fix: surface LORA_MODULES parse failures instead of silently loading zero adapters

Fixes FDE-194. Previously a malformed LORA_MODULES value was swallowed at
info level and the engine would start with no LoRA adapters, causing 500s
on any request using an adapter model name (e.g. npc-sim-*).

Changes:
- Log at error level when LORA_MODULES cannot be parsed as JSON
- Log at error level when individual adapter dicts fail LoRAModulePath validation
- Log a final error when all adapters fail to load so the cause is obvious
- Accept a single adapter dict (not just an array) for convenience
- Return early when LORA_MODULES is unset to skip unnecessary parsing

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
velaraptor-runpod
2026-04-30 17:49:09 -05:00
co-authored by Claude Sonnet 4.6
parent e6950bdebd
commit 178c72238e
+39 -10
View File
@@ -206,19 +206,48 @@ class OpenAIvLLMEngine(vLLMEngine):
self.raw_openai_output = bool(int(raw_output_env))
def _load_lora_adapters(self):
adapters = []
try:
adapters = json.loads(os.getenv("LORA_MODULES", '[]'))
except Exception as e:
logging.info(f"---Initialized adapter json load error: {e}")
lora_modules_env = os.getenv("LORA_MODULES", "")
if not lora_modules_env:
return []
for i, adapter in enumerate(adapters):
try:
parsed = json.loads(lora_modules_env)
except json.JSONDecodeError as e:
logging.error(
"LORA_MODULES could not be parsed as JSON: %s — no LoRA adapters loaded. Value: %r",
e, lora_modules_env,
)
return []
# Accept a single adapter dict as well as an array
if isinstance(parsed, dict):
parsed = [parsed]
if not isinstance(parsed, list):
logging.error(
"LORA_MODULES must be a JSON array of adapter objects, got %s — no LoRA adapters loaded.",
type(parsed).__name__,
)
return []
adapters = []
for i, adapter in enumerate(parsed):
try:
adapters[i] = LoRAModulePath(**adapter)
logging.info(f"---Initialized adapter: {adapter}")
adapters.append(LoRAModulePath(**adapter))
logging.info("Loaded LoRA adapter config [%d]: %s", i, adapter)
except Exception as e:
logging.info(f"---Initialized adapter not worked: {e}")
continue
logging.error(
"Failed to parse LoRA adapter at index %d: %s. Config: %r",
i, e, adapter,
)
if parsed and not adapters:
logging.error(
"LORA_MODULES specified %d adapter(s) but none could be loaded — "
"OpenAI model name lookups for LoRA adapters will fail.",
len(parsed),
)
return adapters
async def _ensure_engines_initialized(self):