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fix(learning-harness): say why the proposer had nothing, and stop hard-coding its vendor

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The meta-agent round journalled `no_proposal`. The real cause was an
authentication failure: `_model_config` hard-coded the anthropic provider
while the detector was talking to DeepSeek and no ANTHROPIC_API_KEY exists
here. The composition itself was fine -- MetaAgent constructed, evolve
started, budget $5 -- and the trace was thrown away.

`no_proposal` covered two different worlds: a proposer that considered the
facts and declined, and one that could not start at all. The journal now
carries the proposer's own reason, and the vendor comes from
`[harnessx] provider` instead of being assumed.

Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG
This commit is contained in:
Marius Ciepluch
2026-09-06 22:24:40 +02:00
co-authored by Claude Opus 5
parent 84b1ba7a72
commit cde57e4293
7 changed files with 66 additions and 12 deletions
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src/openultrasast/cli.py
+3 -3
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@@ -1369,7 +1369,7 @@ def _learning_run(args: argparse.Namespace, cases: Sequence[PairCase], taxonomy:
family=args.family,
taxonomy=taxonomy,
configs_dir=configs_dir,
proposer=_proposer(args, configs_dir, model),
proposer=_proposer(args, configs_dir, model, config.harnessx.provider),
scan_factory=factory,
model=model,
journal=journal,
@@ -1402,13 +1402,13 @@ def _label(case: PairCase, taxonomy: object) -> str:
return _family_of(case, taxonomy) # type: ignore[arg-type]
def _proposer(args: argparse.Namespace, configs_dir: Path, model: str) -> Proposer:
def _proposer(args: argparse.Namespace, configs_dir: Path, model: str, provider: str = "anthropic") -> Proposer:
"""`--proposals FILE` runs a recorded sequence offline; without it the round asks the meta-agent."""
from .learning.proposer import HarnessXProposer, Proposal, ScriptedProposer
path = getattr(args, "proposals", None)
if path is None:
return HarnessXProposer(configs_dir=configs_dir, model=model)
return HarnessXProposer(configs_dir=configs_dir, model=model, provider=provider)
rows = json.loads(Path(path).read_text(encoding="utf-8"))
return ScriptedProposer(
[