Adds the Gemini API orchestrator (ReAct tool loop → Claude responder):
Orchestrator engine + router:
- orchestrator_engine.py: Gemini API tool loop, Claude CLI handoff
- routers/orchestrator.py: POST /orchestrate (async job queue), GET /orchestrate/{job_id}
Tools (cortex/tools/):
- web.py: DuckDuckGo web search (no key required)
- ae_knowledge.py: ae_journal_search + ae_journal_entry_create (AE V3 API)
- ae_tasks.py: ae_task_list (reads agents_sync Kanban filesystem)
- files.py: file_read (path-allowlisted to safe dirs)
Config + deps:
- config.py: orchestrator, DuckDuckGo, and AE API settings
- requirements.txt: google-genai, duckduckgo-search
- .env.default: reference config with all new keys documented
Docs:
- CLAUDE.md, README.md, documentation/ added to repo
- Port references updated 7331 → 8000 throughout
- Default model updated to gemini-2.5-flash
Tested: ae_task_list, ae_journal_search, web_search all working end-to-end.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
101 lines
3.1 KiB
Python
101 lines
3.1 KiB
Python
"""
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Aether task list tool — reads the agents_sync Kanban board.
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Reads task JSON files directly from the agents_sync filesystem rather than
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making an HTTP call, since the tasks directory is always locally available
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(synced via Syncthing). This avoids needing a separate API endpoint for tasks.
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Structure:
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agents_sync/tasks/01_todo/ — pending tasks
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agents_sync/tasks/02_in_progress/ — active tasks
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agents_sync/tasks/03_done/ — completed tasks (not included by default)
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"""
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import asyncio
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import json
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import logging
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from pathlib import Path
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logger = logging.getLogger(__name__)
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# Resolved at import time — agents_sync is always at ~/agents_sync on this machine.
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# If the path doesn't exist the tool returns a helpful error rather than crashing.
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_AGENTS_SYNC = Path.home() / "agents_sync"
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_TASKS_ROOT = _AGENTS_SYNC / "tasks"
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async def task_list(include_done: bool = False) -> str:
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"""List tasks from the agents_sync Kanban board.
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Reads the todo and in_progress buckets (and optionally done).
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Returns a markdown summary grouped by status.
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Args:
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include_done: If True, also include completed tasks (can be noisy).
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"""
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return await asyncio.to_thread(_sync_task_list, include_done)
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def _sync_task_list(include_done: bool) -> str:
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if not _TASKS_ROOT.exists():
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return f"Task directory not found: {_TASKS_ROOT}"
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buckets = [
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("01_todo", "Todo"),
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("02_in_progress", "In Progress"),
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]
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if include_done:
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buckets.append(("03_done", "Done"))
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sections: list[str] = []
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total = 0
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for dir_name, label in buckets:
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bucket_dir = _TASKS_ROOT / dir_name
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if not bucket_dir.exists():
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continue
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tasks = _read_bucket(bucket_dir)
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total += len(tasks)
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if not tasks:
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continue
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lines = [f"## {label} ({len(tasks)})\n"]
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for task in tasks:
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title = task.get("title") or task.get("name") or "(untitled)"
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assigned = task.get("assigned_to") or ""
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task_id = task.get("id") or ""
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desc = task.get("description") or ""
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header = f"- **{title}**"
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if assigned:
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header += f" (assigned: {assigned})"
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if task_id:
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header += f" — `{task_id}`"
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lines.append(header)
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if desc:
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# First sentence / 120 chars of description
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short = desc.split(".")[0][:120]
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lines.append(f" {short}")
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sections.append("\n".join(lines))
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if not sections:
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return "No tasks found on the Kanban board."
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header_line = f"# Kanban Board — {total} task(s)\n"
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return header_line + "\n\n".join(sections)
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def _read_bucket(bucket_dir: Path) -> list[dict]:
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"""Read and parse all JSON task files in a bucket directory."""
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tasks = []
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for path in sorted(bucket_dir.glob("*.json")):
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try:
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data = json.loads(path.read_text())
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tasks.append(data)
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except Exception as e:
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logger.warning("Failed to read task file %s: %s", path, e)
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return tasks
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