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thanhnv
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"""Auto-plan for the Code tab.
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For each Code-tab message we (1) ask the model to split the request into a short
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step checklist (shown in the preview's **Plan** view), then (2) give the agent an
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``update_plan`` tool so it can tick steps off as it works.
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The parse/normalize helpers are pure (no Qt, no provider) and unit-tested;
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``decompose_request`` makes one provider call and is best-effort — it returns
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``[]`` on any problem so it never blocks the chat.
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"""
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from __future__ import annotations
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import json
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import re
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from typing import Any, Dict, List, Optional
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from ..providers.base import Provider, ToolSpec
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from .flows import STEP_DONE, STEP_ERROR, STEP_PENDING, STEP_RUNNING
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_VALID_STATUS = {STEP_PENDING, STEP_RUNNING, STEP_DONE, STEP_ERROR}
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MAX_PLAN_STEPS = 8
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UPDATE_PLAN_SPEC = ToolSpec(
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name="update_plan",
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description=(
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"Update the task checklist shown to the user. Pass the FULL list of steps "
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"with each step's status (pending / running / done / error). Call it as you "
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"work: mark the current step 'running', then 'done' when finished, or "
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"'error' if it genuinely could not be completed (explain why in your reply "
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"text — for an unattended Schedule Task, any step left 'error' or not "
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"'done' by the time you finish means the task is NOT reported as done)."
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),
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parameters={
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"type": "object",
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"properties": {
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"steps": {
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"type": "array",
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"items": {
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"type": "object",
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"properties": {
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"title": {"type": "string"},
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"status": {"type": "string",
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"enum": [STEP_PENDING, STEP_RUNNING, STEP_DONE, STEP_ERROR]},
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},
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"required": ["title"],
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},
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},
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},
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"required": ["steps"],
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},
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)
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def parse_plan_steps(text: str, max_steps: int = MAX_PLAN_STEPS) -> List[str]:
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"""Extract step titles from an LLM response.
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Accepts a JSON array (of strings or ``{title}`` objects); failing that, falls
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back to numbered / bulleted lines. Returns a trimmed, de-duplicated list (empty
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when nothing parses)."""
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text = (text or "").strip()
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if not text:
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return []
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titles: List[str] = []
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# 1) JSON array anywhere in the text.
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start, end = text.find("["), text.rfind("]")
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if 0 <= start < end:
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try:
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arr = json.loads(text[start:end + 1])
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if isinstance(arr, list):
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for item in arr:
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if isinstance(item, str):
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titles.append(item)
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elif isinstance(item, dict) and item.get("title"):
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titles.append(str(item["title"]))
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except json.JSONDecodeError:
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pass
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# 2) Fallback: numbered / bulleted lines.
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if not titles:
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for line in text.splitlines():
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m = re.match(r"\s*(?:\d+[.)]|[-*•])\s+(.*\S)", line)
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if m:
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titles.append(m.group(1))
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# Tidy: strip, drop empties, de-dupe (preserve order), cap at max_steps.
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out: List[str] = []
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seen = set()
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for t in titles:
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t = t.strip().strip('"').strip()
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if t and t.lower() not in seen:
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seen.add(t.lower())
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out.append(t)
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if len(out) >= max_steps:
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break
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return out
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def plan_incomplete_reason(steps: List[Dict[str, str]]) -> str:
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"""``""`` when there's no plan, or every step ended up 'done'; otherwise a
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short human-readable note naming the step(s) that are NOT done (still
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pending/running, or explicitly marked 'error') — used so a Schedule Task
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isn't reported "done" when its own checklist says the work wasn't
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actually finished."""
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if not steps:
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return ""
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bad = [s for s in steps if s.get("status") != STEP_DONE]
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if not bad:
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return ""
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errored = [s["title"] for s in bad if s.get("status") == STEP_ERROR]
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unfinished = [s["title"] for s in bad if s.get("status") != STEP_ERROR]
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parts = []
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if errored:
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parts.append(f"failed: {', '.join(errored)}")
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if unfinished:
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parts.append(f"left unfinished: {', '.join(unfinished)}")
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return "The task's own plan reports steps not completed (" + "; ".join(parts) + ")."
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def normalize_plan_steps(raw: Any) -> List[Dict[str, str]]:
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"""Validate the agent's ``update_plan`` ``steps`` argument into
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``[{title, status}]``. Non-dict items are dropped; an unknown/missing status is
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clamped to ``pending``."""
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out: List[Dict[str, str]] = []
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if not isinstance(raw, list):
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return out
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for item in raw:
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if not isinstance(item, dict):
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continue
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title = str(item.get("title", "")).strip()
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if not title:
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continue
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status = str(item.get("status", STEP_PENDING)).strip().lower()
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if status not in _VALID_STATUS:
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status = STEP_PENDING
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out.append({"title": title, "status": status})
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return out
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_DECOMPOSE_SYSTEM = (
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"You are a planning assistant. Break the user's coding request into a SHORT "
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"ordered checklist of concrete steps (2 to {n} steps; fewer is fine). "
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"Reply with ONLY a JSON array of short imperative step titles — no prose, no "
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"code fences. Example: [\"Read the config\", \"Add the new field\", \"Run tests\"]."
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)
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def decompose_request(provider: Provider, request: str,
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cancel: Optional[Any] = None,
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max_steps: int = MAX_PLAN_STEPS) -> List[str]:
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"""Best-effort: ask the model to split ``request`` into step titles. Returns
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``[]`` on any error/timeout so a failed plan never blocks the turn."""
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request = (request or "").strip()
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if not request:
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return []
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messages = [
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{"role": "system", "content": _DECOMPOSE_SYSTEM.format(n=max_steps)},
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{"role": "user", "content": request},
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]
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try:
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assistant = provider.chat(messages, tools=None, on_text=None, cancel=cancel)
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except Exception: # noqa: BLE001 - planning must never break the turn
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return []
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return parse_plan_steps(assistant.get("content", ""), max_steps)
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