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fix: harden _find_java17 to search multiple vendors, JAVA_HOME, and warn on wrong version

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KoalaTrapLord committed 2026-03-19 15:23:44 -04:00
1 parent 4ec6ed57d5
commit 0e5d7ba7d3
1 file changed
+86 -27
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services/forge_runner.py
+86 -27
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@@ -75,15 +75,80 @@ def _unregister_batch(batch_id: str):
_watchdog_registry.pop(batch_id, None)
# ── Java 17 Discovery ───────────────────────────────────────────────
# Ordered list of directories to scan for JDK 17 installations.
# Covers: Eclipse Temurin, Oracle, Amazon Corretto, Microsoft, Azul Zulu, SAP.
_JAVA17_SEARCH_DIRS = [
r'C:\Program Files\Eclipse Adoptium',
r'C:\Program Files\Java',
r'C:\Program Files\Amazon Corretto',
r'C:\Program Files\Microsoft',
r'C:\Program Files\Zulu',
r'C:\Program Files\BellSoft',
r'C:\Program Files\SapMachine',
]
def _find_java17() -> str:
search_dirs = [r'C:\Program Files\Eclipse Adoptium', r'C:\Program Files\Java']
for d in search_dirs:
if os.path.isdir(d):
for child in os.listdir(d):
if child.startswith('jdk-17'):
candidate = os.path.join(d, child, 'bin', 'java.exe')
if os.path.isfile(candidate):
return candidate
"""
Search well-known JDK install directories for a Java 17 binary.
Falls back to JAVA17_HOME env var, then JAVA_HOME, then warns and returns 'java'.
Returns the absolute path to java.exe if found, otherwise 'java'.
"""
# 1. Explicit override via env var
env_override = os.environ.get('JAVA17_HOME', '').strip()
if env_override:
candidate = os.path.join(env_override, 'bin', 'java.exe')
if os.path.isfile(candidate):
log.info(f"Java 17 found via JAVA17_HOME: {candidate}")
return candidate
log.warning(f"JAVA17_HOME set to '{env_override}' but java.exe not found there.")
# 2. Scan vendor directories
for d in _JAVA17_SEARCH_DIRS:
if not os.path.isdir(d):
continue
try:
children = os.listdir(d)
except OSError:
continue
for child in sorted(children): # sorted = deterministic, picks lowest 17.x
if re.match(r'jdk-?17', child, re.IGNORECASE) or re.match(r'temurin-17', child, re.IGNORECASE):
candidate = os.path.join(d, child, 'bin', 'java.exe')
if os.path.isfile(candidate):
log.info(f"Java 17 found: {candidate}")
return candidate
# 3. JAVA_HOME fallback — only accept if it IS version 17
java_home = os.environ.get('JAVA_HOME', '').strip()
if java_home:
candidate = os.path.join(java_home, 'bin', 'java.exe')
if os.path.isfile(candidate):
try:
result = subprocess.run(
[candidate, '-version'],
capture_output=True, text=True, timeout=5
)
version_output = result.stderr or result.stdout
if 'version "17' in version_output:
log.info(f"Java 17 found via JAVA_HOME: {candidate}")
return candidate
else:
log.warning(
f"JAVA_HOME points to '{java_home}' but it is not Java 17. "
f"Version output: {version_output.strip()!r}"
)
except Exception as e:
log.warning(f"Could not probe JAVA_HOME java version: {e}")
# 4. Nothing found — warn loudly so the log surfaces the issue
log.error(
"Java 17 not found! Forge simulation requires Java 17. "
"Install Eclipse Temurin 17 (winget install EclipseAdoptium.Temurin.17.JDK) "
"or set the JAVA17_HOME environment variable to your JDK 17 install directory. "
"Falling back to system 'java' which may be the wrong version."
)
return 'java'
@@ -97,6 +162,12 @@ def get_java17() -> str:
return _JAVA17_PATH
def reset_java17_cache():
"""Force re-discovery of Java 17 path (useful after installing JDK at runtime)."""
global _JAVA17_PATH
_JAVA17_PATH = None
def build_java_command(
decks: list, num_games: int, threads: int, seed: Optional[int],
clock: int, output_path: str, use_learned_policy: bool = False,
@@ -174,7 +245,9 @@ def _run_process_blocking(state: BatchState, cmd: list):
state.elapsed_ms = int(elapsed)
if proc.returncode != 0:
state.running = False
state.error = f"Exit code {proc.returncode}"
# Include last few log lines in error for easier diagnosis
tail = ' | '.join(state.log_lines[-5:]) if state.log_lines else '(no output)'
state.error = f"Exit code {proc.returncode} — last output: {tail}"
else:
state.running = False
state.completed_games = state.total_games
@@ -230,7 +303,6 @@ def _get_deepseek_brain():
sys.path.insert(0, src_dir)
from commander_ai_lab.sim.deepseek_brain import DeepSeekBrain, DeepSeekConfig
cfg = DeepSeekConfig()
# Allow env var overrides
if os.environ.get('DEEPSEEK_API_BASE'):
cfg.api_base = os.environ['DEEPSEEK_API_BASE']
if os.environ.get('DEEPSEEK_MODEL'):
@@ -272,9 +344,7 @@ def _run_deepseek_batch_thread(
state.log_lines.append(f'[DeepSeek Batch] Connected to {brain.config.model}')
# Load all decks
# ── Look up historical win rates from past batch results ──
deck_win_rates = {} # deck_name -> float (0-100)
deck_win_rates = {}
try:
results_dir = CFG.results_dir
if os.path.isdir(results_dir):
@@ -294,14 +364,13 @@ def _run_deepseek_batch_thread(
pass
loaded_decks = {}
deck_meta = {} # deck_name -> {commander_name, color_identity, archetype}
deck_meta = {}
for dn in deck_names:
raw_cards = _load_deck_cards_by_name(dn)
if not raw_cards:
state.log_lines.append(f'[DeepSeek Batch] WARNING: Could not load deck "{dn}", skipping.')
continue
# Detect commander and color identity from card data
commander_name = ''
color_identity_set = set()
deck_objs = []
@@ -321,11 +390,9 @@ def _run_deepseek_batch_thread(
try: kw = json.loads(kw)
except Exception: kw = []
if isinstance(kw, list): c.keywords = kw
# Set is_commander flag from DB data
if cd.get('is_commander'):
c.is_commander = True
commander_name = cd['name']
# Collect color identity
ci_str = cd.get('color_identity', '')
if ci_str:
try:
@@ -338,7 +405,6 @@ def _run_deepseek_batch_thread(
enrich_card(c)
deck_objs.append(c)
# Infer archetype from deck composition
creature_count = sum(1 for c in deck_objs if c.is_creature())
removal_count = sum(1 for c in deck_objs if c.is_removal)
ramp_count = sum(1 for c in deck_objs if c.is_ramp)
@@ -373,7 +439,6 @@ def _run_deepseek_batch_thread(
state.running = False
return
# Build matchup schedule: each deck plays num_games vs DeepSeek AI
deck_list = list(loaded_decks.keys())
games_per_deck = max(1, num_games // len(deck_list))
total_games = games_per_deck * len(deck_list)
@@ -383,7 +448,7 @@ def _run_deepseek_batch_thread(
engine = DeepSeekGameEngine(
brain=brain,
ai_player_index=0, # AI pilots deck_a (user's deck) with full intelligence
ai_player_index=0,
max_turns=25,
record_log=True,
ml_log=True,
@@ -395,7 +460,6 @@ def _run_deepseek_batch_thread(
for deck_name in deck_list:
deck_a = loaded_decks[deck_name]
# Generate a training opponent for each game
from commander_ai_lab.lab.experiments import _generate_training_deck
deck_stats = {
@@ -458,7 +522,6 @@ def _run_deepseek_batch_thread(
deck_stats['avgDamageReceived'] = round(deck_stats['totalDamageReceived'] / n, 1) if n > 0 else 0.0
deck_stats['avgSpellsCast'] = round(deck_stats['totalSpellsCast'] / n, 1) if n > 0 else 0.0
deck_stats['avgCreaturesPlayed'] = round(deck_stats['totalCreaturesPlayed'] / n, 1) if n > 0 else 0.0
# Include deck intelligence metadata
deck_stats['archetype'] = dk_archetype
deck_stats['commander'] = dk_commander
deck_stats['colorIdentity'] = dk_colors
@@ -469,7 +532,6 @@ def _run_deepseek_batch_thread(
elapsed = time.time() - start_time
ds_stats = brain.get_stats() if brain else {}
# Build result in compatible format
batch_result = {
'metadata': {
'batchId': state.batch_id,
@@ -484,7 +546,6 @@ def _run_deepseek_batch_thread(
'deepseekStats': ds_stats,
}
# Write ML decision JSONL for the training pipeline
ml_decisions = engine.flush_ml_decisions()
if ml_decisions:
ml_jsonl_path = os.path.join(CFG.results_dir, f'ml-decisions-ds-{state.batch_id}.jsonl')
@@ -496,14 +557,12 @@ def _run_deepseek_batch_thread(
else:
state.log_lines.append('[ML Data] No decision snapshots captured (0 decisions)')
# Save to results dir
os.makedirs(os.path.dirname(output_path), exist_ok=True)
with open(output_path, 'w', encoding='utf-8') as f:
json.dump(batch_result, f, indent=2, default=str)
state.result_path = output_path
elapsed_ms = int(elapsed * 1000)
state.elapsed_ms = elapsed_ms
state.elapsed_ms = int(elapsed * 1000)
state.running = False
state.completed_games = total_games