Jaroslav Beneš
dd9e0e9440
LLeMbas now runs end to end. Register, add an OpenAI-compatible connection, and hold a real streaming conversation organised into folders. Verified against the local llama-swap instance. Streaming is the one genuinely tricky part. Sending a message returns two HTML fragments -- the user bubble and an empty assistant bubble carrying an sse-connect -- and that attribute is the ONLY thing that starts a generation. Rendering an incomplete assistant message as a streaming shell falls out of the same template, which means loading a page whose last reply never finished simply picks it up again. Details worth knowing about, each commented where it matters: - SSE payloads are split across several data: lines. A raw newline in one data: line truncates the event, which shows up the first time a model emits a code block. - Markdown is rendered server-side by the same helper for both the page and the final streamed frame, so the two cannot disagree. The fence renderer is replaced outright rather than using markdown-it's highlight option, which re-wraps output in a second <pre>. - escape_text is html.escape, not nh3.clean_text: it escapes character by character, so escaping stream chunks separately equals escaping the whole string. - The stream opens its own session via session_scope(); it outlives the request handler and the dependency-scoped session may be closed. - Deleting a folder keeps the chats inside it (FK is SET NULL). Losing a conversation to a mis-clicked folder delete is unforgivable. - Login failures use one message for "no such account" and "wrong password" so the form cannot enumerate registered addresses. Also adds deploy/ for the gamebox install at https://chat.lan: system unit, nginx vhost with buffering off (buffering on turns streaming into one lump at the end), and install/update scripts following the same service-user and /srv bind-mount conventions as llama-swap and comfyui. 70 tests, ruff clean. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
71 lines
2.1 KiB
Python
71 lines
2.1 KiB
Python
"""Application configuration, loaded from the environment and/or a .env file."""
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from __future__ import annotations
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import secrets
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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 import Field, model_validator
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from pydantic_settings import BaseSettings, SettingsConfigDict
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class Settings(BaseSettings):
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"""Runtime configuration. Every variable is prefixed ``LEMBAS_``."""
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model_config = SettingsConfigDict(
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env_prefix="LEMBAS_",
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env_file=".env",
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env_file_encoding="utf-8",
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extra="ignore",
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)
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secret_key: str = Field(default="")
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# Set when no LEMBAS_SECRET_KEY was supplied and one had to be invented.
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# main.py warns about it at startup; see the validator below.
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secret_key_is_ephemeral: bool = Field(default=False, exclude=True)
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data_dir: Path = Path("./data")
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host: str = "127.0.0.1"
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port: int = 8080
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reload: bool = False
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log_level: Literal["debug", "info", "warning", "error"] = "info"
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allow_signup: bool = True
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default_theme: Literal["moria", "shire"] = "moria"
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session_ttl: int = 60 * 60 * 24 * 30
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request_timeout: float = 300.0
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@model_validator(mode="after")
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def _generate_secret_if_absent(self) -> Settings:
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# A generated key lets `lembas serve` work with no configuration at all,
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# but it changes on every restart: sessions drop and stored API keys
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# become unreadable. Flagged so startup can warn. Never use in anger.
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if not self.secret_key:
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self.secret_key = secrets.token_urlsafe(48)
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self.secret_key_is_ephemeral = True
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return self
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@property
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def db_path(self) -> Path:
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return self.data_dir / "lembas.db"
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@property
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def uploads_dir(self) -> Path:
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return self.data_dir / "uploads"
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def ensure_dirs(self) -> None:
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self.data_dir.mkdir(parents=True, exist_ok=True)
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self.uploads_dir.mkdir(parents=True, exist_ok=True)
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@lru_cache
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def get_settings() -> Settings:
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"""Cached singleton so config is parsed once per process."""
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return Settings()
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settings = get_settings()
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