AutoGPT/classic/direct_benchmark

Direct Benchmark Harness

High-performance benchmark harness for AutoGPT that directly instantiates agents without HTTP server overhead, enabling parallel execution of multiple configurations.

Features

• Direct Agent Instantiation: No HTTP server, no Agent Protocol overhead
• Parallel Execution: Run multiple strategy/model combinations concurrently
• Multiple Attempts: Run each challenge multiple times for statistical reliability
• Rich UI: Live progress display with Rich library
• Multiple Output Modes: Default (rich), quiet, verbose, JSON for CI
• Full CLI Compatibility: All flags from the original agbenchmark supported

Installation

cd classic/direct_benchmark
poetry install

Usage

# Run benchmarks with default settings
poetry run python -m direct_benchmark run

# Run specific strategies and models
poetry run python -m direct_benchmark run \
    --strategies one_shot,rewoo \
    --models claude,openai \
    --parallel 4

# Run a single test
poetry run python -m direct_benchmark run \
    --strategies one_shot \
    --tests ReadFile

# Run multiple attempts per challenge
poetry run python -m direct_benchmark run \
    --strategies one_shot \
    --attempts 3

# Run only regression tests (previously beaten)
poetry run python -m direct_benchmark run --maintain

# Run only non-regression tests (not consistently beaten)
poetry run python -m direct_benchmark run --improve

# Run only never-beaten challenges
poetry run python -m direct_benchmark run --explore

# List available challenges
poetry run python -m direct_benchmark list-challenges

# List model presets
poetry run python -m direct_benchmark list-models

# List strategies
poetry run python -m direct_benchmark list-strategies

CLI Options

Challenge Selection

• --strategies, -s: Comma-separated strategies (one_shot, rewoo, plan_execute, reflexion, tree_of_thoughts)
• --models, -m: Comma-separated model presets (claude, openai, etc.)
• --categories, -c: Filter by challenge categories
• --skip-category, -S: Exclude categories
• --tests, -t: Filter by test names

Execution Control

• --attempts, -N: Number of times to run each challenge
• --parallel, -p: Maximum parallel runs (default: 4)
• --timeout: Per-challenge timeout in seconds (default: 300)
• --cutoff: Alias for --timeout
• --no-cutoff, --nc: Disable time limit
• --max-steps: Maximum steps per challenge (default: 50)

Challenge Filtering Modes

• --maintain: Run only regression tests (previously beaten consistently)
• --improve: Run only non-regression tests (not consistently beaten)
• --explore: Run only challenges that have never been beaten
• --no-dep: Run all challenges regardless of dependency success/failure

Output & Debug

• --quiet, -q: Minimal output
• --verbose, -v: Detailed per-challenge output
• --json: JSON output for CI/scripting
• --debug: Enable debug output
• --keep-answers: Keep answer files for debugging

Paths

• --workspace: Workspace root directory
• --challenges-dir: Path to challenges directory
• --reports-dir: Path to reports directory

Available Strategies

Strategy	Description
one_shot	Single-pass reasoning (default, most reliable)
rewoo	Reasoning with observations
plan_execute	Plan then execute
reflexion	Self-reflection loop
tree_of_thoughts	Multiple reasoning paths

Available Model Presets

Claude

• claude: sonnet-4 smart, haiku fast (default)
• claude-smart: sonnet-4 for both
• claude-fast: haiku for both
• claude-opus: opus smart, sonnet fast
• claude-opus-only: opus for both

Claude with Extended Thinking

• claude-thinking-10k: 10k thinking tokens
• claude-thinking-25k: 25k thinking tokens
• claude-thinking-50k: 50k thinking tokens
• claude-opus-thinking: opus with 25k thinking
• claude-opus-thinking-50k: opus with 50k thinking

OpenAI

• openai: gpt-4o smart, gpt-4o-mini fast
• openai-smart: gpt-4o for both
• openai-fast: gpt-4o-mini for both
• gpt5: gpt-5 smart, gpt-4o fast
• gpt5-only: gpt-5 for both

OpenAI Reasoning Models

• o1, o1-mini: o1 variants
• o1-low, o1-medium, o1-high: o1 with reasoning effort
• o3-low, o3-medium, o3-high: o3 with reasoning effort

Reports

Reports are generated in ./reports/ with format:

reports/
├── {timestamp}_{strategy}_{model}/
│   └── report.json
└── strategy_comparison_{timestamp}.json

Key Differences from agbenchmark

agbenchmark	direct_benchmark
subprocess.Popen + HTTP server	Direct create_agent()
HTTP/REST via Agent Protocol	Direct propose_action()/execute()
Sequential (one config at a time)	Parallel via asyncio semaphore
Port-based isolation	Workspace-based isolation