SaylorTwift HF Staff
Switch sandboxes to Harbor hf-sandbox backend; add pinned task prep with docker_image patch; dataset discovery via prompt_rows()
a7525f2 verified Download serve_env.sh from SaylorTwift/lfm-opencode-lora-rl-code: direct link, hf CLI and curl.
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https://huggingface.co/SaylorTwift/lfm-opencode-lora-rl-code/resolve/main/serve_env.sh
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curl -L -o serve_env.sh https://huggingface.co/SaylorTwift/lfm-opencode-lora-rl-code/resolve/main/serve_env.sh
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| # OpenEnv Harbor environment server: Task API + capture proxy + web UI. | |
| # Sandboxes are HF Sandboxes (Harbor's hf-sandbox backend: each rollout boots an | |
| # HF Jobs cpu-basic machine running the task's prebuilt image). Only HF_TOKEN is | |
| # needed — no Daytona/E2B account. | |
| # | |
| # Concurrency and capture settings are env vars, not CLI flags (verified against | |
| # openenv 0.10.0 and the FineEnvs production env Space). MAX_CONCURRENT_ENVS must | |
| # be >= the GRPO group size (8) or rollouts are rejected with CAPACITY_REACHED — | |
| # it also bounds how many sandbox Jobs run at once under your HF account. | |
| set -euo pipefail | |
| PREPARED="${PREPARED:-/app/prepared}" | |
| export OPENENV_DATASETS="${OPENENV_DATASETS:-$PREPARED/datasets/train,$PREPARED/datasets/test}" | |
| export MAX_CONCURRENT_ENVS="${MAX_CONCURRENT_ENVS:-8}" | |
| export OPENENV_MAX_OUTPUT_TOKENS=4096 # same cap as training + eval | |
| export OPENENV_HARBOR_REWARD_KEY="correctness,reward" | |
| # Pin the harness build so rollouts are reproducible (version from the FineEnvs Space). | |
| export OPENENV_HARBOR_AGENT_VERSIONS='{"opencode":"1.18.31"}' | |
| openenv harbor serve \ | |
| --dataset "$OPENENV_DATASETS" \ | |
| --port "${ENV_PORT:-8000}" \ | |
| --capture-port "${CAPTURE_PORT:-8100}" \ | |
| --expose gradio | |