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2 changes: 1 addition & 1 deletion resources_servers/critpt/configs/critpt.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -3,7 +3,7 @@ critpt_resources_server:
critpt:
entrypoint: app.py
domain: other
api_key: ${artificial_analysis_api_key}
api_key: ${oc.select:artificial_analysis_api_key,null}
verified: false
description: Research-level physics problems scored by the Artificial Analysis API
value: Evaluate model performance on research-level physics reasoning
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22 changes: 22 additions & 0 deletions responses_api_agents/critpt_agent/README.md
Original file line number Diff line number Diff line change
@@ -0,0 +1,22 @@
# CritPt Agent

Custom two-turn agent for the CritPt benchmark (research-level physics problems). For each problem it:

1. **Turn 1 — solve:** sends the problem to the model and collects its reasoning and conclusion.
2. **Turn 2 — fill the template:** strips the Turn 1 thinking blocks (`<think>` / `<thinking>`), then asks
the model to populate the problem's `code_template` using the Turn 1 conclusion as context (the Turn 2
prompt instructs the model not to reason again).

The accumulated Turn 2 output is submitted to the CritPt resources server's `/verify`, which scores it via
the Artificial Analysis API.

## Configuration

- `resources_server`: the CritPt resources server instance to seed sessions and verify against
- `model_server`: the model server used for generation
- `turn2_prompt_fpath`: the Turn 2 user-prompt template filled with the problem's `code_template`
(e.g. `benchmarks/critpt/prompts/turn2.yaml`)

The full wiring (resources server + this agent + example dataset) lives in
`resources_servers/critpt/configs/critpt.yaml`; the benchmark dataset is narrowed in
`benchmarks/critpt/config.yaml`.
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