ProfessorNovaandClaude Opus 5
784b76baf7
Self-hosted knowledge management for SMEs: a split-screen Markdown editor whose sections an LLM refines while you write, and RAG question answering over the documents that result. FastAPI + Postgres/pgvector on the back, SvelteKit on the front, everything OpenAI-compatible and self-hostable. Squashed into a single commit; the development history stays local. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01CA43ZJda8Rbp2hKXNy8f6b
65 lines
2.3 KiB
Python
65 lines
2.3 KiB
Python
from functools import lru_cache
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from pathlib import Path
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from typing import Literal
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from pydantic_settings import BaseSettings, SettingsConfigDict
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# Repo-root .env for native dev; inside Docker the file is absent and
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# configuration comes from real environment variables (which take precedence).
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_REPO_ROOT = Path(__file__).resolve().parents[2]
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_ENV_FILE = _REPO_ROOT / ".env"
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class Settings(BaseSettings):
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model_config = SettingsConfigDict(
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env_prefix="PABLAN_", env_file=_ENV_FILE, extra="ignore"
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)
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env: Literal["development", "production"] = "development"
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database_url: str = "postgresql+asyncpg://pablan:change-me@localhost:5432/pablan"
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# Secure=false is needed for dev over plain http on non-localhost
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# addresses (WireGuard IPs) — see .env.example.
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cookie_secure: bool = True
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auth_session_ttl_days: int = 14
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query_retention_days: int = 90
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# The shipped template catalog (repo templates/ in dev; the customer
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# stack mounts the directory and overrides this path).
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templates_dir: str = str(_REPO_ROOT / "templates")
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help_dir: str = str(_REPO_ROOT / "help")
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# The instance's own language: which blueprint variant the first-install
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# starter set uses, and the fallback when a visitor states no preference.
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# Per-user choice lives on users.locale and wins over this.
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default_locale: Literal["de", "en"] = "de"
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log_level: str = "INFO"
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# Content debug logging (prompts/responses) — NEVER in production.
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debug_log_prompts: bool = False
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llm_timeout_seconds: float = 120.0
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# How many requests Pablan lets one endpoint see at once, and how long a
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# request waits for a free slot before it is answered with "busy". Match
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# llm_max_parallel to the server's parallel slots (llama.cpp: --parallel).
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# See app/llm/gate.py.
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llm_max_parallel: int = 4
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llm_queue_wait_seconds: float = 20.0
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llm_max_queued: int = 24
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job_poll_seconds: float = 1.0
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chat_base_url: str = "http://localhost:8001/v1"
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chat_api_key: str = "none"
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chat_model: str = ""
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utility_base_url: str = "http://localhost:8001/v1"
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utility_api_key: str = "none"
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utility_model: str = ""
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embedding_base_url: str = "http://localhost:8002/v1"
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embedding_api_key: str = "none"
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embedding_model: str = ""
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@lru_cache
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def get_settings() -> Settings:
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return Settings()
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