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feat: add Atlas Cloud media model gateway
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calesthio
252
scripts/atlas_media_smoke.py
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252
scripts/atlas_media_smoke.py
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"""Run the opt-in paid Atlas Cloud media smoke suite through OpenMontage selectors."""
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from __future__ import annotations
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import argparse
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import json
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import sys
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from pathlib import Path
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from typing import Any
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PROJECT_ROOT = Path(__file__).resolve().parent.parent
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if str(PROJECT_ROOT) not in sys.path:
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sys.path.insert(0, str(PROJECT_ROOT))
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from tools.graphics.image_selector import ImageSelector
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from tools.video.video_selector import VideoSelector
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IMAGE_CASES: tuple[dict[str, Any], ...] = (
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{
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"id": "seedream_campaign_key_visual",
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"skill": "campaign-key-visual",
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"model": "bytedance/seedream-v5.0-pro/text-to-image",
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"prompt": (
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"Create a premium vertical 3:4 campaign key visual for the fictional fragrance LUMA VALE. "
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"One faceted cobalt-glass bottle stands on pale travertine, surrounded by three translucent "
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"mineral ribbons and a single hard-edged pool of amber light. Reserve a calm upper-left field "
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"for exactly the headline LUMA VALE and the smaller line MINERAL LIGHT. Editorial art direction, "
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"precise readable typography, tactile glass, stone pores, controlled shadows, deep cobalt, warm "
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"amber and bone palette, 85mm product lens. No extra copy, duplicate bottle, fake certification, "
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"watermark, illegible letters, clutter, or generic luxury-ad styling. Fictional brand concept."
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),
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"width": 1530,
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"height": 2040,
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"output_format": "png",
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},
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{
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"id": "gpt_image_impossible_material_portrait",
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"skill": "impossible-material-fashion-portrait",
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"model": "openai/gpt-image-2/text-to-image",
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"prompt": (
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"Create a 3:4 editorial fashion portrait of one fictional adult model from the waist up, wearing "
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"a sculptural coat made from translucent smoked quartz that bends like tailored wool while retaining "
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"crystalline fracture planes. The face remains natural and unobstructed; the coat has one high collar, "
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"two sleeves, plausible seams and gravity. Charcoal cyclorama, narrow cool rim light, soft frontal fill, "
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"medium-format 100mm look, realistic skin texture, restrained slate and silver palette. No real-person "
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"likeness, extra limbs, fused hands, jewelry, text, logo, watermark, plastic CGI sheen, or broken anatomy."
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),
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"width": 1536,
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"height": 2048,
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"quality": "high",
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"output_format": "png",
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},
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{
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"id": "nano_banana_bottled_world",
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"skill": "bottled-miniature-world",
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"model": "google/nano-banana-2/text-to-image",
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"prompt": (
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"Create a vertical 3:4 cinematic illustration of one complete clear apothecary bottle on an old walnut "
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"desk, sealed with one rough cork. Inside is one coherent fictional 1:500 moonlit canal village: exactly "
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"one stone observatory, one arched bridge, three cottage clusters, one connected path, dark pines and "
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"warm lanterns, with no people or animals. Prove containment with a visible base, rounded shoulders, neck, "
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"thick rim, wall thickness, curved Fresnel highlights, edge refraction, caustics and tabletop contact. "
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"100mm macro, cool moonlight and warm windows. No duplicated landmark, floating architecture, scale drift, "
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"broken glass, cloudy walls, impossible refraction, label, logo, text, or watermark."
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),
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"width": 1536,
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"height": 2048,
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"resolution": "2k",
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"thinking_level": "high",
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"output_format": "png",
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},
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)
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VIDEO_CASES: tuple[dict[str, Any], ...] = (
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{
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"id": "seedance25_architectural_reveal",
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"skill": "architectural-sketch-to-space-reveal",
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"model": "bytedance/seedance-2.5/text-to-video",
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"prompt": (
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"One continuous ten-second architectural transformation. Begin inches above an architect's graphite "
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"section drawing on cream paper; the camera glides forward as drawn contour lines rise into warm limestone "
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"walls, pencil hatching becomes slatted oak, and a blue wash becomes a shallow reflecting pool. Without a "
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"cut, pass through the drawn doorway into the completed sunlit courtyard while construction lines remain "
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"faintly visible in the finished surfaces. End in a stable wide reveal beneath a circular oculus. Precise "
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"geometry, believable material transition, restrained museum atmosphere, synchronized pencil-scratch and "
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"room-tone audio. No people, captions, logos, teleporting objects, melting walls, jump cuts, or watermark."
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),
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"operation": "text_to_video",
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"duration": 10,
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"resolution": "720p",
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"aspect_ratio": "16:9",
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"generate_audio": True,
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},
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{
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"id": "seedance20_food_fantasy",
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"skill": "food-sensory-fantasy-film",
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"model": "bytedance/seedance-2.0/text-to-video",
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"prompt": (
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"A ten-second macro food fantasy in one fluid shot: an immaculate dark-chocolate sphere rests on black "
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"stone; a ribbon of hot espresso pours from above, the shell cracks cleanly and opens like petals, releasing "
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"a miniature saffron cloud and dozens of bright ruby pomegranate seeds that bounce with believable weight. "
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"The camera makes a slow 120-degree orbit and settles on the glossy molten center. High-speed detail, real "
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"fluid viscosity, crisp crumbs, appetizing steam, warm copper highlights, synchronized pour/crack/bounce audio. "
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"No hands, utensils, text, brand, duplicate fruit, dirty surface, implausible splash, jump cut, or watermark."
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),
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"operation": "text_to_video",
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"duration": 10,
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"resolution": "720p",
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"aspect_ratio": "16:9",
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"generate_audio": True,
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},
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{
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"id": "gemini_omni_greenhouse_take",
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"skill": "generated-continuous-take",
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"model": "google/gemini-omni-flash/text-to-video",
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"prompt": (
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"One unbroken ten-second Steadicam journey through a vast night greenhouse during a gentle storm. Start "
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"tight on rain sliding down one glass pane, pull backward through hanging vines, descend beside a narrow "
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"irrigation channel, then curve around a gardener's empty brass cart as hundreds of bioluminescent blue "
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"flowers open in a timed wave toward the lens. Finish at a wide symmetrical view of the glowing conservatory. "
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"Continuous geography and lighting, foreground occlusion motivates the move, realistic wet leaves and glass, "
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"subtle rain and metal resonance. No people, hidden cuts, camera collision, duplicated cart, text, or watermark."
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),
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"operation": "text_to_video",
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"duration": 10,
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"resolution": "720p",
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"aspect_ratio": "16:9",
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"thinking_level": "high",
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},
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{
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"id": "minimax_h3_creature_encounter",
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"skill": "creature-encounter-film",
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"model": "minimax/h3/text-to-video",
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"prompt": (
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"A ten-second cinematic wildlife encounter on a wind-scoured volcanic plateau at dawn. A small six-legged "
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"fictional basalt creature sprints beside the low tracking camera; each footfall kicks loose pumice with "
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"convincing mass. At second four it leaps across a narrow fissure, folds its stone plates midair, lands hard, "
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"slides, and braces while a sheet of dust overtakes the lens. The camera eases to a stop as the creature turns "
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"one luminous amber eye toward us. One continuous shot, consistent anatomy and scale, strong contact shadows, "
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"real inertia and debris physics. No attack, gore, extra creature, morphing limbs, text, logo, cut, or watermark."
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),
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"operation": "text_to_video",
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"duration": 10,
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"resolution": "2K",
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"aspect_ratio": "16:9",
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},
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)
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def _result_record(case: dict[str, Any], result: Any) -> dict[str, Any]:
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return {
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"id": case["id"],
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"skill": case["skill"],
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"model": case["model"],
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"success": result.success,
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"error": result.error,
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"artifacts": result.artifacts,
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"cost_usd": result.cost_usd,
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"data": result.data,
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}
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def run(project_dir: Path, *, images: bool, videos: bool, allow_paid: bool) -> int:
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if not allow_paid:
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raise SystemExit("Refusing paid Atlas calls without --allow-paid")
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project_dir.mkdir(parents=True, exist_ok=True)
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manifest_path = project_dir / "smoke_manifest.json"
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records: list[dict[str, Any]] = []
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if manifest_path.exists():
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previous = json.loads(manifest_path.read_text(encoding="utf-8"))
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records = [record for record in previous.get("records", []) if record.get("success")]
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def checkpoint() -> None:
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manifest = {
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"provider": "atlascloud",
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"endpoint_policy": "OpenMontage selectors -> Atlas Cloud tools -> Atlas Cloud HTTP API",
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"estimated_batch_cost_usd": 4.844,
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"records": records,
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"success": len({record["id"] for record in records if record["success"]}) == len(IMAGE_CASES) + len(VIDEO_CASES),
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}
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manifest_path.write_text(json.dumps(manifest, indent=2), encoding="utf-8")
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completed_ids = {record["id"] for record in records}
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if images:
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selector = ImageSelector()
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for case in IMAGE_CASES:
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if case["id"] in completed_ids:
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continue
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inputs = {
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**case,
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"preferred_provider": "atlascloud",
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"allowed_providers": ["atlascloud"],
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"generation_mode": "generate",
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"output_path": str(project_dir / "images" / f"{case['id']}.png"),
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}
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inputs.pop("id")
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inputs.pop("skill")
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result = selector.execute(inputs)
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records.append(_result_record(case, result))
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checkpoint()
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if not result.success:
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break
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if videos and all(record["success"] for record in records):
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selector = VideoSelector()
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for case in VIDEO_CASES:
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if case["id"] in completed_ids:
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continue
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inputs = {
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**case,
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"preferred_provider": "atlascloud",
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"allowed_providers": ["atlascloud"],
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"output_path": str(project_dir / "videos" / f"{case['id']}.mp4"),
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}
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inputs.pop("id")
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inputs.pop("skill")
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result = selector.execute(inputs)
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records.append(_result_record(case, result))
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checkpoint()
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if not result.success:
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break
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checkpoint()
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manifest = json.loads(manifest_path.read_text(encoding="utf-8"))
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print(json.dumps({
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"success": manifest["success"],
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"manifest": str(manifest_path),
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"results": [{"id": item["id"], "success": item["success"], "error": item["error"]} for item in records],
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}, indent=2))
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return 0 if manifest["success"] else 1
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def main() -> int:
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parser = argparse.ArgumentParser()
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parser.add_argument("--project-dir", type=Path, required=True)
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parser.add_argument("--images-only", action="store_true")
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parser.add_argument("--videos-only", action="store_true")
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parser.add_argument("--allow-paid", action="store_true")
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args = parser.parse_args()
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return run(
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args.project_dir,
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images=not args.videos_only,
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videos=not args.images_only,
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allow_paid=args.allow_paid,
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)
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if __name__ == "__main__":
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raise SystemExit(main())
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