feat: add Harbor integration#751
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bxyu-nvidia merged 18 commits intoNVIDIA-NeMo:mainfrom Mar 11, 2026
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Signed-off-by: Grace Lam <gralam@nvidia.com>
Signed-off-by: Grace Lam <gralam@nvidia.com>
Signed-off-by: Grace Lam <gralam@nvidia.com>
Signed-off-by: Grace Lam <gralam@nvidia.com>
Signed-off-by: Grace Lam <gralam@nvidia.com>
Signed-off-by: Grace Lam <gralam@nvidia.com>
Signed-off-by: Grace Lam <gralam@nvidia.com>
Signed-off-by: Grace Lam <gralam@nvidia.com>
Signed-off-by: Grace Lam <gralam@nvidia.com>
Signed-off-by: Grace Lam <gralam@nvidia.com>
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Signed-off-by: Grace Lam <gralam@nvidia.com>
Signed-off-by: Grace Lam <gralam@nvidia.com>
Signed-off-by: Grace Lam <gralam@nvidia.com>
Signed-off-by: Grace Lam <gralam@nvidia.com>
Signed-off-by: Grace Lam <gralam@nvidia.com>
Signed-off-by: Grace Lam <gralam@nvidia.com>
Signed-off-by: Grace Lam <gralam@nvidia.com>
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Have you been able to run training or reward profiling? |
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Yes, here are sample training and validation plots for an overfitting experiment. A few other team members are currently testing out the agent and/or building on top of this code. 
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bxyu-nvidia
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Mar 11, 2026
MahanFathi
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Mar 24, 2026
Adds the full Harbor agent integration in NeMo Gym for multi-turn RL training workflows, including custom agent/env wiring, rollout conversion, and operational docs. ### Scope This PR covers the full responses_api_agents/harbor_agent/ package: - app.py (Harbor job orchestration + response shaping) - utils.py (trajectory → NeMo Gym output conversion) - custom_agents/ (Terminus-2 NeMo Gym compatibility path) - custom_envs/singularity/ (HPC-oriented execution environment) - configs/harbor_agent.yaml (default agent config) - tests/test_app.py (integration/unit behavior checks) - README.md --------- Signed-off-by: Grace Lam <gralam@nvidia.com>
jsw-zorro
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Apr 7, 2026
Adds the full Harbor agent integration in NeMo Gym for multi-turn RL training workflows, including custom agent/env wiring, rollout conversion, and operational docs. ### Scope This PR covers the full responses_api_agents/harbor_agent/ package: - app.py (Harbor job orchestration + response shaping) - utils.py (trajectory → NeMo Gym output conversion) - custom_agents/ (Terminus-2 NeMo Gym compatibility path) - custom_envs/singularity/ (HPC-oriented execution environment) - configs/harbor_agent.yaml (default agent config) - tests/test_app.py (integration/unit behavior checks) - README.md --------- Signed-off-by: Grace Lam <gralam@nvidia.com>
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Adds the full Harbor agent integration in NeMo Gym for multi-turn RL training workflows, including custom agent/env wiring, rollout conversion, and operational docs.
Scope
This PR covers the full responses_api_agents/harbor_agent/ package: