| import os |
|
|
| |
| PROJECT_DIR = os.path.dirname(os.path.abspath(__file__)) |
| TASKS_DIR = os.path.join(PROJECT_DIR, "tasks") |
|
|
| |
| SANDBOX_IMAGE = os.environ.get("ARENA_SANDBOX_IMAGE", "python:3.12-slim") |
| SANDBOX_NETWORK = os.environ.get("ARENA_SANDBOX_NETWORK", "arena-net") |
| SANDBOX_MEMORY_LIMIT = os.environ.get("ARENA_SANDBOX_MEMORY", "2g") |
|
|
| |
| CLAUDE_CLI_PATH = os.environ.get("CLAUDE_CLI_PATH", "claude") |
| AIDER_CLI_PATH = os.environ.get("AIDER_CLI_PATH", "aider") |
| CODEX_CLI_PATH = os.environ.get("CODEX_CLI_PATH", "codex") |
|
|
| |
| ANTHROPIC_PRICING = { |
| "claude-opus-4-6": (5.00, 6.25, 0.50, 25.0), |
| "claude-sonnet-4-6": (3.00, 3.75, 0.30, 15.0), |
| "claude-haiku-4-5-20251001": (1.00, 1.25, 0.10, 5.0), |
| } |
| DEFAULT_PRICING = (3.00, 3.75, 0.30, 15.0) |
|
|
| |
| OPENAI_PRICING = { |
| "gpt-4o": (2.50, 0, 0, 10.0), |
| "o3": (2.00, 0, 0, 8.0), |
| "o4-mini": (1.10, 0, 0, 4.40), |
| } |
|
|
| |
| AIDER_DEFAULT_MODEL = os.environ.get("AIDER_MODEL", "openai/MiniMax-M2.5") |
|
|
| |
| MINIMAX_BASE_URL = "https://api.minimax.io/v1" |
| MINIMAX_PRICING = { |
| "MiniMax-M2.5": (0.05, 0, 0, 0.05), |
| } |
|
|
| |
| ALL_PRICING = {} |
| ALL_PRICING.update(ANTHROPIC_PRICING) |
| ALL_PRICING.update(OPENAI_PRICING) |
| ALL_PRICING.update(MINIMAX_PRICING) |
|
|
|
|
| def get_pricing(model_id: str) -> tuple: |
| """Look up pricing rates for a model. Returns (input, cache_write, cache_read, output) per 1M tokens.""" |
| if model_id in ALL_PRICING: |
| return ALL_PRICING[model_id] |
| |
| short = model_id.split("/")[-1] if "/" in model_id else model_id |
| if short in ALL_PRICING: |
| return ALL_PRICING[short] |
| |
| lower = short.lower() |
| for key, val in ALL_PRICING.items(): |
| if key.lower() == lower: |
| return val |
| return DEFAULT_PRICING |
|
|
|
|
| |
| DEFAULT_K = 3 |
| MAX_K = 10 |
|
|
| |
| HOST = os.environ.get("ARENA_HOST", "127.0.0.1") |
| PORT = int(os.environ.get("ARENA_PORT", "8420")) |
|
|
