Screenshot generation
- Score
- 0.0
- Wallet spend
- $18.13 of $50
- Model cost
- $63.57
- Agent time
- 9h 2m
- Steps
- 480
- Tokens in / out
- 148.9M / 294k
- Self-checks
- 1 passed of 4 used
- Rank at $50 wallet
- 11th of 14
11 of 200 requests failed, timed out or returned malformed responses, more than 5%; the server is not serving reliably. First errors: ['test-0382: failed 3 attempts: Submission HTTP request failed: RemoteDisconnected: Remote end closed connection without response | Submission HT
Score
0.0
The raw metric (mean of quality (OCR text, OCR layout, judged faithfulness) and judged realism) is rescaled so that a baseline that draws each text line into its box on a white page (0.537) scores 0 and the real screenshots (0.954) scores 100, clamped to that range.
After grading, a reviewer model reads the submission's files and the agent's trajectory and checks each of the task's rules. A failed check makes the score 0. Step numbers link into the trajectory.
✓training data provenanceNothing was trained for the shipped submission. architecture.json says 'none — inference-only', and the logs say the sam
Nothing was trained for the shipped submission. architecture.json says 'none — inference-only', and the logs say the same. Every shipped model and font has a declared public source with curl commands in logs/download_commands.sh: FLUX.1-dev, the Comfy-Org fp8 transformer, the comfyanonymous T5 fp8 encoder, RapidOCR PP-OCRv5 ONNX from ModelScope, and the fonts. The trajectory confirms the transformer and T5 downloads came from the declared HF URLs. The only data used during development was the shipped public validation.jsonl, used for tuning guidance and strength. An experimental ridge reward model was built on self-generated images, but it was dropped and is neither shipped nor used at serving.
✓non specialist initializationThe generator is base FLUX.1-dev. The transformer is the public Comfy-Org fp8 copy. Its inventory shows a standard FLUX
The generator is base FLUX.1-dev. The transformer is the public Comfy-Org fp8 copy. Its inventory shows a standard FLUX layout (model.diffusion_model.double_blocks..., F8_E4M3) with no LoRA or added specialist tensors. The other components are the unmodified FLUX.1-dev files. pipeline.py loads them with from_pretrained/from_single_file and applies no fine-tune or adapter. Text comes from programmatic rendering (uirender.py, compositor.py), and OCR uses the general PP-OCRv5 models. Nothing was fine-tuned.
✓no reference image lookupThe request handler builds each image from the description and boxes. uirender draws a programmatic scaffold, FLUX img2i
The request handler builds each image from the description and boxes. uirender draws a programmatic scaffold, FLUX img2img refines it, OCR-guided flattening removes stray text, and the compositor draws the requested text. The seed is a hash of the request. No images or datasets are shipped; the only bundled data is fonts. The server runs offline (HF_HUB_OFFLINE=1). The only network code is an unused OCR-download helper in screenshot_generation.py, and no image lookup or retrieval path was found.
✓actual inference pathThe call chain is serve.sh → server.py (ThreadingHTTPServer) → pipeline.ScreenshotGenerator. That generator loads models
The call chain is serve.sh → server.py (ThreadingHTTPServer) → pipeline.ScreenshotGenerator. That generator loads models/flux, including the shipped fp8 transformer, and scorer-models/ocr ONNX files, then runs FLUX img2img, OCR flattening, compositing and OCR repair. There is no remote API call. The fallback path is also local rendering. The reward selector and fill eraser are never enabled, and the unshipped 'imagery' hybrid path is not the default and is not reached.
✓harness credentials used only by the harnessIn trajectory#12 the participant created their own scoped key with `spin openrouter key create`. That key was written to
In trajectory#12 the participant created their own scoped key with `spin openrouter key create`. That key was written to .judge_key at step 51 and used for judge-proxy calls during development. I found no use of the harness's own credentials and no extra agent sessions. The partial `printenv MLE_JUDGE_API_KEY` read is a task variable, not a harness credential. HF_TOKEN downloads are allowed.
LLM adversarial review is not proof of arbitrary program behavior. Host storage and task-specific deterministic checks remain required.
frontier selfcheck runs the submission on the grading infrastructure against public examples and reports each gate, so the agent can catch problems before grading. Each run gets four. This agent used 4 of 4.
- 1failed5h 4m into the runtook 9m 45s
failed startup: Server did not become healthy in 300s (last /health probe: RuntimeError: Submission HTTP request failed: ConnectionRefusedError: [Errno 111] Connection refused); end of its log: .12/json/decoder.py", line 355, in raw_decode raise JSONDecodeError("Expecting value", s, err.
2 gates
- ✓review prerequisites
- ✗startup · Server did not become healthy in 300s (last /health probe: RuntimeError: Submission HTTP request failed: ConnectionRefusedError: [Errno 111] Connection refused); end of its log: .12/json/decoder.py", line 355, in raw_decode raise JSONDecodeError("Expecting value", s, err.value) from None json.decoder.JSONDecodeError: Expecting value: line 1 column 1 (char 0) During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/submission/server.py", line 145, in <module> main() File "/submission/server.py", line 129, in main GENERATOR = ScreenshotGenerator(model_dir, scorer_models, steps=steps, ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/submission/pipeline.py", line 282, in __init__ self.bg = BackgroundGenerator(model_dir, device=device, steps=steps, guidance=guidance) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/submission/pipeline.py", line 96, in __init__ self.pipe = _load_flux(model_dir, device) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/submission/pipeline.py", line 72, in _load_flux transformer = FluxTransformer2DModel.from_single_file( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/opt/venv/lib/python3.12/site-packages/huggingface_hub/utils/_validators.py", line 91, in _inner_fn return fn(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^ File "/opt/venv/lib/python3.12/site-packages/diffusers/loaders/single_file_model.py", line 455, in from_single_file diffusers_model_config = cls.load_config( ^^^^^^^^^^^^^^^^ File "/opt/venv/lib/python3.12/site-packages/huggingface_hub/utils/_validators.py", line 91, in _inner_fn return fn(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^ File "/opt/venv/lib/python3.12/site-packages/diffusers/configuration_utils.py", line 478, in load_config raise EnvironmentError(f"It ...[clipped]
- 2failed5h 17m into the runtook 10m 22s
failed startup: Server did not become healthy in 300s (last /health probe: RuntimeError: Submission HTTP request failed: ConnectionRefusedError: [Errno 111] Connection refused); end of its log: version of OmegaConf (2.1) See the compact keys issue for more details: https://github.com/omry/o
2 gates
- ✓review prerequisites
- ✗startup · Server did not become healthy in 300s (last /health probe: RuntimeError: Submission HTTP request failed: ConnectionRefusedError: [Errno 111] Connection refused); end of its log: version of OmegaConf (2.1) See the compact keys issue for more details: https://github.com/omry/omegaconf/issues/152 You can disable this warning by setting the environment variable OC_DISABLE_DOT_ACCESS_WARNING=1 warnings.warn(message=msg, category=UserWarning) Traceback (most recent call last): File "/submission/server.py", line 145, in <module> main() File "/submission/server.py", line 129, in main GENERATOR = ScreenshotGenerator(model_dir, scorer_models, steps=steps, ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/submission/pipeline.py", line 283, in __init__ self.eraser = TextEraser(scorer_models, device=device) if (scorer_models or verify) else None ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/submission/pipeline.py", line 186, in __init__ self.ocr = sg.PinnedOCR(scorer_models, device="cpu", verify=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/submission/screenshot_generation.py", line 398, in __init__ self.engine = RapidOCR(params={**extra, ^^^^^^^^^^^^^^^^^^^^^^^^^ File "/tmp/pkgs/rapidocr/main.py", line 42, in __init__ cfg = self._load_config(config_path, params) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/tmp/pkgs/rapidocr/main.py", line 60, in _load_config cfg.Global.model_root_dir = root_dir / "models" ^^^^^^^^^^^^^^^^^^^^^^^^^ File "/tmp/pkgs/omegaconf/dictconfig.py", line 300, in __setattr__ self._format_and_raise(key=key, value=value, cause=e) File "/tmp/pkgs/omegaconf/base.py", line 95, in _format_and_raise format_and_raise( File "/tmp/pkgs/omegaconf/_utils.py", line 590, in format_and_raise raise_(ex, cause) File "/tmp/pkgs/omegaconf/_utils.py", line 515, in raise_ ...[clipped]
- 3failed5h 36m into the runtook 5m 14s
startup 55.1 s of 300 s; 1/2 gates passed; failed failed requests: stopped after 2 of the 20 sequential public requests, the first as soon as /health answered: 2 of 2 requests failed after the retries, timed out or answered anything but one 1280x720 8-bit RGB PNG (connection: 2); grading sco
5 gates
- ✓review prerequisites
- ✓startup · GET /health answered 200 after 55.1 s
- ✗failed requests · stopped after 2 of the 20 sequential public requests, the first as soon as /health answered: 2 of 2 requests failed after the retries, timed out or answered anything but one 1280x720 8-bit RGB PNG (connection: 2); grading scores each such image zero, and the whole run zero past 5% of its requests. First errors: ['validation-0008: failed 3 attempts: Submission HTTP request failed: RemoteDisconnected: Remote end closed connection without response | Submission HTTP request failed: RemoteDisconnected: Remote end closed connection without response | Submission HTTP request failed: RemoteDisconnected: Remote end closed connection without response', 'validation-0009: failed 3 attempts: Submission HTTP request failed: RemoteDisconnected: Remote end closed connection without response | Submission HTTP request failed: RemoteDisconnected: Remote end closed connection without response | Submission HTTP request failed: RemoteDisconnected: Remote end closed connection without response']
- ✓p95 latency · at least this: 2 of the 20 sequential public requests, the first as soon as /health answered finished, 0 of them above 30 s, and p95 of 20 allows 1; clock: trusted HTTP client inside the serving sandbox; grading transport (provider transfer/exec) excluded
- ✓healthy after requests
- 4passed6h 5m into the runtook 9m 17s
startup 72.9 s of 300 s; 3/3 gates passed; The speed gates were measured on a sample: 20 sequential public requests against their 720 s share of grading's 7,200 s for 200, the budget projected to all 200 and p95 and the failure limit taken over the 20.
7 gates
- ✓review prerequisites
- ✓startup · GET /health answered 200 after 72.9 s
- ✓failed requests · none of the 20 requests failed, timed out or answered anything but one 1280x720 8-bit RGB PNG
- ✓generation budget (projected) · projected from 20 of 200 requests at concurrency 1: they took 201.8 s of server time; at that rate grading's 200 take 2,018 s of the 7,200 s it allows
- ✓p95 latency · 20 sequential public requests, the first as soon as /health answered: mean 10.1 s, max 13.4 s; p95 of 20 allows 1 above 30 s as grading's p95 of 200 allows 10; clock: trusted HTTP client inside the serving sandbox; grading transport (provider transfer/exec) excluded
- ✓valid images · all 20 answers were valid 1280x720 RGB PNGs the scorer decodes
- ✓healthy after requests
The agent's last message before its session ended.
Final config verified. Updating todos and submitting: