equivalence_llm_judge:
  resources_servers:
    equivalence_llm_judge:
      entrypoint: app.py
      judge_model_server:
        type: responses_api_models
        name: policy_model
      judge_responses_create_params:
        input: []
      judge_prompt_template_fpath: prompt_templates/equivalence_llm_judge.txt
      # Concurrency and rate limiting configuration
      judge_endpoint_max_concurrency: 64 # Reduced from 64 to avoid rate limits
      judge_system_message: null
      judge_equal_label: "[[A=B]]"
      judge_not_equal_label: "[[A!=B]]"
      
      # Optional regex to extract question from the last user message. The LAST
      # match is used. If capture groups exist, the first non-empty group is
      # returned; otherwise, the entire last match is used.
      # Example: "^Question:\\s*(.*)$"
      question_extract_regex: null
      
      # Optional regex to extract the generated response from the last assistant message.
      # The LAST match is used. If capture groups exist, the first non-empty
      # group is returned; otherwise, the entire last match is used.
      # Example: "^Answer:\\s*(.*)$"
      response_extract_regex: null
      msg_extraction_failure: "[NO VALID ANSWER EXTRACTED]"
      
      # Swap check: Run second judge pass with swapped expected/generated to detect positional bias
      check_twice_swap: false
      # Reward when the second (swap) pass fails; default 0.0, can be -1.0
      reward_if_swap_fails: 0.0
      
      # ========================================================================
      # Per-Record Regex Features (OpenQA support)
      # ========================================================================
      # These features enable mixed datasets with different answer formats.
      # They only activate when template_metadata.output_regex is present.
      # Safe to enable by default - falls back to response_extract_regex when
      # no per-record regex is present.
      
      # [NEW] Enable per-record regex override from template_metadata.output_regex
      use_per_record_regex: true
      
      # --- The following features ONLY work when use_per_record_regex=true ---
      
      # [NEW] Skip regex extraction when expected_answer length exceeds this threshold.
      # When skipped, the full generation is shown to judge instead of extracting.
      # Only applies when per-record regex is present. Set to null to disable.
      extraction_length_threshold: null
      
      # [NEW] If true, when first pass fails, retry with full generation (no regex) for partial credit.
      # Helps recover from regex extraction failures. Only activates when per-record regex exists.
      check_full_generation_on_fail: false
      
      # [NEW] Reward when full generation check succeeds after first pass fails.
      # Default 0.5 (partial credit). Set to 1.0 for full credit or 0.0 to ignore.
      reward_if_full_generation_succeeds: 0.0
      domain: knowledge
      verified: false
      description: Short answer questions with LLM-as-a-judge
      value: Improve knowledge-related benchmarks like GPQA / HLE
equivalence_llm_judge_simple_agent:
  responses_api_agents:
    simple_agent:
      entrypoint: app.py
      resources_server:
        type: resources_servers
        name: equivalence_llm_judge
      model_server:
        type: responses_api_models
        name: policy_model
      datasets:
      - name: example
        type: example
        license: "TBD"
        jsonl_fpath: resources_servers/equivalence_llm_judge/data/example.jsonl
      - name: example_openqa
        type: example
        license: "TBD"
        jsonl_fpath: resources_servers/equivalence_llm_judge/data/example_openqa.jsonl
      - name: train
        type: example
        license: Apache 2.0
        jsonl_fpath: resources_servers/equivalence_llm_judge/data/train.jsonl
        huggingface_identifier:
          repo_id: nvidia/Nemotron-RL-knowledge-openQA