mirror of
https://github.com/agentscope-ai/ReMe.git
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6a5561f86a
- Add file_graph import to component registry - Register FILE_GRAPH enum in ComponentEnum - Implement BaseFileGraph integration in LinkedFileParser - Replace FileEdge with FileLink for better semantic clarity - Add lazy resolution of file_graph from app_context - Update file watcher logging to reflect links instead of edges refactor: streamline MCP transport layer architecture - Remove redundant step shells from reme2/mcp/steps/ - Consolidate all @R.register components to reme2.memory package - Update server.py to import reme2.memory directly - Revise README.md to document new architecture - Simplify module dependencies and import structure
73 lines
2.7 KiB
Python
73 lines
2.7 KiB
Python
"""memory_lint — read-only projection of the Maintainer's lint findings.
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Tier A surface for the Maintainer service. The host agent calls this
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to discover what's wrong with the vault (broken wikilinks, schema
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violations, stem collisions) and decides what to do with each finding
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using the existing memory_* write primitives.
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Equivalent to invoking `Maintainer.execute(ops=["lint"], dry_run=True)`
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but with a focused response shape and a tighter parameter surface — the
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agent doesn't need to know about decay/merge/split knobs.
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"""
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from __future__ import annotations
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from ..component import R
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from ..component.base_step import BaseStep
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from ..component.runtime_response import _set_answer
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from ..enumeration import ComponentEnum
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@R.register("memory_lint")
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class MemoryLint(BaseStep):
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"""Run the Maintainer's lint pass and surface findings only.
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Inputs (RuntimeContext, all optional):
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target_prefix (str): restrict scan to relpaths starting with
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this prefix (e.g. "events/2026-05-09/").
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Output (context.response.answer):
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{
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"scanned": int, # files inspected
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"findings": [LintFinding, ...], # each {path, kind, detail}
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"target_prefix": str,
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"ran_at": iso,
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}
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"""
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async def execute(self):
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assert self.context is not None
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target_prefix = str(self.context.get("target_prefix") or "")
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# Delegate to a Maintainer step. Force ops=["lint"] + dry_run so
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# we never mutate. The Maintainer reads these from the context
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# and produces a full audit; we narrow the response shape below.
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if getattr(self, "_maintainer", None) is None:
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self._maintainer = R.get(ComponentEnum.STEP, "maintainer")(
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app_context=self.app_context,
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)
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self.context["ops"] = ["lint"]
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self.context["dry_run"] = True
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self.context["target_prefix"] = target_prefix
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await self._maintainer(self.context)
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# The Maintainer wrote a full audit to context.response.answer
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# (proposed/plan/applied/skipped/failed/...). For lint, all the
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# action lives in `proposed` (LintFindings never get applied or
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# dropped). Reshape into a focused response.
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import json
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raw = self.context.response.answer
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audit = json.loads(raw) if isinstance(raw, str) else (raw or {})
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findings = audit.get("proposed") or []
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_set_answer(
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self.context,
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{
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"scanned": audit.get("scanned", 0),
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"findings": findings,
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"target_prefix": target_prefix,
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"ran_at": audit.get("ran_at", ""),
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},
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)
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self.context.response.success = True
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