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Installation

Quick Install

pip install stickler-eval

Requirements

  • Python 3.12+
  • conda (recommended)

Conda Setup

# Create a dedicated environment
conda create -n stickler python=3.12 -y
conda activate stickler

# Install from PyPI
pip install stickler-eval

Development Install

If you want to contribute or run from source:

git clone https://github.com/awslabs/stickler.git
cd stickler

# Create conda environment
conda create -n stickler python=3.12 -y
conda activate stickler

# Install with dev dependencies
pip install -e ".[dev]"

Optional Dependencies

Stickler's core comparators (Exact, Levenshtein, Numeric, Fuzzy) work out of the box. The AI-powered comparators require additional packages, installable via extras:

SemanticComparator

Uses AWS Bedrock Titan embeddings for cosine similarity.

pip install stickler-eval[semantic]
  • AWS credentials configured (aws configure or environment variables)
  • Access to Amazon Bedrock with Titan embedding models enabled

BERTComparator

Uses BERTScore for contextual similarity. Runs locally -- no cloud services needed.

pip install stickler-eval[bert]
  • GPU recommended for performance, but CPU works

LLMComparator

Uses AWS Bedrock via strands-agents for LLM-powered comparison.

pip install stickler-eval[llm]
  • AWS credentials configured
  • Access to Amazon Bedrock with your chosen model enabled

All optional dependencies

Install everything at once:

pip install stickler-eval[bert,semantic,llm]

Verify Installation

python -c "import stickler; print('Stickler installed successfully')"

Run the quick start example:

python examples/scripts/quick_start.py

Run the test suite:

pytest tests/

Troubleshooting

See Known Issues for platform-specific problems (e.g., NumPy/GCC compatibility on RHEL).