#!/bin/bash # Runs an olmocr-bench run using the full pipeline (no fallback) # Without model parameter (default behavior):, uses the default image from hugging face # ./scripts/run_benchmark.sh # With model parameter: for testing custom models # ./scripts/run_benchmark.sh --model your-model-name set -e # Parse command line arguments MODEL="" while [[ $# -gt 0 ]]; do case $1 in --model) MODEL="$2" shift 2 ;; *) echo "Unknown option: $1" echo "Usage: $0 [--model MODEL_NAME]" exit 1 ;; esac done # Check for uncommitted changes if ! git diff-index --quiet HEAD --; then echo "Error: There are uncommitted changes in the repository." echo "Please commit or stash your changes before running the benchmark." echo "" echo "Uncommitted changes:" git status --short exit 1 fi # Use conda environment Python if available, otherwise use system Python if [ -n "$CONDA_PREFIX" ]; then PYTHON="$CONDA_PREFIX/bin/python" echo "Using conda Python from: $CONDA_PREFIX" else PYTHON="python" echo "Warning: No conda environment detected, using system Python" fi # Get version from version.py VERSION=$($PYTHON -c 'import olmocr.version; print(olmocr.version.VERSION)') echo "OlmOCR version: $VERSION" # Get first 10 characters of git hash GIT_HASH=$(git rev-parse HEAD | cut -c1-10) echo "Git hash: $GIT_HASH" # Get current git branch name GIT_BRANCH=$(git rev-parse --abbrev-ref HEAD) echo "Git branch: $GIT_BRANCH" # Create full image tag IMAGE_TAG="olmocr-benchmark-${VERSION}-${GIT_HASH}" echo "Building Docker image with tag: $IMAGE_TAG" # Build the Docker image echo "Building Docker image..." docker build --platform linux/amd64 -f ./Dockerfile -t $IMAGE_TAG . # Get Beaker username BEAKER_USER=$(beaker account whoami --format json | jq -r '.[0].name') echo "Beaker user: $BEAKER_USER" # Push image to beaker echo "Trying to push image to Beaker..." if ! beaker image create --workspace ai2/oe-data-pdf --name $IMAGE_TAG $IMAGE_TAG 2>/dev/null; then echo "Warning: Beaker image with tag $IMAGE_TAG already exists. Using existing image." fi # Create Python script to run beaker experiment cat << 'EOF' > /tmp/run_benchmark_experiment.py import sys from beaker import Beaker, ExperimentSpec, TaskSpec, TaskContext, ResultSpec, TaskResources, ImageSource, Priority, Constraints, EnvVar # Get image tag, beaker user, git branch, git hash, and optional model from command line image_tag = sys.argv[1] beaker_user = sys.argv[2] git_branch = sys.argv[3] git_hash = sys.argv[4] model = sys.argv[5] if len(sys.argv) > 5 else None # Initialize Beaker client b = Beaker.from_env(default_workspace="ai2/olmocr") # Build the pipeline command with optional model parameter pipeline_cmd = "python -m olmocr.pipeline ./localworkspace --markdown --pdfs ./olmOCR-bench/bench_data/pdfs/**/*.pdf" if model: pipeline_cmd += f" --model {model}" # Check if AWS credentials secret exists aws_creds_secret = f"{beaker_user}-AWS_CREDENTIALS_FILE" try: # Try to get the secret to see if it exists b.secret.get(aws_creds_secret, workspace="ai2/olmocr") has_aws_creds = True print(f"Found AWS credentials secret: {aws_creds_secret}") except: has_aws_creds = False print(f"AWS credentials secret not found: {aws_creds_secret}") # Build commands list commands = [] if has_aws_creds: commands.extend([ "mkdir -p ~/.aws", 'echo "$AWS_CREDENTIALS_FILE" > ~/.aws/credentials' ]) commands.extend([ "git clone https://huggingface.co/datasets/allenai/olmOCR-bench", "cd olmOCR-bench && git lfs pull && cd ..", pipeline_cmd, "python olmocr/bench/scripts/workspace_to_bench.py localworkspace/ olmOCR-bench/bench_data/olmocr --bench-path ./olmOCR-bench/", "python -m olmocr.bench.benchmark --dir ./olmOCR-bench/bench_data" ]) # Build task spec with optional env vars task_spec_args = { "name": "olmocr-benchmark", "image": ImageSource(beaker=f"{beaker_user}/{image_tag}"), "command": [ "bash", "-c", " && ".join(commands) ], "context": TaskContext( priority=Priority.normal, preemptible=True, ), "resources": TaskResources(gpu_count=1), "constraints": Constraints(cluster=["ai2/ceres-cirrascale", "ai2/jupiter-cirrascale-2"]), "result": ResultSpec(path="/noop-results"), } # Add env vars if AWS credentials exist if has_aws_creds: task_spec_args["env_vars"] = [ EnvVar(name="AWS_CREDENTIALS_FILE", secret=aws_creds_secret) ] # Create experiment spec experiment_spec = ExperimentSpec( description=f"OlmOCR Benchmark Run - Branch: {git_branch}, Commit: {git_hash}", budget="ai2/oe-data", tasks=[TaskSpec(**task_spec_args)], ) # Create the experiment experiment = b.experiment.create(spec=experiment_spec, workspace="ai2/olmocr") print(f"Created experiment: {experiment.id}") print(f"View at: https://beaker.org/ex/{experiment.id}") EOF # Run the Python script to create the experiment echo "Creating Beaker experiment..." if [ -n "$MODEL" ]; then echo "Using model: $MODEL" $PYTHON /tmp/run_benchmark_experiment.py $IMAGE_TAG $BEAKER_USER $GIT_BRANCH $GIT_HASH "$MODEL" else $PYTHON /tmp/run_benchmark_experiment.py $IMAGE_TAG $BEAKER_USER $GIT_BRANCH $GIT_HASH fi # Clean up temporary file rm /tmp/run_benchmark_experiment.py echo "Benchmark experiment submitted successfully!"