c5d3e83a5f
- Adiciona rastreamento de objetos - Facial detection - Legenda interativa - Cortes mais precisos - Refinamento do Prompt
95 lines
4.0 KiB
Python
95 lines
4.0 KiB
Python
from __future__ import annotations
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import os
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from dataclasses import dataclass
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from pathlib import Path
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BASE_DIR = Path(__file__).resolve().parent.parent
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VIDEOS_ROOT = BASE_DIR / "videos"
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OUTPUTS_ROOT = BASE_DIR / "outputs"
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TEMP_ROOT = BASE_DIR / "temp"
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@dataclass(frozen=True)
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class RabbitMQSettings:
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# host: str = os.environ.get("RABBITMQ_HOST", "154.12.229.181")
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# port: int = int(os.environ.get("RABBITMQ_PORT", 32790))
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host: str = os.environ.get("RABBITMQ_HOST", "rabbitmq")
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port: int = int(os.environ.get("RABBITMQ_PORT", 5672))
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user: str = os.environ.get("RABBITMQ_USER", "admin")
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password: str = os.environ.get("RABBITMQ_PASS")
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consume_queue: str = os.environ.get("RABBITMQ_QUEUE", "to-render")
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publish_queue: str = os.environ.get("RABBITMQ_UPLOAD_QUEUE", "to-upload")
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prefetch_count: int = int(os.environ.get("RABBITMQ_PREFETCH", 1))
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heartbeat: int = int(os.environ.get("RABBITMQ_HEARTBEAT", 60))
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blocked_timeout: int = int(os.environ.get("RABBITMQ_BLOCKED_TIMEOUT", 300))
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@dataclass(frozen=True)
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class OpenRouterSettings:
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api_key: str = os.environ.get("OPENROUTER_API_KEY", "https://openrouter.ai/api/v1/chat/completions")
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model: str = os.environ.get(
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"OPENROUTER_MODEL", "openai/gpt-oss-20b:free"
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)
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temperature: float = float(os.environ.get("OPENROUTER_TEMPERATURE", 0.6))
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prompt_path: str = os.environ.get("OPENROUTER_PROMPT_PATH", "prompts/generate.txt")
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@dataclass(frozen=True)
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class WhisperSettings:
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model_size: str = os.environ.get("FASTER_WHISPER_MODEL_SIZE", "medium")
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device: str | None = os.environ.get("FASTER_WHISPER_DEVICE")
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compute_type: str | None = os.environ.get("FASTER_WHISPER_COMPUTE_TYPE")
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download_root: Path = Path(
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os.environ.get("FASTER_WHISPER_DOWNLOAD_ROOT", str(BASE_DIR / ".whisper"))
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)
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@dataclass(frozen=True)
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class RenderingSettings:
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frame_width: int = int(os.environ.get("RENDER_WIDTH", 1080))
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frame_height: int = int(os.environ.get("RENDER_HEIGHT", 1920))
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fps: int = int(os.environ.get("RENDER_FPS", 30))
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video_codec: str = os.environ.get("RENDER_CODEC", "libx264")
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audio_codec: str = os.environ.get("RENDER_AUDIO_CODEC", "aac")
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bitrate: str = os.environ.get("RENDER_BITRATE", "5000k")
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preset: str = os.environ.get("RENDER_PRESET", "faster")
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highlight_color: str = os.environ.get("SUBTITLE_HIGHLIGHT_COLOR", "#00FF00")
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base_color: str = os.environ.get("SUBTITLE_BASE_COLOR", "#FFFFFF")
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font_path: Path = Path(os.environ.get("RENDER_FONT_PATH", "./Montserrat.ttf"))
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title_font_size: int = int(os.environ.get("RENDER_TITLE_FONT_SIZE", 110))
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subtitle_font_size: int = int(os.environ.get("RENDER_SUBTITLE_FONT_SIZE", 64))
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caption_min_words: int = int(os.environ.get("CAPTION_MIN_WORDS", 2))
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caption_max_words: int = int(os.environ.get("CAPTION_MAX_WORDS", 2))
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# Smart framing settings
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enable_smart_framing: bool = os.environ.get("ENABLE_SMART_FRAMING", "true").lower() in ("true", "1", "yes")
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smart_framing_min_confidence: float = float(os.environ.get("SMART_FRAMING_MIN_CONFIDENCE", 0.5))
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smart_framing_smoothing_window: int = int(os.environ.get("SMART_FRAMING_SMOOTHING_WINDOW", 20))
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smart_framing_frame_skip: int = int(os.environ.get("SMART_FRAMING_FRAME_SKIP", 2)) # Process every Nth frame (CPU optimization)
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@dataclass(frozen=True)
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class Settings:
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rabbitmq: RabbitMQSettings = RabbitMQSettings()
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openrouter: OpenRouterSettings = OpenRouterSettings()
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whisper: WhisperSettings = WhisperSettings()
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rendering: RenderingSettings = RenderingSettings()
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videos_dir: Path = VIDEOS_ROOT
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outputs_dir: Path = OUTPUTS_ROOT
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temp_dir: Path = TEMP_ROOT
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def load_settings() -> Settings:
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settings = Settings()
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if not settings.rabbitmq.password:
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raise RuntimeError("RABBITMQ_PASS must be provided")
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settings.videos_dir.mkdir(parents=True, exist_ok=True)
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settings.outputs_dir.mkdir(parents=True, exist_ok=True)
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settings.temp_dir.mkdir(parents=True, exist_ok=True)
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return settings
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