backup
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Concept Agent
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"""
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Regenerate carpet extraction shots using Veo 3.1.
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Fixes: buffer/rotary/steamer machines replaced with explicit stand-up extractor descriptions.
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Reconcats hero-reel.mp4 when done.
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Run: python3 tools/regen-veo31.py
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"""
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import os, sys, time, subprocess
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try:
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from google import genai
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from google.genai import types
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except ImportError:
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os.system(f"{sys.executable} -m pip install google-genai --quiet")
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from google import genai
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from google.genai import types
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API_KEY = os.environ.get("GEMINI_API_KEY", "AIzaSyB_1p8KvaT_rdNJGPs8HKk8bKsvUlcL6Kg")
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BASE_DIR = os.path.dirname(os.path.dirname(__file__))
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VID_DIR = os.path.join(BASE_DIR, "assets", "videos", "hero", "clips")
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REEL_OUT = os.path.join(BASE_DIR, "assets", "videos", "hero", "hero-reel.mp4")
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client = genai.Client(api_key=API_KEY)
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# Machine description block used across all shots
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MACHINE = (
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"The carpet cleaning machine looks exactly like a Rug Doctor or Bissell Big Green carpet cleaner — "
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"the large upright machines you rent at grocery stores. Tall rectangular body, upright handle, "
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"wide flat cleaning foot at the base. It is pushed forward in straight lines like a vacuum cleaner. "
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"NOT a floor buffer. NOT a rotary disc scrubber. NOT a steam cleaner. NOT circular. "
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"NO spinning parts. NO steam. NO water spraying out. The carpet is cleaned by suction alone."
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)
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SHOTS = [
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{
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"name": "shot-04-extraction-carpet",
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"prompt": (
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f"Cinematic slow-motion wide shot. A man pushes a Rug Doctor style carpet cleaning machine "
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f"steadily forward across a beige residential carpet in a living room. {MACHINE} "
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f"The carpet behind the machine transitions from dirty and matted to bright, clean, and fluffy. "
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f"Warm natural room light. Photorealistic professional video."
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),
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},
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{
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"name": "shot-05-extraction-couch",
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"prompt": (
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"Close-up cinematic slow-motion shot. A professional technician's gloved hand holds a small "
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"flat handheld upholstery cleaning attachment — a rectangular suction wand, flat on the bottom, "
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"no moving parts, no spinning disc. "
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"The technician presses it firmly against a dirty grey sofa cushion and slides it slowly across. "
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"The fabric visibly brightens as the wand moves across it. "
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"NO rotary machine anywhere in frame. NO spinning. NO steam. NO water pouring out. "
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"Natural light. Photorealistic."
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),
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},
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{
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"name": "shot-06-extraction-stairs",
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"prompt": (
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"Cinematic slow-motion shot. A professional technician pushes a Rug Doctor style upright carpet "
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"cleaning machine up a carpeted residential staircase, one stair tread at a time. "
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"The machine is a tall rectangular upright unit with a handle and flat cleaning head — "
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"NOT a buffer, NOT circular, NOT rotating. "
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"Each stair tread brightens and looks freshly cleaned as the machine passes over it. "
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"NO steam, NO water visible. Warm interior light. Photorealistic."
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),
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},
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{
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"name": "shot-09-technician-unloading",
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"prompt": (
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f"Wide cinematic shot. A professional carpet cleaning technician in a plain black shirt "
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f"rolls a Rug Doctor style carpet cleaning machine down a ramp out of a white service van "
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f"parked in a residential driveway in upstate New York. {MACHINE} "
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f"Autumn trees in background, bright daylight. "
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f"Technician shown from the side or behind, no face visible. Photorealistic."
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),
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},
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]
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MODEL = "veo-3.1-generate-preview"
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def poll(op, timeout=600):
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elapsed = 0
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while not op.done:
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if elapsed >= timeout:
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print(f" Timed out after {timeout}s.")
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return None
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print(f" Waiting... ({elapsed}s)")
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time.sleep(15)
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elapsed += 15
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op = client.operations.get(op)
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return op
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saved = []
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for item in SHOTS:
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out_path = os.path.join(VID_DIR, f"{item['name']}.mp4")
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print(f"\n[VID] Generating {item['name']} with {MODEL}...")
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try:
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op = client.models.generate_videos(
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model=MODEL,
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prompt=item["prompt"],
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config=types.GenerateVideosConfig(
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aspect_ratio="16:9",
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resolution="720p",
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duration_seconds=6,
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number_of_videos=1,
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),
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)
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op = poll(op)
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if op is None:
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print(f" FAILED (timeout): {item['name']}")
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continue
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if op.response and op.response.generated_videos:
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vid = op.response.generated_videos[0].video
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# Veo 3.1 download pattern
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video_bytes = client.files.download(file=vid)
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if video_bytes:
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with open(out_path, "wb") as f:
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f.write(video_bytes)
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print(f" Saved {out_path} ({os.path.getsize(out_path)//1024}KB)")
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saved.append(item["name"])
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else:
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# fallback: try .save() method
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try:
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vid.save(out_path)
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print(f" Saved via .save() ({os.path.getsize(out_path)//1024}KB)")
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saved.append(item["name"])
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except Exception as e2:
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print(f" Download failed: {e2}")
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else:
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print(f" No video returned for {item['name']}")
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except Exception as e:
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print(f" Error: {e}")
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print(f"\n{len(saved)}/{len(SHOTS)} shots saved: {saved}")
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# Reconcat full reel
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ORDER = [
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"shot-01-door-opens-trimmed",
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"shot-02-pan-to-stains",
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"shot-03-stain-closeup",
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"shot-04-extraction-carpet",
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"shot-05-extraction-couch",
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"shot-06-extraction-stairs",
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"shot-07-office-entryway",
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"shot-08-showroom",
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"shot-09-technician-unloading",
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]
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missing = [n for n in ORDER if not os.path.exists(os.path.join(VID_DIR, f"{n}.mp4"))]
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if missing:
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print(f"\nSkipping reconcat — missing clips: {missing}")
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else:
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print("\nReconcatenating hero-reel.mp4...")
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concat_file = os.path.join(VID_DIR, "concat.txt")
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with open(concat_file, "w") as f:
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for name in ORDER:
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f.write(f"file '{os.path.join(VID_DIR, name)}.mp4'\n")
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result = subprocess.run(
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["ffmpeg", "-y", "-f", "concat", "-safe", "0", "-i", concat_file,
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"-c:v", "libx264", "-crf", "22", "-preset", "fast",
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"-movflags", "+faststart", REEL_OUT],
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capture_output=True, text=True
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)
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if result.returncode == 0:
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print(f" Reel saved: {REEL_OUT} ({os.path.getsize(REEL_OUT)//1024}KB)")
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else:
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print(f" ffmpeg error: {result.stderr[-400:]}")
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print("\nDone.")
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