518b8eca85
md-first memory extraction framework for AI agents. Markdown is the single source of truth; SQLite holds state and LanceDB provides the rebuildable vector + BM25 + scalar index. The codebase follows a single-direction DDD layering (entrypoints -> service -> memory -> infra, with component / core / config cross-cutting) enforced by import-linter. Engineering surface: - Coding conventions in .claude/rules/ (path-scoped) and workflows in .claude/skills/ (/commit, /new-branch, /pr). - GitHub Actions CI runs make lint + test + integration; pre-commit mirrors the gates locally (ruff, hygiene hooks, gitlint commit-msg). - Commit messages follow Conventional Commits, enforced by gitlint. - make lint also enforces datetime two-zone discipline and OpenAPI drift.
32 lines
866 B
Python
32 lines
866 B
Python
"""AtomicFact daily-log reader — symmetric with :class:`AtomicFactWriter`."""
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from __future__ import annotations
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import datetime as _dt
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from pathlib import Path
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from everos.core.persistence import MemoryRoot
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from ..mds import AtomicFactDailyFrontmatter
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from .base import BaseDailyReader
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class AtomicFactReader(BaseDailyReader):
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"""Read atomic-fact daily-log files."""
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schema = AtomicFactDailyFrontmatter
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def __init__(self, root: MemoryRoot) -> None:
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super().__init__(root)
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def path_for(
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self,
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owner_id: str,
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date: _dt.date | None = None,
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*,
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app_id: str = "default",
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project_id: str = "default",
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) -> Path:
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"""Resolve the atomic-fact daily-log path under the <app>/<project> prefix."""
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return super().path_for(owner_id, date, app_id=app_id, project_id=project_id)
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