#!/usr/bin/env python3
"""Generate comprehensive test matrix for bot configurations."""
from __future__ import annotations
import itertools
from pathlib import Path
import yaml
# Test dimensions
GAMES = ["A", "B", "C"]
STRATEGIES = ["opportunistic", "ai_strategy"]
TURN_LIMITS = [15, 30, 50]
EXPLORATION_LEVELS = [0.2, 0.5, 0.8] # Low, medium, high
BANKING_OPTIONS = [True, False]
INTERVENTION_OPTIONS = [
{"enabled": False},
{"enabled": True, "auto_apply": False},
{"enabled": True, "auto_apply": True},
]
def create_opportunistic_config(game: str, turns: int, explore: float, banking: bool) -> dict:
"""Create opportunistic strategy config."""
return {
"connection": {
"host": "localhost",
"port": 2002,
"game_letter": game,
},
"trading": {
"strategy": "opportunistic",
"opportunistic": {
"explore_chance": explore,
"max_wander_without_trade": 5 if explore > 0.5 else 3,
},
},
"session": {
"max_turns_per_session": turns,
"target_credits": 50000 if turns < 25 else 100000,
},
"banking": {
"enabled": banking,
**({"min_credits_to_bank": 25000} if banking else {}),
},
"upgrades": {
"enabled": False,
},
}
def create_ai_config(
game: str, turns: int, intervention: dict, banking: bool
) -> dict:
"""Create AI strategy config."""
config = {
"connection": {
"host": "localhost",
"port": 2002,
"game_letter": game,
},
"trading": {
"strategy": "ai_strategy",
"ai_strategy": {
"enabled": True,
"fallback_strategy": "opportunistic",
"fallback_threshold": 3,
"intervention": intervention,
},
},
"llm": {
"provider": "ollama",
"ollama": {
"base_url": "http://localhost:11434",
"model": "gemma3",
"timeout_seconds": 30.0,
},
},
"session": {
"max_turns_per_session": turns,
"target_credits": 75000 if turns < 40 else 150000,
},
"banking": {
"enabled": banking,
**({"min_credits_to_bank": 50000} if banking else {}),
},
"upgrades": {
"enabled": False,
},
}
# Add intervention thresholds if enabled
if intervention.get("enabled"):
config["trading"]["ai_strategy"]["intervention"].update({
"min_priority": "low",
"cooldown_turns": 3,
"max_per_session": 20,
"loop_action_threshold": 2,
"loop_sector_threshold": 3,
"stagnation_turns": 8,
"profit_decline_ratio": 0.5,
"turn_waste_threshold": 0.3,
"analysis_temperature": 0.3,
"analysis_max_tokens": 800,
})
return config
def generate_all_configs():
"""Generate all test configuration files."""
output_dir = Path("config/test_matrix")
output_dir.mkdir(parents=True, exist_ok=True)
test_num = 0
# Generate opportunistic configs
for game, turns, explore, banking in itertools.product(
GAMES, TURN_LIMITS, EXPLORATION_LEVELS, BANKING_OPTIONS
):
test_num += 1
config = create_opportunistic_config(game, turns, explore, banking)
filename = f"{test_num:02d}_game{game}_opp_t{turns}_e{int(explore*10)}_b{int(banking)}.yaml"
filepath = output_dir / filename
with open(filepath, "w") as f:
f.write(f"# Test {test_num}: Game {game}, Opportunistic, "
f"{turns} turns, explore={explore}, banking={banking}\n")
yaml.dump(config, f, default_flow_style=False, sort_keys=False)
print(f"Created: {filename}")
# Generate AI strategy configs
for game, turns, intervention, banking in itertools.product(
GAMES, TURN_LIMITS, INTERVENTION_OPTIONS, BANKING_OPTIONS
):
test_num += 1
config = create_ai_config(game, turns, intervention, banking)
intervention_str = (
"no_int" if not intervention["enabled"]
else f"int_auto{int(intervention.get('auto_apply', False))}"
)
filename = f"{test_num:02d}_game{game}_ai_t{turns}_{intervention_str}_b{int(banking)}.yaml"
filepath = output_dir / filename
with open(filepath, "w") as f:
f.write(f"# Test {test_num}: Game {game}, AI Strategy, "
f"{turns} turns, intervention={intervention_str}, banking={banking}\n")
yaml.dump(config, f, default_flow_style=False, sort_keys=False)
print(f"Created: {filename}")
print(f"\n✓ Generated {test_num} test configurations in {output_dir}")
return test_num
if __name__ == "__main__":
total = generate_all_configs()
print(f"\nTotal configurations: {total}")
