bvandeusen
d6f4a6dbb6
- New NoteEmbedding model + migration 0014 stores float embeddings (JSONB) - services/embeddings.py: get_embedding, upsert_note_embedding, semantic_search_notes (cosine similarity), backfill_note_embeddings - build_context() now tries semantic search first, falls back to keyword search; accepts cached_note_ids to reuse last-turn notes and stabilise the system prompt prefix for Ollama's KV cache - generation_buffer.py: per-conversation note ID cache (get/set/clear) - generation_task.py: passes cached IDs into build_context, updates cache after each turn, and invalidates it after create_note/update_note/create_task - app.py: pulls nomic-embed-text at startup and launches a background backfill to embed all existing notes (30 s delay so Ollama has time to load the model) - routes/notes.py + services/tools.py: fire-and-forget embedding update on every note create or update via the API or LLM tool calls Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
47 lines
2.1 KiB
Python
47 lines
2.1 KiB
Python
import os
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def _read_secret(env_var: str, secret_file_var: str, default: str) -> str:
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"""Read a config value from env var, or from a Docker secrets file."""
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value = os.environ.get(env_var)
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if value:
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return value
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secret_file = os.environ.get(secret_file_var)
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if secret_file:
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try:
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with open(secret_file) as f:
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return f.read().strip()
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except FileNotFoundError:
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pass
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return default
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class Config:
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DATABASE_URL: str = _read_secret(
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"DATABASE_URL",
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"DATABASE_URL_FILE",
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"postgresql+asyncpg://fabled:fabled@localhost:5432/fabledassistant",
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)
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OLLAMA_URL: str = os.environ.get("OLLAMA_URL", "http://localhost:11434")
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OLLAMA_MODEL: str = os.environ.get("OLLAMA_MODEL", "qwen3")
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# Optional dedicated model for intent classification (should be small/fast).
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# Falls back to OLLAMA_MODEL if not set. Can also be overridden per-user via settings.
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OLLAMA_INTENT_MODEL: str = os.environ.get("OLLAMA_INTENT_MODEL", "")
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SECRET_KEY: str = _read_secret("SECRET_KEY", "SECRET_KEY_FILE", "dev-secret-change-me")
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SECURE_COOKIES: bool = os.environ.get("SECURE_COOKIES", "").lower() in ("1", "true", "yes")
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LOG_LEVEL: str = os.environ.get("LOG_LEVEL", "INFO")
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LOG_RETENTION_DAYS: int = int(os.environ.get("LOG_RETENTION_DAYS", "90"))
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# Embedding model for semantic note search (served by Ollama)
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EMBEDDING_MODEL: str = os.environ.get("EMBEDDING_MODEL", "nomic-embed-text")
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# SMTP defaults (overridden by DB settings when configured via admin UI)
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SMTP_HOST: str = os.environ.get("SMTP_HOST", "")
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SMTP_PORT: int = int(os.environ.get("SMTP_PORT", "587"))
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SMTP_USERNAME: str = os.environ.get("SMTP_USERNAME", "")
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SMTP_PASSWORD: str = _read_secret("SMTP_PASSWORD", "SMTP_PASSWORD_FILE", "")
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SMTP_FROM_ADDRESS: str = os.environ.get("SMTP_FROM_ADDRESS", "")
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SMTP_FROM_NAME: str = os.environ.get("SMTP_FROM_NAME", "Fabled Assistant")
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SMTP_USE_TLS: bool = os.environ.get("SMTP_USE_TLS", "true").lower() in ("1", "true", "yes")
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BASE_URL: str = os.environ.get("BASE_URL", "http://localhost:5000").rstrip("/")
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