74 lines
2.0 KiB
Python
74 lines
2.0 KiB
Python
"""
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Configuration management for AI Service.
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[AC-AISVC-01] Centralized configuration with environment variable support.
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"""
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from functools import lru_cache
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from pydantic_settings import BaseSettings, SettingsConfigDict
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class Settings(BaseSettings):
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model_config = SettingsConfigDict(env_prefix="AI_SERVICE_", env_file=".env", extra="ignore")
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app_name: str = "AI Service"
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app_version: str = "0.1.0"
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debug: bool = False
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host: str = "0.0.0.0"
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port: int = 8080
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request_timeout_seconds: int = 20
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sse_ping_interval_seconds: int = 15
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log_level: str = "INFO"
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llm_provider: str = "openai"
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llm_api_key: str = ""
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llm_base_url: str = "https://api.openai.com/v1"
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llm_model: str = "gpt-4o-mini"
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llm_max_tokens: int = 2048
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llm_temperature: float = 0.7
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llm_timeout_seconds: int = 30
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llm_max_retries: int = 3
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database_url: str = "postgresql+asyncpg://postgres:postgres@localhost:5432/ai_service"
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database_pool_size: int = 10
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database_max_overflow: int = 20
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qdrant_url: str = "http://localhost:6333"
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qdrant_collection_prefix: str = "kb_"
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qdrant_vector_size: int = 768
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ollama_base_url: str = "http://localhost:11434"
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ollama_embedding_model: str = "nomic-embed-text"
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rag_top_k: int = 5
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rag_score_threshold: float = 0.01
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rag_min_hits: int = 1
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rag_max_evidence_tokens: int = 2000
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rag_two_stage_enabled: bool = True
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rag_two_stage_expand_factor: int = 10
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rag_hybrid_enabled: bool = True
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rag_rrf_k: int = 60
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rag_vector_weight: float = 0.7
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rag_bm25_weight: float = 0.3
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confidence_low_threshold: float = 0.5
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confidence_high_threshold: float = 0.8
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confidence_insufficient_penalty: float = 0.3
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max_history_tokens: int = 4000
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redis_url: str = "redis://localhost:6379/0"
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redis_enabled: bool = True
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dashboard_cache_ttl: int = 60
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stats_counter_ttl: int = 7776000
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frontend_base_url: str = "http://localhost:3000"
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@lru_cache
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def get_settings() -> Settings:
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return Settings()
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