# AgentArena

Benchmark platform for comparing AI agents on real coding tasks.
Agents solve tasks in isolated Docker sandboxes. Results land in a leaderboard
with pass@k, cost, and speed metrics.

## Status

MVP — core evaluation pipeline implemented, E2E Docker test pending.

## Run

```bash
cd ~/Projekte/AgentArena
python3 -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt
uvicorn main:app --reload --port 8420
# → http://localhost:8420
```

## Usage

```bash
# Import a task (YAML)
curl -X POST http://localhost:8420/api/tasks/import \
  --data-binary @tasks/example_task.yaml

# Start a run
curl -X POST http://localhost:8420/api/runs \
  -H "Content-Type: application/json" \
  -d '{"task_slug": "example", "agent_name": "claude-code", "k": 1}'
```

## What works

- Leaderboard: pass@1, pass@3, avg_cost, avg_duration, composite_score
- Task detail: best run per agent, run list
- Run detail: trajectory, diff viewer, metrics
- SSE streaming for live run updates
- Task import via YAML
- Adapters: `claude_code`, `manual`

## Environment

Copy `.env.example` to `.env` and fill in your values.
Docker must be running for sandbox execution.