ai-ecosystem-benchmark 0.0.4

Framework for benchmarking AI ecosystem tools against database backends

AI Ecosystem Benchmark

Generalized framework for benchmarking AI tools that depend on database backends.

Python Package

This repository is also a Python package named ai-ecosystem-benchmark. The package is intentionally minimal for now while the benchmark framework takes shape.

Install and sync the development environment with uv:

uv sync

Run the local checks:

uv run pytest
uv run ruff check .
uv run ruff format --check .
uv run mypy
uv run deptry .

Install pre-commit hooks once per checkout:

uv run pre-commit install

Implementing a Workload

Benchmark workloads should subclass BaseBenchmarkWorkload and implement the required lifecycle hooks:

• setup(): prepare clients, data, or other state before benchmarks run.
• between_benchmarks(): reset or pause between benchmark executions.
• teardown(): clean up resources after benchmarks finish.

Connection strings are optional. If a connection string is omitted, that backend is assumed to be disabled for the benchmark run.

Backend-specific benchmark methods are discovered by name:

• Aerospike methods start with aerospike
• Postgres methods start with postgres
• Redis methods start with redis

from ai_ecosystem_benchmark import BaseBenchmarkWorkload


class MyWorkload(BaseBenchmarkWorkload):
    def __init__(
        self,
        aerospike_connection_string: str | None = None,
        postgres_connection_string: str | None = None,
        redis_connection_string: str | None = None,
    ) -> None:
        super().__init__(
            aerospike_connection_string=aerospike_connection_string,
            postgres_connection_string=postgres_connection_string,
            redis_connection_string=redis_connection_string,
        )

    def setup(self) -> None:
        return None

    def between_benchmarks(self) -> None:
        return None

    def teardown(self) -> None:
        return None

    def aerospike_test_insert(self) -> None:
        ...

    def redis_test_lookup(self) -> None:
        ...

Infrastructure

The first infrastructure target is a GCP Compute Terraform stack that can provision any combination of Redis, Postgres, and Aerospike benchmark clusters. The GitHub Actions workflow in .github/workflows/terraform.yml runs Terraform manually through workflow_dispatch and prints non-sensitive endpoint details after apply.

See infra/terraform/gcp-compute/README.md for setup details.

License

This project is licensed under the Apache License 2.0. See LICENSE for details.