Training-Harness (ACO, Multi-Fidelity), Prüfstand-Benchmark, Agenten-README

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

backend/fake_agents.py

@@ -287,3 +287,59 @@ async def respond(agent_key: str, prompt: str, capabilities: str) -> tuple[int,
     if _WELT is None:
         _WELT = Welt()
     return _WELT.respond(agent_key, prompt, capabilities)
+
+
+def aktivieren(welt: Welt, setattr_fn=setattr) -> None:
+    """Alle Patches für einen Fake-E2E-Lauf (run_agent überall, Tempo-Bremsen raus,
+    Text-Identitäts-Embedding). pytest übergibt monkeypatch.setattr (auto-Rollback);
+    train_f0 nutzt den Default — der Prozess stirbt nach dem Lauf sowieso."""
+    import asyncio
+
+    import agents
+    import blocks
+    import board_artefacts as ba
+    import board_inventory as bi
+    import guide
+    import guide_board
+    import kanban
+    import pipeline
+    import qa
+    import repair
+
+    async def fake_run_agent(agent_key, prompt, timeout, provider="claude", role="fast",
+                             capabilities="none", lane="batch", scope=None, on_line=None, label=""):
+        return welt.respond(agent_key, prompt, capabilities)
+
+    for mod in (agents, pipeline, blocks, guide, repair):
+        setattr_fn(mod, "run_agent", fake_run_agent)
+    setattr_fn(blocks, "CONSENSUS_GRACE", 0)
+    setattr_fn(bi, "_QA_GATE_POLL", 0.05)
+    setattr_fn(kanban, "RETRY_BACKOFF", 0.05)
+    setattr_fn(guide_board, "READABILITY_ACTIVE", False)
+    setattr_fn(bi, "_ingest_lock", asyncio.Lock())
+
+    class _FakeEmb:  # identischer Text → cos 1.0, sonst 0.0 (deterministisch, ohne Modell)
+        @staticmethod
+        def available():
+            return True
+
+        @staticmethod
+        def embed(texts):
+            import numpy as np
+            uniq = {t: k for k, t in enumerate(dict.fromkeys(texts))}
+            arr = np.zeros((len(texts), max(len(uniq), 1)))
+            for r, t in enumerate(texts):
+                arr[r, uniq[t]] = 1.0
+            return arr
+
+        @staticmethod
+        def embed_sims(texts):
+            arr = _FakeEmb.embed(texts)
+            return arr @ arr.T
+
+    for mod in (blocks, ba, qa):
+        setattr_fn(mod, "embedding", _FakeEmb)
+
+    async def emb_ok(flow):  # Board-1-Vektorpfade aus — Judge-Wellen reichen
+        return False
+    setattr_fn(bi, "_emb_ok", emb_ok)