Auth
ResonAuthError: No platform api key
platform_api_key= was omitted and RESON_API_KEY isn't set. Mint one from Profile → Developer and either pass it on the config or export the env var.
ResonAuthError: Wrong API-key type
You passed a predict key (opaque, no rsk_ prefix) where the SDK expected a platform key. Predict keys go on InferenceClient(predict_api_key=...) and ride in X-API-Key; platform keys go on ResonTechConfig(platform_api_key=...) and ride in Authorization: Bearer.
401 invalid_api_key
Key was revoked, expired, or never valid. Rotation takes effect within seconds: if you just rotated, wait a moment, then retry. Otherwise, mint a fresh key from Profile → Developer.
ResonTechError: Cannot reach <base_url>
Almost always a wrong base_url. Open it in a browser — a healthy deployment returns a 404 page, not a login portal or a blank 200.
Storage / Bucket
StorageError: No S3 bucket configured
You haven't provisioned a bucket yet. Open the web UI → Profile → Storage → Provision Bucket, pick an alias and quota, and paste the returned secret into ResonTechConfig.
StorageError: Could not resolve your storage bucket
Your key works, but no bucket is attached to your account yet. The fix is the same: provision a bucket from Profile → Storage → Provision Bucket.
StorageError: s3_access_key_id and s3_secret_access_key are required
You constructed ResonTechConfig with empty strings. Pass both values before creating ResonTech(config).
StorageError: … AccessDenied
Credentials in s3_access_key_id / s3_secret_access_key don't match the bucket on your account. Rotate the key from Profile → Storage → Rotate Key and update your config.
StorageError: … InvalidAccessKeyId
The access key no longer exists. Someone (maybe you) already rotated it. Rotate again to get a fresh pair.
Slow or stalled shard upload
Check your upstream bandwidth. The SDK prints per-file progress to stderr.
Submission
ValidationError: No shard zip files found in './shards'
shards_dir must contain at least one *.zip. The filename pattern is free-form — shard_0.zip, part-01.zip, anything with a .zip suffix works.
ValidationError: shards_dir is not a directory
Typo or wrong path — confirm Path(shards_dir).is_dir() locally first.
ValidationError: model_checkpoint must be a .pt file
The platform enforces exactly one .pt in model/. Rename or convert your checkpoint before passing it.
HTTP 400: Folder not found in your S3 bucket: "/jobs/foo/scripts"
The platform re-checks every path when you submit. This usually means an upload failed silently earlier: re-run rt_submit or inspect the bucket with sdk.storage.list("jobs/foo/").
HTTP 400: Shard count (5) does not match worker count (3)
You passed explicit worker_ids=[...] with a different length than the shard count. Either upload fewer shards or pass the right number of workers. When you omit worker_ids and let the platform select, the platform matches the worker count to your shard count.
Source Extraction
ValueError: Could not extract source of 'MyModel'
Happens in some notebook kernels where torch patches inspect. Workarounds: save the class to a .py file and set ModelConfig(model_class="my_module.MyModel"); or restart the kernel before importing torch and define the class first.
NameError: name 'nn' is not defined (server-side)
Imports live in a different cell from the class. Consolidate them into the same cell and resubmit. Applies to model=, executor=, persistor=.
NameError: name 'torch' is not defined on the worker
Same fix — put import torch in the same cell as your class.
Network / Infrastructure
ResonTechError: Cannot reach <base_url>
The platform is down or your network blocks it. Try the same URL in a browser.
Workers can't read your shards (403)
This is on our side: contact Support with the job id.
Uploads fail with InvalidRequest: The Content-Md5 you specified was invalid
Rare boto3 regression on old versions. Upgrade: pip install -U boto3 (≥ 1.34 required).
Jupyter / Notebook Issues
ModuleNotFoundError: No module named 'resontech'
The SDK is not visible to the Python the notebook kernel is running. Compare sys.executable inside the notebook against the Python that your SDK was installed into — they need to match. The example notebooks call sys.executable when wiring up dependencies to avoid this mismatch.
Where Do I See the Real Error?
job.dashboard_url) is the source of truth for runtime errors. Worker logs, training stdout, Python tracebacks — they all end up there. The SDK only surfaces errors from the submission pipeline itself.