ReMe/reme2/memory/ingestor.py
huangsen 8465f6d06e ```
docs(protocol): add typed edge link protocol documentation

Add comprehensive documentation for the link protocol supporting
typed edges in body text. This includes specification for three
legal inline forms (bare wikilink, line-level Dataview,
inline-bracketed Dataview), predicate syntax rules, and the
machine-managed Relations section convention for organizing
discovered edges.

fix(memory): update path reference from vault_root to working_dir

Change the memory_create operation's path anchoring from
vault_root to working_dir to maintain consistency with the
current working directory configuration.

refactor(components): remove edge_extractor module and simplify parsing

Remove the edge_extractor component module entirely and
inline edge extraction logic directly into LinkedFileParser
using parse_wikilinks utility. This simplifies the architecture
by eliminating the separate edge extraction component and
delegating edge discovery to the maintainer's enrichment operations.

feat(parser): update parse method signature and simplify edge extraction

Modify LinkedFileParser to return (FileNode, list[FileChunk])
tuple instead of ParsedFile, remove dependency on BaseEdgeExtractor,
and implement direct wikilink parsing from body text only.
```
2026-05-11 19:45:53 +08:00

211 lines
8.2 KiB
Python

"""Smart Ingestor — ReAct agent over the Memory File System.
Per `structure.md` L31-44, the Ingestor is the SSOT engine: the **single
write entry point** to the markdown vault. Every mutation (create, body
edit, frontmatter flip, rename, delete, archive) flows through here.
Mirrors `Summarizer`'s pattern — drives a `ReActAgent` whose toolkit is
built by `memory_toolkit.build_memory_toolkit`. The agent runs its own
R-M-W loop: read related files via tools, decide which ones to mutate,
call the right write tool. Every write tool records into an audit list,
so the caller gets a deterministic mutation trail regardless of how the
agent's reasoning unfolded.
When no LLM is configured, falls back to a direct create from
`target_path` + `metadata` + `content`. Edits/renames/deletes are not
available without an LLM.
"""
from __future__ import annotations
import datetime
import json
import zoneinfo
from pathlib import Path
from agentscope.agent import ReActAgent
from agentscope.message import Msg
from agentscope.tool import Toolkit
from pydantic import BaseModel, Field
from ..component.runtime_response import _set_answer, _to_jsonable
from . import memory_io
from .memory_io import create_file
from .memory_toolkit import build_memory_toolkit
from ..component import R
from ..component.base_step import BaseStep
from ..enumeration import ComponentEnum
from ..schema import extract_wikilinks
class IngestResult(BaseModel):
"""Audit trail for a single ingest call."""
applied: list[dict] = Field(default_factory=list, description="Successful ops with paths.")
rejected: list[dict] = Field(default_factory=list, description="Ops the validator refused.")
failed: list[dict] = Field(default_factory=list, description="Ops that errored at apply time.")
skipped: bool = Field(default=False, description="True if the LLM returned a SkipOp.")
used_llm: bool = Field(default=False, description="False = degraded path (no LLM configured).")
@property
def success(self) -> bool:
"""Skipped or any-applied with no failures = success."""
if self.skipped:
return True
return len(self.applied) > 0 and len(self.failed) == 0
@R.register("ingestor")
class Ingestor(BaseStep):
"""R-M-W ingestor exposed as a single-write-entry MCP tool.
Inputs (read from RuntimeContext):
content (str, required): the material being ingested.
hint (str, optional): caller guidance to the LLM.
target_path (str, optional): suggested file path; required for
the degraded path (no LLM).
metadata (dict, optional): suggested frontmatter; used by
the degraded path or as a hint to the LLM.
related_paths (list[str], optional): explicit related files,
auto-extended with wikilinks parsed from `content`.
Output (written to context.response.answer):
IngestResult JSON — applied/failed lists plus used_llm flag and
the agent's final-message summary.
"""
def __init__(
self,
toolkit: Toolkit | None = None,
console_enabled: bool = False,
timezone: str | None = None,
**kwargs,
):
super().__init__(**kwargs)
self.toolkit = toolkit
self.console_enabled = console_enabled
self.timezone = timezone
self._protocol = (Path(__file__).parent / "protocol.md").read_text(encoding="utf-8")
def _now(self) -> datetime.datetime:
if self.timezone:
try:
return datetime.datetime.now(zoneinfo.ZoneInfo(self.timezone))
except Exception as e:
self.logger.error(f"Invalid timezone: {self.timezone}, error={e}")
return datetime.datetime.now()
def _working_dir(self) -> Path:
vr = getattr(self.file_store, "working_dir", None)
return Path(vr).resolve() if vr else Path.cwd().resolve()
async def execute(self):
assert self.context is not None
mode: str = (self.context.get("mode") or "distill").lower()
if mode == "log":
await self._delegate_to_sync()
return
if mode != "distill":
self.context.response.success = False
_set_answer(self.context, {
"error": f"unknown mode {mode!r}; expected 'log' or 'distill'",
})
return
content: str = self.context.get("content", "") or ""
hint: str = self.context.get("hint", "") or ""
target_path: str = self.context.get("target_path") or ""
metadata: dict = dict(self.context.get("metadata") or {})
related_paths: list[str] = list(self.context.get("related_paths") or [])
assert content, "content is required"
# Auto-discover wikilink targets in content as a hint for the agent.
for link in extract_wikilinks(content):
hit = memory_io.resolve_wikilink(self.file_store, link)["path"]
if hit and hit not in related_paths:
related_paths.append(hit)
as_llm = self._get_component_optional(ComponentEnum.AS_LLM, "default", "model")
if as_llm is None:
result = self._degraded(target_path, metadata, content)
self.context.response.success = result.success
_set_answer(self.context, result.model_dump())
return
working_dir = self._working_dir()
audit: list[dict] = []
toolkit = build_memory_toolkit(self.app_context, audit=audit, toolkit=self.toolkit)
agent = ReActAgent(
name="reme_ingestor",
model=self.as_llm,
sys_prompt=self.prompt_format(
"system_prompt",
working_dir=str(working_dir),
protocol=self._protocol,
),
formatter=self.as_llm_formatter,
toolkit=toolkit,
)
agent.set_console_output_enabled(self.console_enabled)
user_message: str = self.prompt_format(
"user_message",
today=self._now().strftime("%Y-%m-%d"),
working_dir=str(working_dir),
hint=hint or "(none)",
target_path=target_path or "(none)",
metadata=json.dumps(_to_jsonable(metadata), ensure_ascii=False),
related=json.dumps(related_paths, ensure_ascii=False),
content=content,
)
final_msg: Msg = await agent.reply(
Msg(name="reme", role="user", content=user_message),
)
summary = final_msg.get_text_content() or ""
result = IngestResult(used_llm=True)
for entry in audit:
(result.applied if entry.get("ok") else result.failed).append(entry)
if not audit and summary.strip().upper().startswith("SKIP"):
result.skipped = True
self.context.response.success = result.success
payload = result.model_dump()
payload["agent_summary"] = summary
_set_answer(self.context, payload)
def _degraded(self, target_path: str, metadata: dict, content: str) -> IngestResult:
"""Without an LLM, only direct create from explicit target_path is
supported. Useful for tests and bootstrap scripts."""
result = IngestResult(used_llm=False)
if not target_path:
result.failed.append({
"op": "create",
"ok": False,
"error": "degraded path: target_path is required when no LLM is configured",
})
return result
path = Path(target_path)
if not path.is_absolute():
path = self._working_dir() / path
ok, payload = create_file(
self.file_store, path,
metadata=metadata, content=content,
)
bucket = result.applied if ok else result.failed
bucket.append({"op": "create", "ok": ok, "path": str(path), "result": payload})
return result
async def _delegate_to_sync(self) -> None:
"""Hot-path event-folder upsert — same code path as the standalone
`sync` step. Lazy-instantiated so we don't pay the construction
cost on every distill call."""
from ..mcp.steps.sync import Sync
if getattr(self, "_sync_step", None) is None:
self._sync_step = Sync(app_context=self.app_context)
await self._sync_step(self.context)