mirror of
https://github.com/shareAI-lab/learn-claude-code.git
synced 2026-05-21 10:43:50 +00:00
* feat: s01-s14 docs quality overhaul — tool pipeline, single-agent, knowledge & resilience Rewrite code.py and README (zh/en/ja) for s01-s14, each chapter building incrementally on the previous. Key fixes across chapters: - s01-s04: agent loop, tool dispatch, permission pipeline, hooks - s05-s08: todo write, subagent, skill loading, context compact - s09-s11: memory system, system prompt assembly, error recovery - s12-s14: task graph, background tasks, cron scheduler All chapters CC source-verified. Code inherits fixes forward (PROMPT_SECTIONS, json.dumps cache, real-state context, can_start dep protection, etc.). * feat: s15-s19 docs quality overhaul — multi-agent platform: teams, protocols, autonomy, worktree, MCP tools Rewrite code.py and README (zh/en/ja) for s15-s19, the multi-agent platform chapters. Each chapter inherits all previous fixes and adds one mechanism: - s15: agent teams (TeamCreate, teammate threads, shared task list) - s16: team protocols (plan approval, shutdown handshake, consume_inbox) - s17: autonomous agents (idle polling, auto-claim, consume_lead_inbox) - s18: worktree isolation (git worktree, bind_task, cwd switching, safety) - s19: MCP tools (MCPClient, normalize_mcp_name, assemble_tool_pool, no cache) All appendix source code references verified against CC source. Config priority corrected: claude.ai < plugin < user < project < local. * fix: 5 regressions across s05-s19 — glob safety, todo validation, memory extraction, protocol types, dep crash - s05-s09: glob results now filter with is_relative_to(WORKDIR) (inherited from s02) - s06-s08: todo_write validates content/status required fields (inherited from s05) - s09: extract_memories uses pre-compression snapshot instead of compacted messages - s16: submit_plan docstring clarifies protocol-only (not code-level gate) - s17-s19: match_response restores type mismatch validation (from s16) - s17-s19: claim_task deps list handles missing dep files without crashing * fix: s12 Todo V2 logic reversal, s14/s15 cron range validation, s18/s19 worktree name validation - s12 README (zh/en/ja): fix Todo V2 direction — interactive defaults to Task, non-interactive/SDK defaults to TodoWrite. Fix env var name to CLAUDE_CODE_ENABLE_TASKS (not TODO_V2). - s14/s15: add _validate_cron_field with per-field range checks (minute 0-59, hour 0-23, dom 1-31, month 1-12, dow 0-6), step > 0, range lo <= hi. Replace old try/except validation that only caught exceptions. - s18/s19: add validate_worktree_name() to remove_worktree and keep_worktree, not just create_worktree. * fix: align s16-s19 teaching tool consistency * fix pr265 chapter diagrams * Add comprehensive s20 harness chapter * Fix chapter smoke test regressions * Clarify README tutorial track transition --------- Co-authored-by: Haoran <bill-billion@outlook.com>
376 lines
13 KiB
Python
376 lines
13 KiB
Python
#!/usr/bin/env python3
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"""
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s12: Task System — file-persisted task graph with blockedBy dependencies.
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Run: python s12_task_system/code.py
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Need: pip install anthropic python-dotenv + .env with ANTHROPIC_API_KEY
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Changes from s11:
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- Task dataclass (id, subject, description, status, owner, blockedBy)
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- TASKS_DIR = .tasks/ for persistent JSON storage
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- create_task / save_task / load_task / list_tasks / get_task
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- can_start: checks blockedBy all completed (missing deps = blocked)
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- claim_task: set owner + pending -> in_progress
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- complete_task: set completed + report unblocked downstream
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- 5 new tools: create_task, list_tasks, get_task, claim_task, complete_task
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Note: Teaching code keeps a basic agent loop to stay focused on the task
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system. S11's full error recovery (RecoveryState, backoff, escalation,
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reactive compact, fallback model) is omitted — in real CC, tasks.ts and
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withRetry are independent layers that compose naturally.
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"""
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import os, subprocess, json, time, random
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from pathlib import Path
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from dataclasses import dataclass, asdict
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try:
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import readline
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readline.parse_and_bind('set bind-tty-special-chars off')
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except ImportError:
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pass
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from anthropic import Anthropic
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from dotenv import load_dotenv
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load_dotenv(override=True)
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if os.getenv("ANTHROPIC_BASE_URL"):
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os.environ.pop("ANTHROPIC_AUTH_TOKEN", None)
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WORKDIR = Path.cwd()
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MEMORY_DIR = WORKDIR / ".memory"
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MEMORY_INDEX = MEMORY_DIR / "MEMORY.md"
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client = Anthropic(base_url=os.getenv("ANTHROPIC_BASE_URL"))
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MODEL = os.environ["MODEL_ID"]
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# ── Task System ──
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TASKS_DIR = WORKDIR / ".tasks"
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TASKS_DIR.mkdir(exist_ok=True)
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@dataclass
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class Task:
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id: str
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subject: str
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description: str
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status: str # pending | in_progress | completed
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owner: str | None # Agent name (multi-agent scenarios)
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blockedBy: list[str] # Dependency task IDs
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def _task_path(task_id: str) -> Path:
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return TASKS_DIR / f"{task_id}.json"
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def create_task(subject: str, description: str = "",
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blockedBy: list[str] | None = None) -> Task:
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task = Task(
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id=f"task_{int(time.time())}_{random.randint(0, 9999):04d}",
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subject=subject,
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description=description,
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status="pending",
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owner=None,
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blockedBy=blockedBy or [],
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)
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save_task(task)
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return task
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def save_task(task: Task):
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_task_path(task.id).write_text(json.dumps(asdict(task), indent=2))
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def load_task(task_id: str) -> Task:
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return Task(**json.loads(_task_path(task_id).read_text()))
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def list_tasks() -> list[Task]:
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return [Task(**json.loads(p.read_text()))
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for p in sorted(TASKS_DIR.glob("task_*.json"))]
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def get_task(task_id: str) -> str:
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"""Return full task details as JSON."""
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task = load_task(task_id)
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return json.dumps(asdict(task), indent=2)
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def can_start(task_id: str) -> bool:
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"""Check if all blockedBy dependencies are completed.
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Missing dependencies are treated as blocked."""
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task = load_task(task_id)
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for dep_id in task.blockedBy:
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if not _task_path(dep_id).exists():
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return False
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if load_task(dep_id).status != "completed":
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return False
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return True
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def claim_task(task_id: str, owner: str = "agent") -> str:
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task = load_task(task_id)
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if task.status != "pending":
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return f"Task {task_id} is {task.status}, cannot claim"
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if not can_start(task_id):
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deps = [d for d in task.blockedBy
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if not _task_path(d).exists() or load_task(d).status != "completed"]
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return f"Blocked by: {deps}"
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task.owner = owner
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task.status = "in_progress"
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save_task(task)
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print(f" \033[36m[claim] {task.subject} → in_progress (owner: {owner})\033[0m")
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return f"Claimed {task.id} ({task.subject})"
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def complete_task(task_id: str) -> str:
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task = load_task(task_id)
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if task.status != "in_progress":
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return f"Task {task_id} is {task.status}, cannot complete"
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task.status = "completed"
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save_task(task)
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unblocked = [t.subject for t in list_tasks()
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if t.status == "pending" and t.blockedBy and can_start(t.id)]
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print(f" \033[32m[complete] {task.subject} ✓\033[0m")
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msg = f"Completed {task.id} ({task.subject})"
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if unblocked:
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msg += f"\nUnblocked: {', '.join(unblocked)}"
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print(f" \033[33m[unblocked] {', '.join(unblocked)}\033[0m")
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return msg
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# ── Prompt Assembly (from s10, synced) ──
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PROMPT_SECTIONS = {
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"identity": "You are a coding agent. Act, don't explain.",
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"tools": "Available tools: bash, read_file, write_file, "
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"create_task, list_tasks, get_task, claim_task, complete_task.",
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"workspace": f"Working directory: {WORKDIR}",
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"memory": "Relevant memories are injected below when available.",
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}
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def assemble_system_prompt(context: dict) -> str:
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sections = [PROMPT_SECTIONS["identity"],
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PROMPT_SECTIONS["tools"],
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PROMPT_SECTIONS["workspace"]]
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memories = context.get("memories", "")
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if memories:
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sections.append(f"Relevant memories:\n{memories}")
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return "\n\n".join(sections)
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_last_context_key, _last_prompt = None, None
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def get_system_prompt(context: dict) -> str:
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global _last_context_key, _last_prompt
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key = json.dumps(context, sort_keys=True, ensure_ascii=False, default=str)
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if key == _last_context_key and _last_prompt:
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return _last_prompt
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_last_context_key = key
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_last_prompt = assemble_system_prompt(context)
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return _last_prompt
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# ── Tools ──
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def safe_path(p: str) -> Path:
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path = (WORKDIR / p).resolve()
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if not path.is_relative_to(WORKDIR):
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raise ValueError(f"Path escapes workspace: {p}")
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return path
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def run_bash(command: str) -> str:
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try:
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r = subprocess.run(command, shell=True, cwd=WORKDIR,
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capture_output=True, text=True, timeout=120)
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out = (r.stdout + r.stderr).strip()
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return out[:50000] if out else "(no output)"
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except subprocess.TimeoutExpired:
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return "Error: Timeout (120s)"
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def run_read(path: str, limit: int | None = None) -> str:
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try:
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lines = safe_path(path).read_text().splitlines()
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if limit and limit < len(lines):
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lines = lines[:limit] + [f"... ({len(lines) - limit} more lines)"]
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return "\n".join(lines)
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except Exception as e:
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return f"Error: {e}"
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def run_write(path: str, content: str) -> str:
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try:
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fp = safe_path(path)
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fp.parent.mkdir(parents=True, exist_ok=True)
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fp.write_text(content)
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return f"Wrote {len(content)} bytes to {path}"
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except Exception as e:
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return f"Error: {e}"
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# Task tools
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def run_create_task(subject: str, description: str = "",
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blockedBy: list[str] | None = None) -> str:
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task = create_task(subject, description, blockedBy)
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deps = f" (blockedBy: {', '.join(blockedBy)})" if blockedBy else ""
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print(f" \033[34m[create] {task.subject}{deps}\033[0m")
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return f"Created {task.id}: {task.subject}{deps}"
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def run_list_tasks() -> str:
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tasks = list_tasks()
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if not tasks:
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return "No tasks. Use create_task to add some."
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lines = []
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for t in tasks:
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icon = {"pending": "○", "in_progress": "●",
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"completed": "✓"}.get(t.status, "?")
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deps = f" (blockedBy: {', '.join(t.blockedBy)})" if t.blockedBy else ""
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owner = f" [{t.owner}]" if t.owner else ""
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lines.append(f" {icon} {t.id}: {t.subject} "
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f"[{t.status}]{owner}{deps}")
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return "\n".join(lines)
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def run_get_task(task_id: str) -> str:
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try:
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return get_task(task_id)
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except FileNotFoundError:
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return f"Error: Task {task_id} not found"
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def run_claim_task(task_id: str) -> str:
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return claim_task(task_id, owner="agent")
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def run_complete_task(task_id: str) -> str:
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return complete_task(task_id)
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TOOLS = [
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{"name": "bash", "description": "Run a shell command.",
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"input_schema": {"type": "object",
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"properties": {"command": {"type": "string"}},
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"required": ["command"]}},
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{"name": "read_file", "description": "Read file contents.",
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"input_schema": {"type": "object",
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"properties": {"path": {"type": "string"},
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"limit": {"type": "integer"}},
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"required": ["path"]}},
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{"name": "write_file", "description": "Write content to a file.",
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"input_schema": {"type": "object",
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"properties": {"path": {"type": "string"},
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"content": {"type": "string"}},
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"required": ["path", "content"]}},
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{"name": "create_task",
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"description": "Create a new task with optional blockedBy dependencies.",
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"input_schema": {"type": "object",
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"properties": {
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"subject": {"type": "string"},
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"description": {"type": "string"},
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"blockedBy": {"type": "array",
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"items": {"type": "string"}}},
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"required": ["subject"]}},
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{"name": "list_tasks",
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"description": "List all tasks with status, owner, and dependencies.",
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"input_schema": {"type": "object", "properties": {},
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"required": []}},
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{"name": "get_task",
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"description": "Get full details of a specific task by ID.",
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"input_schema": {"type": "object",
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"properties": {"task_id": {"type": "string"}},
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"required": ["task_id"]}},
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{"name": "claim_task",
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"description": "Claim a pending task. Sets owner, changes status to in_progress.",
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"input_schema": {"type": "object",
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"properties": {"task_id": {"type": "string"}},
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"required": ["task_id"]}},
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{"name": "complete_task",
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"description": "Complete an in-progress task. Reports unblocked downstream tasks.",
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"input_schema": {"type": "object",
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"properties": {"task_id": {"type": "string"}},
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"required": ["task_id"]}},
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]
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TOOL_HANDLERS = {
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"bash": run_bash, "read_file": run_read, "write_file": run_write,
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"create_task": run_create_task, "list_tasks": run_list_tasks,
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"get_task": run_get_task, "claim_task": run_claim_task,
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"complete_task": run_complete_task,
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}
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# ── Context ──
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def update_context(context: dict, messages: list) -> dict:
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"""Derive context from real state."""
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memories = ""
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if MEMORY_INDEX.exists():
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content = MEMORY_INDEX.read_text().strip()
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if content:
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memories = content
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return {
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"enabled_tools": list(TOOL_HANDLERS.keys()),
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"workspace": str(WORKDIR),
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"memories": memories,
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}
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# ── Agent Loop (simplified, focused on task system) ──
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def agent_loop(messages: list, context: dict):
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system = get_system_prompt(context)
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while True:
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try:
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response = client.messages.create(
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model=MODEL, system=system, messages=messages,
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tools=TOOLS, max_tokens=8000)
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except Exception as e:
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messages.append({"role": "assistant", "content": [
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{"type": "text",
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"text": f"[Error] {type(e).__name__}: {e}"}]})
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return
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messages.append({"role": "assistant", "content": response.content})
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if response.stop_reason != "tool_use":
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return
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results = []
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for block in response.content:
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if block.type != "tool_use":
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continue
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print(f"\033[36m> {block.name}\033[0m")
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handler = TOOL_HANDLERS.get(block.name)
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output = handler(**block.input) if handler else f"Unknown: {block.name}"
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print(str(output)[:300])
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results.append({"type": "tool_result",
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"tool_use_id": block.id, "content": output})
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messages.append({"role": "user", "content": results})
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context = update_context(context, messages)
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system = get_system_prompt(context)
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if __name__ == "__main__":
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print("s12: task system")
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print("Enter a question, press Enter to send. Type q to quit.\n")
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history = []
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context = update_context({}, [])
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while True:
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try:
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query = input("\033[36ms12 >> \033[0m")
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except (EOFError, KeyboardInterrupt):
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break
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if query.strip().lower() in ("q", "exit", ""):
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break
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history.append({"role": "user", "content": query})
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agent_loop(history, context)
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context = update_context(context, history)
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for block in history[-1]["content"]:
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if getattr(block, "type", None) == "text":
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print(block.text)
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print()
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