v1.0.0

skills/creative/comfyui/scripts/fetch_logs.py

@@ -0,0 +1,158 @@
+#!/usr/bin/env python3
+"""
+fetch_logs.py — Retrieve workflow execution diagnostics from a ComfyUI server.
+
+When a workflow errors, the server's /history (local) or /jobs (cloud) entry
+contains the full Python traceback. This script makes it easy to fetch by
+prompt_id, with sensible formatting.
+
+Usage:
+    python3 fetch_logs.py <prompt_id>
+    python3 fetch_logs.py <prompt_id> --host https://cloud.comfy.org
+    python3 fetch_logs.py --tail-queue            # show currently queued/running jobs
+"""
+
+from __future__ import annotations
+
+import argparse
+import json
+import sys
+from pathlib import Path
+
+sys.path.insert(0, str(Path(__file__).resolve().parent))
+from _common import (  # noqa: E402
+    DEFAULT_LOCAL_HOST, ENV_API_KEY, emit_json, http_get, is_cloud_host,
+    resolve_api_key, resolve_url,
+)
+
+
+def fetch_history_entry(host: str, headers: dict, prompt_id: str, *, is_cloud: bool) -> dict:
+    if is_cloud:
+        # Try /jobs/{id} first
+        url = resolve_url(host, f"/jobs/{prompt_id}", is_cloud=True)
+        r = http_get(url, headers=headers, retries=2, timeout=30)
+        if r.status == 200:
+            try:
+                return {"ok": True, "entry": r.json(), "source": "/api/jobs"}
+            except Exception:
+                pass
+        # Fallback to history_v2
+        url = resolve_url(host, f"/history/{prompt_id}", is_cloud=True)
+        r = http_get(url, headers=headers, retries=2, timeout=30)
+        try:
+            data = r.json()
+        except Exception:
+            data = None
+        if r.status == 200 and data:
+            return {"ok": True, "entry": data, "source": "/api/history_v2"}
+        return {"ok": False, "http_status": r.status, "body": r.text()[:500]}
+
+    url = resolve_url(host, f"/history/{prompt_id}", is_cloud=False)
+    r = http_get(url, headers=headers, retries=2, timeout=30)
+    if r.status != 200:
+        return {"ok": False, "http_status": r.status, "body": r.text()[:500]}
+    try:
+        data = r.json()
+    except Exception:
+        return {"ok": False, "reason": "non-JSON response"}
+    if not isinstance(data, dict) or prompt_id not in data:
+        return {"ok": False, "reason": "prompt_id not found in history",
+                "history_keys": list(data.keys())[:5] if isinstance(data, dict) else []}
+    return {"ok": True, "entry": data[prompt_id], "source": "/history"}
+
+
+def fetch_queue(host: str, headers: dict) -> dict:
+    url = resolve_url(host, "/queue")
+    r = http_get(url, headers=headers, retries=2, timeout=15)
+    try:
+        data = r.json()
+    except Exception:
+        data = {"raw": r.text()[:500]}
+    return {"http_status": r.status, "data": data}
+
+
+def extract_diagnostics(entry: dict) -> dict:
+    """Pull out the parts a human cares about: status, errors, traceback, timing."""
+    diag: dict = {}
+    status = entry.get("status") or {}
+    diag["status_str"] = status.get("status_str")
+    diag["completed"] = status.get("completed")
+
+    messages = status.get("messages") or []
+    diag["execution_log"] = []
+    for msg in messages:
+        if isinstance(msg, list) and len(msg) >= 2:
+            mtype, mdata = msg[0], msg[1]
+            diag["execution_log"].append({"type": mtype, "data": mdata})
+        else:
+            diag["execution_log"].append(msg)
+
+    # Look for execution_error inside messages
+    errors = []
+    for msg in messages:
+        if isinstance(msg, list) and len(msg) >= 2 and msg[0] == "execution_error":
+            errors.append(msg[1])
+    if errors:
+        diag["errors"] = errors
+
+    # Cloud's /jobs response shape: top-level outputs / status / etc.
+    if "outputs" in entry:
+        out = entry["outputs"] or {}
+        if isinstance(out, dict):
+            diag["output_node_ids"] = list(out.keys())
+            # Count file refs across all output buckets (images / video / etc.)
+            total = 0
+            for node_output in out.values():
+                if not isinstance(node_output, dict):
+                    continue
+                for v in node_output.values():
+                    if isinstance(v, list):
+                        total += len(v)
+            diag["output_count"] = total
+        else:
+            diag["output_node_ids"] = []
+            diag["output_count"] = 0
+    return diag
+
+
+def main(argv: list[str] | None = None) -> int:
+    p = argparse.ArgumentParser(description="Fetch workflow execution diagnostics")
+    p.add_argument("prompt_id", nargs="?", help="prompt_id to look up")
+    p.add_argument("--host", default=DEFAULT_LOCAL_HOST)
+    p.add_argument("--api-key", help=f"or set ${ENV_API_KEY}")
+    p.add_argument("--raw", action="store_true",
+                   help="Print the full history entry instead of the digest")
+    p.add_argument("--tail-queue", action="store_true",
+                   help="Show currently running/pending jobs instead")
+    args = p.parse_args(argv)
+
+    api_key = resolve_api_key(args.api_key)
+    headers = {"X-API-Key": api_key} if api_key else {}
+    is_cloud = is_cloud_host(args.host)
+
+    if args.tail_queue:
+        emit_json(fetch_queue(args.host, headers))
+        return 0
+
+    if not args.prompt_id:
+        print("Error: prompt_id is required (or use --tail-queue)", file=sys.stderr)
+        return 1
+
+    res = fetch_history_entry(args.host, headers, args.prompt_id, is_cloud=is_cloud)
+    if not res.get("ok"):
+        emit_json(res)
+        return 1
+
+    if args.raw:
+        emit_json(res)
+        return 0
+
+    diag = extract_diagnostics(res["entry"])
+    diag["source"] = res.get("source")
+    diag["prompt_id"] = args.prompt_id
+    emit_json(diag)
+    return 0 if diag.get("status_str") not in ("error",) else 1
+
+
+if __name__ == "__main__":
+    sys.exit(main())