92d26b2b72
Refactor to use IPFS CID as the primary content identifier: - Update database schema: content_hash -> cid, output_hash -> output_cid - Update all services, routers, and tasks to use cid terminology - Update HTML templates to display CID instead of hash - Update cache_manager parameter names - Update README documentation This completes the transition to CID-only content addressing. Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
726 lines
28 KiB
Python
726 lines
28 KiB
Python
"""
|
|
Run Service - business logic for run management.
|
|
|
|
Runs are content-addressed (run_id computed from inputs + recipe).
|
|
Completed runs are stored in PostgreSQL, not Redis.
|
|
In-progress runs are tracked via Celery task state.
|
|
"""
|
|
|
|
import hashlib
|
|
import json
|
|
import os
|
|
from datetime import datetime, timezone
|
|
from pathlib import Path
|
|
from typing import Optional, List, Dict, Any, Tuple
|
|
|
|
|
|
def compute_run_id(input_hashes: list, recipe: str, recipe_hash: str = None) -> str:
|
|
"""
|
|
Compute a deterministic run_id from inputs and recipe.
|
|
|
|
The run_id is a SHA3-256 hash of:
|
|
- Sorted input content hashes
|
|
- Recipe identifier (recipe_hash if provided, else "effect:{recipe}")
|
|
|
|
This makes runs content-addressable: same inputs + recipe = same run_id.
|
|
"""
|
|
# Handle both list and dict inputs
|
|
if isinstance(input_hashes, dict):
|
|
sorted_inputs = sorted(input_hashes.values())
|
|
else:
|
|
sorted_inputs = sorted(input_hashes)
|
|
|
|
data = {
|
|
"inputs": sorted_inputs,
|
|
"recipe": recipe_hash or f"effect:{recipe}",
|
|
"version": "1",
|
|
}
|
|
json_str = json.dumps(data, sort_keys=True, separators=(",", ":"))
|
|
return hashlib.sha3_256(json_str.encode()).hexdigest()
|
|
|
|
|
|
def detect_media_type(cache_path: Path) -> str:
|
|
"""Detect if file is image, video, or audio based on magic bytes."""
|
|
try:
|
|
with open(cache_path, "rb") as f:
|
|
header = f.read(32)
|
|
except Exception:
|
|
return "unknown"
|
|
|
|
# Video signatures
|
|
if header[:4] == b'\x1a\x45\xdf\xa3': # WebM/MKV
|
|
return "video"
|
|
if len(header) > 8 and header[4:8] == b'ftyp': # MP4/MOV/M4A
|
|
# Check for audio-only M4A
|
|
if len(header) > 11 and header[8:12] in (b'M4A ', b'm4a '):
|
|
return "audio"
|
|
return "video"
|
|
if header[:4] == b'RIFF' and len(header) > 12 and header[8:12] == b'AVI ': # AVI
|
|
return "video"
|
|
|
|
# Image signatures
|
|
if header[:8] == b'\x89PNG\r\n\x1a\n': # PNG
|
|
return "image"
|
|
if header[:2] == b'\xff\xd8': # JPEG
|
|
return "image"
|
|
if header[:6] in (b'GIF87a', b'GIF89a'): # GIF
|
|
return "image"
|
|
if header[:4] == b'RIFF' and len(header) > 12 and header[8:12] == b'WEBP': # WebP
|
|
return "image"
|
|
|
|
# Audio signatures
|
|
if header[:3] == b'ID3' or header[:2] == b'\xff\xfb': # MP3
|
|
return "audio"
|
|
if header[:4] == b'fLaC': # FLAC
|
|
return "audio"
|
|
if header[:4] == b'OggS': # Ogg (could be audio or video, assume audio)
|
|
return "audio"
|
|
if header[:4] == b'RIFF' and len(header) > 12 and header[8:12] == b'WAVE': # WAV
|
|
return "audio"
|
|
|
|
return "unknown"
|
|
|
|
|
|
class RunService:
|
|
"""
|
|
Service for managing recipe runs.
|
|
|
|
Uses PostgreSQL for completed runs, Celery for task state.
|
|
Redis is only used for task_id mapping (ephemeral).
|
|
"""
|
|
|
|
def __init__(self, database, redis, cache):
|
|
self.db = database
|
|
self.redis = redis # Only for task_id mapping
|
|
self.cache = cache
|
|
self.task_key_prefix = "artdag:task:" # run_id -> task_id mapping only
|
|
self.cache_dir = Path(os.environ.get("CACHE_DIR", "/tmp/artdag-cache"))
|
|
|
|
def _ensure_inputs_list(self, inputs) -> list:
|
|
"""Ensure inputs is a list, parsing JSON string if needed."""
|
|
if inputs is None:
|
|
return []
|
|
if isinstance(inputs, list):
|
|
return inputs
|
|
if isinstance(inputs, str):
|
|
try:
|
|
parsed = json.loads(inputs)
|
|
if isinstance(parsed, list):
|
|
return parsed
|
|
except json.JSONDecodeError:
|
|
pass
|
|
return []
|
|
return []
|
|
|
|
async def get_run(self, run_id: str) -> Optional[Dict[str, Any]]:
|
|
"""Get a run by ID. Checks database first, then Celery task state."""
|
|
# Check database for completed run
|
|
cached = await self.db.get_run_cache(run_id)
|
|
if cached:
|
|
return {
|
|
"run_id": run_id,
|
|
"status": "completed",
|
|
"recipe": cached.get("recipe"),
|
|
"inputs": self._ensure_inputs_list(cached.get("inputs")),
|
|
"output_cid": cached.get("output_cid"),
|
|
"ipfs_cid": cached.get("ipfs_cid"),
|
|
"provenance_cid": cached.get("provenance_cid"),
|
|
"actor_id": cached.get("actor_id"),
|
|
"created_at": cached.get("created_at"),
|
|
"completed_at": cached.get("created_at"),
|
|
}
|
|
|
|
# Check database for pending run
|
|
pending = await self.db.get_pending_run(run_id)
|
|
if pending:
|
|
task_id = pending.get("celery_task_id")
|
|
if task_id:
|
|
# Check actual Celery task state
|
|
from celery.result import AsyncResult
|
|
from celery_app import app as celery_app
|
|
|
|
result = AsyncResult(task_id, app=celery_app)
|
|
status = result.status.lower()
|
|
|
|
# Normalize status
|
|
status_map = {
|
|
"pending": "pending",
|
|
"started": "running",
|
|
"success": "completed",
|
|
"failure": "failed",
|
|
"retry": "running",
|
|
"revoked": "failed",
|
|
}
|
|
normalized_status = status_map.get(status, status)
|
|
|
|
run_data = {
|
|
"run_id": run_id,
|
|
"status": normalized_status,
|
|
"celery_task_id": task_id,
|
|
"actor_id": pending.get("actor_id"),
|
|
"recipe": pending.get("recipe"),
|
|
"inputs": self._ensure_inputs_list(pending.get("inputs")),
|
|
"output_name": pending.get("output_name"),
|
|
"created_at": pending.get("created_at"),
|
|
"error": pending.get("error"),
|
|
}
|
|
|
|
# If task completed, get result
|
|
if result.ready():
|
|
if result.successful():
|
|
run_data["status"] = "completed"
|
|
task_result = result.result
|
|
if isinstance(task_result, dict):
|
|
run_data["output_cid"] = task_result.get("output_cid")
|
|
else:
|
|
run_data["status"] = "failed"
|
|
run_data["error"] = str(result.result)
|
|
|
|
return run_data
|
|
|
|
# No task_id but have pending record - return from DB
|
|
return {
|
|
"run_id": run_id,
|
|
"status": pending.get("status", "pending"),
|
|
"recipe": pending.get("recipe"),
|
|
"inputs": self._ensure_inputs_list(pending.get("inputs")),
|
|
"output_name": pending.get("output_name"),
|
|
"actor_id": pending.get("actor_id"),
|
|
"created_at": pending.get("created_at"),
|
|
"error": pending.get("error"),
|
|
}
|
|
|
|
# Fallback: Check Redis for backwards compatibility
|
|
task_data = self.redis.get(f"{self.task_key_prefix}{run_id}")
|
|
if task_data:
|
|
if isinstance(task_data, bytes):
|
|
task_data = task_data.decode()
|
|
|
|
# Parse task data (supports both old format string and new JSON format)
|
|
try:
|
|
parsed = json.loads(task_data)
|
|
task_id = parsed.get("task_id")
|
|
task_actor_id = parsed.get("actor_id")
|
|
task_recipe = parsed.get("recipe")
|
|
task_recipe_name = parsed.get("recipe_name")
|
|
task_inputs = parsed.get("inputs")
|
|
# Ensure inputs is a list (might be JSON string)
|
|
if isinstance(task_inputs, str):
|
|
try:
|
|
task_inputs = json.loads(task_inputs)
|
|
except json.JSONDecodeError:
|
|
task_inputs = None
|
|
task_output_name = parsed.get("output_name")
|
|
task_created_at = parsed.get("created_at")
|
|
except json.JSONDecodeError:
|
|
# Old format: just the task_id string
|
|
task_id = task_data
|
|
task_actor_id = None
|
|
task_recipe = None
|
|
task_recipe_name = None
|
|
task_inputs = None
|
|
task_output_name = None
|
|
task_created_at = None
|
|
|
|
# Get task state from Celery
|
|
from celery.result import AsyncResult
|
|
from celery_app import app as celery_app
|
|
|
|
result = AsyncResult(task_id, app=celery_app)
|
|
status = result.status.lower()
|
|
|
|
# Normalize Celery status names
|
|
status_map = {
|
|
"pending": "pending",
|
|
"started": "running",
|
|
"success": "completed",
|
|
"failure": "failed",
|
|
"retry": "running",
|
|
"revoked": "failed",
|
|
}
|
|
normalized_status = status_map.get(status, status)
|
|
|
|
run_data = {
|
|
"run_id": run_id,
|
|
"status": normalized_status,
|
|
"celery_task_id": task_id,
|
|
"actor_id": task_actor_id,
|
|
"recipe": task_recipe,
|
|
"recipe_name": task_recipe_name,
|
|
"inputs": self._ensure_inputs_list(task_inputs),
|
|
"output_name": task_output_name,
|
|
"created_at": task_created_at,
|
|
}
|
|
|
|
# If task completed, get result
|
|
if result.ready():
|
|
if result.successful():
|
|
run_data["status"] = "completed"
|
|
task_result = result.result
|
|
if isinstance(task_result, dict):
|
|
run_data["output_cid"] = task_result.get("output_cid")
|
|
else:
|
|
run_data["status"] = "failed"
|
|
run_data["error"] = str(result.result)
|
|
|
|
return run_data
|
|
|
|
return None
|
|
|
|
async def list_runs(self, actor_id: str, offset: int = 0, limit: int = 20) -> list:
|
|
"""List runs for a user. Returns completed and pending runs from database."""
|
|
# Get completed runs from database
|
|
completed_runs = await self.db.list_runs_by_actor(actor_id, offset=0, limit=limit + 50)
|
|
|
|
# Get pending runs from database
|
|
pending_db = await self.db.list_pending_runs(actor_id=actor_id)
|
|
|
|
# Convert pending runs to run format with live status check
|
|
pending = []
|
|
for pr in pending_db:
|
|
run_id = pr.get("run_id")
|
|
# Skip if already in completed
|
|
if any(r.get("run_id") == run_id for r in completed_runs):
|
|
continue
|
|
|
|
# Get live status
|
|
run = await self.get_run(run_id)
|
|
if run and run.get("status") in ("pending", "running"):
|
|
pending.append(run)
|
|
|
|
# Combine and sort
|
|
all_runs = pending + completed_runs
|
|
all_runs.sort(key=lambda r: r.get("created_at", ""), reverse=True)
|
|
|
|
return all_runs[offset:offset + limit]
|
|
|
|
async def create_run(
|
|
self,
|
|
recipe: str,
|
|
inputs: list,
|
|
output_name: str = None,
|
|
use_dag: bool = True,
|
|
dag_json: str = None,
|
|
actor_id: str = None,
|
|
l2_server: str = None,
|
|
recipe_name: str = None,
|
|
) -> Tuple[Optional[Dict[str, Any]], Optional[str]]:
|
|
"""
|
|
Create a new rendering run. Checks cache before executing.
|
|
|
|
Returns (run_dict, error_message).
|
|
"""
|
|
import httpx
|
|
try:
|
|
from legacy_tasks import render_effect, execute_dag, build_effect_dag
|
|
except ImportError as e:
|
|
return None, f"Celery tasks not available: {e}"
|
|
|
|
# Handle both list and dict inputs
|
|
if isinstance(inputs, dict):
|
|
input_list = list(inputs.values())
|
|
else:
|
|
input_list = inputs
|
|
|
|
# Compute content-addressable run_id
|
|
run_id = compute_run_id(input_list, recipe)
|
|
|
|
# Generate output name if not provided
|
|
if not output_name:
|
|
output_name = f"{recipe}-{run_id[:8]}"
|
|
|
|
# Check database cache first (completed runs)
|
|
cached_run = await self.db.get_run_cache(run_id)
|
|
if cached_run:
|
|
output_cid = cached_run.get("output_cid")
|
|
if output_cid and self.cache.has_content(output_cid):
|
|
return {
|
|
"run_id": run_id,
|
|
"status": "completed",
|
|
"recipe": recipe,
|
|
"inputs": input_list,
|
|
"output_name": output_name,
|
|
"output_cid": output_cid,
|
|
"ipfs_cid": cached_run.get("ipfs_cid"),
|
|
"provenance_cid": cached_run.get("provenance_cid"),
|
|
"created_at": cached_run.get("created_at"),
|
|
"completed_at": cached_run.get("created_at"),
|
|
"actor_id": actor_id,
|
|
}, None
|
|
|
|
# Check L2 if not in local cache
|
|
if l2_server:
|
|
try:
|
|
async with httpx.AsyncClient(timeout=10) as client:
|
|
l2_resp = await client.get(f"{l2_server}/assets/by-run-id/{run_id}")
|
|
if l2_resp.status_code == 200:
|
|
l2_data = l2_resp.json()
|
|
output_cid = l2_data.get("output_cid")
|
|
ipfs_cid = l2_data.get("ipfs_cid")
|
|
if output_cid and ipfs_cid:
|
|
# Pull from IPFS to local cache
|
|
try:
|
|
import ipfs_client
|
|
legacy_dir = self.cache_dir / "legacy"
|
|
legacy_dir.mkdir(parents=True, exist_ok=True)
|
|
recovery_path = legacy_dir / output_cid
|
|
if ipfs_client.get_file(ipfs_cid, str(recovery_path)):
|
|
# Save to database cache
|
|
await self.db.save_run_cache(
|
|
run_id=run_id,
|
|
output_cid=output_cid,
|
|
recipe=recipe,
|
|
inputs=input_list,
|
|
ipfs_cid=ipfs_cid,
|
|
provenance_cid=l2_data.get("provenance_cid"),
|
|
actor_id=actor_id,
|
|
)
|
|
return {
|
|
"run_id": run_id,
|
|
"status": "completed",
|
|
"recipe": recipe,
|
|
"inputs": input_list,
|
|
"output_cid": output_cid,
|
|
"ipfs_cid": ipfs_cid,
|
|
"provenance_cid": l2_data.get("provenance_cid"),
|
|
"created_at": datetime.now(timezone.utc).isoformat(),
|
|
"actor_id": actor_id,
|
|
}, None
|
|
except Exception:
|
|
pass # IPFS recovery failed, continue to run
|
|
except Exception:
|
|
pass # L2 lookup failed, continue to run
|
|
|
|
# Not cached - submit to Celery
|
|
try:
|
|
if use_dag or recipe == "dag":
|
|
if dag_json:
|
|
dag_data = dag_json
|
|
else:
|
|
dag = build_effect_dag(input_list, recipe)
|
|
dag_data = dag.to_json()
|
|
|
|
task = execute_dag.delay(dag_data, run_id)
|
|
else:
|
|
if len(input_list) != 1:
|
|
return None, "Legacy mode only supports single-input recipes. Use use_dag=true for multi-input."
|
|
task = render_effect.delay(input_list[0], recipe, output_name)
|
|
|
|
# Store pending run in database for durability
|
|
try:
|
|
await self.db.create_pending_run(
|
|
run_id=run_id,
|
|
celery_task_id=task.id,
|
|
recipe=recipe,
|
|
inputs=input_list,
|
|
actor_id=actor_id,
|
|
dag_json=dag_json,
|
|
output_name=output_name,
|
|
)
|
|
except Exception as e:
|
|
import logging
|
|
logging.getLogger(__name__).error(f"Failed to save pending run: {e}")
|
|
|
|
# Also store in Redis for backwards compatibility (shorter TTL)
|
|
task_data = json.dumps({
|
|
"task_id": task.id,
|
|
"actor_id": actor_id,
|
|
"recipe": recipe,
|
|
"recipe_name": recipe_name,
|
|
"inputs": input_list,
|
|
"output_name": output_name,
|
|
"created_at": datetime.now(timezone.utc).isoformat(),
|
|
})
|
|
self.redis.setex(
|
|
f"{self.task_key_prefix}{run_id}",
|
|
3600 * 4, # 4 hour TTL (database is primary now)
|
|
task_data
|
|
)
|
|
|
|
return {
|
|
"run_id": run_id,
|
|
"status": "running",
|
|
"recipe": recipe,
|
|
"recipe_name": recipe_name,
|
|
"inputs": input_list,
|
|
"output_name": output_name,
|
|
"celery_task_id": task.id,
|
|
"created_at": datetime.now(timezone.utc).isoformat(),
|
|
"actor_id": actor_id,
|
|
}, None
|
|
|
|
except Exception as e:
|
|
return None, f"Failed to submit task: {e}"
|
|
|
|
async def discard_run(
|
|
self,
|
|
run_id: str,
|
|
actor_id: str,
|
|
username: str,
|
|
) -> Tuple[bool, Optional[str]]:
|
|
"""
|
|
Discard (delete) a run record.
|
|
|
|
Note: This removes the run record but not the output content.
|
|
"""
|
|
run = await self.get_run(run_id)
|
|
if not run:
|
|
return False, f"Run {run_id} not found"
|
|
|
|
# Check ownership
|
|
run_owner = run.get("actor_id")
|
|
if run_owner and run_owner not in (username, actor_id):
|
|
return False, "Access denied"
|
|
|
|
# Remove task_id mapping from Redis
|
|
self.redis.delete(f"{self.task_key_prefix}{run_id}")
|
|
|
|
# Note: We don't delete from run_cache as that's a permanent record
|
|
# of completed work. The content itself remains in cache.
|
|
|
|
return True, None
|
|
|
|
async def get_run_plan(self, run_id: str) -> Optional[Dict[str, Any]]:
|
|
"""Get execution plan for a run.
|
|
|
|
Plans are just node outputs - cached by content hash like everything else.
|
|
"""
|
|
# Get run to find plan_cache_id
|
|
run = await self.get_run(run_id)
|
|
if not run:
|
|
return None
|
|
|
|
plan_cache_id = run.get("plan_cache_id")
|
|
if plan_cache_id:
|
|
# Get plan from cache by content hash
|
|
plan_path = self.cache.get_by_cid(plan_cache_id)
|
|
if plan_path and plan_path.exists():
|
|
with open(plan_path) as f:
|
|
content = f.read()
|
|
# Detect format
|
|
if content.strip().startswith("("):
|
|
return {"sexp": content, "format": "sexp"}
|
|
else:
|
|
plan = json.loads(content)
|
|
plan["format"] = "json"
|
|
return plan
|
|
|
|
# Fall back to legacy plans directory
|
|
sexp_path = self.cache_dir / "plans" / f"{run_id}.sexp"
|
|
if sexp_path.exists():
|
|
with open(sexp_path) as f:
|
|
return {"sexp": f.read(), "format": "sexp"}
|
|
|
|
json_path = self.cache_dir / "plans" / f"{run_id}.json"
|
|
if json_path.exists():
|
|
with open(json_path) as f:
|
|
plan = json.load(f)
|
|
plan["format"] = "json"
|
|
return plan
|
|
|
|
return None
|
|
|
|
async def get_run_plan_sexp(self, run_id: str) -> Optional[str]:
|
|
"""Get execution plan as S-expression string."""
|
|
plan = await self.get_run_plan(run_id)
|
|
if plan and plan.get("format") == "sexp":
|
|
return plan.get("sexp")
|
|
return None
|
|
|
|
async def get_run_artifacts(self, run_id: str) -> List[Dict[str, Any]]:
|
|
"""Get all artifacts (inputs + outputs) for a run."""
|
|
run = await self.get_run(run_id)
|
|
if not run:
|
|
return []
|
|
|
|
artifacts = []
|
|
|
|
def get_artifact_info(cid: str, role: str, name: str) -> Optional[Dict]:
|
|
if self.cache.has_content(cid):
|
|
path = self.cache.get_by_cid(cid)
|
|
if path and path.exists():
|
|
return {
|
|
"hash": cid,
|
|
"size_bytes": path.stat().st_size,
|
|
"media_type": detect_media_type(path),
|
|
"role": role,
|
|
"step_name": name,
|
|
}
|
|
return None
|
|
|
|
# Add inputs
|
|
inputs = run.get("inputs", [])
|
|
if isinstance(inputs, dict):
|
|
inputs = list(inputs.values())
|
|
for i, h in enumerate(inputs):
|
|
info = get_artifact_info(h, "input", f"Input {i + 1}")
|
|
if info:
|
|
artifacts.append(info)
|
|
|
|
# Add output
|
|
if run.get("output_cid"):
|
|
info = get_artifact_info(run["output_cid"], "output", "Output")
|
|
if info:
|
|
artifacts.append(info)
|
|
|
|
return artifacts
|
|
|
|
async def get_run_analysis(self, run_id: str) -> List[Dict[str, Any]]:
|
|
"""Get analysis data for each input in a run."""
|
|
run = await self.get_run(run_id)
|
|
if not run:
|
|
return []
|
|
|
|
analysis_dir = self.cache_dir / "analysis"
|
|
results = []
|
|
|
|
inputs = run.get("inputs", [])
|
|
if isinstance(inputs, dict):
|
|
inputs = list(inputs.values())
|
|
|
|
for i, input_hash in enumerate(inputs):
|
|
analysis_path = analysis_dir / f"{input_hash}.json"
|
|
analysis_data = None
|
|
|
|
if analysis_path.exists():
|
|
try:
|
|
with open(analysis_path) as f:
|
|
analysis_data = json.load(f)
|
|
except (json.JSONDecodeError, IOError):
|
|
pass
|
|
|
|
results.append({
|
|
"input_hash": input_hash,
|
|
"input_name": f"Input {i + 1}",
|
|
"has_analysis": analysis_data is not None,
|
|
"tempo": analysis_data.get("tempo") if analysis_data else None,
|
|
"beat_times": analysis_data.get("beat_times", []) if analysis_data else [],
|
|
"raw": analysis_data,
|
|
})
|
|
|
|
return results
|
|
|
|
def detect_media_type(self, path: Path) -> str:
|
|
"""Detect media type for a file path."""
|
|
return detect_media_type(path)
|
|
|
|
async def recover_pending_runs(self) -> Dict[str, int]:
|
|
"""
|
|
Recover pending runs after restart.
|
|
|
|
Checks all pending runs in the database and:
|
|
- Updates status for completed tasks
|
|
- Re-queues orphaned tasks that can be retried
|
|
- Marks as failed if unrecoverable
|
|
|
|
Returns counts of recovered, completed, failed runs.
|
|
"""
|
|
from celery.result import AsyncResult
|
|
from celery_app import app as celery_app
|
|
|
|
try:
|
|
from legacy_tasks import execute_dag
|
|
except ImportError:
|
|
return {"error": "Celery tasks not available"}
|
|
|
|
stats = {"recovered": 0, "completed": 0, "failed": 0, "still_running": 0}
|
|
|
|
# Get all pending/running runs from database
|
|
pending_runs = await self.db.list_pending_runs()
|
|
|
|
for run in pending_runs:
|
|
run_id = run.get("run_id")
|
|
task_id = run.get("celery_task_id")
|
|
status = run.get("status")
|
|
|
|
if not task_id:
|
|
# No task ID - try to re-queue if we have dag_json
|
|
dag_json = run.get("dag_json")
|
|
if dag_json:
|
|
try:
|
|
new_task = execute_dag.delay(dag_json, run_id)
|
|
await self.db.create_pending_run(
|
|
run_id=run_id,
|
|
celery_task_id=new_task.id,
|
|
recipe=run.get("recipe", "unknown"),
|
|
inputs=run.get("inputs", []),
|
|
actor_id=run.get("actor_id"),
|
|
dag_json=dag_json,
|
|
output_name=run.get("output_name"),
|
|
)
|
|
stats["recovered"] += 1
|
|
except Exception as e:
|
|
await self.db.update_pending_run_status(
|
|
run_id, "failed", f"Recovery failed: {e}"
|
|
)
|
|
stats["failed"] += 1
|
|
else:
|
|
await self.db.update_pending_run_status(
|
|
run_id, "failed", "No DAG data for recovery"
|
|
)
|
|
stats["failed"] += 1
|
|
continue
|
|
|
|
# Check Celery task state
|
|
result = AsyncResult(task_id, app=celery_app)
|
|
celery_status = result.status.lower()
|
|
|
|
if result.ready():
|
|
if result.successful():
|
|
# Task completed - move to run_cache
|
|
task_result = result.result
|
|
if isinstance(task_result, dict) and task_result.get("output_cid"):
|
|
await self.db.save_run_cache(
|
|
run_id=run_id,
|
|
output_cid=task_result["output_cid"],
|
|
recipe=run.get("recipe", "unknown"),
|
|
inputs=run.get("inputs", []),
|
|
ipfs_cid=task_result.get("ipfs_cid"),
|
|
provenance_cid=task_result.get("provenance_cid"),
|
|
actor_id=run.get("actor_id"),
|
|
)
|
|
await self.db.complete_pending_run(run_id)
|
|
stats["completed"] += 1
|
|
else:
|
|
await self.db.update_pending_run_status(
|
|
run_id, "failed", "Task completed but no output hash"
|
|
)
|
|
stats["failed"] += 1
|
|
else:
|
|
# Task failed
|
|
await self.db.update_pending_run_status(
|
|
run_id, "failed", str(result.result)
|
|
)
|
|
stats["failed"] += 1
|
|
elif celery_status in ("pending", "started", "retry"):
|
|
# Still running
|
|
stats["still_running"] += 1
|
|
else:
|
|
# Unknown state - try to re-queue if we have dag_json
|
|
dag_json = run.get("dag_json")
|
|
if dag_json:
|
|
try:
|
|
new_task = execute_dag.delay(dag_json, run_id)
|
|
await self.db.create_pending_run(
|
|
run_id=run_id,
|
|
celery_task_id=new_task.id,
|
|
recipe=run.get("recipe", "unknown"),
|
|
inputs=run.get("inputs", []),
|
|
actor_id=run.get("actor_id"),
|
|
dag_json=dag_json,
|
|
output_name=run.get("output_name"),
|
|
)
|
|
stats["recovered"] += 1
|
|
except Exception as e:
|
|
await self.db.update_pending_run_status(
|
|
run_id, "failed", f"Recovery failed: {e}"
|
|
)
|
|
stats["failed"] += 1
|
|
else:
|
|
await self.db.update_pending_run_status(
|
|
run_id, "failed", f"Task in unknown state: {celery_status}"
|
|
)
|
|
stats["failed"] += 1
|
|
|
|
return stats
|