Spaces:

FineEnvs
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smoldataenv-multi-harness-opencode

Running

@@ -1,12 +1,9 @@
-FROM ghcr.io/astral-sh/uv@sha256:85d4cb1afa769a7338e095b927bee941cf5ec92266c7424b3f6c0f2748567248
-USER root
-RUN useradd -m -u 1000 user
-WORKDIR /workspace/repro
-COPY requirements-env.lock /tmp/requirements-env.lock
-RUN uv venv --python 3.12 /opt/environment && uv pip sync --python /opt/environment/bin/python --require-hashes /tmp/requirements-env.lock
-COPY bundle.tar.gz /tmp/bundle.tar.gz
-RUN python -c "import tarfile; tarfile.open('/tmp/bundle.tar.gz').extractall('/workspace/repro', filter='data')" && rm /tmp/bundle.tar.gz
-RUN chown -R user:user /workspace /opt/environment
 USER user
-ENV PYTHONUNBUFFERED=1 PYTHONPATH=/workspace/repro/hf/runtime REPRO_ROOT=/workspace/repro PORT=7860
-CMD ["/opt/environment/bin/python", "-u", "/workspace/repro/hf/runtime/opencode_space.py"]

+FROM python:3.12-slim
+RUN apt-get update && apt-get install -y --no-install-recommends git curl && rm -rf /var/lib/apt/lists/*
+WORKDIR /app
+COPY . /app
+RUN bash install.sh && useradd --create-home --uid 1000 user && chown -R user:user /app
 USER user
+ENV HOME=/home/user HF_HOME=/home/user/.cache/huggingface PYTHONUNBUFFERED=1 PORT=7860 ENABLE_WEB_INTERFACE=true
+EXPOSE 7860
+CMD ["bash", "start.sh"]

README.md CHANGED Viewed

@@ -1,7 +1,58 @@
 ---
-title: Data Agent Blackbox OpenCode Env
 sdk: docker
 app_port: 7860
 ---
-Interactive OpenEnv environment for data-agent training and evaluation.

 ---
+title: SmolDataEnv Native OpenCode
+emoji: 🧪
+colorFrom: blue
+colorTo: green
 sdk: docker
 app_port: 7860
 ---
+# SmolDataEnv: Native OpenCode
+Native OpenCode runs inside the sandbox. The server grades its answer and returns a typed token trace for AsyncGRPO.
+This directory is the complete Space source. Copy it on its own, build it locally or upload it to a Docker Space. It has no imports from the other tutorial environments.
+[Open the deployed UI](https://fineenvs-data-agent-blackbox-opencode-env.hf.space/web/) · [Space](https://huggingface.co/spaces/FineEnvs/data-agent-blackbox-opencode-env)
+## Read the code
+- [`smoldataenv_opencode/environment.py`](smoldataenv_opencode/environment.py): task execution and grading.
+- [`smoldataenv_opencode/server.py`](smoldataenv_opencode/server.py): OpenEnv server and UI.
+- [`prepare.py`](prepare.py) and [`data/`](data/): the pinned 1,000 train / 250 test tasks, with grader and split checks.
+- [`Dockerfile`](Dockerfile): exactly what the Space builds.
+## Run locally
+Use Python 3.12. From this directory:
+```bash
+uv venv --python 3.12 --seed .venv
+source .venv/bin/activate
+bash install.sh
+hf auth login
+export HF_TOKEN="$(hf auth token)"
+export DAYTONA_API_KEY="your-key"
+bash start.sh
+```
+Open **http://localhost:7860/**. It opens the UI at `/web/`; the API is at `/docs` and health at `/health`. `install.sh` installs OpenEnv from main and its environment examples from the same checkout. This server needs no GPU or TRL installation.
+For agent rollouts, set `SANDBOX_VLLM_URL` and the secret `SANDBOX_VLLM_KEY` to an inference endpoint reachable by the sandbox. Training requires engine token IDs and logprobs.
+## Deploy this folder
+```bash
+python deploy.py --repo YOUR_ORG/data-agent-blackbox-opencode-env --public
+```
+Add `HF_TOKEN` and `DAYTONA_API_KEY` as Space secrets. The uploader sends the files in this directory, without generating or swapping application code. It enables the UI and preserves an existing concurrency limit. For a new Space the limit defaults to 40; use `--concurrency` to change it. CPU Basic serves the API; actual tasks run in Daytona.
+You can test the same image locally:
+```bash
+docker build -t smoldataenv-opencode .
+docker run --rm -p 7860:7860 -e HF_TOKEN -e DAYTONA_API_KEY smoldataenv-opencode
+```
+Runtime downloads, local credentials and old deployment archives are excluded from uploads and Docker builds. Task questions and held-out answers are never bundled into the image; the pinned tasks are prepared at startup.

data/test.json ADDED Viewed

	@@ -0,0 +1,252 @@

+[
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+  {"name": "0000_340_340599_qa_1", "source": "0000/340/340599.ipynb_qa_1", "notebook": "0000/340/340599.ipynb", "difficulty": "medium", "instruction_sha256": "dd7911b3032aa469ef4f7cd9c71748c62cb560dcfc2bcc897e6111f4197f0383"},
+  {"name": "0000_340_340599_qa_3", "source": "0000/340/340599.ipynb_qa_3", "notebook": "0000/340/340599.ipynb", "difficulty": "easy", "instruction_sha256": "dac579f315382a7411af51143da96cfddafa1a68a0271d8e80e7da09a2e49d8c"},
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+  {"name": "0001_672_1672543_qa_5", "source": "0001/672/1672543.ipynb_qa_5", "notebook": "0001/672/1672543.ipynb", "difficulty": "hard", "instruction_sha256": "1ba665756c4f3fcb0d07f2abdc7a9853170e4c81642b9fff058c5bc10a127c24"},
+  {"name": "0001_696_1696691_qa_1", "source": "0001/696/1696691.ipynb_qa_1", "notebook": "0001/696/1696691.ipynb", "difficulty": "hard", "instruction_sha256": "6c14738467827b31deda06561554f1c3521fd11647a4ab5a848d26927d847787"},
+  {"name": "0001_696_1696691_qa_3", "source": "0001/696/1696691.ipynb_qa_3", "notebook": "0001/696/1696691.ipynb", "difficulty": "hard", "instruction_sha256": "3cb33e4394b6837aa9942b597b5e88f2fdb1f65ff80a1e98cfd15653ec76c8b7"},
+  {"name": "0001_727_1727043_qa_4", "source": "0001/727/1727043.ipynb_qa_4", "notebook": "0001/727/1727043.ipynb", "difficulty": "hard", "instruction_sha256": "429ffd1a334140546f178c4f4018e23e43532f13175dc7ea15684c0bd0cd3bbc"},
+  {"name": "0001_757_1757917_qa_3", "source": "0001/757/1757917.ipynb_qa_3", "notebook": "0001/757/1757917.ipynb", "difficulty": "hard", "instruction_sha256": "a27ba8c5f95a5f3526c800182637473d31ce521f96ccc7a0e7bf754ade0b8a7c"},
+  {"name": "0001_770_1770623_qa_1", "source": "0001/770/1770623.ipynb_qa_1", "notebook": "0001/770/1770623.ipynb", "difficulty": "hard", "instruction_sha256": "1f234bae8511b49bedfe4bd30176e7d1a4c31bedf2ea5cdf85f559f75559b942"},
+  {"name": "0001_875_1875067_qa_3", "source": "0001/875/1875067.ipynb_qa_3", "notebook": "0001/875/1875067.ipynb", "difficulty": "hard", "instruction_sha256": "0a7f4c30e394b577f8b0222c643047494a68d82bd0b17d859f9924a4139539c5"},
+  {"name": "0001_892_1892658_qa_3", "source": "0001/892/1892658.ipynb_qa_3", "notebook": "0001/892/1892658.ipynb", "difficulty": "hard", "instruction_sha256": "fc99f18b9f27e2c5aa143bed56acffe6e6897b68f5435c78659e456c24e0640e"},
+  {"name": "0001_893_1893978_qa_5", "source": "0001/893/1893978.ipynb_qa_5", "notebook": "0001/893/1893978.ipynb", "difficulty": "hard", "instruction_sha256": "73b861c118c1bdf4a9bf5cac14f52422f69f4412de02e3c9338552542689e31a"},
+  {"name": "0001_895_1895893_qa_2", "source": "0001/895/1895893.ipynb_qa_2", "notebook": "0001/895/1895893.ipynb", "difficulty": "hard", "instruction_sha256": "6132d4a5dcb443f53cb6d53348a1a76d56d95b9af841f88f42f9f847f934f92b"},
+  {"name": "0001_903_1903634_qa_1", "source": "0001/903/1903634.ipynb_qa_1", "notebook": "0001/903/1903634.ipynb", "difficulty": "hard", "instruction_sha256": "9943c21454817f59a1b0a64a64802d7d7d3d876a63e3bb9a8ef7a17fdcedfc80"},
+  {"name": "0001_903_1903634_qa_4", "source": "0001/903/1903634.ipynb_qa_4", "notebook": "0001/903/1903634.ipynb", "difficulty": "hard", "instruction_sha256": "bc69bbc99fe61207b27eda417f0304091e95c82f18bd8c3d69505ce0e6203456"},
+  {"name": "0001_903_1903634_qa_5", "source": "0001/903/1903634.ipynb_qa_5", "notebook": "0001/903/1903634.ipynb", "difficulty": "hard", "instruction_sha256": "dfd05c52775022a3a62f8506c5124e61d2264900a31bc742d6969f5c8da7d1a7"},
+  {"name": "0001_904_1904638_qa_1", "source": "0001/904/1904638.ipynb_qa_1", "notebook": "0001/904/1904638.ipynb", "difficulty": "hard", "instruction_sha256": "47a1a9cfe9326e2f6bfc7592637a473eb2c195fc31f0e722f3a176d60be32baf"},
+  {"name": "0001_904_1904638_qa_2", "source": "0001/904/1904638.ipynb_qa_2", "notebook": "0001/904/1904638.ipynb", "difficulty": "hard", "instruction_sha256": "69c8eedddd4580a3cb1ac73d6b93911b7e3be20aea7d8d7079fac7dae148785d"},
+  {"name": "0001_912_1912867_qa_2", "source": "0001/912/1912867.ipynb_qa_2", "notebook": "0001/912/1912867.ipynb", "difficulty": "hard", "instruction_sha256": "7d7d5fe2651b4ab7cb0f28d7f5b07fd249e4d64c136e68a4f91bd30923042925"},
+  {"name": "0001_912_1912867_qa_5", "source": "0001/912/1912867.ipynb_qa_5", "notebook": "0001/912/1912867.ipynb", "difficulty": "hard", "instruction_sha256": "03e34fcaeab8293895ab6769b24729fceae98e25c019963214c9cd56b1514de8"},
+  {"name": "0001_918_1918012_qa_1", "source": "0001/918/1918012.ipynb_qa_1", "notebook": "0001/918/1918012.ipynb", "difficulty": "hard", "instruction_sha256": "413ec54174c4fee088e32ea8fa2304eab6383ead00a0ad8b649d02c8ff19d060"},
+  {"name": "0001_922_1922748_qa_4", "source": "0001/922/1922748.ipynb_qa_4", "notebook": "0001/922/1922748.ipynb", "difficulty": "hard", "instruction_sha256": "1d0234376e455d67f95f2e112ab1e9be75814ecf85182614d60292529cca4cec"},
+  {"name": "0001_991_1991000_qa_3", "source": "0001/991/1991000.ipynb_qa_3", "notebook": "0001/991/1991000.ipynb", "difficulty": "hard", "instruction_sha256": "1cb0f2552b0eff9384273ded32b00f1a609f5840dd1ff516ee6b2820f434b55f"},
+  {"name": "0001_991_1991376_qa_1", "source": "0001/991/1991376.ipynb_qa_1", "notebook": "0001/991/1991376.ipynb", "difficulty": "hard", "instruction_sha256": "3e7e7c3a681602573090f8446187bbe6615ee1c5a043733c59b7231b075468ad"},
+  {"name": "0001_991_1991376_qa_5", "source": "0001/991/1991376.ipynb_qa_5", "notebook": "0001/991/1991376.ipynb", "difficulty": "hard", "instruction_sha256": "a0aba7aa773ec3c3352f677b70131c33083b135e3d0bd776d525a3f81ecfb435"},
+  {"name": "0002_134_2134700_qa_5", "source": "0002/134/2134700.ipynb_qa_5", "notebook": "0002/134/2134700.ipynb", "difficulty": "hard", "instruction_sha256": "d2bd38963709deb5780643df0b05fd1bb8491da390a3c0b400ae35fc8d16db54"},
+  {"name": "0002_169_2169008_qa_1", "source": "0002/169/2169008.ipynb_qa_1", "notebook": "0002/169/2169008.ipynb", "difficulty": "hard", "instruction_sha256": "1ec8adf67ef5d0bbf5bc364bbc7c51a06815f721736560d9a664997f756bf100"},
+  {"name": "0002_187_2187459_qa_3", "source": "0002/187/2187459.ipynb_qa_3", "notebook": "0002/187/2187459.ipynb", "difficulty": "hard", "instruction_sha256": "70b17eebda3078b92ef0b110633ced726155d4722af943a520dcdf021b09e645"},
+  {"name": "0002_189_2189266_qa_2", "source": "0002/189/2189266.ipynb_qa_2", "notebook": "0002/189/2189266.ipynb", "difficulty": "hard", "instruction_sha256": "57caf0bf7a5e06ccbf95d0749c7456e092cb472e32ea7d54e3ddc29795b22548"},
+  {"name": "0014_516_14516985_qa_4", "source": "0014/516/14516985.ipynb_qa_4", "notebook": "0014/516/14516985.ipynb", "difficulty": "hard", "instruction_sha256": "6097e844a6f616ec28fc8c8ddcd5defd6d794cd01c729d66ada1c2aa4a30812e"},
+  {"name": "0032_521_32521554_qa_3", "source": "0032/521/32521554.ipynb_qa_3", "notebook": "0032/521/32521554.ipynb", "difficulty": "hard", "instruction_sha256": "67a31e3f106b773fd6c1225f700f30be451668cac4a0aebebc57e2f261bb9571"},
+  {"name": "0036_284_36284344_qa_5", "source": "0036/284/36284344.ipynb_qa_5", "notebook": "0036/284/36284344.ipynb", "difficulty": "hard", "instruction_sha256": "dc64eec5ba515a04b10f692ec9a102389309c2d2015995e5de59f61645fcb49b"},
+  {"name": "0041_214_41214590_qa_4", "source": "0041/214/41214590.ipynb_qa_4", "notebook": "0041/214/41214590.ipynb", "difficulty": "hard", "instruction_sha256": "1b60982b46ee4257d89781b0d8411fd5e9de960223680028457bce8f002f2316"},
+  {"name": "0048_996_48996091_qa_5", "source": "0048/996/48996091.ipynb_qa_5", "notebook": "0048/996/48996091.ipynb", "difficulty": "hard", "instruction_sha256": "adf2ebed947e03a15c108ed522b720b068371f65629c7c9f719e2a6c877ba745"},
+  {"name": "0049_302_49302290_qa_3", "source": "0049/302/49302290.ipynb_qa_3", "notebook": "0049/302/49302290.ipynb", "difficulty": "hard", "instruction_sha256": "ba6cf04cb5182218a7bdffb662e3384bfc9cb9c38b367c37849a9eb2b42fa3b6"},
+  {"name": "0051_018_51018932_qa_4", "source": "0051/018/51018932.ipynb_qa_4", "notebook": "0051/018/51018932.ipynb", "difficulty": "hard", "instruction_sha256": "299852a89a08120ce05b91762ce1e13467107d00c3eb23ffd76c24fc5a774612"},
+  {"name": "0060_085_60085489_qa_4", "source": "0060/085/60085489.ipynb_qa_4", "notebook": "0060/085/60085489.ipynb", "difficulty": "hard", "instruction_sha256": "db2a6a0d4db73ddfce498cb4bae9542c73849ccb39fa6d43862bbee0457858c9"},
+  {"name": "0064_089_64089732_qa_5", "source": "0064/089/64089732.ipynb_qa_5", "notebook": "0064/089/64089732.ipynb", "difficulty": "hard", "instruction_sha256": "01459031a14193b4fbe987f4e4c1466488f33b4283451476e04dda4d5906aab1"},
+  {"name": "0065_262_65262139_qa_5", "source": "0065/262/65262139.ipynb_qa_5", "notebook": "0065/262/65262139.ipynb", "difficulty": "hard", "instruction_sha256": "0ab09f6bd0d928239f60bcde97931436721925aa77348c2d91ca342518cbb68e"},
+  {"name": "0075_374_75374659_qa_2", "source": "0075/374/75374659.ipynb_qa_2", "notebook": "0075/374/75374659.ipynb", "difficulty": "hard", "instruction_sha256": "3323a5edef46c2ffe235d7a7a215cfecda1601808e48ae91eabecffa13f65ab0"},
+  {"name": "0092_637_92637915_qa_2", "source": "0092/637/92637915.ipynb_qa_2", "notebook": "0092/637/92637915.ipynb", "difficulty": "hard", "instruction_sha256": "902721593434f0b3ed7435c7ac9c0c2d09799697e1aa03e4f33f3b7ab141ba53"},
+  {"name": "0096_776_96776427_qa_5", "source": "0096/776/96776427.ipynb_qa_5", "notebook": "0096/776/96776427.ipynb", "difficulty": "hard", "instruction_sha256": "cb45bd02629e73b9fc7ea3629d1300a521ec74b9bcb89392ae59e8792cc1356d"},
+  {"name": "0099_089_99089980_qa_5", "source": "0099/089/99089980.ipynb_qa_5", "notebook": "0099/089/99089980.ipynb", "difficulty": "hard", "instruction_sha256": "e934a92dd25e11ac99781af75ab5433c4c8804cfb8a4fd4ead47b9b24b954227"},
+  {"name": "0104_079_104079493_qa_4", "source": "0104/079/104079493.ipynb_qa_4", "notebook": "0104/079/104079493.ipynb", "difficulty": "hard", "instruction_sha256": "906e1a55aec2a70fa6c5310a87f36d0d6121fbce5c3ac32a4641f1c765d0c06d"},
+  {"name": "0115_735_115735943_qa_1", "source": "0115/735/115735943.ipynb_qa_1", "notebook": "0115/735/115735943.ipynb", "difficulty": "hard", "instruction_sha256": "dbfafc2ca0f02cbc4b1e07e68b62efde9450653099780475121f1304c465b269"},
+  {"name": "0117_122_117122383_qa_3", "source": "0117/122/117122383.ipynb_qa_3", "notebook": "0117/122/117122383.ipynb", "difficulty": "hard", "instruction_sha256": "bd17eea23c6cb3ae28e35ede16102611d27634015e351807154ff37fe43cb4b1"},
+  {"name": "0122_938_122938717_qa_4", "source": "0122/938/122938717.ipynb_qa_4", "notebook": "0122/938/122938717.ipynb", "difficulty": "hard", "instruction_sha256": "ba8b1221265a98d6ced0f68c49dd8fb8ea04e2afc03733b77475c3ee98ec353c"},
+  {"name": "0126_223_126223416_qa_5", "source": "0126/223/126223416.ipynb_qa_5", "notebook": "0126/223/126223416.ipynb", "difficulty": "hard", "instruction_sha256": "bf9fdef8013dfd12241731291f01a41c77d85f4f0f423f4612147d71949a74f2"},
+  {"name": "0138_500_138500445_qa_1", "source": "0138/500/138500445.ipynb_qa_1", "notebook": "0138/500/138500445.ipynb", "difficulty": "hard", "instruction_sha256": "f1ecbcaab9a48a1ab5481192443d0749968e40988ca0f7df06ffc13230ac5277"}
+]

data/train.json ADDED Viewed

The diff for this file is too large to render. See raw diff

deploy.py ADDED Viewed

	@@ -0,0 +1,68 @@

+"""Upload this standalone directory to a Docker Space."""
+import argparse
+from pathlib import Path
+from huggingface_hub import HfApi
+ROOT = Path(__file__).resolve().parent
+def main():
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument("--repo", required=True)
+    parser.add_argument("--public", action="store_true")
+    parser.add_argument("--concurrency", type=int)
+    args = parser.parse_args()
+    if args.concurrency is not None and args.concurrency < 1:
+        parser.error("Concurrency must be positive")
+    api = HfApi()
+    api.create_repo(
+        args.repo,
+        repo_type="space",
+        space_sdk="docker",
+        private=not args.public,
+        exist_ok=True,
+    )
+    variables = api.get_space_variables(args.repo)
+    concurrency = args.concurrency or (
+        int(variables["MAX_CONCURRENT_ENVS"].value)
+        if "MAX_CONCURRENT_ENVS" in variables
+        else 40
+    )
+    api.add_space_variable(args.repo, "MAX_CONCURRENT_ENVS", str(concurrency))
+    api.add_space_variable(args.repo, "ENABLE_WEB_INTERFACE", "true")
+    api.upload_folder(
+        repo_id=args.repo,
+        repo_type="space",
+        folder_path=ROOT,
+        allow_patterns=[
+            "*.py",
+            "*.json",
+            "*.toml",
+            "*.txt",
+            "*.sh",
+            "*.yaml",
+            "README.md",
+            "Dockerfile",
+            ".dockerignore",
+            ".gitignore",
+            ".gitattributes",
+        ],
+        ignore_patterns=[
+            ".deps/**",
+            ".venv/**",
+            "prepared/**",
+            ".archive/**",
+            "**/__pycache__/**",
+            "**/*.egg-info/**",
+            ".env",
+            ".git/**",
+        ],
+        commit_message="Deploy standalone SmolDataEnv Native OpenCode",
+    )
+    print(f"https://huggingface.co/spaces/{args.repo}")
+if __name__ == "__main__":
+    main()

install.sh ADDED Viewed

	@@ -0,0 +1,18 @@

+#!/usr/bin/env bash
+set -euo pipefail
+cd "$(dirname "$0")"
+mkdir -p .deps
+if [[ ! -d .deps/OpenEnv/.git ]]; then
+    git clone --depth 1 https://github.com/huggingface/OpenEnv.git .deps/OpenEnv
+else
+    git -C .deps/OpenEnv pull --ff-only origin main
+fi
+python -m pip install -e .deps/OpenEnv -r requirements.txt
+python -m pip install --no-deps -e .
+python - <<'SETUP'
+from pathlib import Path
+import site
+Path(site.getsitepackages()[0], "openenv_examples.pth").write_text(
+    str(Path(".deps/OpenEnv/envs").resolve()) + "\n"
+)
+SETUP

openenv.yaml ADDED Viewed

	@@ -0,0 +1,6 @@

+spec_version: 1
+name: smoldataenv_opencode
+type: space
+runtime: fastapi
+app: smoldataenv_opencode.server:app
+port: 7860

prepare.py ADDED Viewed

	@@ -0,0 +1,138 @@

+"""Materialize the fixed train/test tasks from corrected, pinned Harbor datasets."""
+from __future__ import annotations
+import argparse
+import hashlib
+import json
+import shutil
+from pathlib import Path
+import tomllib
+ROOT = Path(__file__).resolve().parent
+def task_rows(split):
+    return json.loads((ROOT / "data" / f"{split}.json").read_text())
+def write_json(path, data):
+    path.parent.mkdir(parents=True, exist_ok=True)
+    path.write_text(json.dumps(data, indent=2) + "\n")
+DATASETS = {
+    "train": (
+        "FineEnvs/SmolDataEnvs-harbor-train",
+        "4719635555de1666f374d847baebb500d368e493",
+    ),
+    "test": (
+        "FineEnvs/SmolDataEnvs-harbor-test",
+        "b130595b579fc6026ad5762925a9a3b40e72f5bb",
+    ),
+}
+GRADER_SHA256 = "16f906e9248fa8b7e1141939e425e88e59d52d65e98e360bbacef3720a43629f"
+def prepare(destination, sources=None):
+    import tomli_w
+    from huggingface_hub import snapshot_download
+    destination = Path(destination).resolve()
+    manifests = {}
+    for split in ("train", "test"):
+        rows = task_rows(split)
+        repo, revision = DATASETS[split]
+        source = (sources or {}).get(split)
+        if source is None:
+            source = snapshot_download(
+                repo,
+                repo_type="dataset",
+                revision=revision,
+                allow_patterns=[f"tasks/{r['name']}/*" for r in rows],
+                max_workers=16,
+            )
+        source = Path(source)
+        tasks = []
+        for row in rows:
+            folder = source / "tasks" / row["name"]
+            instruction = (folder / "instruction.md").read_bytes()
+            if hashlib.sha256(instruction).hexdigest() != row["instruction_sha256"]:
+                raise ValueError(
+                    f"Historical task instruction changed: {split}/{row['name']}"
+                )
+            grader = (folder / "tests/grader.py").read_bytes()
+            if hashlib.sha256(grader).hexdigest() != GRADER_SHA256:
+                raise ValueError(
+                    f"Expected corrected numeric-only Harbor grader: {folder}"
+                )
+            target = destination / "datasets" / split / "tasks" / row["name"]
+            target.mkdir(parents=True, exist_ok=True)
+            for rel in (
+                "instruction.md",
+                "task.toml",
+                "environment/Dockerfile",
+                "environment/pull_bucket.py",
+                "tests/grader.py",
+                "tests/test.sh",
+            ):
+                dst = target / rel
+                dst.parent.mkdir(parents=True, exist_ok=True)
+                shutil.copyfile(folder / rel, dst)
+            spec = tomllib.loads((target / "task.toml").read_text())
+            spec["environment"]["memory_mb"] = 4096
+            spec["environment"]["cpus"] = 1
+            # Cluster user IDs may not exist inside Daytona's user namespace.
+            spec["environment"].setdefault("env", {})["TAR_OPTIONS"] = "--no-same-owner"
+            (target / "task.toml").write_text(tomli_w.dumps(spec))
+            hashes = {
+                str(f.relative_to(destination / "datasets" / split)): hashlib.sha256(
+                    f.read_bytes()
+                ).hexdigest()
+                for f in sorted(target.rglob("*"))
+                if f.is_file()
+            }
+            tasks.append({**row, "file_hashes": hashes})
+        local = (sources or {}).get(split)
+        manifest = {
+            "source_dataset": repo,
+            "source_revision": None if local else revision,
+            "expected_hub_revision": revision,
+            "local_source": str(local) if local else None,
+            "task_count": len(tasks),
+            "tasks": tasks,
+        }
+        write_json(destination / f"{split}_manifest.json", manifest)
+        manifests[split] = manifest
+    train = {r["source"] for r in manifests["train"]["tasks"]}
+    test = {r["source"] for r in manifests["test"]["tasks"]}
+    notebooks = [
+        {r.get("notebook") for r in manifests[s]["tasks"]} - {None}
+        for s in ("train", "test")
+    ]
+    if train & test or notebooks[0] & notebooks[1]:
+        raise ValueError("Train/test overlap")
+    write_json(
+        destination / "ready.json",
+        {
+            "train": len(train),
+            "test": len(test),
+            "grader_sha256": GRADER_SHA256,
+            "train_test_overlap": 0,
+        },
+    )
+    return manifests
+if __name__ == "__main__":
+    p = argparse.ArgumentParser(description=__doc__)
+    p.add_argument("--output", type=Path, default=ROOT / "prepared")
+    p.add_argument("--train-source", type=Path)
+    p.add_argument("--test-source", type=Path)
+    a = p.parse_args()
+    result = prepare(
+        a.output,
+        {s: v for s, v in (("train", a.train_source), ("test", a.test_source)) if v},
+    )
+    print(json.dumps({s: m["task_count"] for s, m in result.items()}))

pyproject.toml ADDED Viewed

	@@ -0,0 +1,11 @@

+[build-system]
+requires = ["setuptools>=68"]
+build-backend = "setuptools.build_meta"
+[project]
+name = "smoldataenv-opencode"
+version = "0.1.0"
+requires-python = ">=3.12"
+[tool.setuptools.packages.find]
+include = ["smoldataenv_opencode*"]

requirements.txt ADDED Viewed

	@@ -0,0 +1,9 @@

+# OpenEnv main is installed by install.sh. No trainer or GPU packages are needed.
+harbor[daytona]>=0.22.0
+daytona>=0.203.0
+fastmcp>=2
+uvicorn[standard]
+gradio
+huggingface-hub
+math-verify
+tomli-w

smoldataenv_opencode.egg-info/SOURCES.txt ADDED Viewed

	@@ -0,0 +1,13 @@

+README.md
+pyproject.toml
+smoldataenv_opencode/__init__.py
+smoldataenv_opencode/catalog.py
+smoldataenv_opencode/client.py
+smoldataenv_opencode/daytona.py
+smoldataenv_opencode/environment.py
+smoldataenv_opencode/server.py
+smoldataenv_opencode/tasks.py
+smoldataenv_opencode.egg-info/PKG-INFO
+smoldataenv_opencode.egg-info/SOURCES.txt
+smoldataenv_opencode.egg-info/dependency_links.txt
+smoldataenv_opencode.egg-info/top_level.txt

smoldataenv_opencode.egg-info/dependency_links.txt ADDED Viewed

	@@ -0,0 +1 @@


1	+

smoldataenv_opencode.egg-info/top_level.txt ADDED Viewed

	@@ -0,0 +1 @@


1	+ smoldataenv_opencode

smoldataenv_opencode/__init__.py ADDED Viewed

File without changes

smoldataenv_opencode/catalog.py ADDED Viewed

	@@ -0,0 +1,39 @@

+"""The Task API serves names and instructions, never private verifier answers."""
+import os
+from functools import lru_cache
+from .tasks import load_tasks
+@lru_cache
+def tasks(split):
+    if split not in {"train", "test"}:
+        raise ValueError("Choose train or test")
+    return load_tasks(os.environ.get("SMOLDATA_DATA", "prepared"), split)
+def task_by_name(split, name):
+    return next(row for row in tasks(split) if row["name"] == name)
+class TaskCatalog:
+    def list_splits(self):
+        return ["train", "test"]
+    def num_tasks(self, split):
+        return len(tasks(split))
+    def get_task(self, split, index):
+        return {
+            key: value for key, value in tasks(split)[index].items() if key != "folder"
+        }
+    def get_task_range(self, split, start=None, stop=None):
+        return [
+            self.get_task(split, i)
+            for i in range(*slice(start, stop).indices(self.num_tasks(split)))
+        ]
+    def list_tasks(self, split):
+        return self.get_task_range(split)

smoldataenv_opencode/client.py ADDED Viewed

	@@ -0,0 +1,68 @@

+"""The public OpenEnv training session contract over a remote native OpenCode server."""
+from pathlib import Path
+from openenv.core.harness import (
+    ResourceSession,
+    ToolResult,
+    TrainingTrace,
+    VerifyResult,
+)
+from openenv.core.mcp_client import MCPToolClient
+class RemoteSession(ResourceSession):
+    def __init__(self, server, row, model, sampling):
+        self.client = MCPToolClient(server, message_timeout_s=1800).sync()
+        self.row, self.model, self.sampling = row, model, sampling
+        self.result = None
+    def initial_messages(self):
+        return [{"role": "user", "content": self.row["instruction"]}]
+    def list_tools(self):
+        return []
+    def call_tool(self, name, arguments):
+        return ToolResult(error="OpenCode owns its tool loop")
+    def wait_for_completion(self, timeout_s=None):
+        self.client.reset()
+        folder = Path(self.row["folder"])
+        self.result = self.client.call_tool(
+            "run_rollout",
+            split=folder.parent.parent.name,
+            task_name=folder.name,
+            model=self.model,
+            sampling=self.sampling,
+        )
+        return 0
+    def fetch_training_trace(self):
+        if self.result is None:
+            raise RuntimeError("Rollout has not completed")
+        if "capture_error" in self.result:
+            raise ValueError(self.result["capture_error"])
+        return TrainingTrace.model_validate(self.result["training_trace"])
+    def verify(self, transcript, final_state=None):
+        return VerifyResult(
+            env_reward=self.result["correctness"] if self.result else None, done=True
+        )
+    def close(self):
+        self.client.close()
+class RemoteTaskFactory:
+    def __init__(self, args, tasks, *, sampling):
+        self.args, self.sampling = args, sampling
+        self.tasks = {row["instruction"]: row for row in tasks}
+    def create(self, task, seed=None, episode_id=None):
+        return RemoteSession(
+            self.args.server,
+            self.tasks[task[-1]["content"]],
+            self.args.model,
+            self.sampling,
+        )

smoldataenv_opencode/daytona.py ADDED Viewed

	@@ -0,0 +1,144 @@

+"""Daytona implementation of the standalone OpenCode sandbox protocol."""
+from __future__ import annotations
+import math
+import os
+import shlex
+import time
+import uuid
+from functools import lru_cache
+from opencode_env.sandbox.base import ExecResult
+@lru_cache(maxsize=1)
+def client():
+    from daytona import Daytona
+    return Daytona()
+class DaytonaBgJob:
+    def __init__(self, handle, directory, pid):
+        self.handle, self.directory, self._pid = handle, directory, pid
+    @property
+    def pid(self):
+        return self._pid
+    def wait(self, timeout=None):
+        deadline = time.monotonic() + timeout if timeout is not None else float("inf")
+        while time.monotonic() < deadline:
+            if self.handle.exists(self.directory + "/exit"):
+                return int(self.handle.read_text(self.directory + "/exit").strip())
+            time.sleep(min(0.5, max(0, deadline - time.monotonic())))
+        raise TimeoutError("Background command exceeded its deadline")
+    def kill(self):
+        self.handle.exec(f"kill -TERM -- -{self.pid} 2>/dev/null || true", timeout=10)
+class DaytonaSandboxHandle:
+    def __init__(self, sandbox):
+        self._sandbox = sandbox
+        self._deleted = False
+    @property
+    def sandbox_id(self):
+        return self._sandbox.id
+    def exec(self, cmd, *, envs=None, cwd=None, timeout=60):
+        # The SDK's exec is not a shell. Quote the complete script once and let bash
+        # interpret it; neither user text nor environment values are interpolated.
+        result = self._sandbox.process.exec(
+            "bash -lc " + shlex.quote(cmd),
+            cwd=cwd,
+            env=envs,
+            timeout=max(1, math.ceil(timeout)) if timeout is not None else None,
+        )
+        code = result.exit_code
+        return ExecResult(124 if code is None else int(code), result.result or "", "")
+    def write_text(self, path, content):
+        parent = path.rsplit("/", 1)[0] or "."
+        result = self.exec("mkdir -p " + shlex.quote(parent))
+        if result.exit_code:
+            raise RuntimeError("Could not create sandbox directory")
+        self._sandbox.fs.upload_file(content.encode(), path)
+    def read_text(self, path):
+        return self._sandbox.fs.download_file(path).decode()
+    def exists(self, path):
+        return self.exec("test -e " + shlex.quote(path), timeout=15).exit_code == 0
+    def start_bg(self, cmd, *, envs=None, cwd=None):
+        directory = "/tmp/openenv-process-" + uuid.uuid4().hex
+        self.write_text(
+            directory + "/run.sh",
+            "#!/bin/bash\n(\n"
+            + cmd
+            + "\n)"
+            + "\ncode=$?\nprintf '%s' \"$code\" > "
+            + shlex.quote(directory + "/exit")
+            + "\n",
+        )
+        result = self.exec(
+            "setsid bash "
+            + shlex.quote(directory + "/run.sh")
+            + " > "
+            + shlex.quote(directory + "/output")
+            + " 2>&1 < /dev/null & echo $!",
+            envs=envs,
+            cwd=cwd,
+            timeout=15,
+        )
+        if result.exit_code:
+            raise RuntimeError("Could not launch background command")
+        return DaytonaBgJob(
+            self, directory, int(result.stdout.strip().splitlines()[-1])
+        )
+    def kill(self):
+        if not self._deleted:
+            client().delete(self._sandbox, timeout=60, wait=True)
+            self._deleted = True
+class DaytonaSandboxBackend:
+    def __init__(self, *, image, snapshot=None):
+        self.image, self.snapshot = (
+            image,
+            snapshot or os.environ.get("DATA_AGENT_DAYTONA_SNAPSHOT"),
+        )
+    def create(self, *, timeout_s=900, envs=None, metadata=None):
+        from daytona import (
+            CreateSandboxFromImageParams,
+            CreateSandboxFromSnapshotParams,
+            Resources,
+        )
+        options = {
+            "language": "python",
+            "os_user": "root",
+            "env_vars": envs,
+            "labels": {
+                **(metadata or {}),
+                "openenv_component": "blackbox-opencode",
+                "openenv_owner": os.environ.get("RUN_OWNER", "local"),
+            },
+            "public": False,
+            "auto_stop_interval": max(30, math.ceil(timeout_s / 60)),
+            "auto_delete_interval": 0,
+        }
+        if self.snapshot:
+            params = CreateSandboxFromSnapshotParams(snapshot=self.snapshot, **options)
+        else:
+            params = CreateSandboxFromImageParams(
+                image=self.image,
+                resources=Resources(cpu=1, memory=4, disk=5),
+                **options,
+            )
+        return DaytonaSandboxHandle(client().create(params, timeout=300))

smoldataenv_opencode/environment.py ADDED Viewed

	@@ -0,0 +1,98 @@

+"""Native OpenCode sessions on the fixed SmolDataEnvs tasks."""
+import json
+import os
+from opencode_env.config import OpenCodeConfig
+from opencode_env.harness import OpenCodeSessionFactory
+from opencode_env.task import OpenCodeTask
+from openenv.core.harness import VerifyResult
+from .daytona import DaytonaSandboxBackend
+from .tasks import grade_answer, stage_task
+class TaskSession:
+    def __init__(self, session):
+        self.session = session
+    def __getattr__(self, name):
+        return getattr(self.session, name)
+    def fetch_training_trace(self):
+        trace = self.session.fetch_training_trace()
+        try:
+            events = [
+                json.loads(line)
+                for line in self.session.fetch_trace().splitlines()
+                if line.strip()
+            ]
+            parts = [
+                event["part"] for event in events if event.get("type") == "tool_use"
+            ]
+            ids = [part["callID"] for part in parts]
+            if not any(event.get("type") == "step_finish" for event in events):
+                raise ValueError("Incomplete OpenCode event stream")
+            if any(not value for value in ids) or len(set(ids)) != len(ids):
+                raise ValueError("Missing or repeated tool action IDs")
+            if any(
+                part.get("state", {}).get("status") not in {"completed", "error"}
+                for part in parts
+            ):
+                raise ValueError("Unfinished tool action")
+            calls = len(ids)
+        except (OSError, ValueError, KeyError, TypeError):
+            calls = None
+        for turn in trace.turns:
+            turn.metadata["native_tool_calls"] = calls
+        return trace
+def verify(sandbox, task):
+    return VerifyResult(
+        env_reward=grade_answer(sandbox, task.metadata["folder"]), done=True
+    )
+class TaskFactory:
+    def __init__(self, args, tasks, *, sampling):
+        self.tasks = {task["instruction"]: task for task in tasks}
+        config = OpenCodeConfig(
+            base_url=os.environ["SANDBOX_VLLM_URL"].rstrip("/") + "/v1",
+            api_key=os.environ["SANDBOX_VLLM_KEY"],
+            model=args.model,
+            opencode_version="1.18.31",
+            sandbox_home="/root",
+            proxy_disable_thinking=True,
+            proxy_max_tokens_cap=4096,
+            agent_timeout_s=600,
+            run_format="json",
+            extra_setup_shell="mkdir -p /workdir && rmdir /root/workdir && ln -s /workdir /root/workdir",
+            disabled_tools=["webfetch", "question", "task"],
+            extra_opencode_json={"permission": {"*": "allow"}},
+        )
+        self.factory = OpenCodeSessionFactory(
+            config=config,
+            sampling=sampling,
+            verifier=verify,
+            mode="transparent_proxy",
+            sandbox_backend=DaytonaSandboxBackend(
+                image="docker.io/savatar101/env-data-agent-train:base"
+            ),
+        )
+    def create(self, task, seed=None, episode_id=None):
+        row = self.tasks[task[-1]["content"]]
+        task = OpenCodeTask(
+            instruction=row["instruction"], metadata={"folder": row["folder"]}
+        )
+        session = self.factory.create(
+            task, seed=seed, episode_id=episode_id, start_agent=False
+        )
+        try:
+            stage_task(session.sandbox, row["folder"])
+            session.start_agent()
+            return TaskSession(session)
+        except BaseException:
+            session.close()
+            raise

smoldataenv_opencode/server.py ADDED Viewed

	@@ -0,0 +1,72 @@

+"""Run native OpenCode on SmolDataEnvs through the OpenEnv protocol."""
+import os
+from types import SimpleNamespace
+from fastmcp import FastMCP
+from openenv.core.env_server import create_app
+from openenv.core.env_server.mcp_environment import MCPEnvironment
+from openenv.core.env_server.mcp_types import CallToolAction, CallToolObservation
+from openenv.core.env_server.types import Observation, State
+from .catalog import TaskCatalog, task_by_name
+from .environment import TaskFactory
+class OpenCodeEnvironment(TaskCatalog, MCPEnvironment):
+    SUPPORTS_CONCURRENT_SESSIONS = True
+    def __init__(self):
+        self._state = State()
+        mcp = FastMCP("smoldataenv-opencode")
+        @mcp.tool
+        def run_rollout(split: str, task_name: str, model: str, sampling: dict) -> dict:
+            """Run OpenCode, grade its answer, and export its typed training trace."""
+            row = task_by_name(split, task_name)
+            factory = TaskFactory(
+                SimpleNamespace(model=model), [row], sampling=sampling
+            )
+            session = factory.create([{"role": "user", "content": row["instruction"]}])
+            try:
+                session.wait_for_completion(timeout_s=900)
+                try:
+                    trace = session.fetch_training_trace()
+                except (ValueError, TypeError, KeyError) as exc:
+                    return {"capture_error": str(exc)}
+                grade = session.verify([]).env_reward
+                return {
+                    "training_trace": trace.model_dump(mode="json"),
+                    "correctness": grade,
+                }
+            finally:
+                session.close()
+        super().__init__(mcp)
+    def reset(self, seed=None, episode_id=None, **kwargs):
+        self._state = State(episode_id=episode_id)
+        return Observation(metadata={"status": "Call run_rollout with a task name"})
+    @property
+    def state(self):
+        return self._state
+    def _step_impl(self, action, **kwargs):
+        raise ValueError("Use an MCP tool action")
+    def step(self, action, timeout_s=None, **kwargs):
+        return super().step(action, timeout_s=timeout_s or 1800, **kwargs)
+    async def step_async(self, action, timeout_s=None, **kwargs):
+        return await super().step_async(action, timeout_s=timeout_s or 1800, **kwargs)
+os.environ.setdefault("ENABLE_WEB_INTERFACE", "true")
+app = create_app(
+    OpenCodeEnvironment,
+    CallToolAction,
+    CallToolObservation,
+    env_name="smoldataenv_opencode",
+    max_concurrent_envs=int(os.environ.get("MAX_CONCURRENT_ENVS", "40")),
+)

smoldataenv_opencode/tasks.py ADDED Viewed

	@@ -0,0 +1,75 @@

+"""Stage public task files in a sandbox; run the held-out grader on the host."""
+import json
+import os
+import subprocess
+import sys
+from pathlib import Path
+import tomllib
+def load_tasks(data, split):
+    root = Path(data).resolve() / "datasets" / split / "tasks"
+    tasks = []
+    for folder in sorted(root.iterdir()):
+        spec = tomllib.loads((folder / "task.toml").read_text())
+        tasks.append(
+            {
+                "name": folder.name,
+                "folder": str(folder),
+                "instruction": (folder / "instruction.md").read_text(),
+                "difficulty": spec["metadata"]["difficulty_tier"],
+            }
+        )
+    if not tasks or len({t["instruction"] for t in tasks}) != len(tasks):
+        raise ValueError("Tasks must have unique instructions; run prepare.py first")
+    return tasks
+def stage_task(sandbox, folder):
+    folder = Path(folder)
+    spec = tomllib.loads((folder / "task.toml").read_text())
+    # Only data-download credentials enter the sandbox, never verifier answers.
+    env = {
+        key: os.path.expandvars(value)
+        for key, value in spec["environment"]["env"].items()
+    }
+    if any("${" in value for value in env.values()):
+        raise ValueError("Set HF_TOKEN before staging task data")
+    sandbox.write_text(
+        "/opt/pull_bucket.py", (folder / "environment/pull_bucket.py").read_text()
+    )
+    result = sandbox.exec(
+        "mkdir -p /workdir /home/user/input && python3 /opt/pull_bucket.py "
+        '&& test -n "$(ls -A /home/user/input)"',
+        envs=env,
+        timeout=300,
+    )
+    if result.exit_code:
+        raise RuntimeError("Task data download failed")
+def grade_answer(sandbox, folder):
+    folder = Path(folder)
+    spec = tomllib.loads((folder / "task.toml").read_text())
+    answer = (
+        sandbox.read_text("/workdir/answer.txt")
+        if sandbox.exists("/workdir/answer.txt")
+        else ""
+    )
+    result = subprocess.run(
+        [sys.executable, str(folder / "tests/grader.py"), "--json"],
+        input=answer,
+        text=True,
+        capture_output=True,
+        timeout=120,
+        check=False,
+        env={**os.environ, **spec["verifier"]["env"]},
+    )
+    if result.returncode:
+        raise RuntimeError("Task grader failed")
+    value = json.loads(result.stdout)["correctness"]
+    if value not in (0, 1):
+        raise ValueError("Expected a binary correctness grade")
+    return float(value)

start.sh ADDED Viewed

	@@ -0,0 +1,5 @@

+#!/usr/bin/env bash
+set -euo pipefail
+cd "$(dirname "$0")"
+python prepare.py --output "${SMOLDATA_DATA:-prepared}"
+exec uvicorn smoldataenv_opencode.server:app --host 0.0.0.0 --port "${PORT:-7860}" --ws-ping-timeout 1800