165 lines
4.8 KiB
Python
165 lines
4.8 KiB
Python
# -*- coding: utf-8 -*-
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"""Ralph gate — PRD-driven continuous loop with reviewer + deslop."""
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from __future__ import annotations
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import asyncio
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from dataclasses import dataclass, field
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from pathlib import Path
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from typing import Any, Optional
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from pineagents.loop.gates.base import StopAction, StopHandlerResult
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from pineagents.loop.gates.loop_gate import LoopGate
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from ..shared.constants import RALPH_MAX_ITERATIONS
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from ..shared.state import WorkflowState
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from .prompts import build_continuation as _build_prompt
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@dataclass
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class _RalphState:
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loop_dir: Path
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workspace_dir: Path
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active: bool = True
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iteration: int = 0
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max_iterations: int = RALPH_MAX_ITERATIONS
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no_deslop: bool = False
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critic_type: str = "architect"
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prd_summary: str = ""
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prd_cache: dict[str, Any] = field(default_factory=dict)
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prd_mtime_ns: int = -1
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class RalphGate(LoopGate):
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"""Stop gate for the Ralph PRD-driven loop."""
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@property
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def name(self) -> str:
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return "ralph"
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@property
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def priority(self) -> int:
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return 50
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def activate_for_ralph(
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self,
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workspace_dir: Path,
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no_deslop: bool = False,
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critic_type: str = "architect",
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max_iterations: int = RALPH_MAX_ITERATIONS,
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) -> Path:
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wf = WorkflowState(workspace_dir, "ralph")
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loop_dir = wf.create_instance()
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state = _RalphState(
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loop_dir=loop_dir,
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workspace_dir=workspace_dir,
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max_iterations=max_iterations,
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no_deslop=no_deslop,
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critic_type=critic_type,
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)
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wf.write_state(
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{
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"iteration": 0,
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"completed": False,
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},
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)
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self.activate(state)
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return loop_dir
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async def check(self, ctx: Any) -> Optional[StopHandlerResult]:
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if isinstance(ctx, dict) and ctx.get("has_tool_calls"):
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return StopHandlerResult(action=StopAction.BYPASS)
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st: _RalphState | None = self._state()
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if st is None:
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return StopHandlerResult(
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action=StopAction.BYPASS,
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)
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wf = WorkflowState.from_existing(
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st.workspace_dir,
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"ralph",
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st.loop_dir,
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)
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data = await asyncio.to_thread(wf.read_state)
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prd = await asyncio.to_thread(_read_prd_cached, st, wf)
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# Gate owns iteration in memory.
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st.iteration += 1
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if st.iteration > st.max_iterations:
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await asyncio.to_thread(wf.cleanup)
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self.deactivate()
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return StopHandlerResult(
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action=StopAction.TERMINATE,
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reason=f"Reached max iterations ({st.max_iterations})",
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)
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st.prd_summary = _summarize_prd(prd)
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completed = bool(data.get("completed")) or _all_stories_passed(prd)
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if completed:
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await asyncio.to_thread(wf.cleanup)
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self.deactivate()
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return StopHandlerResult(
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action=StopAction.TERMINATE,
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reason="All stories completed and verified",
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)
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await asyncio.to_thread(
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wf.update_state,
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{"iteration": st.iteration},
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)
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return StopHandlerResult(
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action=StopAction.INTERRUPT_AND_CONTINUE,
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reason="Ralph iteration in progress",
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)
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def build_continuation(self) -> str:
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"""Build Ralph continuation from gate state."""
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st: _RalphState | None = self._state()
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if st is None:
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return ""
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return _build_prompt(
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iteration=st.iteration,
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max_iterations=st.max_iterations,
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critic_type=st.critic_type,
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no_deslop=st.no_deslop,
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loop_dir=st.loop_dir,
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prd_summary=st.prd_summary,
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)
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def _read_prd_cached(
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st: _RalphState,
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wf: WorkflowState,
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) -> dict[str, Any]:
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"""Reload prd.json only when the file mtime changes."""
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prd_path = st.loop_dir / "prd.json"
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try:
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mtime_ns = prd_path.stat().st_mtime_ns if prd_path.exists() else -1
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except OSError:
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mtime_ns = -1
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if mtime_ns == st.prd_mtime_ns:
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return st.prd_cache
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prd = wf.read_prd()
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st.prd_cache = prd
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st.prd_mtime_ns = mtime_ns
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return prd
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def _all_stories_passed(prd: dict) -> bool:
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"""Return True when PRD exists and every story has passes=true."""
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stories = prd.get("stories") or []
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if not stories:
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return False
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return all(s.get("passes") for s in stories)
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def _summarize_prd(prd: dict) -> str:
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"""Build a one-line PRD progress summary."""
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stories = prd.get("stories", [])
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if not stories:
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return "PRD: not yet created."
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done = sum(1 for s in stories if s.get("passes"))
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return f"PRD progress: {done}/{len(stories)} stories completed."
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