ce9f27320a
This adds the full Atlas (总助 Claw / 老板视角项目执行雷达) scaffolding as a sibling profile to the existing Vega general-purpose assistant. All Atlas content lives under atlas/ to keep the existing top-level skeleton intact. What's included: - atlas/IDENTITY.md, SOUL.md, USER.md, AGENTS.md, MEMORY.md, BOOTSTRAP.md, HEARTBEAT.md, TOOLS.md (+ zh-CN mirrors) — full OpenClaw 8-piece set matching the zero-cca convention - atlas/skills/ — 6 sub-skills with frontmatter: claw-email-parser / claw-project-tracker / claw-people-observer / claw-customer-radar / claw-boss-distiller / claw-report-writer - atlas/skills/claw-boss-distiller/ — adapter notes for nuwa-skill, 5-layer boss_skill seed template (23 rules across Expression DNA / Mental Models / Decision Heuristics / Anti-Patterns / Honest Boundaries), and a complete synthetic distillation demo (10 input emails -> validated 5-layer output) - atlas/mcp-tools/email-extractor/ — Python implementation of stages 1-3 (fetch + decode + dequote), 7 pytest tests passing, CLI: atlas-extract - atlas/state-schemas/ — formal JSON schemas for project / person / customer cards with the no-employee-rating hard constraint baked in - atlas/client-deck/ — 2-page client-facing pitch document - autopilots/atlas-*.yaml — 5 autopilot configs (daily / weekly / monthly / quarterly + andon event-triggered) for a future Multica-side scheduler Notes: - nuwa-skill (MIT, https://github.com/alchaincyf/nuwa-skill) NOT vendored; fetch at deploy time via instructions in atlas/skills/claw-boss-distiller/upstream/README.md - Vega-side prompts/skills/tools/autopilots/docs scaffold left untouched - Top-level README.md updated with a brief Atlas pointer; rest preserved
120 lines
3.6 KiB
Python
120 lines
3.6 KiB
Python
"""Stage 1: Fetch.
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IMAP-based incremental fetcher. Persists `last_uid` per (account, folder)
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in a JSON sidecar so re-runs only pull new messages.
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"""
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from __future__ import annotations
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import json
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from dataclasses import dataclass
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from datetime import datetime, timezone
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from pathlib import Path
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from typing import Iterator
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from imap_tools import MailBox, AND
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@dataclass
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class FetchedRaw:
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account: str
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folder: str
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uid: str
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internal_date: datetime
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raw_mime: bytes
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def _sync_state_path(state_dir: Path, account: str, folder: str) -> Path:
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safe = f"{account}__{folder}".replace("/", "_").replace("@", "_at_")
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return state_dir / f".sync__{safe}.json"
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def _load_last_uid(state_dir: Path, account: str, folder: str) -> int | None:
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p = _sync_state_path(state_dir, account, folder)
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if not p.exists():
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return None
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try:
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return int(json.loads(p.read_text(encoding="utf-8"))["last_uid"])
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except (KeyError, ValueError, json.JSONDecodeError):
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return None
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def _save_last_uid(state_dir: Path, account: str, folder: str, last_uid: int) -> None:
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p = _sync_state_path(state_dir, account, folder)
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p.parent.mkdir(parents=True, exist_ok=True)
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p.write_text(
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json.dumps(
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{
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"account": account,
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"folder": folder,
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"last_uid": last_uid,
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"updated_at": datetime.now(timezone.utc).isoformat(),
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},
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ensure_ascii=False,
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indent=2,
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),
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encoding="utf-8",
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)
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def fetch_imap(
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*,
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host: str,
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port: int,
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username: str,
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password: str,
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folders: list[str],
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state_dir: Path,
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since: datetime | None = None,
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max_per_run: int = 5000,
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) -> Iterator[FetchedRaw]:
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"""Yield raw MIME messages incrementally per folder.
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Sync model: per (username, folder) we remember the highest UID seen.
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On re-run we fetch UIDs strictly greater. First run may use `since`
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to bound the cold-start window.
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"""
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with MailBox(host, port).login(username, password) as mailbox:
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for folder in folders:
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mailbox.folder.set(folder)
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last_uid = _load_last_uid(state_dir, username, folder)
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if last_uid is None:
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# cold start
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criteria = AND(date_gte=since.date()) if since else "ALL"
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msgs = mailbox.fetch(
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criteria=criteria,
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bulk=True,
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headers_only=False,
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limit=max_per_run,
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mark_seen=False,
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)
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else:
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# incremental: UID > last_uid
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# imap-tools UIDRange string form
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msgs = mailbox.fetch(
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f"UID {last_uid + 1}:*",
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bulk=True,
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headers_only=False,
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limit=max_per_run,
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mark_seen=False,
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)
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highest_seen = last_uid or 0
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for m in msgs:
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yield FetchedRaw(
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account=username,
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folder=folder,
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uid=str(m.uid),
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internal_date=m.date or datetime.now(timezone.utc),
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raw_mime=m.obj.as_bytes(), # full MIME bytes
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)
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try:
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if int(m.uid) > highest_seen:
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highest_seen = int(m.uid)
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except (TypeError, ValueError):
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continue
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if highest_seen and (last_uid is None or highest_seen > last_uid):
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_save_last_uid(state_dir, username, folder, highest_seen)
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