55 lines
2.0 KiB
Python
55 lines
2.0 KiB
Python
"""
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Configuration schema with Pydantic models
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Single source of truth for all configuration defaults and validation.
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"""
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from pydantic import BaseModel, Field
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class LLMConfig(BaseModel):
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"""LLM configuration"""
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api_key: str = Field(default="", description="LLM API Key")
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base_url: str = Field(default="", description="LLM API Base URL")
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model: str = Field(default="", description="LLM Model Name")
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class TTSConfig(BaseModel):
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"""TTS configuration"""
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default: str = Field(default="edge", description="Default TTS workflow")
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class ImageConfig(BaseModel):
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"""Image generation configuration"""
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default: str = Field(default="image_default.json", description="Default image workflow")
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comfyui_url: str = Field(default="http://127.0.0.1:8188", description="ComfyUI Server URL")
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runninghub_api_key: str = Field(default="", description="RunningHub API Key (optional)")
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prompt_prefix: str = Field(
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default="Pure white background, minimalist illustration, matchstick figure style, black and white line drawing, simple clean lines",
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description="Prompt prefix for all image generation"
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)
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class ReelForgeConfig(BaseModel):
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"""ReelForge main configuration"""
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project_name: str = Field(default="ReelForge", description="Project name")
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llm: LLMConfig = Field(default_factory=LLMConfig)
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tts: TTSConfig = Field(default_factory=TTSConfig)
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image: ImageConfig = Field(default_factory=ImageConfig)
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def is_llm_configured(self) -> bool:
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"""Check if LLM is properly configured"""
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return bool(
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self.llm.api_key and self.llm.api_key.strip() and
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self.llm.base_url and self.llm.base_url.strip() and
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self.llm.model and self.llm.model.strip()
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)
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def validate_required(self) -> bool:
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"""Validate required configuration"""
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return self.is_llm_configured()
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def to_dict(self) -> dict:
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"""Convert to dictionary (for backward compatibility)"""
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return self.model_dump()
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