feat: learn framework architecture incompatibilities

README.md

@@ -110,6 +110,19 @@ idle card does not permanently poison otherwise successful evidence.
 Candidate shortages expand the model search window; they never unlock an
 unvetted GPU or framework.
 
+Failed-task archives are also classified conservatively. When ModelHub explicitly
+says that the selected framework does not support the model or architecture, the
+runner learns an exact GPU + framework + task type + architecture block from the
+candidate repository's `config.json`. Repository names are never used as
+architecture evidence. Exact `architectures` values take priority and
+`model_type` is used only when `architectures` is absent; missing metadata does
+not create a block. Generic unsupported operators, attention backends, GPU types,
+quantization failures, and OOMs cannot enter this blacklist. A newer success for
+the same exact combination clears the block, and otherwise it expires after 30
+days. Set `MODELHUB_ARCHITECTURE_BLOCK_TTL_DAYS` to a value from 1 to 365 to
+change that window. The stats report exposes `architectureCompatibilityBlocks`
+and per-GPU/framework block counts.
+
 Before a candidate reaches the submit queue, failure-informed preflight checks
 the actual ModelScope repository structure and file sizes. Non-GGUF text
 frameworks require root-level config, weights, and tokenizer assets. The memory
@@ -253,12 +266,16 @@ and startup cleanup, then limit minus 5 for scheduled dynamic cleanup.
 Version `2026.08.12.1` protects running tasks from age-based cleanup and records
 worker-initiated stops as `policy_cancelled`, excluding them from success-rate,
 failure-cooldown, and circuit-breaker evidence.
+Version `2026.08.12.2` learns conservative, expiring GPU/framework/architecture
+compatibility blocks only from explicit ModelHub failure text, matches candidate
+`config.json` metadata instead of repository names, and lets newer success
+evidence clear stale blocks.
 
 ## Deploy
 
 Create a tag and submit the repository URL plus tag in "我的适配智能体".
 
 ```bash
-git tag agent-v19
-git push origin agent-v19
+git tag agent-v20
+git push origin agent-v20
 ```

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

modelhub_submmit_api/architecture_compatibility.py

@@ -0,0 +1,65 @@
+from __future__ import annotations
+
+from collections.abc import Iterable
+from typing import Any
+
+
+EXPLICIT_ARCHITECTURE_FAILURE_CATEGORY = "framework_architecture_unsupported"
+EXPLICIT_ARCHITECTURE_FAILURE_ACTION = "block_gpu_framework_architecture"
+EXPLICIT_ARCHITECTURE_FAILURE_REASON = "explicit_framework_model_unsupported"
+DEFAULT_ARCHITECTURE_BLOCK_TTL_DAYS = 30
+
+
+def architecture_profile(
+    model_type: Any,
+    architectures: Any,
+) -> dict[str, Any] | None:
+    """Build a stable, conservative architecture identity for feedback matching."""
+    normalized_architectures = _normalize_architectures(architectures)
+    normalized_model_type = _normalize(model_type)
+    if normalized_architectures:
+        return {
+            "matchType": "architectures",
+            "signature": "architectures:" + ",".join(normalized_architectures),
+            "architectures": normalized_architectures,
+            "modelType": normalized_model_type or None,
+        }
+    if normalized_model_type:
+        return {
+            "matchType": "model_type",
+            "signature": f"model_type:{normalized_model_type}",
+            "architectures": [],
+            "modelType": normalized_model_type,
+        }
+    return None
+
+
+def architecture_compatibility_key(
+    target_gpu: Any,
+    framework: Any,
+    task_type: Any,
+    signature: Any,
+) -> str | None:
+    parts = (
+        _normalize(target_gpu),
+        _normalize(framework),
+        _normalize(task_type),
+        _normalize(signature),
+    )
+    if not all(parts):
+        return None
+    return "|".join(parts)
+
+
+def _normalize_architectures(value: Any) -> list[str]:
+    if isinstance(value, str):
+        values: Iterable[Any] = [value]
+    elif isinstance(value, (list, tuple, set)):
+        values = value
+    else:
+        values = []
+    return sorted({_normalize(item) for item in values if _normalize(item)})
+
+
+def _normalize(value: Any) -> str:
+    return str(value or "").strip().casefold()

modelhub_submmit_api/candidate_preflight.py

@@ -8,6 +8,7 @@ from dataclasses import dataclass
 from datetime import timedelta
 from typing import Any
 
+from architecture_compatibility import architecture_compatibility_key, architecture_profile
 from llm_classifier import LLMAssistedClassifier
 from models import ModelInspection
 from common import parse_datetime, utc_now
@@ -150,10 +151,16 @@ class CandidatePreflightAdvisor:
         self._llm_blocks = 0
         self._context_clamps = 0
         self._ambiguous = 0
+        self._architecture_blocks_applied = 0
         self._feedback_stats: dict[str, Any] = {}
+        self._architecture_compatibility_blocks: dict[str, dict[str, Any]] = {}
 
     def set_feedback_stats(self, report: dict[str, Any] | None) -> None:
         self._feedback_stats = report if isinstance(report, dict) else {}
+        raw_blocks = self._feedback_stats.get("architectureCompatibilityBlocks") or {}
+        self._architecture_compatibility_blocks = (
+            raw_blocks if isinstance(raw_blocks, dict) else {}
+        )
         for gpu, value in (self._feedback_stats.get("observedGpuMemoryGiB") or {}).items():
             try:
                 memory_gib = float(value)
@@ -190,6 +197,24 @@ class CandidatePreflightAdvisor:
         with self._lock:
             self._assessed += 1
 
+        learned_block = self._matching_architecture_block(
+            inspection=inspection,
+            target_gpu=target_gpu,
+            framework=framework,
+            task_type=task_type,
+        )
+        if learned_block is not None:
+            metadata["architectureCompatibilityBlock"] = learned_block
+            with self._lock:
+                self._architecture_blocks_applied += 1
+            return self._hard_block(
+                config_params,
+                "preflight_learned_architecture_incompatible",
+                warnings,
+                ambiguous,
+                metadata,
+            )
+
         # Empty file_paths means an injected/test inspection lacks structural
         # metadata. Real discoveries with an empty tree already fail the weight
         # compatibility gate, so do not make this test/fallback state a blocker.
@@ -389,6 +414,33 @@ class CandidatePreflightAdvisor:
             metadata=metadata,
         )
 
+    def _matching_architecture_block(
+        self,
+        *,
+        inspection: ModelInspection,
+        target_gpu: str,
+        framework: str,
+        task_type: str,
+    ) -> dict[str, Any] | None:
+        profile = architecture_profile(inspection.model_type, inspection.architectures)
+        if profile is None:
+            return None
+        key = architecture_compatibility_key(
+            target_gpu,
+            framework,
+            task_type,
+            profile["signature"],
+        )
+        if key is None:
+            return None
+        block = self._architecture_compatibility_blocks.get(key)
+        if not isinstance(block, dict):
+            return None
+        expires_at = parse_datetime(block.get("expiresAt"))
+        if expires_at is None or expires_at <= utc_now():
+            return None
+        return dict(block)
+
     def summary(self) -> dict[str, Any]:
         with self._lock:
             summary = {
@@ -397,6 +449,10 @@ class CandidatePreflightAdvisor:
                 "hardBlocks": self._hard_blocks,
                 "llmBlocks": self._llm_blocks,
                 "ambiguousCandidates": self._ambiguous,
+                "architectureCompatibilityBlocksLoaded": len(
+                    self._architecture_compatibility_blocks
+                ),
+                "architectureCompatibilityBlocksApplied": self._architecture_blocks_applied,
                 "contextLengthClamps": self._context_clamps,
                 "knownGpuMemoryGiB": dict(self.gpu_memory_gib),
                 "gpuMemoryEvidence": dict(self.gpu_memory_evidence),

modelhub_submmit_api/failure_log_inspector.py

@@ -18,7 +18,8 @@ MAX_ERROR_REPORT_BYTES = 1_000_000
 ERROR_LINE_PATTERN = re.compile(
     r"(?:\b(?:[A-Za-z_]*(?:Error|Exception)|PREFLIGHT_[A-Z_]+|OOM)\b|"
     r"out of memory|not supported|unsupported|does not recognize|cannot|can.t|"
-    r"not found|no such file|failed to|invalid|traceback|找不到空闲卡)",
+    r"not found|no such file|failed to|invalid|traceback|"
+    r"找不到空闲卡|不支持|暂不支持|不兼容|请换用|请更换)",
     re.IGNORECASE,
 )
 
@@ -74,10 +75,14 @@ def classify_failure_archive(
 
     error_lines = _extract_error_lines(runtime_log)
     report_code = str(report.get("code") or "").strip() or None
-    classification = classify_failure_report(report_code, error_lines)
+    suggestion = str(report.get("suggestion") or "")[:500] or None
+    classification_inputs = [*error_lines]
+    if suggestion:
+        classification_inputs.append(suggestion)
+    classification = classify_failure_report(report_code, classification_inputs)
     result: dict[str, Any] = {
         "failureCode": report_code,
-        "failureSuggestion": str(report.get("suggestion") or "")[:500] or None,
+        "failureSuggestion": suggestion,
         "failureCategory": classification.category,
         "failureScope": classification.scope,
         "failureAction": classification.action,

modelhub_submmit_api/failure_taxonomy.py

@@ -4,6 +4,12 @@ import re
 from dataclasses import asdict, dataclass
 from typing import Iterable
 
+from architecture_compatibility import (
+    EXPLICIT_ARCHITECTURE_FAILURE_ACTION,
+    EXPLICIT_ARCHITECTURE_FAILURE_CATEGORY,
+    EXPLICIT_ARCHITECTURE_FAILURE_REASON,
+)
+
 
 @dataclass(frozen=True)
 class FailureClassification:
@@ -70,6 +76,42 @@ DETERMINISTIC_LOG_PATTERNS = (
     (re.compile(r"config\.json.*(?:not found|no config)|Invalid repository ID or local directory", re.I), "MODEL_FILE_NOT_FOUND"),
 )
 
+# These patterns deliberately require both framework and model/architecture
+# semantics. Generic messages such as "attention backend not supported" or
+# "GPU type not supported" must not create an architecture blacklist.
+EXPLICIT_FRAMEWORK_MODEL_UNSUPPORTED_PATTERNS = (
+    re.compile(
+        r"(?:当前|该|此)(?:推理)?框架.{0,100}(?:不支持|暂不支持|无法支持|不兼容)"
+        r".{0,100}(?:该|此|当前)?(?:模型架构|模型|架构)",
+        re.I,
+    ),
+    re.compile(
+        r"(?:该|此|当前)?(?:模型架构|模型|架构).{0,100}"
+        r"(?:不被|不受).{0,50}(?:当前|该|此)?(?:推理)?框架.{0,30}支持",
+        re.I,
+    ),
+    re.compile(
+        r"\b(?:this|the|current)\s+framework\b.{0,100}"
+        r"\b(?:does\s+not|doesn't|cannot|can't)\s+support\b.{0,100}"
+        r"\b(?:model|model\s+architecture|architecture)\b",
+        re.I,
+    ),
+    re.compile(
+        r"\b(?:model|model\s+architecture|architecture)\b.{0,100}"
+        r"\b(?:is\s+)?not\s+supported\s+by\b.{0,80}\bframework\b",
+        re.I,
+    ),
+)
+
+MODEL_NOT_SUPPORTED_SUGGESTION_PATTERNS = (
+    re.compile(r"请(?:更换|换用|使用|选择).{0,50}(?:受支持|支持的)(?:模型|模型架构)", re.I),
+    re.compile(
+        r"\b(?:please\s+)?(?:change|switch|use|choose).{0,60}"
+        r"\b(?:a\s+)?supported\s+(?:model|model\s+architecture)\b",
+        re.I,
+    ),
+)
+
 
 def classify_failure_report(report_code: str | None, log_lines: Iterable[str] = ()) -> FailureClassification:
     code = str(report_code or "").strip().upper()
@@ -93,6 +135,18 @@ def classify_failure_report(report_code: str | None, log_lines: Iterable[str] =
     for pattern, inferred_code in DETERMINISTIC_LOG_PATTERNS:
         if pattern.search(text):
             return DETERMINISTIC_POLICIES[inferred_code]
+    if any(pattern.search(text) for pattern in EXPLICIT_FRAMEWORK_MODEL_UNSUPPORTED_PATTERNS) or (
+        code == "MODEL_NOT_SUPPORTED"
+        and any(pattern.search(text) for pattern in MODEL_NOT_SUPPORTED_SUGGESTION_PATTERNS)
+    ):
+        return FailureClassification(
+            EXPLICIT_ARCHITECTURE_FAILURE_CATEGORY,
+            "model_gpu_framework",
+            EXPLICIT_ARCHITECTURE_FAILURE_ACTION,
+            True,
+            False,
+            EXPLICIT_ARCHITECTURE_FAILURE_REASON,
+        )
     if code in SEMANTIC_POLICIES:
         return SEMANTIC_POLICIES[code]
     return FailureClassification(

modelhub_submmit_api/outcome_tracker.py

@@ -3,9 +3,17 @@ from __future__ import annotations
 from collections import defaultdict
 from concurrent.futures import ThreadPoolExecutor, as_completed
 from datetime import datetime, timedelta
+import os
 from pathlib import Path
 from typing import Any
 
+from architecture_compatibility import (
+    DEFAULT_ARCHITECTURE_BLOCK_TTL_DAYS,
+    EXPLICIT_ARCHITECTURE_FAILURE_CATEGORY,
+    EXPLICIT_ARCHITECTURE_FAILURE_REASON,
+    architecture_compatibility_key,
+    architecture_profile,
+)
 from common import append_jsonl, parse_datetime, read_jsonl, update_jsonl, utc_now
 from failure_log_inspector import fetch_and_classify_failure_log
 from history_stats import classify_failure, is_failure, is_success
@@ -245,7 +253,8 @@ class OutcomeTracker:
         return failed_at >= now - timedelta(hours=max(0, int(cooldown_hours)))
 
     def get_stats_report(self) -> dict[str, Any]:
-        now = _now_iso()
+        now_datetime = utc_now()
+        now = now_datetime.isoformat()
         terminal = [r for r in self._records if r.get("outcome") in {"success", "failed"}]
 
         gpu_groups: dict[str, list[dict[str, Any]]] = defaultdict(list)
@@ -344,6 +353,17 @@ class OutcomeTracker:
                 previous = observed_gpu_memory.get(gpu)
                 observed_gpu_memory[gpu] = min(previous, memory_gib) if previous else memory_gib
 
+        architecture_block_ttl_days = _architecture_block_ttl_days()
+        architecture_blocks = _build_architecture_compatibility_blocks(
+            terminal,
+            now=now_datetime,
+            ttl_days=architecture_block_ttl_days,
+        )
+        architecture_blocks_by_gpu_framework: dict[str, int] = defaultdict(int)
+        for block in architecture_blocks.values():
+            combination = f"{block['targetGpu']}|{block['framework']}"
+            architecture_blocks_by_gpu_framework[combination] += 1
+
         return {
             "generatedAt": now,
             "totalRecords": len(self._records),
@@ -356,6 +376,12 @@ class OutcomeTracker:
             "recentCombinationStats": recent_combination_stats,
             "profileCombinationStats": profile_combination_stats,
             "recentProfileCombinationStats": recent_profile_combination_stats,
+            "architectureCompatibilityBlocks": architecture_blocks,
+            "architectureCompatibilitySummary": {
+                "activeBlockCount": len(architecture_blocks),
+                "ttlDays": architecture_block_ttl_days,
+                "byGpuFramework": dict(architecture_blocks_by_gpu_framework),
+            },
             "observedGpuMemoryGiB": observed_gpu_memory,
             "totals": _summarize(terminal),
             "warnings": warnings,
@@ -489,6 +515,118 @@ def _summarize(records: list[dict[str, Any]]) -> dict[str, Any]:
     }
 
 
+def _architecture_block_ttl_days() -> int:
+    raw = os.getenv("MODELHUB_ARCHITECTURE_BLOCK_TTL_DAYS")
+    if raw is None:
+        return DEFAULT_ARCHITECTURE_BLOCK_TTL_DAYS
+    try:
+        value = int(raw)
+    except ValueError:
+        return DEFAULT_ARCHITECTURE_BLOCK_TTL_DAYS
+    return min(365, max(1, value))
+
+
+def _build_architecture_compatibility_blocks(
+    records: list[dict[str, Any]],
+    *,
+    now: datetime,
+    ttl_days: int,
+) -> dict[str, dict[str, Any]]:
+    successes: dict[str, list[tuple[datetime, dict[str, Any]]]] = defaultdict(list)
+    failures: dict[str, list[tuple[datetime, dict[str, Any], dict[str, Any]]]] = defaultdict(list)
+    cutoff = now - timedelta(days=max(1, int(ttl_days)))
+
+    for record in records:
+        profile_data = record.get("modelProfile")
+        if not isinstance(profile_data, dict):
+            continue
+        profile = architecture_profile(
+            profile_data.get("modelType"),
+            profile_data.get("architectures"),
+        )
+        if profile is None:
+            continue
+        target_gpu = str(record.get("targetGpu") or "").strip()
+        framework = str(record.get("framework") or "").strip()
+        task_type = str(record.get("taskType") or "").strip()
+        key = architecture_compatibility_key(
+            target_gpu,
+            framework,
+            task_type,
+            profile["signature"],
+        )
+        event_time = (
+            parse_datetime(record.get("submitTime"))
+            or parse_datetime(record.get("lastSyncTime"))
+        )
+        if key is None or event_time is None:
+            continue
+        if record.get("outcome") == "success":
+            successes[key].append((event_time, record))
+            continue
+        if not _is_explicit_architecture_failure(record) or event_time < cutoff:
+            continue
+        failures[key].append((event_time, record, profile))
+
+    blocks: dict[str, dict[str, Any]] = {}
+    for key, failure_events in failures.items():
+        failure_events.sort(key=lambda item: item[0])
+        latest_failure_at, latest_failure, latest_profile = failure_events[-1]
+        success_events = successes.get(key) or []
+        latest_success_at = max((item[0] for item in success_events), default=None)
+        if latest_success_at is not None and latest_success_at >= latest_failure_at:
+            continue
+        effective_failures = [
+            item
+            for item in failure_events
+            if latest_success_at is None or item[0] > latest_success_at
+        ]
+        expires_at = latest_failure_at + timedelta(days=max(1, int(ttl_days)))
+        if expires_at <= now:
+            continue
+        blocks[key] = {
+            "targetGpu": str(latest_failure.get("targetGpu") or ""),
+            "framework": str(latest_failure.get("framework") or ""),
+            "taskType": str(latest_failure.get("taskType") or ""),
+            "matchType": latest_profile["matchType"],
+            "architectureSignature": latest_profile["signature"],
+            "architectures": latest_profile["architectures"],
+            "modelType": latest_profile["modelType"],
+            "evidenceCount": len(effective_failures),
+            "latestFailureAt": latest_failure_at.isoformat(),
+            "latestSuccessfulAt": latest_success_at.isoformat() if latest_success_at else None,
+            "expiresAt": expires_at.isoformat(),
+            "sourceTaskIds": _bounded_unique(
+                record.get("taskId") for _, record, _ in reversed(effective_failures)
+            ),
+            "sourceModelIds": _bounded_unique(
+                record.get("modelId") for _, record, _ in reversed(effective_failures)
+            ),
+        }
+    return blocks
+
+
+def _is_explicit_architecture_failure(record: dict[str, Any]) -> bool:
+    return bool(
+        record.get("outcome") == "failed"
+        and record.get("failureCategory") == EXPLICIT_ARCHITECTURE_FAILURE_CATEGORY
+        and record.get("failureDeterministic") is True
+        and record.get("failureClassificationReason") == EXPLICIT_ARCHITECTURE_FAILURE_REASON
+    )
+
+
+def _bounded_unique(values: Any, limit: int = 5) -> list[str]:
+    result: list[str] = []
+    for value in values:
+        rendered = str(value or "").strip()
+        if not rendered or rendered in result:
+            continue
+        result.append(rendered)
+        if len(result) >= limit:
+            break
+    return result
+
+
 def _is_platform_failure(record: dict[str, Any]) -> bool:
     if record.get("outcome") != "failed":
         return False

modelhub_submmit_api/poll_runner.py

@@ -428,7 +428,8 @@ def run_poll_loop(
                     f"success={totals.get('successCount', 0)} "
                     f"failed={totals.get('failureCount', 0)} "
                     f"success_rate={totals.get('successRate', 0):.3f} "
-                    f"failure_rate={totals.get('failureRate', 0):.3f}"
+                    f"failure_rate={totals.get('failureRate', 0):.3f} "
+                    f"architecture_blocks={len(stats.get('architectureCompatibilityBlocks') or {})}"
                 )
             except Exception as exc:
                 log(f"[poll] cycle={cycles} outcome_stats_error={exc}")

modelhub_submmit_api/version.py

@@ -1 +1 @@
-AGENT_VERSION = "2026.08.12.1"
+AGENT_VERSION = "2026.08.12.2"

tests/test_candidate_preflight.py

@@ -6,7 +6,7 @@ import sys
 import tempfile
 import unittest
 import zipfile
-from datetime import datetime, timezone
+from datetime import datetime, timedelta, timezone
 from pathlib import Path
 from unittest.mock import patch
 
@@ -475,6 +475,41 @@ class CandidatePreflightTests(unittest.TestCase):
         self.assertTrue(model.needs_llm)
         self.assertTrue(oom.deterministic)
 
+    def test_explicit_framework_model_error_is_deterministic_architecture_feedback(self) -> None:
+        classifier = FailureClassifier()
+        result = classify_failure_archive(
+            make_failure_archive(
+                "MODEL_NOT_SUPPORTED",
+                "",
+                "该框架不支持该模型，请换用支持的模型",
+            ),
+            llm_classifier=classifier,  # type: ignore[arg-type]
+        )
+
+        self.assertEqual("framework_architecture_unsupported", result["failureCategory"])
+        self.assertEqual("block_gpu_framework_architecture", result["failureAction"])
+        self.assertTrue(result["failureDeterministic"])
+        self.assertFalse(result["failureNeedsLlm"])
+        self.assertEqual(0, classifier.calls)
+
+    def test_generic_unsupported_backend_does_not_create_architecture_feedback(self) -> None:
+        classification = classify_failure_report(
+            "ATTENTION_NOT_SUPPORTED",
+            ["Flash attention backend is not supported on this GPU"],
+        )
+
+        self.assertEqual("attention_backend", classification.category)
+        self.assertFalse(classification.deterministic)
+
+    def test_structured_oom_takes_priority_over_architecture_wording(self) -> None:
+        classification = classify_failure_report(
+            "PREFLIGHT_OOM",
+            ["该框架不支持该模型，请换用支持的模型"],
+        )
+
+        self.assertEqual("memory_capacity", classification.category)
+        self.assertEqual("structured_oom", classification.reason)
+
     def test_failure_archive_uses_deterministic_platform_signature_without_llm(self) -> None:
         classifier = FailureClassifier()
         result = classify_failure_archive(
@@ -511,6 +546,123 @@ class CandidatePreflightTests(unittest.TestCase):
         self.assertFalse(result["failureNeedsLlm"])
         self.assertEqual(1, classifier.calls)
 
+    def test_explicit_failure_learns_exact_gpu_framework_architecture_block(self) -> None:
+        now = datetime.now(timezone.utc)
+        with tempfile.TemporaryDirectory() as temporary_dir:
+            tracker = OutcomeTracker(Path(temporary_dir) / "outcomes.jsonl")
+            tracker.record_submission(
+                "owner/source-model",
+                "Biren_166m",
+                "vllm",
+                "text-generation",
+                "task-architecture-failure",
+                (now - timedelta(minutes=5)).isoformat(),
+                model_profile={
+                    "modelType": "qwen2",
+                    "architectures": ["Qwen2ForCausalLM"],
+                },
+            )
+            tracker._records[0].update(  # noqa: SLF001
+                {
+                    "outcome": "failed",
+                    "failureCategory": "framework_architecture_unsupported",
+                    "failureAction": "block_gpu_framework_architecture",
+                    "failureDeterministic": True,
+                    "failureClassificationReason": "explicit_framework_model_unsupported",
+                }
+            )
+            report = tracker.get_stats_report()
+
+        key = "biren_166m|vllm|text-generation|architectures:qwen2forcausallm"
+        self.assertIn(key, report["architectureCompatibilityBlocks"])
+        self.assertEqual(
+            1,
+            report["architectureCompatibilitySummary"]["activeBlockCount"],
+        )
+
+        advisor = CandidatePreflightAdvisor(gpu_memory_gib={})
+        advisor.set_feedback_stats(report)
+        exact_architecture = ModelInspection(
+            repo_id="different-name/no-string-match-needed",
+            model_config={
+                "model_type": "qwen2",
+                "architectures": ["Qwen2ForCausalLM"],
+            },
+        )
+        blocked = advisor.assess(
+            inspection=exact_architecture,
+            task_type="text-generation",
+            target_gpu="Biren_166m",
+            framework="vllm",
+            config_params="",
+        )
+        other_framework = advisor.assess(
+            inspection=exact_architecture,
+            task_type="text-generation",
+            target_gpu="Biren_166m",
+            framework="mindie",
+            config_params="",
+        )
+        other_architecture = advisor.assess(
+            inspection=ModelInspection(
+                repo_id="owner/other",
+                model_config={
+                    "model_type": "qwen2",
+                    "architectures": ["Qwen2ForSequenceClassification"],
+                },
+            ),
+            task_type="text-generation",
+            target_gpu="Biren_166m",
+            framework="vllm",
+            config_params="",
+        )
+
+        self.assertFalse(blocked.allowed)
+        self.assertEqual("preflight_learned_architecture_incompatible", blocked.reason)
+        self.assertTrue(other_framework.allowed)
+        self.assertTrue(other_architecture.allowed)
+        self.assertEqual(1, advisor.summary()["architectureCompatibilityBlocksApplied"])
+
+    def test_later_success_clears_learned_architecture_block(self) -> None:
+        now = datetime.now(timezone.utc)
+        profile = {
+            "modelType": "qwen2",
+            "architectures": ["Qwen2ForCausalLM"],
+        }
+        with tempfile.TemporaryDirectory() as temporary_dir:
+            tracker = OutcomeTracker(Path(temporary_dir) / "outcomes.jsonl")
+            tracker.record_submission(
+                "owner/failed",
+                "gpu",
+                "vllm",
+                "text-generation",
+                "task-failed",
+                (now - timedelta(hours=2)).isoformat(),
+                model_profile=profile,
+            )
+            tracker._records[0].update(  # noqa: SLF001
+                {
+                    "outcome": "failed",
+                    "failureCategory": "framework_architecture_unsupported",
+                    "failureDeterministic": True,
+                    "failureClassificationReason": "explicit_framework_model_unsupported",
+                }
+            )
+            tracker.record_submission(
+                "owner/succeeded",
+                "gpu",
+                "vllm",
+                "text-generation",
+                "task-success",
+                (now - timedelta(hours=1)).isoformat(),
+                model_profile=profile,
+            )
+            tracker._records[1]["outcome"] = "success"  # noqa: SLF001
+
+            report = tracker.get_stats_report()
+
+        self.assertEqual({}, report["architectureCompatibilityBlocks"])
+
     def test_outcome_sync_enriches_failure_and_excludes_platform_fault_from_feedback(self) -> None:
         with tempfile.TemporaryDirectory() as temporary_dir:
             path = Path(temporary_dir) / "outcomes.jsonl"