Bump agent-eval to 0.1.51 and litellm to 1.88.1 (sync cost map to v1.88.1)#154
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agent-eval 0.1.51 (agent-eval#84) registers the litellm v1.88.1 price map so submissions can be priced against newer models. But that is not sufficient on its own: agenteval.log.compute_model_cost prices each call via litellm.cost_per_token(usage_object=...), which resolves the model's provider from the installed litellm's model registry, not from the registered price map. litellm 1.82.3 does not know gemini-3.5-flash, so cost_per_token raises "LLM Provider NOT provided", and compute_model_cost then nulls the entire task cost. Bumping litellm to 1.88.1 lets provider resolution succeed. Both pins must move together (cf. #144, which bumped both "to support scoring for additional models"). Bumps astabench version to 0.5.4. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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dirkraft
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Jun 17, 2026
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What
agent-eval[leaderboard]==0.1.50→==0.1.51litellm==1.82.3→==1.88.1astabenchversion0.5.3→0.5.4, plus a CHANGELOG entryWhy both pins must move together
Cost calculation lives entirely in agent-eval (asta-bench has no cost code), so it's natural to ask why asta-bench's
litellmpin needs to move at all. The reason: agent-eval'sagenteval.log.compute_model_costprices each model call vialitellm.cost_per_token(model=..., usage_object=...), and that function resolves the model's provider from the installed litellm's built-in model registry — which is independent of the price map that agent-eval#84 registers viaprep_litellm_cost_map().So registering the v1.88.1 price map (what agent-eval 0.1.51 does) is necessary but not sufficient. A/B test with the same v1.88.1 map registered, varying only the installed litellm:
model_costdictgpt-5.5-2026-04-23gemini-3.5-flashBadRequestError: LLM Provider NOT provided … model=gemini-3.5-flashWhen
cost_per_tokenraises,compute_model_costsetstotal_cost = Noneand breaks, nulling the whole task's cost. A real submission that made gemini-3.5-flash calls therefore published to the leaderboard with a null DS_1000 cost under litellm 1.82.3, and a correct non-null cost under 1.88.1.This matches prior art: #144 bumped agent-eval and litellm together "to support scoring for additional models", while agent-eval-only bumps that added no new models (#146, #147) left the litellm pin alone. agent-eval carries the cost-map SHA (in
agenteval/cli.py:prep_litellm_cost_map); asta-bench carries no cost-map of its own, so this is purely a dependency-pin bump.Validation
uv pip compile pyproject.tomlresolves cleanly with the new pins (agent-eval==0.1.51,litellm==1.88.1,inspect-ai==0.3.203; no lockfile to update).astabench score/lb publish/lb viewall succeed, and a previously cost-null submission (usedgemini-3.5-flash) now scores a non-null DS_1000 cost.🤖 Generated with Claude Code