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f27702b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 | """Run a simple multi-step simulation to compare and rank email variants."""
from __future__ import annotations
import argparse
import csv
import os
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, List
from clothing_brand_ctr_env import ClothingBrandCtrAction
from clothing_brand_ctr_env.server.clothing_brand_ctr_env_environment import (
ClothingBrandCtrEnvironment,
)
@dataclass(frozen=True)
class EmailVariant:
"""Single email variant configuration."""
name: str
brand_voice: str
key_value_prop: str
call_to_action: str
def default_variants() -> List[EmailVariant]:
"""Default set of variants for quick comparisons."""
return [
EmailVariant(
name="Bold Launch",
brand_voice="bold",
key_value_prop="premium t-shirts for standing out when you travel",
call_to_action="Shop the launch collection now",
),
EmailVariant(
name="Minimal Core",
brand_voice="minimal",
key_value_prop="clean wardrobe staples designed for bringing to the airport",
call_to_action="Explore the core collection",
),
EmailVariant(
name="Quiet Luxury",
brand_voice="luxury",
key_value_prop="soft luxury items for traveling",
call_to_action="View the curated edit",
),
EmailVariant(
name="Playful Drop",
brand_voice="playful",
key_value_prop="the only t-shirt you need for a 14 hour flight",
call_to_action="See what's new today",
),
]
def run_simulation(
brand_name: str,
target_audience: str,
variants: List[EmailVariant],
) -> List[Dict[str, object]]:
"""Evaluate variants over multiple steps and return ranked results."""
env = ClothingBrandCtrEnvironment()
env.reset()
results: List[Dict[str, object]] = []
for variant in variants:
action = ClothingBrandCtrAction(
brand_name=brand_name,
target_audience=target_audience,
brand_voice=variant.brand_voice,
key_value_prop=variant.key_value_prop,
call_to_action=variant.call_to_action,
metadata={"variant_name": variant.name},
)
observation = env.step(action)
passed_rules = sum(1 for passed in observation.validation.values() if passed)
results.append(
{
"variant_name": variant.name,
"brand_voice": variant.brand_voice,
"ctr_proxy_score": observation.ctr_proxy_score,
"validation_passed": observation.validation_passed,
"passed_rules": passed_rules,
"generation_source": observation.metadata.get(
"generation_source",
"unknown",
),
"subject_line": observation.subject_line,
"preview_text": observation.preview_text,
"email_copy": observation.email_copy,
"word_count": observation.word_count,
"validation": observation.validation,
}
)
return sorted(
results,
key=lambda item: (
float(item["ctr_proxy_score"]),
int(item["passed_rules"]),
int(item["word_count"]),
),
reverse=True,
)
def print_rankings(rankings: List[Dict[str, object]]) -> None:
"""Print a compact leaderboard for quick comparison."""
print("\nEmail Variant Leaderboard")
print("-" * 116)
print(
f"{'Rank':<5} {'Variant':<16} {'Voice':<9} {'Score':<7} {'Checks':<7} {'Source':<18} {'Subject Line'}"
)
print("-" * 116)
for rank, row in enumerate(rankings, start=1):
subject = str(row["subject_line"])
if len(subject) > 46:
subject = subject[:43] + "..."
checks = f"{row['passed_rules']}/{len(row['validation'])}"
print(
f"{rank:<5} {str(row['variant_name']):<16} {str(row['brand_voice']):<9} "
f"{float(row['ctr_proxy_score']):<7.2f} {checks:<7} "
f"{str(row['generation_source']):<18} {subject}"
)
best = rankings[0]
print("\nTop Variant")
print("-" * 96)
print(f"Name: {best['variant_name']}")
print(f"Voice: {best['brand_voice']}")
print(f"Score: {best['ctr_proxy_score']}")
print(f"Validation Passed: {best['validation_passed']}")
print(f"Generation Source: {best['generation_source']}")
print(f"Preview: {best['preview_text']}")
print("\nEmail Copy:\n")
print(best["email_copy"])
def save_rankings_csv(rankings: List[Dict[str, object]], output_path: Path) -> None:
"""Persist ranking output for later analysis."""
output_path.parent.mkdir(parents=True, exist_ok=True)
with output_path.open("w", newline="", encoding="utf-8") as handle:
writer = csv.DictWriter(
handle,
fieldnames=[
"rank",
"variant_name",
"brand_voice",
"ctr_proxy_score",
"validation_passed",
"passed_rules",
"generation_source",
"word_count",
"subject_line",
"preview_text",
],
)
writer.writeheader()
for rank, row in enumerate(rankings, start=1):
writer.writerow(
{
"rank": rank,
"variant_name": row["variant_name"],
"brand_voice": row["brand_voice"],
"ctr_proxy_score": row["ctr_proxy_score"],
"validation_passed": row["validation_passed"],
"passed_rules": row["passed_rules"],
"generation_source": row["generation_source"],
"word_count": row["word_count"],
"subject_line": row["subject_line"],
"preview_text": row["preview_text"],
}
)
def main() -> None:
parser = argparse.ArgumentParser(
description="Run a multi-step simulation and rank email campaign variants."
)
parser.add_argument("--brand-name", default="AIRPORT CLUB")
parser.add_argument(
"--target-audience",
default="fellow traveler",
)
parser.add_argument(
"--output-csv",
default="outputs/evals/email_variant_rankings.csv",
help="Path to save CSV ranking output",
)
parser.add_argument(
"--hf-model-id",
default=None,
help="Optional override for HF model id (e.g., deepseek-ai/DeepSeek-V3).",
)
parser.add_argument(
"--disable-llm",
action="store_true",
help="Disable HF generation and use deterministic template fallback.",
)
args = parser.parse_args()
if args.hf_model_id:
os.environ["HF_MODEL_ID"] = args.hf_model_id
if args.disable_llm:
os.environ["USE_HF_LLM"] = "false"
rankings = run_simulation(
brand_name=args.brand_name,
target_audience=args.target_audience,
variants=default_variants(),
)
print_rankings(rankings)
save_rankings_csv(rankings, Path(args.output_csv))
print(f"\nSaved rankings to: {args.output_csv}")
if __name__ == "__main__":
main()
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