tensorbench dataset

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.avro filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.lz4 filter=lfs diff=lfs merge=lfs -text
+*.mds filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
+# Audio files - uncompressed
+*.pcm filter=lfs diff=lfs merge=lfs -text
+*.sam filter=lfs diff=lfs merge=lfs -text
+*.raw filter=lfs diff=lfs merge=lfs -text
+# Audio files - compressed
+*.aac filter=lfs diff=lfs merge=lfs -text
+*.flac filter=lfs diff=lfs merge=lfs -text
+*.mp3 filter=lfs diff=lfs merge=lfs -text
+*.ogg filter=lfs diff=lfs merge=lfs -text
+*.wav filter=lfs diff=lfs merge=lfs -text
+# Image files - uncompressed
+*.bmp filter=lfs diff=lfs merge=lfs -text
+*.gif filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text
+*.tiff filter=lfs diff=lfs merge=lfs -text
+# Image files - compressed
+*.jpg filter=lfs diff=lfs merge=lfs -text
+*.jpeg filter=lfs diff=lfs merge=lfs -text
+*.webp filter=lfs diff=lfs merge=lfs -text
+# Video files - compressed
+*.mp4 filter=lfs diff=lfs merge=lfs -text
+*.webm filter=lfs diff=lfs merge=lfs -text

Dockerfile

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+FROM python:3.11-slim
+
+ENV DEBIAN_FRONTEND=noninteractive
+ENV TZ=Etc/UTC
+ENV PYTHONUNBUFFERED=1
+ENV PYTHONDONTWRITEBYTECODE=1
+
+# System dependencies for C++ extension compilation
+RUN apt-get update && apt-get install -y \
+    git \
+    patch \
+    build-essential \
+    g++ \
+    cmake \
+    libgomp1 \
+    ninja-build \
+    && rm -rf /var/lib/apt/lists/*
+
+RUN pip install --upgrade pip
+
+WORKDIR /testbed
+
+# Full clone of the `bench` branch — every dataset base_commit lives on
+# this branch, and a full (non-treeless, non-shallow) clone guarantees
+# their trees are all locally available. A treeless or shallow clone
+# would force git to lazy-fetch on the harness's per-task
+# `git reset --hard <base_commit>`, and that fetch is flaky enough in
+# CI sandboxes to silently leave the working tree on the wrong commit.
+RUN git clone --branch bench https://github.com/bobbyyyan/scorch.git .
+
+# Pre-create venv with CPU-only PyTorch so setup.sh's `pip install -r
+# requirements.txt` (unpinned `torch`) sees the requirement as already
+# satisfied. The default Linux torch wheel pulls in ~3.8GiB of CUDA libs
+# (nvidia/, triton/, libtorch_cuda.so) that the 2-CPU Daytona sandboxes
+# never use — the CPU wheel skips all of that.
+RUN python3 -m venv venv && \
+    venv/bin/pip install --no-cache-dir --upgrade pip && \
+    venv/bin/pip install --no-cache-dir --index-url https://download.pytorch.org/whl/cpu torch
+
+# Run setup.sh to install remaining requirements and build the C++
+# extension; then drop the pip cache (~2.7GiB, only needed during install).
+RUN bash setup.sh && \
+    rm -rf /root/.cache
+
+# Activate venv for subsequent commands
+ENV PATH="/testbed/venv/bin:$PATH"
+ENV VIRTUAL_ENV="/testbed/venv"
+
+COPY run_tests.sh /testbed/run_tests.sh
+RUN chmod +x /testbed/run_tests.sh
+
+CMD ["/testbed/run_tests.sh"]

README.md

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+---
+license: mit
+task_categories:
+  - text-generation
+language:
+  - en
+tags:
+  - benchmark
+  - code
+  - llm-evaluation
+  - feature-addition
+  - python
+size_categories:
+  - n<1K
+configs:
+  - config_name: default
+    data_files:
+      - split: test
+        path: tensorbench.json
+---
+
+# TensorBench
+
+Feature-addition benchmark for LLMs and coding agents, evaluated against the
+[Scorch](https://github.com/bobbyyyan/scorch) codebase. Each task asks a model
+to add a feature (or otherwise extend functionality) to Scorch. Success is
+defined as the full pytest suite (original + any new tests the model adds)
+passing after the patch is applied inside a Docker container.
+
+This is the dataset artifact for the TensorBench paper (NeurIPS 2026
+Evaluations & Datasets track, double-blind submission).
+
+## At a glance
+
+| | |
+|---|---|
+| Tasks | 199 (194 feature-addition, 5 refactor) |
+| Target codebase | [`bobbyyyan/scorch`](https://github.com/bobbyyyan/scorch) — a sparse+dense PyTorch compiler |
+| Base commits | 5 distinct SHAs across the `bench` branch |
+| Language | Python (with C++ extension) |
+| Test runner | `pytest -v` inside Docker |
+
+## Files
+
+| File | Purpose |
+|---|---|
+| `tensorbench.json` | Task list. JSON array of 199 task records. |
+| `Dockerfile` | Eval image: `python:3.11-slim` + Scorch's C++ build deps + the upstream `bench` clone. |
+| `run_tests.sh` | Container `CMD`: rebuilds the C++ extension and runs `pytest`. |
+| `croissant.json` | Croissant metadata (core + RAI fields). |
+
+## Task schema
+
+Each record in `tensorbench.json` has:
+
+| Field | Type | Description |
+|---|---|---|
+| `instance_id` | string | e.g. `bobbyyyan__scorch-feature_kernel_fusion`. The `feature_*` / `refactor_*` suffix follows the original taxonomy; semantics for both is feature-addition. |
+| `repo_id` | string | `bobbyyyan__scorch` for every task. |
+| `repo_url` | string | Upstream Scorch URL. |
+| `base_commit` | string | The SHA the task is anchored at. The harness `git reset --hard`s to this before applying patches. |
+| `language` | string | `python`. |
+| `setup_commands` | list[string] | Container-side setup hooks. |
+| `test_command` | string | `/testbed/run_tests.sh`. |
+| `test_timeout` | int | Seconds. Default 3000. |
+| `refactor_type` | string | Mostly empty (legacy field from the original taxonomy). |
+| `description` | string | Natural-language task prompt the model receives. |
+| `files` | list[string] | Files relevant to the task. |
+| `task_type` | string | `feature` or `refactor`. |
+| `categories` | list[string] | Topical tags (kernel, codegen, format, etc.). |
+
+## Grading
+
+Run with `pytest -v`; the grading strategy parses verbose lines (preserving
+parametrized brackets like `[False]`) and uses a custom preservation rule:
+
+```
+success  ⇔  after.failed == 0
+```
+
+This handles the common case where an agent adds new tests alongside new
+code: if every test (original + agent-added) passes, the task is a success.
+Default exact-match preservation would flag the new tests as "changed" and
+produce false failures.
+
+## How to evaluate a model
+
+The full evaluation harness (`codebench`) and the project-local benchmark
+glue (`tensorbench`) are in the supplementary code submission.
+
+```bash
+# 1. Install the harness and benchmark glue
+git clone <tensorbench-repo>     ~/tensorbench
+git clone <codebench-repo>       ~/codebench
+pip install -e ~/codebench
+pip install -r ~/tensorbench/requirements.txt
+
+# 2. Build the eval image
+cd ~/tensorbench
+docker build -t scorch-eval -f dockerfiles/scorch/Dockerfile dockerfiles/scorch/
+
+# 3. Generate predictions, then grade them
+python run.py predict scorch sonnet-4.5
+python run.py eval    scorch sonnet-4.5
+```
+
+Predictions land in `predictions/`; eval outputs in `evaluation_results/<run_id>/`.
+
+## Anonymity
+
+This is a double-blind submission. Personally identifying information has
+been scrubbed from the supplementary code. Reviewers should not attempt to
+identify the authors via the target codebase URL or other public references.
+
+## License
+
+MIT for the benchmark scaffolding (this dataset, Dockerfile, grading
+strategy). The target Scorch codebase is governed by its own upstream
+license.
+
+## Citation
+
+(Anonymized for double-blind review. Citation will be added at camera-ready.)

croissant.json

@@ -0,0 +1,264 @@
+{
+  "@context": {
+    "@language": "en",
+    "@vocab": "https://schema.org/",
+    "citeAs": "cr:citeAs",
+    "column": "cr:column",
+    "conformsTo": "dct:conformsTo",
+    "cr": "http://mlcommons.org/croissant/",
+    "rai": "http://mlcommons.org/croissant/RAI/",
+    "data": {
+      "@id": "cr:data",
+      "@type": "@json"
+    },
+    "dataType": {
+      "@id": "cr:dataType",
+      "@type": "@vocab"
+    },
+    "dct": "http://purl.org/dc/terms/",
+    "equivalentProperty": {
+      "@id": "cr:equivalentProperty",
+      "@type": "@vocab"
+    },
+    "samplingRate": "cr:samplingRate",
+    "examples": {
+      "@id": "cr:examples",
+      "@type": "@json"
+    },
+    "extract": "cr:extract",
+    "field": "cr:field",
+    "fileProperty": "cr:fileProperty",
+    "fileObject": "cr:fileObject",
+    "fileSet": "cr:fileSet",
+    "format": "cr:format",
+    "includes": "cr:includes",
+    "isLiveDataset": "cr:isLiveDataset",
+    "jsonPath": "cr:jsonPath",
+    "key": "cr:key",
+    "md5": "cr:md5",
+    "parentField": "cr:parentField",
+    "path": "cr:path",
+    "recordSet": "cr:recordSet",
+    "references": "cr:references",
+    "regex": "cr:regex",
+    "repeated": "cr:repeated",
+    "replace": "cr:replace",
+    "sc": "https://schema.org/",
+    "separator": "cr:separator",
+    "source": "cr:source",
+    "subField": "cr:subField",
+    "transform": "cr:transform"
+  },
+  "@type": "sc:Dataset",
+  "conformsTo": "http://mlcommons.org/croissant/1.0",
+  "name": "TensorBench",
+  "description": "Feature-addition benchmark for LLMs and coding agents, evaluated against the Scorch codebase (a sparse+dense PyTorch compiler). Each task asks a model to add a feature; success is the full pytest suite passing after the patch is applied inside a Docker container. 199 tasks total (194 feature-addition, 5 refactor) across 5 base commits on the upstream `bench` branch.",
+  "url": "https://huggingface.co/datasets/tensorbench/tensorbench-1.0",
+  "license": "https://opensource.org/licenses/MIT",
+  "version": "1.0.0",
+  "citeAs": "(Anonymized for double-blind review.)",
+  "datePublished": "2026-05-06",
+  "keywords": [
+    "benchmark",
+    "code-generation",
+    "llm-evaluation",
+    "feature-addition",
+    "python",
+    "pytorch",
+    "sparse-tensors"
+  ],
+  "rai:dataCollection": "Each task is a natural-language prompt paired with a `base_commit` SHA from the upstream Scorch repository's `bench` branch. Prompts were drafted with LLM assistance against the target codebase and then reviewed and curated by the authors. The upstream codebase, tests, and SHAs are pre-existing artifacts of the Scorch project.",
+  "rai:annotationsPerItem": "Each task has a single author-curated description and a fixed `base_commit`. There are no per-item human annotations beyond the prompt itself; success is computed automatically by running the patched repo's pytest suite.",
+  "rai:dataLimitations": "All tasks target a single Python codebase (Scorch). Performance does not generalize across languages or unrelated repositories. Test suites authored by the agent are accepted at face value, which can permit a small number of vacuous tests; the paper's adversarial-behavior audit (see supplementary code) characterizes this rate. Container builds depend on a network clone of the upstream repository and may be affected by upstream availability.",
+  "rai:dataBiases": "All tasks were curated by the same set of authors. The category distribution skews toward runtime/dispatch, scheduler/loop transformations, linear-algebra ops, sparse formats, and IR/codegen surface area — i.e. the parts of a sparse-tensor compiler the authors found tractable to specify. Because prompts were drafted with LLM assistance, phrasing and structure also reflect the drafting model's stylistic patterns. The benchmark therefore measures a slice of `extend an existing PyTorch-extension codebase`-style work, not all of `software engineering with LLMs`.",
+  "rai:dataUseCases": "Evaluating coding agents and LLMs on extending a real, non-trivial Python+C++ codebase. Useful for: comparing agent frameworks (e.g. Claude Code, OpenAI Codex CLI, Gemini CLI, OpenHands), comparing model capabilities at fixed agent harness, and characterizing failure modes (test fail, patch apply fail, timeout, empty patch, vacuous added tests).",
+  "rai:personalSensitiveInformation": "None. Tasks describe code changes; no human-subject data is involved.",
+  "rai:dataSocialImpact": "The benchmark is intended for AI/ML research on code-generation evaluation. It does not target sensitive domains (medical, legal, financial). Like other code-evaluation benchmarks, it could in principle be used to filter or rank developers, which is not its intended use.",
+  "rai:hasSyntheticData": "Task prompts were drafted with LLM assistance against the target codebase and then reviewed and curated by the authors. The underlying `base_commit` SHAs, source code, and pytest infrastructure are pre-existing upstream artifacts and were not generated.",
+  "rai:dataReleaseMaintenancePlan": "The dataset will be made public under the authors' real names at the camera-ready deadline. Future revisions will be tagged via the `version` field. Bug reports and corrections will be tracked on the public repository.",
+  "distribution": [
+    {
+      "@type": "cr:FileObject",
+      "@id": "tensorbench.json",
+      "name": "tensorbench.json",
+      "description": "JSON array of 199 task records.",
+      "contentUrl": "https://huggingface.co/datasets/tensorbench/tensorbench-1.0/resolve/main/tensorbench.json",
+      "encodingFormat": "application/json",
+      "sha256": "41b9cf73e37f8458990584a21882575040c360d08935c135eedfc5f474d155f7"
+    },
+    {
+      "@type": "cr:FileObject",
+      "@id": "Dockerfile",
+      "name": "Dockerfile",
+      "description": "Eval image: python:3.11-slim plus Scorch's C++ build deps and a clone of the upstream `bench` branch.",
+      "contentUrl": "https://huggingface.co/datasets/tensorbench/tensorbench-1.0/resolve/main/Dockerfile",
+      "encodingFormat": "text/plain",
+      "sha256": "130e9738bd764e26f5b655d9e3b72fcfc4c7d9df9687cead2b7d53b930289873"
+    },
+    {
+      "@type": "cr:FileObject",
+      "@id": "run_tests.sh",
+      "name": "run_tests.sh",
+      "description": "Container CMD: rebuild the C++ extension and run pytest -v.",
+      "contentUrl": "https://huggingface.co/datasets/tensorbench/tensorbench-1.0/resolve/main/run_tests.sh",
+      "encodingFormat": "application/x-sh",
+      "sha256": "5bcab82be4065de1002995baea922492ba77063f52f4da191df2bf8d23096dc1"
+    }
+  ],
+  "recordSet": [
+    {
+      "@type": "cr:RecordSet",
+      "@id": "tasks",
+      "name": "tasks",
+      "description": "One record per benchmark task.",
+      "field": [
+        {
+          "@type": "cr:Field",
+          "@id": "tasks/instance_id",
+          "name": "instance_id",
+          "description": "Unique task id, e.g. bobbyyyan__scorch-feature_kernel_fusion. The feature_/refactor_ suffix follows the original taxonomy; semantics for both is feature-addition.",
+          "dataType": "sc:Text",
+          "source": {
+            "fileObject": {"@id": "tensorbench.json"},
+            "extract": {"jsonPath": "$[*].instance_id"}
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "tasks/repo_id",
+          "name": "repo_id",
+          "description": "Always bobbyyyan__scorch — used by the grading registry to route to the project-specific strategy.",
+          "dataType": "sc:Text",
+          "source": {
+            "fileObject": {"@id": "tensorbench.json"},
+            "extract": {"jsonPath": "$[*].repo_id"}
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "tasks/repo_url",
+          "name": "repo_url",
+          "description": "Git clone URL for the upstream Scorch repository. Identical for every task: https://github.com/bobbyyyan/scorch.git",
+          "dataType": "sc:URL",
+          "source": {
+            "fileObject": {"@id": "tensorbench.json"},
+            "extract": {"jsonPath": "$[*].repo_url"}
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "tasks/base_commit",
+          "name": "base_commit",
+          "description": "Commit SHA the task is anchored at. The harness git reset --hards to this before applying patches.",
+          "dataType": "sc:Text",
+          "source": {
+            "fileObject": {"@id": "tensorbench.json"},
+            "extract": {"jsonPath": "$[*].base_commit"}
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "tasks/language",
+          "name": "language",
+          "description": "Source language. Always python for this dataset.",
+          "dataType": "sc:Text",
+          "source": {
+            "fileObject": {"@id": "tensorbench.json"},
+            "extract": {"jsonPath": "$[*].language"}
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "tasks/setup_commands",
+          "name": "setup_commands",
+          "description": "Optional list of shell commands run inside the container before the test command. Empty for all current Scorch tasks (setup is baked into the Docker image); the field is present for harness compatibility with other consumers.",
+          "dataType": "sc:Text",
+          "repeated": true,
+          "source": {
+            "fileObject": {"@id": "tensorbench.json"},
+            "extract": {"jsonPath": "$[*].setup_commands"}
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "tasks/test_command",
+          "name": "test_command",
+          "description": "Shell command that runs the pytest suite (typically /testbed/run_tests.sh).",
+          "dataType": "sc:Text",
+          "source": {
+            "fileObject": {"@id": "tensorbench.json"},
+            "extract": {"jsonPath": "$[*].test_command"}
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "tasks/test_timeout",
+          "name": "test_timeout",
+          "description": "Test-runner timeout in seconds. 3000 for every current task.",
+          "dataType": "sc:Integer",
+          "source": {
+            "fileObject": {"@id": "tensorbench.json"},
+            "extract": {"jsonPath": "$[*].test_timeout"}
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "tasks/refactor_type",
+          "name": "refactor_type",
+          "description": "Mostly empty (legacy field from the original taxonomy; only a handful of tasks have extract/consolidate populated).",
+          "dataType": "sc:Text",
+          "source": {
+            "fileObject": {"@id": "tensorbench.json"},
+            "extract": {"jsonPath": "$[*].refactor_type"}
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "tasks/description",
+          "name": "description",
+          "description": "Natural-language task prompt the model receives.",
+          "dataType": "sc:Text",
+          "source": {
+            "fileObject": {"@id": "tensorbench.json"},
+            "extract": {"jsonPath": "$[*].description"}
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "tasks/files",
+          "name": "files",
+          "description": "Optional list of upstream-codebase files relevant to the task, surfaced as a hint to the model. Empty for all current Scorch tasks; the field is present for harness compatibility with other consumers.",
+          "dataType": "sc:Text",
+          "repeated": true,
+          "source": {
+            "fileObject": {"@id": "tensorbench.json"},
+            "extract": {"jsonPath": "$[*].files"}
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "tasks/task_type",
+          "name": "task_type",
+          "description": "feature or refactor. Both are evaluated as feature-addition (success = pytest passes).",
+          "dataType": "sc:Text",
+          "source": {
+            "fileObject": {"@id": "tensorbench.json"},
+            "extract": {"jsonPath": "$[*].task_type"}
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "tasks/categories",
+          "name": "categories",
+          "description": "Hierarchical category paths (e.g. `Runtime/Caching & dispatch`, `API/Linear Algebra/Matmul variants`, `Scheduler/Loop transformations/Tiling`). A task may carry multiple categories.",
+          "dataType": "sc:Text",
+          "repeated": true,
+          "source": {
+            "fileObject": {"@id": "tensorbench.json"},
+            "extract": {"jsonPath": "$[*].categories"}
+          }
+        }
+      ]
+    }
+  ]
+}

run_tests.sh

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+#!/bin/bash
+
+echo "============================================"
+echo "Running Scorch Test Suite"
+echo "============================================"
+
+# Clear JIT-compiled kernel cache to prevent stale .so files
+rm -rf ~/.cache/torch_extensions/ 2>/dev/null || true
+rm -rf /tmp/torch_extensions_* 2>/dev/null || true
+
+# Clear build artifacts and inline-compiled extension so rebuild picks up new csrc/.
+# scorch's setup.py uses package_dir={"":"src"}, so build_ext --inplace writes the
+# top-level scorch_ops extension to /testbed/src/scorch_ops*.so (NOT /testbed/).
+# We must delete both candidate paths or a silent build failure will fall through
+# to a stale snapshot-baked .so and the test run will silently use the wrong build.
+rm -rf /testbed/build/ /testbed/scorch.egg-info/ 2>/dev/null || true
+rm -f /testbed/scorch_ops*.so /testbed/src/scorch_ops*.so 2>/dev/null || true
+
+# Rebuild scorch_ops C++ extension to match current source. Fail loudly if the
+# build fails so a stale .so doesn't silently masquerade as the patched build.
+cd /testbed
+if ! python setup.py build_ext --inplace --force 2>&1 | tee build_output.log | tail -3; then
+    echo "============================================"
+    echo "BUILD FAILED - scorch_ops C++ extension did not compile"
+    echo "============================================"
+    tail -30 build_output.log
+    exit 1
+fi
+
+python -m pytest tests/ -v --tb=short --no-header 2>&1 | tee test_output.log
+
+if [ -f test_output.log ]; then
+    echo ""
+    echo "============================================"
+    echo "TEST SUMMARY"
+    echo "============================================"
+
+    SUMMARY_LINE=$(grep -E "={5,}.*in [0-9]+\.[0-9]+s.*={5,}" test_output.log | tail -1)
+
+    if [ -n "$SUMMARY_LINE" ]; then
+        PASSED=$(echo "$SUMMARY_LINE" | grep -oE '[0-9]+ passed' | grep -oE '[0-9]+' || echo "0")
+        FAILED=$(echo "$SUMMARY_LINE" | grep -oE '[0-9]+ failed' | grep -oE '[0-9]+' || echo "0")
+        SKIPPED=$(echo "$SUMMARY_LINE" | grep -oE '[0-9]+ skipped' | grep -oE '[0-9]+' || echo "0")
+        ERRORS=$(echo "$SUMMARY_LINE" | grep -oE '[0-9]+ error' | grep -oE '[0-9]+' || echo "0")
+
+        PASSED=${PASSED:-0}
+        FAILED=${FAILED:-0}
+        SKIPPED=${SKIPPED:-0}
+        ERRORS=${ERRORS:-0}
+
+        TOTAL=$((PASSED + FAILED + SKIPPED + ERRORS))
+
+        echo "Total: $TOTAL | Passed: $PASSED | Failed: $FAILED | Skipped: $SKIPPED | Errors: $ERRORS"
+
+        if [ "$FAILED" -eq "0" ] && [ "$ERRORS" -eq "0" ]; then
+            echo "ALL TESTS PASSED!"
+            exit 0
+        else
+            echo "SOME TESTS FAILED!"
+            grep -E "(FAILED|ERROR)" test_output.log | head -10
+            exit 1
+        fi
+    else
+        echo "Could not parse pytest output"
+        tail -10 test_output.log
+        exit 1
+    fi
+fi