feat: 优化模特上身图提示词

2026-07-14 15:18:54 +08:00
parent da58f99293
commit 0a58b89919
8 changed files with 1973 additions and 15 deletions
@@ -0,0 +1,271 @@
+"""模特上身图 V2 同输入 A/B：默认只预估，显式 --execute 才创建计费任务。"""
+
+from __future__ import annotations
+
+import json
+import uuid
+from decimal import Decimal, InvalidOperation
+from pathlib import Path
+from time import monotonic
+
+import requests
+from django.core.management.base import BaseCommand, CommandError
+
+
+class Command(BaseCommand):
+    help = "对同一商品、模特、提示词和比例提交 Seedream/GPT 模特上身图 A/B；默认 dry-run"
+
+    def add_arguments(self, parser):
+        parser.add_argument("--product", default="", help="商品 UUID")
+        parser.add_argument("--model-asset", default="", help="模特肖像 Asset UUID")
+        parser.add_argument("--model-entity", default="", help="可选：模特库 Model UUID，仅作溯源")
+        parser.add_argument("--prompt", default="", help="两组共同使用的用户提示词")
+        parser.add_argument("--ratio", default="3:4", help="两组共同使用的比例，默认 3:4")
+        parser.add_argument("--count", type=int, default=1, choices=(1, 2, 4), help="每个模型生成张数")
+        parser.add_argument(
+            "--variants",
+            nargs="+",
+            default=("volcano", "gpt-image"),
+            help="模型路由键，默认 volcano gpt-image",
+        )
+        parser.add_argument("--max-points", default="", help="硬预算上限；--execute 时必填")
+        parser.add_argument("--experiment", default="", help="可选实验 UUID；默认自动生成")
+        parser.add_argument("--execute", action="store_true", help="真正预扣积分并提交任务")
+        parser.add_argument("--report", default="", help="只读查看指定实验 UUID 的任务与结果")
+        parser.add_argument("--export-dir", default="", help="配合 --report 匿名导出 A/B 图片与独立答案文件")
+
+    def handle(self, *args, **opts):
+        if opts["report"]:
+            self._report(opts["report"], opts["export_dir"])
+            return
+
+        from apps.ai.services import resolve_image_model
+        from apps.assets.models import Asset
+        from apps.billing.models import CreditAccount
+        from apps.billing.pricing import quote_flat
+        from apps.products.models import Product
+
+        if not opts["product"] or not opts["model_asset"] or not opts["prompt"].strip():
+            raise CommandError("dry-run/execute 必须提供 --product、--model-asset 和 --prompt")
+
+        product = Product.objects.select_related("team", "created_by", "team__owner").filter(
+            id=opts["product"], purged_at__isnull=True
+        ).first()
+        if product is None:
+            raise CommandError("商品不存在或已清理")
+        model_asset = Asset.objects.filter(
+            id=opts["model_asset"],
+            team=product.team,
+            is_deleted=False,
+            purged_at__isnull=True,
+        ).first()
+        if model_asset is None:
+            raise CommandError("模特肖像不存在、已删除或不属于商品团队")
+        from apps.ai.services import _asset_preview_url, _product_reference_urls
+
+        product_reference_count = len(_product_reference_urls(product, limit=3))
+        if product_reference_count < 1:
+            raise CommandError("商品没有可用的真实参考图，不能执行同输入上身图 A/B")
+        if not _asset_preview_url(model_asset):
+            raise CommandError("模特肖像没有可用图片文件")
+        user = product.created_by or product.team.owner
+        if user is None:
+            raise CommandError("商品团队没有可用于计费的提交用户")
+
+        variants: list[tuple[str, object, Decimal]] = []
+        seen: set[str] = set()
+        for key in opts["variants"]:
+            key = str(key).strip()
+            if not key or key in seen:
+                continue
+            seen.add(key)
+            model = resolve_image_model(key)
+            if model is None:
+                raise CommandError(f"找不到图像模型路由：{key}")
+            quote = quote_flat(model, team=product.team)
+            variants.append((key, model, quote.points))
+        if len(variants) < 2:
+            raise CommandError("A/B 至少需要两个不同模型路由")
+
+        total_points = sum((points * opts["count"] for _, _, points in variants), Decimal("0"))
+        account, _ = CreditAccount.objects.get_or_create(team=product.team)
+        available = account.balance - account.reserved_balance
+        experiment_id = self._experiment_id(opts["experiment"])
+
+        self.stdout.write(f"experiment={experiment_id}")
+        self.stdout.write(
+            f"product={product.id} {product.title} · model_asset={model_asset.id} · "
+            f"product_refs={product_reference_count} · ratio={opts['ratio']} · count/model={opts['count']}"
+        )
+        for key, model, points in variants:
+            self.stdout.write(
+                f"  {key}: {model.provider.name}:{model.name} · {points} 积分/张 · "
+                f"小计 {points * opts['count']}"
+            )
+        self.stdout.write(f"总预算={total_points} 积分 · 当前可用={available} 积分")
+
+        if not opts["execute"]:
+            self.stdout.write(self.style.WARNING("DRY-RUN：未创建任务、未预扣积分；加 --execute --max-points N 才会提交"))
+            return
+
+        max_points = self._max_points(opts["max_points"])
+        if total_points > max_points:
+            raise CommandError(f"预计 {total_points} 积分，超过硬预算 {max_points}，已拒绝提交")
+        if available < total_points:
+            raise CommandError(f"当前可用 {available} 积分，低于预计 {total_points}，已拒绝提交")
+
+        from apps.ai.services import enqueue_standalone_images
+
+        submitted = []
+        for key, model, points in variants:
+            tasks = enqueue_standalone_images(
+                team=product.team,
+                user=user,
+                prompt=opts["prompt"].strip(),
+                mode="model",
+                count=opts["count"],
+                product_id=str(product.id),
+                model_id=str(model_asset.id),
+                model_entity_id=str(opts["model_entity"] or "") or None,
+                ratio=str(opts["ratio"] or "").strip() or None,
+                image_model=key,
+                tryon_prompt_v2_override=True,
+                tryon_ab={"experiment_id": experiment_id, "variant": key},
+                dispatch=False,
+            )
+            submitted.append((key, model, points, tasks))
+
+        for key, model, points, tasks in submitted:
+            batch_id = (tasks[0].request_payload or {}).get("batch_id") if tasks else ""
+            ids = ",".join(str(task.id) for task in tasks)
+            self.stdout.write(
+                self.style.SUCCESS(
+                    f"RESERVED {key} · model={model.provider.name}:{model.name} · "
+                    f"batch={batch_id} · tasks={ids} · reserved={points * len(tasks)}"
+                )
+            )
+
+        # 不投递在线 Worker：它可能仍是未部署 V2 的旧版本。由当前命令进程串行执行，确保代码版本一致。
+        from apps.ai.services import run_standalone_image_task
+
+        for key, model, _points, tasks in submitted:
+            for task in tasks:
+                started = monotonic()
+                run_standalone_image_task(task_id=str(task.id))
+                elapsed = round(monotonic() - started, 3)
+                task.refresh_from_db()
+                payload = dict(task.request_payload or {})
+                ab = dict(payload.get("tryon_ab") or {})
+                ab["elapsed_seconds"] = elapsed
+                payload["tryon_ab"] = ab
+                task.request_payload = payload
+                task.save(update_fields=["request_payload", "updated_at"])
+                assets = ",".join(str(asset.id) for asset in task.generated_assets.all()) or "-"
+                self.stdout.write(
+                    f"FINISHED {key} index={payload.get('index')} status={task.status} "
+                    f"elapsed={elapsed}s actual={task.actual_cost} asset={assets} "
+                    f"error={task.error_code or '-'}"
+                )
+
+    def _max_points(self, raw: str) -> Decimal:
+        if not str(raw or "").strip():
+            raise CommandError("--execute 必须同时提供正数 --max-points")
+        try:
+            value = Decimal(str(raw))
+        except InvalidOperation as exc:
+            raise CommandError("--max-points 必须是数字") from exc
+        if value <= 0:
+            raise CommandError("--max-points 必须大于 0")
+        return value
+
+    def _experiment_id(self, raw: str) -> str:
+        if not str(raw or "").strip():
+            return str(uuid.uuid4())
+        try:
+            return str(uuid.UUID(str(raw)))
+        except ValueError as exc:
+            raise CommandError("--experiment 必须是合法 UUID") from exc
+
+    def _report(self, experiment_id: str, export_dir: str = "") -> None:
+        from apps.ai.models import AITask
+
+        experiment_id = self._experiment_id(experiment_id)
+        tasks = list(
+            AITask.objects.filter(request_payload__tryon_ab__experiment_id=experiment_id)
+            .select_related("model_config", "model_config__provider")
+            .prefetch_related("generated_assets", "generated_assets__files")
+            .order_by("created_at")
+        )
+        if not tasks:
+            raise CommandError("找不到该 A/B 实验")
+        self.stdout.write(f"experiment={experiment_id} · tasks={len(tasks)}")
+        for task in tasks:
+            payload = task.request_payload or {}
+            ab = payload.get("tryon_ab") or {}
+            trace = payload.get("tryon_prompt") or {}
+            assets = ",".join(str(asset.id) for asset in task.generated_assets.all()) or "-"
+            self.stdout.write(
+                f"  {ab.get('variant')} index={payload.get('index')} status={task.status} "
+                f"model={task.model_config.provider.name}:{task.model_config.name} "
+                f"estimated={task.estimated_cost} actual={task.actual_cost} "
+                f"prompt_v2={trace.get('applied')} elapsed={ab.get('elapsed_seconds')}s "
+                f"asset={assets} error={task.error_code or '-'}"
+            )
+        if export_dir:
+            self._blind_export(experiment_id, tasks, export_dir)
+
+    def _blind_export(self, experiment_id: str, tasks: list, export_dir: str) -> None:
+        from apps.ai.services import _asset_preview_url
+
+        output = Path(export_dir).expanduser().resolve()
+        output.mkdir(parents=True, exist_ok=True)
+        variants = sorted({str((task.request_payload.get("tryon_ab") or {}).get("variant") or "") for task in tasks})
+        variants = [variant for variant in variants if variant]
+        if len(variants) < 2:
+            raise CommandError("匿名导出至少需要两个有效 A/B 变体")
+        # 实验 UUID 决定匿名标签顺序；报告正文不输出映射，评分完成后再单独读取 answer_key.json。
+        if uuid.UUID(experiment_id).int % 2:
+            variants.reverse()
+        labels = {variant: chr(ord("A") + index) for index, variant in enumerate(variants)}
+        manifest = {"experiment_id": experiment_id, "samples": []}
+        answer_key = {"experiment_id": experiment_id, "labels": {label: variant for variant, label in labels.items()}}
+
+        for task in tasks:
+            payload = task.request_payload or {}
+            variant = str((payload.get("tryon_ab") or {}).get("variant") or "")
+            label = labels.get(variant)
+            asset = task.generated_assets.first()
+            if not label or asset is None:
+                continue
+            url = _asset_preview_url(asset)
+            if not url:
+                raise CommandError(f"任务 {task.id} 的成图没有可下载地址")
+            primary = asset.files.filter(is_primary=True).first() or asset.files.first()
+            content_type = str(getattr(primary, "content_type", "") or "")
+            suffix = ".jpg" if "jpeg" in content_type else (".webp" if "webp" in content_type else ".png")
+            shot_index = int(payload.get("index") or 0)
+            filename = f"{label}_{shot_index + 1}{suffix}"
+            response = requests.get(url, timeout=60)
+            response.raise_for_status()
+            (output / filename).write_bytes(response.content)
+            manifest["samples"].append(
+                {
+                    "label": label,
+                    "shot_index": shot_index,
+                    "filename": filename,
+                    "task_id": str(task.id),
+                    "asset_id": str(asset.id),
+                }
+            )
+
+        (output / "blind_manifest.json").write_text(
+            json.dumps(manifest, ensure_ascii=False, indent=2), encoding="utf-8"
+        )
+        (output / "answer_key.json").write_text(
+            json.dumps(answer_key, ensure_ascii=False, indent=2), encoding="utf-8"
+        )
+        self.stdout.write(
+            self.style.SUCCESS(
+                f"BLIND_EXPORT samples={len(manifest['samples'])} dir={output} · 评分前不要读取 answer_key.json"
+            )
+        )