oclaw/runtime/tools/experts/generalist/text_query.py
oliver 37a2ef35f4 实现附件处理链路的统一引用化与可检索增强,避免大文件/多模态内容直接撑爆上下文并提升工具可用性。
本次补齐 text/image/video/archive 的标准化处理、会话级工具守卫、回放压缩、配置与文档对齐,并修复表格与流式输出相关体验问题。

Made-with: Cursor
2026-04-26 15:25:50 +08:00

41 lines
1.3 KiB
Python

from __future__ import annotations
from typing import Any
from oclaw.platform.files.text_attachment_store import query_text_document
from oclaw.runtime.tools.base import ToolSpec
def query_text_attachment_tool() -> ToolSpec:
def handler(args: dict[str, Any]) -> dict[str, Any]:
text_id = str(args.get("text_id") or "").strip()
if not text_id:
return {"ok": False, "error": "text_id_required"}
return query_text_document(
text_id=text_id,
query=str(args.get("query") or "").strip() or None,
top_k=int(args.get("top_k") or 5),
offset=int(args.get("offset") or 0),
)
return ToolSpec(
name="query_text_attachment",
description="Query long text attachment chunks by text_id with optional keyword search.",
parameters={
"type": "object",
"properties": {
"text_id": {"type": "string"},
"query": {"type": "string"},
"top_k": {"type": "integer", "minimum": 1, "maximum": 50},
"offset": {"type": "integer", "minimum": 0},
},
"required": ["text_id"],
"additionalProperties": False,
},
handler=handler,
read_only=True,
)
__all__ = ["query_text_attachment_tool"]