "field": field},
}
points = _downsample(raw, max_points=max_points)
values = [v for _, v in raw]
return {
"points": [{"ts": ts, "value": v} for ts, v in points],
"samples": len(raw),
"min": min(values),
"max": max(values),
"slope_per_min": _slope_per_min(raw),
"window": {"start": start, "end": end, "variant": variant, "field": field},
}
def packets_window(
start: Any = "-5m",
end: Any = "now",
*,
portnum: str | None = None,
from_node: str | None = None,
to_node: str | None = None,
max: int = 200,
) -> dict[str, Any]:
s = _parse_time(start)
e = _parse_time(end)
portnums = _split_set(portnum)
base = get_recorder().base_dir
matched = 0
out: list[dict[str, Any]] = []
for rec in _iter_jsonl(base / "packets.jsonl", since=s, until=e):
if portnums and rec.get("portnum") not in portnums:
continue
if from_node and str(rec.get("from_node")) != str(from_node):
continue
if to_node and str(rec.get("to_node")) != str(to_node):
continue
matched += 1
out.append(rec)
if len(out) > max:
out.pop(0)
return {
"packets": out,
"total_matched": matched,
"dropped": matched - max if matched > max else 0,
"window": {"start": s, "end": e},
}
def events_window(
start: Any = "-1h",
end: Any = "now",
*,
kind: str | None = None,
max: int = 200,
) -> dict[str, Any]:
s = _parse_time(start)
e = _parse_time(end)
kinds = _split_set(kind)
base = get_recorder().base_dir
matched = 0
out: list[dict[str, Any]] = []
for rec in _iter_jsonl(base / "events.jsonl", since=s, until=e):
if kinds and rec.get("kind") not in kinds:
continue
matched += 1
out.append(rec)
if len(out) > max:
out.pop(0)
return {
"events": out,
"total_matched": matched,
"dropped": matched - max if matched > max else 0,
"window": {"start": s, "end": e},
}
def export(
start: Any,
end: Any,
dest_dir: str,
*,
streams: list[str] | None = None,
) -> dict[str, Any]:
"""Bundle a slice of each requested stream into `dest_dir`.
For a notebook, a bug report, or a Datadog backfill. Output files
are uncompressed JSONL (callers gzip themselves if they want to).
"""
s = _parse_time(start)
e = _parse_time(end)
selected = streams or ["logs", "telemetry", "packets", "events"]
dest = Path(dest_dir)
dest.mkdir(parents=True, exist_ok=True)
base = get_recorder().base_dir
paths: dict[str, str] = {}
for stream in selected:
src = base / f"{stream}.jsonl"
if not src.exists() and not list(base.glob(f"{stream}.*.jsonl.gz")):
continue
out_path = dest / f"{stream}.jsonl"
n = 0
with out_path.open("w", encoding="utf-8") as fh:
for rec in _iter_jsonl(src, since=s, until=e):
fh.write(json.dumps(rec, separators=(",", ":")) + "\n")
n += 1
paths[stream] = str(out_path)
paths[f"{stream}_count"] = str(n)
return {"dest_dir": str(dest), "paths": paths, "window": {"start": s, "end": e}}
# -- helpers ------------------------------------------------------------
def _split_set(value: str | None) -> set[str] | None:
if not value:
return None
return {v.strip() for v in value.split("|") if v.strip()}
def _field_aliases(field: str) -> list[str]:
"""Accept snake_case OR camelCase, plus a few legacy aliases."""
snake = field
camel = _snake_to_camel(field)
aliases = {snake, camel}
# Old protobuf fields (pre-LocalStats) used different names
legacy = {
"free_heap": ["free_heap", "freeHeap", "heap_free_bytes", "heapFreeBytes"],
"heap_free_bytes": [
"heap_free_bytes",
"heapFreeBytes",
"free_heap",
"freeHeap",
],
"total_heap": ["total_heap", "totalHeap", "heap_total_bytes", "heapTotalBytes"],
"heap_total_bytes": [
"heap_total_bytes",
"heapTotalBytes",
"total_heap",
"totalHeap",
],
}
if field in legacy:
aliases.update(legacy[field])
return list(aliases)
def _snake_to_camel(name: str) -> str:
parts = name.split("_")
return parts[0] + "".join(p.title() for p in parts[1:])
def _downsample(
points: list[tuple[float, float]], *, max_points: int
) -> list[tuple[float, float]]:
if len(points) <= max_points:
return points
# Even-bucket mean. Preserves shape better than nth-sample picking.
n = len(points)
bucket = n / max_points
out: list[tuple[float, float]] = []
i = 0
for k in range(max_points):
end = int((k + 1) * bucket)
end = min(end, n)
if end <= i:
continue
chunk = points[i:end]
ts = chunk[len(chunk) // 2][0]
val = statistics.fmean(v for _, v in chunk)
out.append((ts, val))
i = end
return out
def _slope_per_min(points: list[tuple[float, float]]) -> float | None:
"""Least-squares slope (units per minute). None if too few points."""
if len(points) < 2:
return None
xs = [t for t, _ in points]
ys = [v for _, v in points]
n = len(xs)
mean_x = sum(xs) / n
mean_y = sum(ys) / n
num = sum((xs[i] - mean_x) * (ys[i] - mean_y) for i in range(n))
den = sum((x - mean_x) ** 2 for x in xs)
if den == 0:
return None
slope_per_sec = num / den
return slope_per_sec * 60.0