lahrcarpetcleaning.com/tools/regen-v3.py

"""
Hero reel v3 — 7 shots with corrected prompts.
"""
import os, sys, time, subprocess

try:
    from google import genai
    from google.genai import types
except ImportError:
    os.system(f"{sys.executable} -m pip install google-genai --quiet")
    from google import genai
    from google.genai import types

API_KEY  = os.environ.get("GEMINI_API_KEY", "AIzaSyB_1p8KvaT_rdNJGPs8HKk8bKsvUlcL6Kg")
BASE_DIR = os.path.dirname(os.path.dirname(__file__))
VID_DIR  = os.path.join(BASE_DIR, "assets", "videos", "hero", "clips")
REEL_OUT = os.path.join(BASE_DIR, "assets", "videos", "hero", "hero-reel.mp4")
os.makedirs(VID_DIR, exist_ok=True)
client   = genai.Client(api_key=API_KEY)

SHOTS = [
    {
        "name": "v3-shot-01",
        "prompt": (
            "Medium shot. A family of four — two adults and two children — walks through the front door "
            "of a warm residential home. Camera is inside the home facing them as they enter. "
            "After they walk in, the camera slowly pans down to the carpet, revealing dirty footprints "
            "and mud tracked onto the beige carpet. Warm natural light. Photorealistic."
        ),
    },
    {
        "name": "v3-shot-02",
        "prompt": (
            "Medium shot, slow zoom in. A glass of red wine has spilled onto a light grey upholstered sofa. "
            "The camera starts wide on the sofa then slowly zooms in on the dark wine stain spreading "
            "across the fabric. The stain is clearly visible, soaked into the cushion. "
            "Warm living room light. No people. Photorealistic."
        ),
    },
    {
        "name": "v3-shot-03",
        "prompt": (
            "Medium shot at low angle, camera near floor level. Inside a bright commercial office entryway. "
            "A person wearing work boots walks through the entry door toward the camera and past it. "
            "The camera is low, showing the boots and lower legs as they walk across the carpet past the lens. "
            "Office carpet visible, natural light from glass doors behind. Photorealistic."
        ),
    },
    {
        "name": "v3-shot-04",
        "prompt": (
            "Close-up cinematic shot. A technician's gloved hand holds a small upholstery extraction wand — "
            "a flat rectangular handheld tool. The technician presses the wand firmly onto a wine-stained "
            "sofa cushion and draws it slowly across the fabric. The stain visibly lifts as the wand moves. "
            "Suction only — no water sprays out. Slow motion. Natural light. Photorealistic."
        ),
    },
    {
        "name": "v3-shot-05",
        "prompt": (
            "Wide cinematic shot. Camera slowly pans across the entrance of a modern commercial office building. "
            "Clean grey commercial carpet stretches across the lobby floor. Large windows, glass doors, "
            "professional lighting. The carpet looks freshly cleaned and spotless. "
            "No people. No machines. Photorealistic."
        ),
    },
    {
        "name": "v3-shot-06",
        "prompt": (
            "Wide cinematic shot. Camera slowly pans across a bright, clean residential living room. "
            "Plush clean beige carpet throughout. Comfortable furniture — sofa, armchairs, coffee table. "
            "Warm natural afternoon light through large windows. The room looks fresh and inviting. "
            "No people. No cleaning equipment. Photorealistic."
        ),
    },
    {
        "name": "v3-shot-07",
        "prompt": (
            "Wide cinematic shot. Camera moves slowly forward through an upscale restaurant dining room. "
            "Rich carpet covers the floor. White tablecloths, warm ambient lighting, wood accents. "
            "The carpet looks clean, deep, and well-maintained as the camera glides through the space. "
            "No people. Photorealistic, luxurious atmosphere."
        ),
    },
]

MODEL = "veo-3.1-generate-preview"

def poll(op, timeout=600):
    elapsed = 0
    while not op.done:
        if elapsed >= timeout:
            return None
        print(f"  Waiting... ({elapsed}s)")
        time.sleep(15)
        elapsed += 15
        op = client.operations.get(op)
    return op

saved = []
for i, item in enumerate(SHOTS):
    out_path = os.path.join(VID_DIR, f"{item['name']}.mp4")
    print(f"\n[{i+1}/{len(SHOTS)}] {item['name']}...")
    try:
        op = client.models.generate_videos(
            model=MODEL,
            prompt=item["prompt"],
            config=types.GenerateVideosConfig(
                aspect_ratio="16:9", resolution="720p",
                duration_seconds=6, number_of_videos=1,
            ),
        )
        op = poll(op)
        if op and op.response and op.response.generated_videos:
            vid = op.response.generated_videos[0].video
            video_bytes = client.files.download(file=vid)
            if video_bytes:
                with open(out_path, "wb") as f:
                    f.write(video_bytes)
                print(f"  Saved ({os.path.getsize(out_path)//1024}KB)")
                saved.append(out_path)
            else:
                try:
                    vid.save(out_path)
                    print(f"  Saved via .save()")
                    saved.append(out_path)
                except Exception as e2:
                    print(f"  Download failed: {e2}")
        else:
            print(f"  No video returned")
    except Exception as e:
        print(f"  Error: {e}")

print(f"\n{len(saved)}/{len(SHOTS)} shots saved")

if len(saved) >= 2:
    concat_file = os.path.join(VID_DIR, "concat-v3.txt")
    clips = [os.path.join(VID_DIR, f"{s['name']}.mp4") for s in SHOTS
             if os.path.exists(os.path.join(VID_DIR, f"{s['name']}.mp4"))]
    with open(concat_file, "w") as f:
        for p in clips:
            f.write(f"file '{p}'\n")
    result = subprocess.run(
        ["ffmpeg", "-y", "-f", "concat", "-safe", "0", "-i", concat_file,
         "-c:v", "libx264", "-crf", "22", "-preset", "fast", "-movflags", "+faststart", REEL_OUT],
        capture_output=True, text=True
    )
    if result.returncode == 0:
        print(f"  Reel saved ({os.path.getsize(REEL_OUT)//1024}KB)")
    else:
        print(f"  ffmpeg error: {result.stderr[-300:]}")

print("\nDone.")