Production source excerpts. These document the implementation; they are not a complete standalone build kit.

replicate-ending.py
Source SHA-256: 8b6c1d1c47087996d7a23d245de8dd597d3cbc26e23240a0bf64d853009a622f
Starting source line: 48

elif args.action=='submit':
    assert path and not path.exists(),'Attempt number must be new; never re-submit after an unknown outcome.'
    previous=[load(p) for p in OUT.glob('attempt-*.json')]
    assert len(previous)<plan['max_attempts']
    assert all(p.get('submission_state')!='unknown' for p in previous)
    assert all(p.get('prediction',{}).get('status') in ('succeeded','failed','canceled') for p in previous)
    estimate=plan['input']['duration']*plan['usd_per_second']
    assert sum(p['reserved_usd'] for p in previous)+estimate<=plan['total_cap_usd']
    assert plan['paid_execution_allowed'] and estimate<=2
    schema=load(OUT/'model-input-schema.json')
    inputs={**plan['input'],'prompt':(OUT/'prompt.txt').read_text(encoding='utf-8'),
            'image':uri(OUT/plan['first_frame']),'last_frame_image':uri(OUT/plan['last_frame'])}
    assert set(inputs)<=set(schema['properties']),set(inputs)-set(schema['properties'])
    inputs['seed']+=args.attempt-1
    receipt={'attempt':args.attempt,'reserved_usd':estimate,'budget_cap_usd':plan['total_cap_usd'],
             'submission_state':'unknown','created_at':datetime.now(timezone.utc).isoformat(),
             'model':plan['model'],'duration':inputs['duration'],'resolution':inputs['resolution']}
    persist(path,receipt)
    prediction=client.request('/models/'+plan['model']+'/predictions','POST',{'input':inputs})
    receipt.update(submission_state='accepted',prediction=client.save_prediction(OUT/f'prediction-{args.attempt:02}.json',prediction))
    persist(path,receipt)
    print(json.dumps({'attempt':args.attempt,'id':prediction['id'],'status':prediction['status'],'reserved_usd':estimate}))


grade-greenhouse.py
Source SHA-256: ae94915ce5de4b0124613e2546cdb71c078c48d637758f6dab2fd72d90ebcdfd
Starting source line: 25

# Derive the look once from the people-and-tomatoes image, then lock it.
original, corrected = pixels(source), pixels(reference)
percentiles = (0, 8, 25, 50, 75, 92, 100)
points = []
for channel in range(3):
    x = np.percentile(original[:,:,channel], percentiles)/255
    y = np.percentile(corrected[:,:,channel], percentiles)/255
    x[0],y[0],x[-1],y[-1] = 0,0,1,1
    points.append([(round(float(a),6),round(float(b),6)) for a,b in zip(x,y)])
filter_text = 'curves='+':'.join(f"{name}='"+' '.join(f'{x}/{y}' for x,y in values)+"'"
                               for name,values in zip('rgb',points))
manifest = {'method':'One common ffmpeg RGB curve for all three original video plates.',
            'look_reference':str(reference), 'filter':filter_text,
            'locked_curve_points':dict(zip('rgb',points)), 'plates':{},
            'regenerated_match_attempts':'Retained separately; not used because colour checks showed more background drift.'}
for name in ('original','tomatoes','no-people'):
    path = ASSETS/f'greenhouse-{name}.png'
    movie = OUT/f'{name}.mkv'
    subprocess.run(['ffmpeg','-hide_banner','-loglevel','error','-y','-i',str(path),
                    '-vf',filter_text+',scale=1920:1080:flags=lanczos',
                    '-frames:v','1','-c:v','ffv1','-pix_fmt','bgr0',str(movie)],check=True)
    manifest['plates'][name]={'video':str(movie),
                              'source_sha256':hashlib.sha256(path.read_bytes()).hexdigest(),
                              'same_filter':True}


score.py
Source SHA-256: 277429c2c6929a8a7417b2068e4235c2dd80985fba05874dc06a722dd28d2248
Starting source line: 34

# An authored four-chord cycle, with sparse upper notes and long soft envelopes.
chords=[(50,57,60,65,69),(53,60,64,67,72),(48,55,60,62,67),(43,50,57,60,65)]
for bar,start in enumerate(np.arange(0,SECONDS,6.0)):
    chord=chords[bar%4]
    for i,note in enumerate(chord):add(tone(note,8,.0065,pad=True),float(start),(-.45+i*.22))
    for step,offset in enumerate((.75,3.0,4.5)):
        note=chord[(bar+step*2)%len(chord)]+12
        add(tone(note,3.8,.012),float(start+offset),(-.35,.35,.05)[step])



verify-export.py
Source SHA-256: cb5ffa15a5e2a1ea375054299bed81caf32949a3d9f2625f918ffcb064ba54ad
Starting source line: 20

probe=json.loads(subprocess.check_output(['ffprobe','-v','error','-show_streams','-show_format','-of','json',str(movie)],text=True))
video=next(s for s in probe['streams'] if s['codec_type']=='video')
audio=next(s for s in probe['streams'] if s['codec_type']=='audio')
assert (video['width'],video['height'],video['r_frame_rate'])==(1920,1080,'24/1')
assert int(video['nb_frames'])==round(settings['seconds']*settings['fps'])
assert abs(float(probe['format']['duration'])-settings['seconds'])<.05
assert int(audio['sample_rate'])==48000 and audio['channels']==2
decode=subprocess.run(['ffmpeg','-hide_banner','-i',str(movie),'-af','loudnorm=I=-27:TP=-2:LRA=9:print_format=json','-f','null','-'],capture_output=True,text=True)
assert decode.returncode==0,decode.stderr[-2000:]
match=re.search(r'\{\s*"input_i".*?\}',decode.stderr,re.S)
assert match,'Audio measurement was not returned'
levels=json.loads(match[0])
assert abs(float(levels['input_i'])+27)<1.0,levels
assert float(levels['input_tp']) < -1,levels


record.py
Source SHA-256: c6b9fee090b239bf941a413c755ed94968702d84c49a55f7401b0a4e7b7c68a0
Starting source line: 36

        if 'title' in update:
            entry = {'at':at, 'title':update['title'], 'body':update.get('body', '')}
            data['history'].insert(0, entry)
            with (ROOT / 'production' / 'journal.jsonl').open('a', encoding='utf-8') as journal:
                journal.write(json.dumps(entry, ensure_ascii=False) + '\n')


review_utils.py
Source SHA-256: d97eb8c2b15c79d6783092c5e1d4ce929a30cd23873faea3c8e30b33313f65bf
Starting source line: 33

def opening_hashes(revision):
    raw = subprocess.check_output(['ffmpeg','-v','error','-i',str(ROOT/f'landscape-rough-cut-{revision}.mp4'),
        '-t','4','-map','0:v:0','-f','framemd5','-'], text=True)
    return [line.rsplit(',',1)[1].strip() for line in raw.splitlines() if line and not line.startswith('#')]


cut-visuals-10.py
Source SHA-256: b768634d67c4179bcbe884cf9c2b258eba97ecf99327bf61224d498916d5513b

STARTS = dict(splash=0, opening=120, camera_request=360, camera=528, greenhouse=744,
    bees=1032, game_request=1354, game=1416, loom_request=1524, loom=1596,
    loom_overhead=1812, butterfly_request=1872, photo=1944, construction=1980,
    flight=2232, video_request=2472, recap=2640, closing=2928, site_tour=3072,
    credits=3600, end=3744)


polish_style.py
Source SHA-256: 6587c6ecae243809411fb5d4531b18629382d4303abb35865df4c75837132688

def lettering(layer, value, xy, size, width=1696, bold=False, serif=False, colour=CREAM):
    """Never shrink text to fit; fail if approved sizes exceed the safe frame."""
    draw = ImageDraw.Draw(layer)
    face = font(size, bold, serif)
    rows = lines(value, size, width, bold, serif)
    boxes = []
    for i, row in enumerate(rows):
        point = (xy[0], xy[1] + i * (size + 17))
        box = draw.textbbox(point, row, font=face, anchor='lt')
        assert box[0] >= MARGIN_X and box[2] <= W - MARGIN_X, (value, box)
        assert box[1] >= MARGIN_Y and box[3] <= H - MARGIN_Y, (value, box)
        draw.text(point, row, font=face, fill=colour, anchor='lt')
        boxes.append(box)
    LAYOUT_AUDIT[(value, size, xy)] = dict(text=value, size=size, boxes=boxes, safe=True)
    return len(rows) * (size + 17) - 17


native_sources.py
Source SHA-256: a1cf8598d541c27dd0278ac438af8fe474227a445c817ea02c1b96ad1c07e8f8

def construction(t):
    source_tick = min(275, round(int(t * 24) * 276 / 252))
    source_t = source_tick / 24
    plate = load(str(PROD / 'butterfly/local-motion-05/construction' / f'frame-{source_tick + 1:04}.png'))
    plate = plate.resize((1000, 1000), Image.Resampling.LANCZOS)
    match = smooth((source_t - 9.85) / .95)
    if match:
        original = load(str(PROD / 'assets/butterfly-source.jpg')).resize((1000, 1000), Image.Resampling.LANCZOS)
        plate = Image.blend(plate, original, match)
    image = Image.new('RGB', (W, H), DARK)
    image.paste(plate, (850, 40))
    index = max(i for i, (start, _) in enumerate(STAGES) if source_t >= start)
    lettering(image, 'Build in Blender.', (128, 128), SUPPORT, width=650)
    lettering(image, STAGES[index][1], (128, 360), EDIT, width=650, serif=True)
    lettering(image, 'Photograph →\nBlender → photograph', (128, 650), SUPPORT, width=650)
    draw = ImageDraw.Draw(image)
    for i in range(len(STAGES)):
        draw.rounded_rectangle((128 + i * 61, 875, 172 + i * 61, 883), radius=3, fill=GOLD if i <= index else '#3a5147')
    return image


opening_sound.py
Source SHA-256: d2617514055d3c2e857c46d76cab4a26c99cb1cf51682d9ec2459c7465165ba1

"""A locally authored fast-forward texture; never changes the master score."""
import json
import subprocess
import wave
from pathlib import Path

import numpy as np

RATE = 48000
SECONDS = 12
STOP = 5


def smooth(values):
    values = np.clip(values, 0, 1)
    return values * values * (3 - 2 * values)


def write_wave(path, samples):
    with wave.open(str(path), 'wb') as output:
        output.setnchannels(2)
        output.setsampwidth(2)
        output.setframerate(RATE)
        output.writeframes((np.clip(samples, -1, 1) * 32767).astype('<i2').tobytes())


def prepare(source: Path, destination: Path):
    """Use decoded final-release audio so the comparison keeps its actual gain."""
    raw = subprocess.check_output(['ffmpeg', '-v', 'error', '-i', str(source),
        '-t', str(SECONDS), '-map', '0:a:0', '-f', 'f32le', '-ar', str(RATE),
        '-ac', '2', '-'])
    baseline = np.frombuffer(raw, dtype='<f4').reshape(-1, 2).copy()
    assert baseline.shape == (RATE * SECONDS, 2)
    count = RATE * STOP
    time = np.arange(count) / RATE
    generator = np.random.default_rng(20261016)
    noise = generator.standard_normal(count)
    # Band-limited air with a dry, accelerating transport flutter. No samples,
    # melody, voice, API calls, or high-pitched rewind whistle are used.
    spectrum = np.fft.rfft(noise)
    frequency = np.fft.rfftfreq(count, 1 / RATE)
    band = (frequency / 240) ** 2 / (1 + (frequency / 240) ** 2)
    band /= 1 + (frequency / 3400) ** 6
    air = np.fft.irfft(spectrum * band, count)
    air /= np.sqrt(np.mean(air ** 2))
    phase = 2 * np.pi * (18 * time + 2.8 * time ** 2)
    flutter = (.16 + .84 * (.5 + .5 * np.sin(phase)) ** 3)
    level = .0105 * (.8 + .2 * time / STOP)
    envelope = smooth(time / .045) * smooth((STOP - time) / .012)
    transport = air * flutter * level * envelope
    transport *= .036 / np.sqrt(np.mean(transport ** 2))
    transport = .12 * np.tanh(transport / .12)
    # Subtle stereo movement, with both channels stopping together at 5.000 s.
    effect = np.stack((transport, np.roll(transport, 83)), axis=1)
    effect *= envelope[:, None]
    times = np.arange(len(baseline)) / RATE
    bed_gain = .28 + .72 * smooth((times - 4.99) / .16)
    proposed = baseline * bed_gain[:, None]
    proposed[:count] += effect
    assert np.array_equal(proposed[round(5.15 * RATE):], baseline[round(5.15 * RATE):])
    assert np.max(np.abs(proposed)) < .9
    write_wave(destination / 'opening-a-current.wav', baseline)
    write_wave(destination / 'opening-b-fast-forward.wav', proposed)
    isolated = np.zeros_like(baseline)
    isolated[:count] = effect
    write_wave(destination / 'fast-forward-effect.wav', isolated)
    manifest = dict(seconds=SECONDS, sample_rate=RATE, channels=2,
        source='Decoded audio of the released revision 10; original gain retained.',
        effect='Original NumPy band-limited noise with accelerating transport flutter.',
        effect_stop_seconds=STOP, fade_out_seconds=.012,
        calm_bed_gain_during_splash=.28, calm_bed_restored_seconds=5.15,
        samples_after_5_15_seconds_equal=True, paid_calls=0,
        a_peak=float(np.max(np.abs(baseline))),
        b_peak=float(np.max(np.abs(proposed))),
        effect_rms=float(np.sqrt(np.mean(effect ** 2))),
        source_splash_rms=float(np.sqrt(np.mean(baseline[:count] ** 2))),
        proposed_splash_rms=float(np.sqrt(np.mean(proposed[:count] ** 2))),
        status='Private opening proof only; not mixed into the complete reel.')
    (destination / 'audio-method.json').write_text(json.dumps(manifest, indent=2), encoding='utf-8')
    return manifest


build-final-12.py
Source SHA-256: 7aa2576afb1d6cb963e4a9a45298034f5b7c4529c113703051886ba68d503201

SUPPORT = 'Describe what you want to make.\nLet the agent work out how.'
HEADING = 'The tools Codex put to work.'
COPY = read(PROD / 'on-screen-copy-10.json')
COPY['opening'][0]['support'] = SUPPORT
COPY['credit_heading'] = HEADING
COPY['credit_rows'] = list(ROWS)