Add SCML arena

Author: Muhtasham

README.md

@@ -95,6 +95,15 @@ Critically, *LMs don't play the game directly*.
 Their code serves as their competitive proxy.
 The winner is the LM agent who wins the most rounds.
 
+## 🧩 Available Arenas
+
+CodeClash includes competitive programming games and simulation-backed arenas, including BattleSnake,
+CoreWar, Halite, HuskyBench, RoboCode, RobotRumble, and SCML.
+
+SCML is a supply-chain negotiation arena based on the ANAC Supply Chain Management League OneShot
+track. Agents edit a Python `scml_agent.py` implementation and compete to maximize average profit
+across multiple simulated supply-chain worlds.
+
 ## 🚀 Get Involved
 
 - Check out our [docs](https://docs.codeclash.ai/) for more details on running different arenas, configuring tournaments, etc.

codeclash/arenas/__init__.py

@@ -15,6 +15,7 @@
 from codeclash.arenas.huskybench.huskybench import HuskyBenchArena
 from codeclash.arenas.robocode.robocode import RoboCodeArena
 from codeclash.arenas.robotrumble.robotrumble import RobotRumbleArena
+from codeclash.arenas.scml.scml import SCMLOneShotArena
 
 ARENAS = [
     BattleCode23Arena,
@@ -33,6 +34,7 @@
     HuskyBenchArena,
     RoboCodeArena,
     RobotRumbleArena,
+    SCMLOneShotArena,
 ]
 
 

codeclash/arenas/scml/SCML.Dockerfile

@@ -0,0 +1,23 @@
+FROM python:3.11-slim-bookworm
+
+ENV DEBIAN_FRONTEND=noninteractive \
+    PYTHONDONTWRITEBYTECODE=1 \
+    PIP_NO_CACHE_DIR=1
+
+RUN apt-get update \
+ && apt-get install -y --no-install-recommends \
+    ca-certificates git build-essential jq \
+ && rm -rf /var/lib/apt/lists/*
+
+RUN python -m pip install --upgrade pip \
+ && python -m pip install scml==0.8.2
+
+WORKDIR /workspace
+
+COPY codeclash/arenas/scml/runtime/ /workspace/
+
+RUN git init \
+ && git config user.email "player@codeclash.com" \
+ && git config user.name "Player" \
+ && git add . \
+ && git commit -m "Initial SCML workspace"

codeclash/arenas/scml/__init__.py

@@ -0,0 +1 @@
+

codeclash/arenas/scml/runtime/.gitignore

@@ -0,0 +1,2 @@
+__pycache__/
+*.py[cod]

codeclash/arenas/scml/runtime/README.md

@@ -0,0 +1,15 @@
+# SCML OneShot CodeClash Workspace
+
+Edit `scml_agent.py`.
+
+Your file must define `MyAgent`, an SCML OneShot agent class. A safe starting point is:
+
+```python
+from scml.oneshot.agents import GreedySyncAgent
+
+
+class MyAgent(GreedySyncAgent):
+    pass
+```
+
+The arena runs multiple SCML2024 OneShot worlds and scores agents by average profit.

codeclash/arenas/scml/runtime/run_scml.py

@@ -0,0 +1,125 @@
+import argparse
+import importlib.util
+import json
+import random
+import re
+from pathlib import Path
+
+import numpy as np
+from scml.oneshot import SCML2024OneShotWorld
+
+
+def safe_class_name(player_name: str) -> str:
+    safe = re.sub(r"\W+", "_", player_name)
+    if not safe or safe[0].isdigit():
+        safe = f"player_{safe}"
+    return f"CodeClash_{safe}"
+
+
+def load_agent_class(player_name: str, path: str):
+    module_name = f"codeclash_scml_{safe_class_name(player_name).lower()}"
+    spec = importlib.util.spec_from_file_location(module_name, path)
+    if spec is None or spec.loader is None:
+        raise RuntimeError(f"Could not load module spec from {path}")
+    module = importlib.util.module_from_spec(spec)
+    spec.loader.exec_module(module)
+    if not hasattr(module, "MyAgent"):
+        raise RuntimeError(f"{path} does not define MyAgent")
+    base_class = module.MyAgent
+    return type(safe_class_name(player_name), (base_class,), {"__module__": module.__name__})
+
+
+def run_world(agent_classes: dict[str, type], *, sim_idx: int, steps: int, lines: int) -> dict:
+    seed = 1729 + sim_idx
+    random.seed(seed)
+    np.random.seed(seed)
+
+    player_names = list(agent_classes.keys())
+    offset = sim_idx % len(player_names)
+    ordered_names = player_names[offset:] + player_names[:offset]
+    wrapped_classes = [agent_classes[name] for name in ordered_names]
+    class_to_player = {cls.__name__: player for player, cls in agent_classes.items()}
+
+    config = SCML2024OneShotWorld.generate(
+        agent_types=wrapped_classes,
+        agent_processes=[0 for _ in wrapped_classes],
+        n_steps=steps,
+        n_processes=1,
+        n_lines=lines,
+        random_agent_types=False,
+    )
+    world = SCML2024OneShotWorld(
+        **config,
+        no_logs=True,
+        compact=True,
+        fast=True,
+        agent_name_reveals_type=True,
+        agent_name_reveals_position=True,
+    )
+    world.run()
+
+    raw_scores = world.scores()
+    player_scores = {player: 0.0 for player in player_names}
+    details = []
+    for agent_id, score in raw_scores.items():
+        world_agent = world.agents[agent_id]
+        player = class_to_player.get(world_agent.short_type_name)
+        if player is None:
+            continue
+        numeric_score = float(score)
+        player_scores[player] = numeric_score
+        details.append(
+            {
+                "sim": sim_idx,
+                "player": player,
+                "world_agent_id": agent_id,
+                "score": numeric_score,
+            }
+        )
+
+    return {"scores": player_scores, "details": details}
+
+
+def parse_agent_arg(value: str) -> tuple[str, str]:
+    if "=" not in value:
+        raise argparse.ArgumentTypeError("--agent values must be NAME=/path/to/scml_agent.py")
+    name, path = value.split("=", 1)
+    if not name:
+        raise argparse.ArgumentTypeError("agent name cannot be empty")
+    if not Path(path).exists():
+        raise argparse.ArgumentTypeError(f"agent path does not exist: {path}")
+    return name, path
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--agent", action="append", type=parse_agent_arg, required=True)
+    parser.add_argument("--sims", type=int, default=3)
+    parser.add_argument("--steps", type=int, default=10)
+    parser.add_argument("--lines", type=int, default=2)
+    parser.add_argument("--output", required=True)
+    args = parser.parse_args()
+
+    agent_classes = {name: load_agent_class(name, path) for name, path in args.agent}
+    totals = {name: 0.0 for name in agent_classes}
+    details = []
+
+    for sim_idx in range(args.sims):
+        result = run_world(agent_classes, sim_idx=sim_idx, steps=args.steps, lines=args.lines)
+        for player, score in result["scores"].items():
+            totals[player] += score
+        details.extend(result["details"])
+
+    averages = {player: score / args.sims for player, score in totals.items()}
+    output = {
+        "average_scores": averages,
+        "total_scores": totals,
+        "sims": args.sims,
+        "details": [json.dumps(item, sort_keys=True) for item in details],
+    }
+    Path(args.output).parent.mkdir(parents=True, exist_ok=True)
+    Path(args.output).write_text(json.dumps(output, indent=2, sort_keys=True))
+
+
+if __name__ == "__main__":
+    main()

codeclash/arenas/scml/runtime/scml_agent.py

@@ -0,0 +1,10 @@
+from scml.oneshot.agents import GreedySyncAgent
+
+
+class MyAgent(GreedySyncAgent):
+    """Baseline SCML OneShot agent.
+
+    Improve this class to negotiate better supply-chain contracts and maximize profit.
+    """
+
+    pass

codeclash/arenas/scml/scml.py

@@ -0,0 +1,125 @@
+import json
+import shlex
+import subprocess
+
+from codeclash.agents.player import Player
+from codeclash.arenas.arena import CodeArena, RoundStats
+from codeclash.constants import RESULT_TIE
+from codeclash.utils.environment import assert_zero_exit_code
+
+RESULTS_JSON = "scml_results.json"
+
+
+class SCMLOneShotArena(CodeArena):
+    name: str = "SCML"
+    submission: str = "scml_agent.py"
+    description: str = """SCML OneShot is a supply-chain negotiation simulator based on the ANAC Supply Chain Management League.
+
+Your bot is a Python file named `scml_agent.py` that defines a class named `MyAgent`.
+`MyAgent` should inherit from an SCML OneShot agent class, for example:
+
+    from scml.oneshot.agents import GreedySyncAgent
+
+    class MyAgent(GreedySyncAgent):
+        ...
+
+Each round runs several SCML2024 OneShot worlds. Your agent negotiates with the other submitted
+agents to buy or sell goods in a simulated supply chain. The objective is to maximize profit. The
+arena score is your average SCML score across all worlds in the round.
+"""
+    default_args: dict = {
+        "sims_per_round": 3,
+        "n_steps": 10,
+        "n_lines": 2,
+        "timeout": 180,
+    }
+
+    def _game_arg(self, key: str):
+        return self.game_config.get(key, self.default_args[key])
+
+    def validate_code(self, agent: Player) -> tuple[bool, str | None]:
+        quoted_submission = shlex.quote(self.submission)
+        file_check = agent.environment.execute(f"test -f {quoted_submission} && echo exists")
+        if "exists" not in file_check["output"]:
+            return False, f"Submission file `{self.submission}` not found in the workspace root"
+
+        content = agent.environment.execute(f"cat {quoted_submission}")["output"]
+        if not content.strip():
+            return False, f"`{self.submission}` is empty"
+
+        syntax_check = agent.environment.execute(f"python -m py_compile {quoted_submission}")
+        if syntax_check["returncode"] != 0:
+            return False, f"Python syntax error in `{self.submission}`:\n{syntax_check['output']}"
+
+        import_check = agent.environment.execute(
+            "python - <<'PY'\n"
+            "import importlib.util\n"
+            f"spec = importlib.util.spec_from_file_location('submission_agent', {self.submission!r})\n"
+            "module = importlib.util.module_from_spec(spec)\n"
+            "spec.loader.exec_module(module)\n"
+            "assert hasattr(module, 'MyAgent'), 'MyAgent class not found'\n"
+            "from scml.oneshot.agent import OneShotAgent\n"
+            "assert issubclass(module.MyAgent, OneShotAgent), 'MyAgent must inherit from an SCML OneShotAgent class'\n"
+            "PY"
+        )
+        if import_check["returncode"] != 0:
+            return False, f"Could not import `MyAgent` from `{self.submission}`:\n{import_check['output']}"
+
+        return True, None
+
+    def execute_round(self, agents: list[Player]) -> None:
+        agent_args = []
+        for agent in agents:
+            agent_args.extend(["--agent", f"{agent.name}=/{agent.name}/{self.submission}"])
+
+        cmd = [
+            "python",
+            "run_scml.py",
+            "--sims",
+            str(self._game_arg("sims_per_round")),
+            "--steps",
+            str(self._game_arg("n_steps")),
+            "--lines",
+            str(self._game_arg("n_lines")),
+            "--output",
+            str(self.log_env / RESULTS_JSON),
+            *agent_args,
+        ]
+        full_cmd = " ".join(shlex.quote(part) for part in cmd)
+        self.logger.info(f"Running game: {full_cmd}")
+        try:
+            response = self.environment.execute(full_cmd, timeout=int(self._game_arg("timeout")))
+        except subprocess.TimeoutExpired as exc:
+            raise RuntimeError("SCML round timed out") from exc
+        assert_zero_exit_code(response, logger=self.logger)
+
+    def get_results(self, agents: list[Player], round_num: int, stats: RoundStats):
+        result_file = self.log_round(round_num) / RESULTS_JSON
+        if not result_file.exists():
+            self.logger.error(f"Missing result file: {result_file}")
+            stats.winner = RESULT_TIE
+            for agent in agents:
+                stats.scores[agent.name] = 0.0
+                stats.player_stats[agent.name].score = 0.0
+            return
+
+        with open(result_file) as f:
+            result = json.load(f)
+
+        scores = {agent.name: 0.0 for agent in agents}
+        for player, score in result.get("average_scores", {}).items():
+            if player in scores:
+                scores[player] = float(score)
+
+        stats.scores = scores
+        stats.details = result.get("details", [])
+        for player, score in scores.items():
+            stats.player_stats[player].score = score
+
+        if not scores:
+            stats.winner = RESULT_TIE
+            return
+
+        top_score = max(scores.values())
+        winners = [player for player, score in scores.items() if score == top_score]
+        stats.winner = winners[0] if len(winners) == 1 else RESULT_TIE

configs/examples/SCML__dummy__r1__s2.yaml

@@ -0,0 +1,31 @@
+tournament:
+  rounds: 1
+game:
+  name: SCML
+  sims_per_round: 2
+  n_steps: 5
+  n_lines: 2
+  timeout: 240
+players:
+- agent: dummy
+  name: alpha
+- agent: dummy
+  name: beta
+prompts:
+  game_description: |-
+    You are a software developer ({{player_id}}) competing in CodeClash's SCML OneShot arena.
+
+    The game is played in {{total_rounds}} rounds. For every round, you and your competitors edit
+    code that controls an autonomous supply-chain negotiation agent. This is round {{round}}.
+
+    Your task: improve `scml_agent.py`, located in {{working_dir}}.
+    All commands run from {{working_dir}}.
+
+    Your file must define `MyAgent`, an SCML OneShot agent class. A valid starting point is:
+
+    from scml.oneshot.agents import GreedySyncAgent
+
+    class MyAgent(GreedySyncAgent):
+        pass
+
+    The arena runs multiple SCML2024 OneShot worlds. Your objective is to maximize average profit.