a5d3af55ca
- "backend/rate_limiter.py" - "backend/models.py" - "backend/routers/chat.py" - "backend/chat_service.py" - "backend/config.py" - "alembic/versions/031_add_chat_usage_log.py" GSD-Task: S04/T01
112 lines
3.6 KiB
Python
112 lines
3.6 KiB
Python
"""Application configuration loaded from environment variables."""
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from functools import lru_cache
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from pydantic_settings import BaseSettings
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class Settings(BaseSettings):
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"""Chrysopedia API settings.
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Values are loaded from environment variables (or .env file via
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pydantic-settings' dotenv support).
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"""
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# Database
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database_url: str = "postgresql+asyncpg://chrysopedia:changeme@localhost:5433/chrysopedia"
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# Redis
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redis_url: str = "redis://localhost:6379/0"
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# Application
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app_env: str = "development"
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app_log_level: str = "info"
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app_secret_key: str = "changeme-generate-a-real-secret"
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# CORS
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cors_origins: list[str] = ["*"]
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# LLM endpoint (OpenAI-compatible)
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llm_api_url: str = "http://localhost:11434/v1"
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llm_api_key: str = "sk-placeholder"
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llm_model: str = "fyn-llm-agent-chat"
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llm_fallback_url: str = "http://localhost:11434/v1"
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llm_fallback_model: str = "fyn-llm-agent-chat"
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# Per-stage model overrides (optional — falls back to llm_model / "chat")
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llm_stage2_model: str | None = "fyn-llm-agent-chat" # segmentation — mechanical, fast chat
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llm_stage2_modality: str = "chat"
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llm_stage3_model: str | None = "fyn-llm-agent-think" # extraction — reasoning
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llm_stage3_modality: str = "thinking"
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llm_stage4_model: str | None = "fyn-llm-agent-chat" # classification — mechanical, fast chat
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llm_stage4_modality: str = "chat"
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llm_stage5_model: str | None = "fyn-llm-agent-think" # synthesis — reasoning
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llm_stage5_modality: str = "thinking"
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# Token limits — static across all stages
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llm_max_tokens_hard_limit: int = 96000 # Hard ceiling for dynamic estimator
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llm_max_tokens: int = 96000 # Fallback when no estimate is provided (must not exceed hard_limit)
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llm_temperature: float = 0.0 # Deterministic output for structured JSON extraction
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# Stage 5 synthesis chunking — max moments per LLM call before splitting
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synthesis_chunk_size: int = 30
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# Embedding endpoint
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embedding_api_url: str = "http://localhost:11434/v1"
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embedding_model: str = "nomic-embed-text"
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embedding_dimensions: int = 768
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# Qdrant
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qdrant_url: str = "http://localhost:6333"
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qdrant_collection: str = "chrysopedia"
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# LightRAG
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lightrag_url: str = "http://chrysopedia-lightrag:9621"
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lightrag_search_timeout: float = 2.0
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lightrag_min_query_length: int = 3
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# Prompt templates
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prompts_path: str = "./prompts"
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# Debug mode — when True, pipeline captures full LLM prompts and responses
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debug_mode: bool = False
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# MinIO (file storage for post attachments)
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minio_url: str = "chrysopedia-minio:9000"
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minio_access_key: str = "chrysopedia"
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minio_secret_key: str = "changeme-minio"
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minio_bucket: str = "chrysopedia"
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minio_secure: bool = False
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# File storage
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transcript_storage_path: str = "/data/transcripts"
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video_metadata_path: str = "/data/video_meta"
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video_source_path: str = "/videos"
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# SMTP (email digests)
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smtp_host: str = ""
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smtp_port: int = 587
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smtp_user: str = ""
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smtp_password: str = ""
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smtp_from_address: str = ""
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smtp_tls: bool = True
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# Rate limiting (per hour)
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rate_limit_user_per_hour: int = 30
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rate_limit_ip_per_hour: int = 10
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rate_limit_creator_per_hour: int = 60
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# Git commit SHA (set at Docker build time or via env var)
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git_commit_sha: str = "unknown"
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model_config = {
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"env_file": ".env",
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"env_file_encoding": "utf-8",
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"case_sensitive": False,
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}
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@lru_cache
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def get_settings() -> Settings:
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"""Return cached application settings (singleton)."""
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return Settings()
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