mirror of
https://github.com/NousResearch/hermes-agent.git
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Interactive `hermes` launch drops from ~21s to ~2.5s. Three independent
fixes, each targets a distinct hot spot in the banner / tool-registration
path that fires on every CLI invocation.
1. `get_external_skills_dirs()` in-process mtime cache (~10s saved)
The function re-read + YAML-parsed the full ~/.hermes/config.yaml on
every call. Banner build invokes it once per skill to resolve the
category column, which on a 120-skill install meant ~120 reparses of
a 15 KB config (~85 ms each). Added a
`(config_path, mtime_ns) -> list[Path]` memo; stat() is ~2 us vs
~85 ms for the parse. Edits to config.yaml invalidate the cache on
the next call via mtime.
2. Feishu availability probe uses `importlib.util.find_spec` (~5.2s saved)
`tools/feishu_doc_tool.py::_check_feishu` and the identical helper in
`feishu_drive_tool.py` were calling `import lark_oapi` purely to
detect whether the SDK was installed. Executing the real import pulls
in websockets + dispatcher + every v2 API model — ~5 seconds of work
that fires at every tool-registry bootstrap. `find_spec` answers the
same question ("is lark_oapi importable?") without executing the
module. The actual tool handlers still do the real import on invoke,
so runtime behavior is unchanged.
3. `_web_requires_env` no longer triggers Nous portal refresh (~800ms saved)
`tools/web_tools.py::_web_requires_env` used
`managed_nous_tools_enabled()` to gate four gateway env-var names in
the returned list. The gate called `get_nous_auth_status()` ->
`resolve_nous_runtime_credentials()` -> live HTTP POST to the portal
on every tool-registry bootstrap. But the list is pure metadata — if
the env var is set at runtime, the tool lights up; otherwise it
doesn't. Including the four names unconditionally is harmless for
unsubscribed users (vars just aren't set) and eliminates the sync
HTTP round trip from startup.
Test:
- tests/agent/test_external_skills_dirs_cache.py (new, 6 cases):
returns config'd dir, caches on second call (yaml_load patched to
raise — never invoked), invalidates on mtime bump, empty when config
missing, returned list is a defensive copy, per-HERMES_HOME cache key
isolation.
- Existing tests/agent/test_external_skills.py and tests/tools/
continue to pass modulo pre-existing flakes on main (test_delegate,
test_send_message — unrelated, pass in isolation).
Measured: bare `hermes` (cold → REPL ready) 21,519ms -> 2,618ms on
Teknium's install (119 skills, 15 KB config.yaml, Nous auth logged in,
lark_oapi installed). 8x faster.
138 lines
4.4 KiB
Python
138 lines
4.4 KiB
Python
"""Feishu Document Tool -- read document content via Feishu/Lark API.
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Provides ``feishu_doc_read`` for reading document content as plain text.
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Uses the same lazy-import + BaseRequest pattern as feishu_comment.py.
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"""
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import json
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import logging
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import threading
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from tools.registry import registry, tool_error, tool_result
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logger = logging.getLogger(__name__)
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# Thread-local storage for the lark client injected by feishu_comment handler.
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_local = threading.local()
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def set_client(client):
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"""Store a lark client for the current thread (called by feishu_comment)."""
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_local.client = client
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def get_client():
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"""Return the lark client for the current thread, or None."""
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return getattr(_local, "client", None)
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# ---------------------------------------------------------------------------
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# feishu_doc_read
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# ---------------------------------------------------------------------------
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_RAW_CONTENT_URI = "/open-apis/docx/v1/documents/:document_id/raw_content"
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FEISHU_DOC_READ_SCHEMA = {
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"name": "feishu_doc_read",
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"description": (
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"Read the full content of a Feishu/Lark document as plain text. "
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"Useful when you need more context beyond the quoted text in a comment."
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),
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"parameters": {
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"type": "object",
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"properties": {
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"doc_token": {
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"type": "string",
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"description": "The document token (from the document URL or comment context).",
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},
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},
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"required": ["doc_token"],
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},
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}
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def _check_feishu():
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# Use ``importlib.util.find_spec`` — it checks whether ``lark_oapi``
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# is importable without actually executing its ``__init__``.
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# Executing the real import here costs ~5 seconds (the SDK eagerly
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# loads websockets, dispatcher, every api/v2 model) and this probe
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# fires at every ``hermes`` startup during tool-availability
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# evaluation. Correctness is preserved because the actual tool
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# handler still does the real import when invoked.
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import importlib.util
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try:
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return importlib.util.find_spec("lark_oapi") is not None
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except (ImportError, ValueError):
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return False
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def _handle_feishu_doc_read(args: dict, **kwargs) -> str:
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doc_token = args.get("doc_token", "").strip()
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if not doc_token:
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return tool_error("doc_token is required")
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client = get_client()
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if client is None:
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return tool_error("Feishu client not available (not in a Feishu comment context)")
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try:
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from lark_oapi import AccessTokenType
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from lark_oapi.core.enum import HttpMethod
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from lark_oapi.core.model.base_request import BaseRequest
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except ImportError:
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return tool_error("lark_oapi not installed")
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request = (
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BaseRequest.builder()
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.http_method(HttpMethod.GET)
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.uri(_RAW_CONTENT_URI)
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.token_types({AccessTokenType.TENANT})
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.paths({"document_id": doc_token})
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.build()
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)
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# Tool handlers run synchronously in a worker thread (no running event
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# loop), so call the blocking lark client directly.
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response = client.request(request)
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code = getattr(response, "code", None)
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if code != 0:
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msg = getattr(response, "msg", "unknown error")
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return tool_error(f"Failed to read document: code={code} msg={msg}")
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raw = getattr(response, "raw", None)
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if raw and hasattr(raw, "content"):
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try:
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body = json.loads(raw.content)
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content = body.get("data", {}).get("content", "")
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return tool_result(success=True, content=content)
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except (json.JSONDecodeError, AttributeError):
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pass
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# Fallback: try response.data
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data = getattr(response, "data", None)
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if data:
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if isinstance(data, dict):
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content = data.get("content", "")
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else:
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content = getattr(data, "content", str(data))
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return tool_result(success=True, content=content)
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return tool_error("No content returned from document API")
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# ---------------------------------------------------------------------------
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# Registration
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# ---------------------------------------------------------------------------
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registry.register(
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name="feishu_doc_read",
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toolset="feishu_doc",
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schema=FEISHU_DOC_READ_SCHEMA,
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handler=_handle_feishu_doc_read,
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check_fn=_check_feishu,
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requires_env=[],
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is_async=False,
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description="Read Feishu document content",
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emoji="\U0001f4c4",
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)
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