Fu DaiandClaude Opus 4.8
1a585693be
FastAPI service wrapping the Surya-OCR-2 model (datalab-to) served through vLLM: legacy /v1/api/ai/* endpoints, an OpenAI-compatible /v1/chat/completions endpoint, a coalescing request batcher, a local OCR CLI, Docker packaging, multilingual example outputs, and quantization/concurrency benchmarks. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
69 lines
2.2 KiB
Python
69 lines
2.2 KiB
Python
"""Parse surya_timing_summary lines from logs/info.log and aggregate spans.
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Usage:
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python scripts/parse_timing.py logs/info.log
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"""
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from __future__ import annotations
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import argparse
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import ast
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import json
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import re
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from collections import defaultdict
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from pathlib import Path
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from typing import Any, Dict, List, Optional
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_BATCH_RE = re.compile(r"batch_size=(\d+)")
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_REQID_RE = re.compile(r"request_id=(\S+)")
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def parse_line(line: str) -> Optional[Dict[str, Any]]:
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if "surya_timing_summary" not in line or "events=" not in line:
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return None
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events_str = line.split("events=", 1)[1].strip()
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try:
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events = ast.literal_eval(events_str)
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except (ValueError, SyntaxError):
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return None
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batch_match = _BATCH_RE.search(line)
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reqid_match = _REQID_RE.search(line)
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return {
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"request_id": reqid_match.group(1) if reqid_match else "-",
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"batch_size": int(batch_match.group(1)) if batch_match else 0,
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"events": events,
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}
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def aggregate(records: List[Dict[str, Any]]) -> Dict[str, Dict[str, float]]:
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stats: Dict[str, Dict[str, float]] = defaultdict(
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lambda: {"count": 0, "total_ms": 0.0, "mean_ms": 0.0, "total_tokens": 0}
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)
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for rec in records:
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for event in rec["events"]:
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s = stats[event["name"]]
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s["count"] += 1
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s["total_ms"] += event.get("duration_ms", 0.0)
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tokens = (event.get("metadata") or {}).get("token_count")
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if tokens:
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s["total_tokens"] += tokens
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for s in stats.values():
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s["mean_ms"] = round(s["total_ms"] / s["count"], 2) if s["count"] else 0.0
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s["total_ms"] = round(s["total_ms"], 2)
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return dict(stats)
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def main() -> None:
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parser = argparse.ArgumentParser(description="Aggregate surya timing spans from a log file.")
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parser.add_argument("logfile", type=Path)
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args = parser.parse_args()
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records = [
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rec
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for rec in (parse_line(line) for line in args.logfile.read_text(encoding="utf-8").splitlines())
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if rec is not None
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]
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print(json.dumps({"records": len(records), "spans": aggregate(records)}, indent=2))
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if __name__ == "__main__":
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main()
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