135 lines
4.8 KiB
Python
135 lines
4.8 KiB
Python
"""
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Configuration management for AI Skills API.
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Supports YAML config file with environment variable overrides.
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"""
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import os
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from dataclasses import dataclass, field
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from typing import List
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import yaml
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@dataclass
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class RAGConfig:
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max_skills: int = 3
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max_conventions: int = 2
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max_snippets: int = 2
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min_skill_score: float = 0.3
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min_snippet_score: float = 0.25
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embedding_model: str = "all-MiniLM-L6-v2"
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@dataclass
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class CompressionConfig:
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enabled: bool = True
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strategy: str = "extractive"
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keep_last_n: int = 3
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max_tokens: int = 2000
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ollama_model: str = "phi3:mini"
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ollama_url: str = "http://localhost:11434"
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@dataclass
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class AuthConfig:
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enabled: bool = False
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api_key: str = "change-me-in-production"
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header_name: str = "X-API-Key"
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@dataclass
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class LoggingConfig:
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level: str = "INFO"
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format: str = "json"
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@dataclass
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class Config:
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host: str = "0.0.0.0"
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port: int = 8675
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database_url: str = "sqlite+aiosqlite:///./ai.db"
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rag: RAGConfig = field(default_factory=RAGConfig)
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compression: CompressionConfig = field(default_factory=CompressionConfig)
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auth: AuthConfig = field(default_factory=AuthConfig)
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logging: LoggingConfig = field(default_factory=LoggingConfig)
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cors_origins: List[str] = field(default_factory=lambda: ["*"])
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def _coerce_value(value, cast_type):
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"""Coerce string to type"""
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if cast_type is bool:
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return str(value).lower() in ('true', '1', 'yes', 'on')
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if cast_type is int:
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return int(value)
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if cast_type is float:
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return float(value)
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if cast_type is list:
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return str(value).split(',') if value else []
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return str(value) if value is not None else None
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def load_config(config_path: str = "/app/config.yaml") -> Config:
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"""Load configuration from YAML file with environment overrides"""
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# Find config file
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locations = [config_path, "/app/config.yaml", "./config.yaml"]
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file_data = {}
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for path in locations:
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if os.path.exists(path):
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with open(path, 'r') as f:
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file_data = yaml.safe_load(f) or {}
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break
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# Helper to get value: env > file > default
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def get(prefix, key, default, cast=None):
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env_key = f"{prefix}_{key}".upper() if prefix else key.upper()
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env_val = os.getenv(env_key)
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if env_val is not None:
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return _coerce_value(env_val, cast if cast else type(default))
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if key in file_data:
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return file_data[key]
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return default
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# Build nested configs
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rag_file = file_data.get('rag', {})
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rag = RAGConfig(
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max_skills=get('RAG', 'MAX_SKILLS', rag_file.get('max_skills', 3), int),
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max_conventions=get('RAG', 'MAX_CONVENTIONS', rag_file.get('max_conventions', 2), int),
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max_snippets=get('RAG', 'MAX_SNIPPETS', rag_file.get('max_snippets', 2), int),
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min_skill_score=get('RAG', 'MIN_SKILL_SCORE', rag_file.get('min_skill_score', 0.3), float),
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min_snippet_score=get('RAG', 'MIN_SNIPPET_SCORE', rag_file.get('min_snippet_score', 0.25), float),
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embedding_model=get('RAG', 'EMBEDDING_MODEL', rag_file.get('embedding_model', 'all-MiniLM-L6-v2'), str),
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)
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comp_file = file_data.get('compression', {})
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compression = CompressionConfig(
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enabled=get('COMPRESSION', 'ENABLED', comp_file.get('enabled', True), bool),
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strategy=get('COMPRESSION', 'STRATEGY', comp_file.get('strategy', 'extractive'), str),
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keep_last_n=get('COMPRESSION', 'KEEP_LAST_N', comp_file.get('keep_last_n', 3), int),
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max_tokens=get('COMPRESSION', 'MAX_TOKENS', comp_file.get('max_tokens', 2000), int),
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ollama_model=get('COMPRESSION', 'OLLAMA_MODEL', comp_file.get('ollama_model', 'phi3:mini'), str),
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ollama_url=get('COMPRESSION', 'OLLAMA_URL', comp_file.get('ollama_url', 'http://localhost:11434'), str),
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)
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auth_file = file_data.get('auth', {})
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auth = AuthConfig(
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enabled=get('AUTH', 'ENABLED', auth_file.get('enabled', False), bool),
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api_key=os.getenv('API_KEY', auth_file.get('api_key', 'change-me-in-production')),
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header_name=get('AUTH', 'HEADER_NAME', auth_file.get('header_name', 'X-API-Key'), str),
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)
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log_file = file_data.get('logging', {})
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logging = LoggingConfig(
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level=get('LOGGING', 'LEVEL', log_file.get('level', 'INFO'), str),
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format=get('LOGGING', 'FORMAT', log_file.get('format', 'json'), str),
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)
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return Config(
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host=get('APP', 'HOST', file_data.get('host', '0.0.0.0'), str),
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port=get('APP', 'PORT', file_data.get('port', 8675), int),
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database_url=os.getenv('DATABASE_URL', file_data.get('database_url', 'sqlite+aiosqlite:///./ai.db')),
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rag=rag,
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compression=compression,
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auth=auth,
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logging=logging,
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cors_origins=file_data.get('cors_origins', ["*"])
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)
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