feat: learn framework architecture incompatibilities

modelhub_submmit_api/README.md

@@ -23,6 +23,7 @@ It currently supports:
 - `history_stats.py`: online history aggregation, ranking, and warnings
 - `candidate_preflight.py`: deterministic repository, memory, context, and compatibility gates
 - `failure_taxonomy.py`: deterministic/platform/semantic failure routing
+- `architecture_compatibility.py`: exact architecture identities and learned compatibility keys
 - `llm_classifier.py`: offline-only experimental ambiguity-analysis helper
 - `template_selector.py`: template lookup and GPU normalization
 - `task_registry.py`: task-type and framework selection rules
@@ -93,6 +94,11 @@ bash run_poll.sh --dry-run
   validation and a confidence score at least 10% above the best incumbent.
 - Five consecutive local failures pause a GPU/framework pair for 12 hours; a
   sub-20% rate over the latest 20 terminal tasks pauses it for 6 hours.
+- An explicit "framework does not support this model/architecture" failure learns
+  a 30-day GPU + framework + task + architecture block. Architecture identity
+  comes from candidate `config.json` (`architectures`, with `model_type` only as
+  fallback), never from repository names. A newer success clears the block, and
+  generic unsupported backend/operator messages cannot create one.
 - A strategy generation lasts exactly 200 platform-accepted submissions. Rejected API calls and
   duplicates do not advance it. The next cycle refreshes platform history before submitting again.
 - Strategy state is stored in `.modelhub_state/gpu_strategy.json`; a generation never recalculates