text stringlengths 3 8.33k | repo stringclasses 52
values | path stringlengths 6 141 | language stringclasses 35
values | sha stringlengths 64 64 | chunk_index int32 0 273 | n_tokens int32 1 896 |
|---|---|---|---|---|---|---|
from __future__ import annotations
import logging
from pathlib import Path
from elevenlabs import ElevenLabs
logger = logging.getLogger(__name__)
class VoiceChanger:
def __init__(
self,
api_key: str,
model_id: str = "eleven_multilingual_sts_v2",
):
self.client = ElevenLabs(a... | ai-video | scripts/audio/voice_changer.py | Python | 7155f59c509edb9a42206482d895c70909f7906c3c005d1d9157c2d4247bffd7 | 0 | 553 |
from __future__ import annotations
import base64
import logging
from pathlib import Path
from elevenlabs import ElevenLabs
from scripts.core.models import VoiceProfile
logger = logging.getLogger(__name__)
class VoiceDesigner:
def __init__(self, api_key: str):
self.client = ElevenLabs(api_key=api_key)
... | ai-video | scripts/audio/voice_designer.py | Python | a5b2f92dad93627a0a974ffc1c3d3912a6fec3ae3ad0ca244070cf57f36077e6 | 0 | 707 |
from __future__ import annotations
import hashlib
import json
import logging
import re
import shutil
from datetime import datetime
from pathlib import Path
from .models import CharacterIdentity, CharacterProfile, VoiceProfile
logger = logging.getLogger(__name__)
def _slugify(text: str) -> str:
"""Convert *text... | ai-video | scripts/core/character_store.py | Python | 9a30073b95ef2243b936bf48ddb770fd05bd3a6ac14e89132b5f6e869830ea88 | 0 | 896 |
):
return characters
for entry in sorted(self.characters_dir.iterdir()):
identity_file = entry / "identity.json"
if entry.is_dir() and identity_file.exists():
try:
characters.append(self.load(entry.name))
except Exception as... | ai-video | scripts/core/character_store.py | Python | d02234561004189741109c1fcef4c154d71342a7e876195f9e90d57e5dc64609 | 1 | 896 |
-------------------------------------------------
def get_voice_id(self, character_id: str) -> str | None:
"""Return the cached ElevenLabs voice ID, or ``None``."""
voice_file = self.characters_dir / character_id / "voice" / "voice_id.txt"
if voice_file.exists():
return voice_fi... | ai-video | scripts/core/character_store.py | Python | f66cab38df2a1c1c2e8062d2de0226f96cdeec4d706831ee7755b7fed23213ae | 2 | 603 |
from __future__ import annotations
import json
import logging
from datetime import datetime
from pathlib import Path
from typing import Any
from .models import Checkpoint, CostEntry, ProjectState, StageStatus
logger = logging.getLogger(__name__)
class CheckpointManager:
def __init__(self, project_dir: Path):
... | ai-video | scripts/core/checkpoint.py | Python | 9d47fc1b6505d2b3bcadde207ab0a37cba093d0fcaa0363a48cccc0e78e5b58a | 0 | 833 |
from __future__ import annotations
import json
import logging
import os
from pathlib import Path
from dotenv import load_dotenv
from .models import ProjectConfig
logger = logging.getLogger(__name__)
_ROOT = Path(__file__).resolve().parent.parent.parent
class ConfigManager:
def __init__(self, project_dir: Pat... | ai-video | scripts/core/config_manager.py | Python | 67dd69c46b66bd37a8654b954b706b0898c79bad77d319d41af295ac628718fd | 0 | 896 |
-specific keys found.
"""
keys: list[str] = []
# Try numbered Veo keys first
i = 1
while True:
key_name = f"VEO_API_KEY_{i}"
key_value = os.environ.get(key_name)
if not key_value:
break
keys.append(key_value... | ai-video | scripts/core/config_manager.py | Python | 2b4767e943c9207495c0bf318bfc65031e6a805f118ab319df43d997787c0d75 | 1 | 111 |
"""Project-wide constants and defaults.
This module centralizes magic numbers and configuration defaults
used throughout the AI video pipeline.
"""
from __future__ import annotations
# =============================================================================
# Audio Processing
# ==================================... | ai-video | scripts/core/constants.py | Python | 4aa061fcbaa990b05019d4981eedb7667b9582e570a76bcbabdc3749a50ab489 | 0 | 896 |
======================================
# Remotion Graphics
# =============================================================================
INTRO_DURATION_SECONDS = 5.0
OUTRO_OFFSET_SECONDS = 8.0
CHAPTER_CARD_DURATION_SECONDS = 3.0
LOWER_THIRD_DURATION_SECONDS = 5.0
# ===================================================... | ai-video | scripts/core/constants.py | Python | 326b90fe308fe005a69c5ae79f5f4735067c5368d40c1a34d33468b9ce724b35 | 1 | 805 |
from __future__ import annotations
from typing import Optional
from .edit_plan import EditPlan
from .models import CostBreakdown, ProjectConfig
PRICING = {
"gemini_image": {
"gemini-3-pro-image-preview": 0.134,
"imagen-4.0-generate-001": 0.030,
},
"veo": {
"veo-3.1-generate-previe... | ai-video | scripts/core/cost_estimator.py | Python | d87333d71fe4d7ed80b88a22df039d7d1dbde22cb57cca146b3490955bdf4348 | 0 | 896 |
append("\U0001f4a1 Notes:")
for note in breakdown.notes:
lines.append(f" \u2022 {note}")
return "\n".join(lines)
def _image_price(self) -> float:
return PRICING["gemini_image"].get(self.config.image_model, 0.134)
def _estimate_from_edit_plan(self, edit_plan: EditPl... | ai-video | scripts/core/cost_estimator.py | Python | 611eb3d67af68b0c228e29e80ef6d745992fcd9a7d4e7c177e76725973a88ad6 | 1 | 584 |
from __future__ import annotations
from datetime import datetime
from enum import Enum
from typing import Optional
from pydantic import BaseModel, Field
class SegmentType(str, Enum):
TALKING_HEAD = "talking_head"
BROLL_STOCK = "broll_stock"
BROLL_GENERATED = "broll_generated"
MOTION_GRAPHIC = "motio... | ai-video | scripts/core/edit_plan.py | Python | cc4d207766f04b447f9bc4d20e441ce06adf4515d0917d3cd8103e531e344180 | 0 | 499 |
from __future__ import annotations
from pathlib import Path
from typing import Optional
from pydantic import BaseModel, Field
class LongFormVideoConfig(BaseModel):
"""Configuration for long-form video generation (10+ minutes)."""
# Veo Key Rotation
veo_keys: list[str] = Field(default_factory=list) # V... | ai-video | scripts/core/long_form_config.py | Python | 4e543b8ec93dc933a32361c16e87b0eba146428c465ddc986a9e17edfeeabe33 | 0 | 303 |
from __future__ import annotations
from datetime import datetime
from enum import Enum
from pathlib import Path
from typing import Any, Optional
from pydantic import BaseModel, Field
class StageStatus(str, Enum):
PENDING = "pending"
ACTIVE = "active"
COMPLETED = "completed"
ERROR = "error"
SKIPP... | ai-video | scripts/core/models.py | Python | fe5f074b28c40fe956eb11e71af0be452b3497f233a40865c46b04d698f8b31e | 0 | 896 |
eleven_multilingual_sts_v2"
# --- Video provider ---
video_provider: str = "veo" # "veo", "replicate", "local"
replicate_model_id: str = "" # e.g. "kling/v2.6", "wan-video/wan-2.5-i2v-fast"
# --- Video output ---
default_aspect_ratio: str = "9:16"
default_resolution: str = "1080p"
fps: i... | ai-video | scripts/core/models.py | Python | 19960d925addc839eec007bde134689109fd7324b23b499a404a8a09649395ad | 1 | 616 |
from __future__ import annotations
import logging
from pathlib import Path
from .models import CharacterProfile, InputMode, Script, ScriptSegment
logger = logging.getLogger(__name__)
_ROOT = Path(__file__).resolve().parent.parent.parent
_PROMPTS_DIR = _ROOT / "templates" / "prompts"
class ScriptEngine:
def __... | ai-video | scripts/core/script_engine.py | Python | ba14ba943508a829250d13acb111374ea73cf70f432faac6fd5b13d596c7daac | 0 | 872 |
from __future__ import annotations
import time
from pathlib import Path
from .models import ProjectState, StageStatus
_STAGE_LABELS = {
"input_parsing": "Input Parsing",
"script_generation": "Script Generation",
"character_design": "Character Design",
"image_generation": "Image Generation",
"fram... | ai-video | scripts/core/status_bar.py | Python | c91baed43f83191ee34ab4403e0f352da6ecd666ed68731b8ae1b0431739e075 | 0 | 896 |
, "Idle")
sub = getattr(self, "_sub_progress", "")
action_text = f"Current: {action}"
if sub:
action_text += f" ({sub})"
lines.append(self._pad(action_text, width))
lines.append("\u255a" + "\u2550" * width + "\u255d")
return "\n".join(lines)
def print_st... | ai-video | scripts/core/status_bar.py | Python | cb33ac33a16d670e3962e90e283c73dafb3ed6daaa8103f3a94f52f461e7bf5d | 1 | 203 |
from __future__ import annotations
import json
import logging
from concurrent.futures import ThreadPoolExecutor, as_completed
from dataclasses import dataclass, field
from pathlib import Path
from google.genai.errors import ClientError
from scripts.core.models import ScriptSegment
from .video_generator import Video... | ai-video | scripts/generation/batch_generator.py | Python | 06843567e0f7bb9bba0b8bb7ac4ca4633f7fe351a3d52f85c727a643ff6baf6e | 0 | 896 |
,
variants: int,
) -> list[Path]:
return self.generator.generate_variants(
prompt=task.prompt,
start_frame=task.start_frame,
end_frame=task.end_frame,
count=variants,
output_dir=output_dir,
)
@staticmethod
def build_tasks(
... | ai-video | scripts/generation/batch_generator.py | Python | bd1544bda35cf85ad2629091240439c72a9543952bf7b5ad1541f9bcbed82807 | 1 | 279 |
from __future__ import annotations
import json
import logging
from pathlib import Path
from google import genai
from google.genai import types
from scripts.core.models import CharacterIdentity, CharacterProfile
logger = logging.getLogger(__name__)
_ROOT = Path(__file__).resolve().parent.parent.parent
_PROMPTS_DIR ... | ai-video | scripts/generation/character_generator.py | Python | 2c626cb905c7917e345a5a5f92e508812bd4097d43bfb41458d97bc2821e3134 | 0 | 896 |
]:
output_dir.mkdir(parents=True, exist_ok=True)
paths: list[Path] = []
for i, data in enumerate(images):
path = output_dir / f"{prefix}_v{i}.png"
path.write_bytes(data)
paths.append(path)
logger.info("Saved %s", path)
return paths
d... | ai-video | scripts/generation/character_generator.py | Python | d72416e3a749330f34deb8885fd27fd68c52ce0a2cbab3a341aef0e79684da59 | 1 | 896 |
* total references.
"""
for img in new_images[:max_references]:
store.add_reference_image(identity.id, img) # type: ignore[attr-defined]
# Reload so reference_images list is up to date
updated = store.load(identity.id) # type: ignore[attr-defined]
logger.info(
... | ai-video | scripts/generation/character_generator.py | Python | dd8bf50ab1addc3901a881eeeb9b9cde2932b7646e5b37e2c22aeeee30b24c2f | 2 | 108 |
from __future__ import annotations
import json
import logging
from pathlib import Path
from google import genai
from google.genai import types
from scripts.core.models import CharacterProfile, ScriptSegment
logger = logging.getLogger(__name__)
_ROOT = Path(__file__).resolve().parent.parent.parent
_PROMPTS_DIR = _R... | ai-video | scripts/generation/frame_generator.py | Python | 65e6eb5c64a55927ffbc7fd9906e3e99b86162091acaf79046ec635f7f1cc9d8 | 0 | 896 |
json.dumps(metadata, indent=2), encoding="utf-8")
return path
def _generate_single_frame(
self,
prompt: str,
reference_images: list[bytes] | None = None,
aspect_ratio: str = "9:16",
attempt: int = 0,
) -> bytes | None:
contents: list[types.Part] = []
... | ai-video | scripts/generation/frame_generator.py | Python | 49a18745040df91cd3bbb526157a7755fccbfb62e89b5906e0adf5d4e40977c1 | 1 | 356 |
from __future__ import annotations
import logging
from concurrent.futures import CancelledError, ThreadPoolExecutor, as_completed
from pathlib import Path
from google.genai.errors import ClientError
from scripts.core.models import CharacterProfile
from .frame_generator import FrameGenerator
logger = logging.getLog... | ai-video | scripts/generation/parallel_frames.py | Python | 9b1473d34337450537379d4104aeaf9237254e8b31bce1b64790eea7c6edbad5 | 0 | 896 |
, e)
# ==================================================================
# Phase 2: Generate middle frames sequentially with references
# ==================================================================
if n > 2:
logger.info("Phase 2: Generating %d middle frames sequentia... | ai-video | scripts/generation/parallel_frames.py | Python | 815f4cff1d1e51f661198a2d6777015136c19b263ff9dccae5de954d733d5f8a | 1 | 896 |
list[list[bytes]],
output_dir: Path,
) -> list[list[Path]]:
"""Save all frame variants to disk."""
all_paths: list[list[Path]] = []
for idx, variants in enumerate(results):
paths = self.frame_gen.save_frames(variants, output_dir, idx)
all_paths.append(paths)
... | ai-video | scripts/generation/parallel_frames.py | Python | 8597ea5f118110c288e60eeef77c8742b045f0f01676236838d50aa51ad784e3 | 2 | 80 |
from __future__ import annotations
import logging
from pathlib import Path
from scripts.core.models import CharacterProfile, ScriptSegment
from scripts.generation.providers.base import VideoProvider
from scripts.generation.providers.factory import VideoProviderFactory
logger = logging.getLogger(__name__)
# -------... | ai-video | scripts/generation/video_generator.py | Python | 6636d326b42c6d214ddf5dace19efd649a0654a2479da9adb545478a49204427 | 0 | 896 |
---------------------
environment = character.setting or "a clean, well-lit interior"
# --- Technical specs ---------------------------------------------------
lighting = character.lighting or "bright, even lighting"
# --- Anti-perfection details (naturalness) -----------------------------
anti = ... | ai-video | scripts/generation/video_generator.py | Python | c4c8f07b7700ffca31c9f4d35172609888e0a7b8976a43d870f31c344b37573f | 1 | 896 |
-> VideoProvider:
return self._provider
# ------------------------------------------------------------------
# Delegated methods — same signatures as before
# ------------------------------------------------------------------
def generate_clip(
self,
prompt: str,
start_... | ai-video | scripts/generation/video_generator.py | Python | cd0efa9092fe649d1232a84fbb8b87bdb7917953a83a12ada60c6456d33db8a1 | 2 | 497 |
from .base import VideoProvider
from .factory import VideoProviderFactory
__all__ = ["VideoProvider", "VideoProviderFactory"]
| ai-video | scripts/generation/providers/__init__.py | Python | 0ccbcb17336b7409495e9946331a354a820607ee1b5ee03362d2d2e9f11765b8 | 0 | 21 |
from __future__ import annotations
import abc
from pathlib import Path
class VideoProvider(abc.ABC):
"""Abstract base class for video generation providers.
Each provider wraps a specific API (Veo, Replicate, local endpoint)
and exposes a common interface for the pipeline to consume.
"""
# -----... | ai-video | scripts/generation/providers/base.py | Python | 846231b66736c99d8d73d338b532e3f68e563100e2ca561fd8c4f88f21ac9455 | 0 | 896 |
9:16",
person_generation: str = "allow_adult",
output_dir: Path | None = None,
retries: int = 2,
) -> Path | None:
"""Generate an initial clip then extend it N-1 times.
The default implementation raises :class:`NotImplementedError`
for providers that do not support e... | ai-video | scripts/generation/providers/base.py | Python | 5782878931eb28eb5947ac4842bb64f0688916506491c2df51f110b968603f99 | 1 | 425 |
from __future__ import annotations
import logging
from .base import VideoProvider
logger = logging.getLogger(__name__)
class VideoProviderFactory:
"""Instantiate the correct :class:`VideoProvider` by name."""
@staticmethod
def create(
provider_name: str,
api_key: str,
model: st... | ai-video | scripts/generation/providers/factory.py | Python | 37b368c52a8ca6076a7ed05fc26deec34e25f60611b3830a36e75627a023e065 | 0 | 335 |
from __future__ import annotations
import base64
import logging
import time
from pathlib import Path
from uuid import uuid4
import requests
from .base import VideoProvider
logger = logging.getLogger(__name__)
# Default polling settings for Replicate predictions
_POLL_INTERVAL = 5
_MAX_POLL_SECONDS = 600 # 10 minu... | ai-video | scripts/generation/providers/replicate_provider.py | Python | 18e03454a2e9f9eec84d1f5038db7a2ad37e34ab68248b443f6fa1290cab7c43 | 0 | 896 |
-----------------------------
# Capability flags
# ------------------------------------------------------------------
@property
def name(self) -> str:
return f"Replicate ({self.model_id})"
@property
def supports_extension(self) -> bool:
return False # Replicate models generall... | ai-video | scripts/generation/providers/replicate_provider.py | Python | 15e02814824ba18aebb38310e28cb99de759987ce7251d123eaaae16a0bf653a | 1 | 896 |
prediction: object) -> str | None:
"""Poll a Replicate prediction until it completes or fails.
Returns the output URL string, or ``None``.
"""
deadline = time.time() + _MAX_POLL_SECONDS
while time.time() < deadline:
prediction.reload()
status = predictio... | ai-video | scripts/generation/providers/replicate_provider.py | Python | 2bf87513802f810aaa6c0a13806438383710e8d857bef17078e8c3a700e71ee8 | 2 | 421 |
from __future__ import annotations
import logging
import time
from pathlib import Path
from typing import Optional
from uuid import uuid4
from google import genai
from google.genai import types
from google.genai.errors import ClientError
from .base import VideoProvider
from scripts.core.constants import (
VEO_PO... | ai-video | scripts/generation/providers/veo.py | Python | c4b208da386e39a7b9cf915fc09f1134e8d115e68d5d5a9ad2ba10158f3d0594 | 0 | 896 |
jpeg",
)
config = types.GenerateVideosConfig(
aspect_ratio=aspect_ratio,
person_generation=person_generation,
)
kwargs: dict = {
"model": self.model,
"prompt": prompt,
"image": start_image,
"config": config,
... | ai-video | scripts/generation/providers/veo.py | Python | 984eea2e3131f1454828d9e44818177a4c9756b7152f17b5591ee964e6157945 | 1 | 896 |
< retries:
self._current_client = None
continue
else:
backoff = VEO_RATE_LIMIT_BACKOFF[
min(attempt, len(VEO_RATE_LIMIT_BACKOFF) - 1)
]
logger.w... | ai-video | scripts/generation/providers/veo.py | Python | e2e0f5e8e17745b2d99043f3d7d1f627820c016867cf858b8ad8a406146d31da | 2 | 896 |
, retrying in 10s...")
time.sleep(10)
if not initial_path:
logger.error("Extension chain: initial clip generation failed")
return None
if len(prompts) == 1:
return initial_path
# --- Steps 2..N: extend for each subsequent segment ---
... | ai-video | scripts/generation/providers/veo.py | Python | 8220f36e724c7544e62c0a4c8fb56ebe4a65d0ca6cf828c0fc262cd62a71ffe6 | 3 | 756 |
from .remotion_renderer import RemotionRenderer
__all__ = ["RemotionRenderer"]
| ai-video | scripts/graphics/__init__.py | Python | e0c865db8a68eca43ceba771877302ae1a70a39afd53cf24e02dfdd61868d3ef | 0 | 12 |
from __future__ import annotations
import hashlib
import json
import logging
import shutil
import subprocess
from pathlib import Path
from typing import Optional
from scripts.core.constants import (
INTRO_DURATION_SECONDS,
OUTRO_OFFSET_SECONDS,
CHAPTER_CARD_DURATION_SECONDS,
LOWER_THIRD_DURATION_SECON... | ai-video | scripts/graphics/remotion_renderer.py | Python | 77190ad1a133ecb25b66288add8b2a31c760bbfc1b3b713ff3bb93052b29de43 | 0 | 896 |
%s", composition, e)
return None
return None
def _build_props(
self,
edit_plan: EditPlan,
character: CharacterProfile,
total_duration: float,
) -> dict:
"""Build props JSON for Remotion."""
# Extract character name from profile or use default... | ai-video | scripts/graphics/remotion_renderer.py | Python | 265ab540911e58b98f7c22bd7f12f2983b0ba991f90dd160487bf1807348cbb8 | 1 | 673 |
from __future__ import annotations
import json
import logging
import re
from pathlib import Path
from scripts.core.models import Script, ScriptSegment
from scripts.core.constants import (
DEFAULT_WORDS_PER_MINUTE,
SEGMENT_CORRUPTION_THRESHOLD,
)
logger = logging.getLogger(__name__)
_SEGMENT_PATTERN = re.com... | ai-video | scripts/input/script_parser.py | Python | b81ebabe8a74ca89212d645f1c72ad760844208c77d0d23d528132337f96d2a3 | 0 | 896 |
.
Args:
word_count: Number of words in the segment
fallback: Duration to return if word_count is 0
Returns:
Duration in seconds, clamped between 3.0 and 25.0 seconds
"""
if word_count == 0:
return fallback
dura... | ai-video | scripts/input/script_parser.py | Python | 263d75806b2aecd728e39ac773056315005abbbf265686b6345903d678f52c71 | 1 | 896 |
=language, segments=segments)
def _parse_freeform(self, text: str, language: str) -> Script:
sentences = self._split_sentences(text)
segments: list[ScriptSegment] = []
current_text: list[str] = []
current_words = 0
target_words = 25 if language.startswith("en") else 22
... | ai-video | scripts/input/script_parser.py | Python | a180f75e49b2592cbbe577232512d40aa20781f412abbd53391571e20b1d3470 | 2 | 625 |
from __future__ import annotations
import json
import logging
from pathlib import Path
from elevenlabs import ElevenLabs
from scripts.core.models import Script, ScriptSegment
logger = logging.getLogger(__name__)
class TranscriptExtractor:
def __init__(self, api_key: str):
self.client = ElevenLabs(api_... | ai-video | scripts/input/transcript_extractor.py | Python | f9c88251425b02f7906ddebfb42f5f692a12e4c289f6b3494516cb1a9eef30db | 0 | 896 |
?])\s+', text)
segments: list[ScriptSegment] = []
current: list[str] = []
seg_id = 1
target_words = 25
for sentence in sentences:
word_count = len(sentence.split())
current_count = sum(len(s.split()) for s in current)
if current_count + word_... | ai-video | scripts/input/transcript_extractor.py | Python | b0b2377fcf43b545bf00b6a250b465bb3dbf977b52791537c5e32ee492b5714b | 1 | 157 |
from __future__ import annotations
import json
import logging
import subprocess
from pathlib import Path
logger = logging.getLogger(__name__)
class YouTubeAnalyzer:
def __init__(self, output_dir: Path):
self.output_dir = output_dir
self.output_dir.mkdir(parents=True, exist_ok=True)
def down... | ai-video | scripts/input/youtube_analyzer.py | Python | 0bd3615a362768dd02ef28a3dd20672ff53bb6d706138713084c3bf4eaae7948 | 0 | 896 |
.run(cmd, check=True, capture_output=True)
paths.append(out)
return paths
def build_source_analysis(self, metadata: dict, scenes: list[dict]) -> dict:
duration = float(metadata.get("duration", 0))
title = metadata.get("title", "")
description = metadata.get("description... | ai-video | scripts/input/youtube_analyzer.py | Python | c61b0c2a374861f104d5dcf6ced68280154fdfa2868941084fec5b070f337efd | 1 | 267 |
from __future__ import annotations
import concurrent.futures
import logging
from concurrent.futures import ThreadPoolExecutor, as_completed
from pathlib import Path
from typing import Any
from scripts.core.checkpoint import CheckpointManager
from scripts.core.constants import DEFAULT_WORKSTREAM_TIMEOUT
from scripts.c... | ai-video | scripts/orchestration/parallel_workstream.py | Python | 87d33a452abaf69bd7817fafb62891a9a690253c5d314638c414d16c0f5b87f0 | 0 | 896 |
,
project_dir: Path,
) -> dict[str, Any]:
"""Workstream 7c: Render motion graphics."""
logger.info("Workstream: Rendering motion graphics")
# Placeholder - actual implementation would use RemotionRenderer
return {"outputs": [], "status": "completed"}
def _generate_voice_... | ai-video | scripts/orchestration/parallel_workstream.py | Python | bb47278a1997dbf22a17edfdadf103ff4c608ed1c6dced6fccbb9cd8960419fc | 1 | 222 |
from .edit_plan_generator import EditPlanGenerator
__all__ = ["EditPlanGenerator"]
| ai-video | scripts/planning/__init__.py | Python | bc43b3c3e92e18efe95d04fceb98b3e40005786bb39db0dc85e25b75d1b49924 | 0 | 12 |
from __future__ import annotations
import json
import logging
import re
import time
from pathlib import Path
from scripts.core.constants import (
DEFAULT_VEO_COST_PER_CALL,
BROLL_MIN_DURATION_SECONDS,
BROLL_MAX_DURATION_SECONDS,
BROLL_DURATION_FACTOR,
)
from scripts.core.edit_plan import EditPlan
from... | ai-video | scripts/planning/edit_plan_generator.py | Python | 0e43e000309ff07ead892b332291e3f6833e2c109d586d9fe3c20f3d0b5e9b38 | 0 | 896 |
{script.title}", f"Language: {script.language}", ""]
for seg in script.segments:
lines.append(f"Segment {seg.id}: {seg.text}")
if seg.action:
lines.append(f" Action: {seg.action}")
if seg.emotion:
lines.append(f" Emotion: {seg.emotion}")
... | ai-video | scripts/planning/edit_plan_generator.py | Python | acb5835df3bf90491cf26552832481dba92abd00aa1f69d75c06c3f59852d95a | 1 | 896 |
).strip()
# Classify as stock vs generated
is_stock = any(keyword in broll_text for keyword in STOCK_KEYWORDS) or len(broll_text.split()) <= 2
seg_type = SegmentType.BROLL_STOCK if is_stock else SegmentType.BROLL_GENERATED
... | ai-video | scripts/planning/edit_plan_generator.py | Python | 6e4dfdb873f4df93406f54559317041ed159dbe9cbbda1c1adf6932044e8c536 | 2 | 730 |
from .veo_key_manager import VeoKeyRotationManager, VeoKeyState
__all__ = ["VeoKeyRotationManager", "VeoKeyState"]
| ai-video | scripts/providers/__init__.py | Python | 529c0da70fd7cd13589a48566b95669d4ca1c37348ddff35e104de4e0cebfb3d | 0 | 18 |
from __future__ import annotations
import hashlib
import json
import logging
import threading
from datetime import datetime, timedelta
from pathlib import Path
from typing import Optional
from pydantic import BaseModel, Field
logger = logging.getLogger(__name__)
class VeoKeyState(BaseModel):
"""State tracking ... | ai-video | scripts/providers/veo_key_manager.py | Python | d91dfbf61cf199a38ca9062f3209ebded4b6f43aefee502a36523abc943adb69 | 0 | 896 |
None
) -> None:
"""Mark a request as rate limited (429)."""
with self._lock:
key_state = self._find_key(api_key)
if key_state:
key_state.in_flight_count = max(0, key_state.in_flight_count - 1)
if retry_after:
key_state.rate_... | ai-video | scripts/providers/veo_key_manager.py | Python | 94e453f361295b5f911a985aef4a0c147310d2aa8338d1fa29cf4be4a5fa3ea3 | 1 | 896 |
:
logger.warning("Failed to load persisted key state: %s", e)
def _persist_state(self) -> None:
"""Persist key state to disk."""
try:
data = {
"keys": [
{
"key_id": k.key_id,
"usage_count": k... | ai-video | scripts/providers/veo_key_manager.py | Python | bc12de4014dc6e01eb37452ff704318e0e4a1aeb5042d8b0174f647723087143 | 2 | 282 |
from __future__ import annotations
import logging
import subprocess
from pathlib import Path
import numpy as np
from PIL import Image
logger = logging.getLogger(__name__)
FRAMES_TO_CHECK = 10
class ArtifactDetector:
def detect(self, clip_path: Path, work_dir: Path) -> list[dict]:
frames = self._extrac... | ai-video | scripts/qa/artifact_detector.py | Python | 2d176d882a5ab5038ee8ff3ec88e9469dd846d10a3ffcf7e5146aa848574a8d3 | 0 | 896 |
count)}))",
"-frames:v", str(count),
"-vsync", "vfr",
str(output_dir / "frame_%03d.png"),
]
subprocess.run(cmd, check=True, capture_output=True)
return sorted(output_dir.glob("frame_*.png"))
| ai-video | scripts/qa/artifact_detector.py | Python | 2b2f3f4c56a65cea96ba0088dad171e647e2215f2526796da87c2cc31c249bde | 1 | 72 |
from __future__ import annotations
import logging
import subprocess
from pathlib import Path
import numpy as np
from scripts.core.constants import AUDIO_SYNC_TOLERANCE_MS
logger = logging.getLogger(__name__)
class AudioSyncChecker:
@staticmethod
def check_sync(
video_path: Path,
audio_path... | ai-video | scripts/qa/audio_sync_check.py | Python | 769bf9bd588b666a5a620e513d18ddfa5016d8d41420991f0d4bf3912e9f3b32 | 0 | 737 |
from __future__ import annotations
import json
import logging
import subprocess
from datetime import datetime
from pathlib import Path
from .artifact_detector import ArtifactDetector
from .audio_sync_check import AudioSyncChecker
from .visual_consistency import VisualConsistencyChecker
from scripts.core.constants imp... | ai-video | scripts/qa/full_qa_report.py | Python | 01feb6f12375b9da12301475ec629750bfdd17579d63ec7b4e2d0edb789404d6 | 0 | 896 |
("checks", {}).items():
if not isinstance(check, dict):
continue
score = check.get("score", "N/A")
label = name.replace("_", " ").title()
icon = "\u2705" if (isinstance(score, (int, float)) and score >= 0.8) else "\u26a0\ufe0f"
if isinstance(sc... | ai-video | scripts/qa/full_qa_report.py | Python | 747a8ff7b3fde5bc630ce0dce93577328dce1b695e9a800a9d226406b94f8abc | 1 | 896 |
result.stdout.strip())
durations.append(d)
total += d
except subprocess.CalledProcessError:
durations.append(0.0)
except ValueError:
durations.append(0.0)
return {
"total_seconds": round(total, 2),
"... | ai-video | scripts/qa/full_qa_report.py | Python | c672563c6ba2b7fe85f849bed123a82a8f9102f82b29184f841269615d85bd42 | 2 | 84 |
from __future__ import annotations
import logging
import subprocess
from pathlib import Path
import imagehash
import numpy as np
from PIL import Image
logger = logging.getLogger(__name__)
class VisualConsistencyChecker:
@staticmethod
def extract_boundary_frames(
clip_paths: list[Path],
outp... | ai-video | scripts/qa/visual_consistency.py | Python | a4f1871254911f6a9938397583af355c4563d436b79b5edc24d87bcd16a3976b | 0 | 896 |
str(clip),
]
result = subprocess.run(cmd, capture_output=True, text=True, check=True)
w, h = result.stdout.strip().split(",")
resolutions.append((int(w), int(h)))
unique = set(resolutions)
consistent = len(unique) == 1
return {
"consi... | ai-video | scripts/qa/visual_consistency.py | Python | 74d78281a32253a485d643347c9f28c39118f47201241880f9b6c6707ac395f5 | 1 | 150 |
from .asset_cache import AssetCache
from .broll_sourcer import BRollSourcer
from .pexels_client import PexelsClient
__all__ = ["AssetCache", "BRollSourcer", "PexelsClient"]
| ai-video | scripts/sourcing/__init__.py | Python | 9124885797ad06db1ca39c70af6be78f222beab34528d81a7de1f2d7119dcf2b | 0 | 30 |
from __future__ import annotations
import hashlib
import json
import logging
import shutil
from pathlib import Path
from typing import Optional
import numpy as np
from sentence_transformers import SentenceTransformer
logger = logging.getLogger(__name__)
class AssetCache:
"""Semantic cache for b-roll assets wit... | ai-video | scripts/sourcing/asset_cache.py | Python | 91e8af3e6ea39d97c8de24d494a3ca1f195898ff44fda879adaf228ad9104999 | 0 | 896 |
= None
for i, meta in enumerate(self.metadata):
if meta.get("file_path") == str(cached_path):
existing_idx = i
break
if existing_idx is not None:
self.metadata[existing_idx] = asset_meta
else:
self.metadata.append(asset_meta)
... | ai-video | scripts/sourcing/asset_cache.py | Python | 05042aa414efeb103e76c12b3913dfdf7c21b0b7fc0f59a2f1b55053c148c7db | 1 | 366 |
from __future__ import annotations
import logging
from pathlib import Path
from typing import Optional, Tuple
from scripts.core.constants import CLIP_DURATION_MATCH_THRESHOLD
from scripts.core.edit_plan import EditPlanSegment, SegmentType
from scripts.generation.providers.veo import VeoProvider
from .asset_cache imp... | ai-video | scripts/sourcing/broll_sourcer.py | Python | 128b400339a83836f970a83edb1df5cce3610b3b283fc4624d7bf5c97dae7150 | 0 | 896 |
":"))
return "landscape" if w > h else "portrait"
return "landscape"
@staticmethod
def _build_veo_prompt(segment: EditPlanSegment) -> str:
"""Build Veo prompt from segment."""
parts = [segment.visual_description]
if segment.broll_keywords:
parts.append("K... | ai-video | scripts/sourcing/broll_sourcer.py | Python | 3cecc3b4b3b9588433a559e51ebb8f68f2c8142afaad3fc4309db8e0ac5a2e37 | 1 | 87 |
from __future__ import annotations
import logging
import time
from pathlib import Path
from typing import Optional
from urllib.parse import urlencode
import requests
logger = logging.getLogger(__name__)
PEXELS_API_BASE = "https://api.pexels.com/videos"
PEXELS_RATE_LIMIT = 200 # requests per hour (free tier)
PEXELS... | ai-video | scripts/sourcing/pexels_client.py | Python | ea3251ff988622b1cb0eeaef277a970bf799f5261df7bb37ae01cf66621bbcd0 | 0 | 896 |
(key=lambda x: x["score"], reverse=True)
return scored
def _get_best_video_url(self, video: dict) -> Optional[str]:
"""Get best quality video URL from video object."""
video_files = video.get("video_files", [])
if not video_files:
return None
# Prefer HD (1080p)... | ai-video | scripts/sourcing/pexels_client.py | Python | 17ba4b34e8d7a5382cfb4a0eda4e6b13ddc8ae02e6950f8d656e11d9fbff439c | 1 | 509 |
from .subtitle_burner import SubtitleBurner
from .subtitle_generator import SubtitleGenerator
__all__ = ["SubtitleGenerator", "SubtitleBurner"]
| ai-video | scripts/subtitles/__init__.py | Python | cf1a656bddc8c0cc9b39e61c989efde51ae3647d74738fb7a4548a183925f110 | 0 | 21 |
from __future__ import annotations
import logging
import subprocess
from pathlib import Path
logger = logging.getLogger(__name__)
class SubtitleBurner:
"""Burn subtitles into video using FFmpeg."""
@staticmethod
def burn_subtitles(
video_path: Path,
srt_path: Path,
output_path: ... | ai-video | scripts/subtitles/subtitle_burner.py | Python | f5c8836704e621d84982c5a4ed8cf1904886be1d5e292a934026e14918a095e1 | 0 | 372 |
from __future__ import annotations
import logging
from pathlib import Path
from typing import Optional
logger = logging.getLogger(__name__)
class SubtitleGenerator:
"""Generate subtitles using Whisper."""
def __init__(self, model_size: str = "base"):
"""Initialize subtitle generator.
... | ai-video | scripts/subtitles/subtitle_generator.py | Python | c9ee92107d50eb91c59e09029d026bafcc91cdcc6bd2fc1010bba6669c99d83e | 0 | 804 |
{
"id": "english-presenter",
"name": "English Presenter",
"language": "en-US",
"tags": ["presenter", "male", "tech", "english", "professional"],
"character": {
"age_range": "25-35",
"gender": "male",
"style": "smart casual, clean background, tech YouTuber aesthetic",
"setting": "home office, m... | ai-video | templates/presets/english-presenter.json | JSON | 64e115831e3f949774cfbeb6df69c560e71cfa3b4b1820de8be8ce357caa089e | 0 | 241 |
{
"id": "german-vlogger",
"name": "German Vlogger",
"language": "de-DE",
"tags": ["vlogger", "female", "young", "german", "casual"],
"character": {
"age_range": "18-25",
"gender": "female",
"style": "casual, Gen-Z, streetwear or cozy",
"setting": "bedroom or living room, slightly messy",
"... | ai-video | templates/presets/german-vlogger.json | JSON | 8403b0cb350267782bcc5cc18ad1816b97c59a55dad866e9ff42d49c5078a805 | 0 | 244 |
{
"id": "storyteller",
"name": "Storyteller",
"language": "en-US",
"tags": ["storyteller", "female", "warm", "english", "intimate"],
"character": {
"age_range": "30-45",
"gender": "female",
"style": "warm, approachable, cozy sweater or blouse",
"setting": "cozy living room, warm lighting, book... | ai-video | templates/presets/storyteller.json | JSON | 677abd6d86b02fd9fd3cb0ec7719cbe6c77cf5b4a4cf08ab41fb2ffe49d3c0c7 | 0 | 242 |
Anti-perfection rules for realistic AI-generated content.
The goal is to make generated images and videos look like they were captured by a real person
with a phone camera, NOT like professional studio content or obvious AI art.
ALWAYS include these elements in image/video prompts:
Skin & Face:
- "natural skin textu... | ai-video | templates/prompts/anti-perfection.md | Markdown | 66345e99ef61bf47d7a7100911ef3a99bdfbd57cb1bf1644256892ad14b90388 | 0 | 284 |
You are a professional video editor specializing in YouTube long-form content. Analyze the provided script and create a detailed edit plan following YouTube retention best practices.
SCRIPT:
{script_text}
CHARACTER PROFILE:
{character_summary}
TARGET DURATION: {target_duration} seconds
REQUIREMENTS:
1. Hook: Ensure... | ai-video | templates/prompts/edit-plan-generator.md | Markdown | dc3100d7d16e2f8778a809ccc2f32dba9b5cb2607683e807acf32da4c9f61169 | 0 | 238 |
You are planning a sequence of {num_frames} key frames for a {duration}-second talking-head video.
These frames will be used as start/end frames for AI video generation (Veo 3.1).
Adjacent video clips share frames: Clip 1 uses Frame A→B, Clip 2 uses Frame B→C, etc.
Character description:
{character_description}
Scri... | ai-video | templates/prompts/frame-planner.md | Markdown | a1f35f60d078aa1cc19233a76b02b4813af2916ebe4f983ec1107669e1ddb2b7 | 0 | 260 |
Analyze this reference image and extract a detailed JSON descriptor of the person shown.
Focus on characteristics that can be reproduced consistently across multiple AI-generated images.
Extract the following attributes:
{
"physical": {
"age_apparent": "estimated age range",
"gender_presentation": "how they... | ai-video | templates/prompts/image-analyzer.md | Markdown | e59a97561ce5177571c41d93914ac497c674c93656f6f0f7daac883fb92f9f2a | 0 | 371 |
You are adapting a video transcript from {source_language} to {target_language}.
Rules:
- Do NOT literally translate. Adapt for natural speech in the target language.
- Preserve the tone, pacing, and energy level.
- Preserve filler words but use target-language equivalents.
- Preserve humor — adapt jokes to work in ta... | ai-video | templates/prompts/script-adapter.md | Markdown | 069605321f16d6fdbcb725426bd43b43efe67fd6f980cdb71423bd8121c65a2d | 0 | 178 |
You are a script writer for AI-generated talking-head videos. Your scripts must
sound like natural, spontaneous speech — NOT written prose read aloud.
Rules:
- Include filler words naturally: "ähm", "also", "irgendwie", "na ja" (German) or "um", "like", "you know", "so" (English)
- Vary sentence length. Mix short punc... | ai-video | templates/prompts/script-writer.md | Markdown | aad11318baff78a6e67ecdc9095fc98c7998083377b633457853f84b70a8c798 | 0 | 896 |
you know how ice floats, right? Like, in your drink, in a lake… it just… bobs there on top. But have you ever really stopped to think why?"
Action: (Leans slightly forward, gestures inquisitively)
Emotion: (Engaging, curious, slightly playful)
Camera: Medium close-up, slight push in
word_count: 30
duration_seconds: 13.... | ai-video | templates/prompts/script-writer.md | Markdown | ad7da8cca61384272847d801b21c1e92b25b6e64a64b62c1e2fd24e65041ffa0 | 1 | 88 |
You are writing prompts for Veo 3.1 video generation. Each prompt describes an 8-second video clip
of a talking-head character transitioning from one pose/expression to another.
You will receive:
- Start frame description (the first frame of this clip)
- End frame description (the last frame of this clip)
- Script seg... | ai-video | templates/prompts/veo-prompt-writer.md | Markdown | 31759bd7c208d03d962b6539579beafd4ec13ecda1255e04421f2ab8f38175b7 | 0 | 271 |
{
"name": "ai-video-editor",
"version": "1.0.0",
"private": true,
"scripts": {
"start": "npx remotion studio",
"build": "npx remotion render VideoAssembly out/video.mp4",
"upgrade": "npx remotion upgrade"
},
"dependencies": {
"@remotion/cli": "^4.0.0",
"@remotion/player": "^4.0.0",
"... | ai-video | templates/remotion-project/package.json | JSON | 94e2b9e88eeb125c1941dbd59731f2d867425fb4cb2418952966f8796a391157 | 0 | 196 |
import { Config } from "@remotion/cli/config";
Config.setVideoImageFormat("jpeg");
Config.setOverwriteOutput(true);
| ai-video | templates/remotion-project/remotion.config.ts | TypeScript | 38e9e6394e32f151e454efdeb84da8bcc616da7550bc8ef52e1721a001745394 | 0 | 30 |
{
"compilerOptions": {
"target": "ES2022",
"module": "ES2022",
"moduleResolution": "bundler",
"jsx": "react-jsx",
"strict": true,
"esModuleInterop": true,
"skipLibCheck": true,
"forceConsistentCasingInFileNames": true,
"resolveJsonModule": true,
"declaration": true,
"declar... | ai-video | templates/remotion-project/tsconfig.json | JSON | a81856ef1c06f621deef2debb0e6dfef6443460cbfbc3fe3ff728369fd2d2349 | 0 | 138 |
import { Composition } from "remotion";
import { VideoAssembly } from "./compositions/VideoAssembly";
import { VideoAssemblySchema } from "./lib/props-schema";
import { calculateTotalDuration } from "./lib/timing";
const defaultProps = {
segments: [
{
src: "/segments/segment_01.mp4",
durationFrames: ... | ai-video | templates/remotion-project/src/Root.tsx | TypeScript | e612e75f3e799be300270fad37153c05f399a9aab483f9588f253c7d8f626948 | 0 | 202 |
import React from "react";
import {
AbsoluteFill,
Img,
useCurrentFrame,
useVideoConfig,
interpolate,
} from "remotion";
interface KenBurnsEffectProps {
src: string;
zoomStart: number;
zoomEnd: number;
panX: number;
panY: number;
}
export const KenBurnsEffect: React.FC<KenBurnsEffectProps> = ({
s... | ai-video | templates/remotion-project/src/components/KenBurnsEffect.tsx | TypeScript | 7bbcd15b296ab236c02fb12b4b2bd295f6bda8ccc0a0fd90a18936db95850eda | 0 | 262 |
import React from "react";
import { AbsoluteFill, useCurrentFrame, interpolate } from "remotion";
interface TransitionEffectProps {
type: "crossDissolve" | "fade";
durationFrames: number;
children: React.ReactNode;
}
export const TransitionEffect: React.FC<TransitionEffectProps> = ({
type,
durationFrames,
... | ai-video | templates/remotion-project/src/components/TransitionEffect.tsx | TypeScript | 7f350112ec2df18c364261f28dcba98c3929188b733be3f92071561c6b10b736 | 0 | 164 |
import React from "react";
import { Audio, Sequence } from "remotion";
interface AudioTrack {
src: string;
startFrame: number;
volume: number;
}
interface AudioLayerProps {
tracks: AudioTrack[];
}
export const AudioLayer: React.FC<AudioLayerProps> = ({ tracks }) => {
return (
<>
{tracks.map((trac... | ai-video | templates/remotion-project/src/compositions/AudioLayer.tsx | TypeScript | 4aef8c84e16b2be5e84d0f026cc60f79618c5b979d1178e651a85cf7e92d212a | 0 | 127 |
import React from "react";
import { AbsoluteFill, OffthreadVideo } from "remotion";
interface ClipSequenceProps {
src: string;
trimStartFrames: number;
trimEndFrames: number;
durationFrames: number;
}
export const ClipSequence: React.FC<ClipSequenceProps> = ({
src,
trimStartFrames,
trimEndFrames,
dura... | ai-video | templates/remotion-project/src/compositions/ClipSequence.tsx | TypeScript | 0f9b7e334a06e0fd6df5392611e0e28a256a938ca693dcc1fbc5ab2f3de6289d | 0 | 123 |
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