Delete config/settings.py

config/settings.py

@@ -1,226 +0,0 @@
-"""
-Application Settings
-Design System Extractor v2
-
-Loads configuration from environment variables and YAML files.
-"""
-
-import os
-from pathlib import Path
-from typing import Optional
-from dataclasses import dataclass, field
-from dotenv import load_dotenv
-import yaml
-
-# Load environment variables from .env file
-env_path = Path(__file__).parent / ".env"
-if env_path.exists():
-    load_dotenv(env_path)
-else:
-    # Try loading from parent directory (for development)
-    load_dotenv(Path(__file__).parent.parent / ".env")
-
-
-@dataclass
-class HFSettings:
-    """Hugging Face configuration."""
-    hf_token: str = field(default_factory=lambda: os.getenv("HF_TOKEN", ""))
-    hf_space_name: str = field(default_factory=lambda: os.getenv("HF_SPACE_NAME", ""))
-    use_inference_api: bool = field(default_factory=lambda: os.getenv("USE_HF_INFERENCE_API", "true").lower() == "true")
-    inference_timeout: int = field(default_factory=lambda: int(os.getenv("HF_INFERENCE_TIMEOUT", "120")))
-    max_new_tokens: int = field(default_factory=lambda: int(os.getenv("HF_MAX_NEW_TOKENS", "2048")))
-    temperature: float = field(default_factory=lambda: float(os.getenv("HF_TEMPERATURE", "0.3")))
-
-
-@dataclass
-class ModelSettings:
-    """Model configuration for each agent — Diverse providers."""
-    # Agent 1: Rule-based, no LLM needed
-    
-    # Agent 2 (Normalizer): Fast structured output
-    # Default: Microsoft Phi (fast, great structured output)
-    agent2_model: str = field(default_factory=lambda: os.getenv("AGENT2_MODEL", "microsoft/Phi-3.5-mini-instruct"))
-    
-    # Agent 3 (Advisor): Strong reasoning - MOST IMPORTANT
-    # Default: Qwen 2.5 72B (freely available on HF serverless, no gated access needed)
-    # Alternative: meta-llama/Llama-3.1-70B-Instruct (requires Meta license acceptance)
-    agent3_model: str = field(default_factory=lambda: os.getenv("AGENT3_MODEL", "Qwen/Qwen2.5-72B-Instruct"))
-    
-    # Agent 4 (Generator): Code/JSON specialist
-    # Default: Mistral Codestral (code specialist)
-    agent4_model: str = field(default_factory=lambda: os.getenv("AGENT4_MODEL", "mistralai/Codestral-22B-v0.1"))
-    
-    # Fallback (must be freely available on HF serverless inference)
-    fallback_model: str = field(default_factory=lambda: os.getenv("FALLBACK_MODEL", "Qwen/Qwen2.5-7B-Instruct"))
-
-
-@dataclass
-class APISettings:
-    """API key configuration (optional alternatives)."""
-    anthropic_api_key: str = field(default_factory=lambda: os.getenv("ANTHROPIC_API_KEY", ""))
-    openai_api_key: str = field(default_factory=lambda: os.getenv("OPENAI_API_KEY", ""))
-
-
-@dataclass
-class BrowserSettings:
-    """Playwright browser configuration."""
-    browser_type: str = field(default_factory=lambda: os.getenv("BROWSER_TYPE", "chromium"))
-    headless: bool = field(default_factory=lambda: os.getenv("BROWSER_HEADLESS", "true").lower() == "true")
-    timeout: int = field(default_factory=lambda: int(os.getenv("BROWSER_TIMEOUT", "30000")))
-    network_idle_timeout: int = field(default_factory=lambda: int(os.getenv("NETWORK_IDLE_TIMEOUT", "5000")))
-
-
-@dataclass
-class CrawlSettings:
-    """Website crawling configuration."""
-    max_pages: int = field(default_factory=lambda: int(os.getenv("MAX_PAGES", "20")))
-    min_pages: int = field(default_factory=lambda: int(os.getenv("MIN_PAGES", "10")))
-    crawl_delay_ms: int = field(default_factory=lambda: int(os.getenv("CRAWL_DELAY_MS", "1000")))
-    max_concurrent: int = field(default_factory=lambda: int(os.getenv("MAX_CONCURRENT_CRAWLS", "3")))
-    respect_robots_txt: bool = field(default_factory=lambda: os.getenv("RESPECT_ROBOTS_TXT", "true").lower() == "true")
-
-
-@dataclass
-class ViewportSettings:
-    """Viewport configuration for extraction."""
-    desktop_width: int = 1440
-    desktop_height: int = 900
-    mobile_width: int = 375
-    mobile_height: int = 812
-
-
-@dataclass
-class StorageSettings:
-    """Persistent storage configuration."""
-    storage_path: str = field(default_factory=lambda: os.getenv("STORAGE_PATH", "/data"))
-    enable_persistence: bool = field(default_factory=lambda: os.getenv("ENABLE_PERSISTENCE", "true").lower() == "true")
-    max_versions: int = field(default_factory=lambda: int(os.getenv("MAX_VERSIONS", "10")))
-
-
-@dataclass
-class UISettings:
-    """UI configuration."""
-    server_port: int = field(default_factory=lambda: int(os.getenv("SERVER_PORT", "7860")))
-    share: bool = field(default_factory=lambda: os.getenv("SHARE", "false").lower() == "true")
-    theme: str = field(default_factory=lambda: os.getenv("UI_THEME", "soft"))
-
-
-@dataclass
-class FeatureFlags:
-    """Feature toggles."""
-    color_ramps: bool = field(default_factory=lambda: os.getenv("FEATURE_COLOR_RAMPS", "true").lower() == "true")
-    type_scales: bool = field(default_factory=lambda: os.getenv("FEATURE_TYPE_SCALES", "true").lower() == "true")
-    a11y_checks: bool = field(default_factory=lambda: os.getenv("FEATURE_A11Y_CHECKS", "true").lower() == "true")
-    parallel_extraction: bool = field(default_factory=lambda: os.getenv("FEATURE_PARALLEL_EXTRACTION", "true").lower() == "true")
-
-
-@dataclass
-class Settings:
-    """Main settings container."""
-    debug: bool = field(default_factory=lambda: os.getenv("DEBUG", "false").lower() == "true")
-    log_level: str = field(default_factory=lambda: os.getenv("LOG_LEVEL", "INFO"))
-    
-    hf: HFSettings = field(default_factory=HFSettings)
-    models: ModelSettings = field(default_factory=ModelSettings)
-    api: APISettings = field(default_factory=APISettings)
-    browser: BrowserSettings = field(default_factory=BrowserSettings)
-    crawl: CrawlSettings = field(default_factory=CrawlSettings)
-    viewport: ViewportSettings = field(default_factory=ViewportSettings)
-    storage: StorageSettings = field(default_factory=StorageSettings)
-    ui: UISettings = field(default_factory=UISettings)
-    features: FeatureFlags = field(default_factory=FeatureFlags)
-    
-    # Agent configuration loaded from YAML
-    agents_config: dict = field(default_factory=dict)
-    
-    def __post_init__(self):
-        """Load agent configuration from YAML after initialization."""
-        self.load_agents_config()
-    
-    def load_agents_config(self):
-        """Load agent personas and settings from YAML file."""
-        yaml_path = Path(__file__).parent / "agents.yaml"
-        if yaml_path.exists():
-            with open(yaml_path, "r") as f:
-                self.agents_config = yaml.safe_load(f)
-        else:
-            print(f"Warning: agents.yaml not found at {yaml_path}")
-            self.agents_config = {}
-    
-    def get_agent_persona(self, agent_name: str) -> str:
-        """Get persona string for an agent."""
-        agent_key = f"agent_{agent_name}"
-        if agent_key in self.agents_config:
-            return self.agents_config[agent_key].get("persona", "")
-        return ""
-    
-    def get_agent_config(self, agent_name: str) -> dict:
-        """Get full configuration for an agent."""
-        agent_key = f"agent_{agent_name}"
-        return self.agents_config.get(agent_key, {})
-    
-    def get_model_for_agent(self, agent_name: str) -> str:
-        """Get the model ID for a specific agent."""
-        model_map = {
-            # Legacy agents
-            "normalizer": self.models.agent2_model,
-            "advisor": self.models.agent3_model,
-            "generator": self.models.agent4_model,
-            
-            # Stage 2 New Architecture agents
-            "brand_identifier": self.models.agent3_model,  # Llama 70B - needs context understanding
-            "benchmark_advisor": self.models.agent3_model,  # Llama 70B - needs reasoning
-            "best_practices_validator": self.models.agent3_model,  # Llama 70B - needs judgment
-            "head_synthesizer": self.models.agent3_model,  # Llama 70B - needs synthesis
-            "benchmark_extractor": self.models.agent2_model,  # Phi-3.5 - structured extraction
-        }
-        return model_map.get(agent_name, self.models.fallback_model)
-    
-    def validate(self) -> list[str]:
-        """Validate settings and return list of errors."""
-        errors = []
-        
-        if not self.hf.hf_token:
-            errors.append("HF_TOKEN is required for model inference")
-        
-        if self.crawl.max_pages < self.crawl.min_pages:
-            errors.append("MAX_PAGES must be >= MIN_PAGES")
-        
-        return errors
-
-
-# Global settings instance
-settings = Settings()
-
-
-def get_settings() -> Settings:
-    """Get the global settings instance."""
-    return settings
-
-
-def reload_settings() -> Settings:
-    """Reload settings from environment and config files."""
-    global settings
-    settings = Settings()
-    return settings
-
-
-# Convenience functions
-def is_debug() -> bool:
-    """Check if debug mode is enabled."""
-    return settings.debug
-
-
-def get_hf_token() -> str:
-    """Get HuggingFace token."""
-    return settings.hf.hf_token
-
-
-def get_agent_persona(agent_name: str) -> str:
-    """Get persona for an agent."""
-    return settings.get_agent_persona(agent_name)
-
-
-def get_model_for_agent(agent_name: str) -> str:
-    """Get model ID for an agent."""
-    return settings.get_model_for_agent(agent_name)