116 lines
5.1 KiB
Python
116 lines
5.1 KiB
Python
from __future__ import annotations
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from pathlib import Path
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from typing import Any
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from meeting_memory.service import MeetingKnowledgeService
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from .registry import ToolContext, ToolRegistry
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def build_meeting_registry(data_dir: str | Path = "data") -> ToolRegistry:
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registry = ToolRegistry()
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meeting_service = MeetingKnowledgeService(data_dir=data_dir, workspace=Path.cwd())
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registry.register(
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name="import_meeting_transcript",
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description="导入一份会议原文，交给会议整理子Agent按项目梳理重点内容，并把结果更新到指定知识库的同一份Markdown项目台账。",
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parameters={
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"type": "object",
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"properties": {
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"file_path": {"type": "string", "description": "会议转录文本文件路径。"},
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"knowledge_base_id": {
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"type": "string",
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"description": "知识库ID，对应 data/ 下的文件夹名。用户未说明时可以省略；工具会在只有一个知识库时自动使用该库。",
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},
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"team_id": {
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"type": "string",
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"description": "兼容旧参数：等同于 knowledge_base_id。新代码优先使用 knowledge_base_id。",
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},
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"meeting_date": {"type": "string", "description": "会议日期，YYYY-MM-DD，可省略。"},
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},
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"required": ["file_path"],
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"additionalProperties": False,
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},
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handler=lambda ctx, args: _import_meeting(meeting_service, ctx, args),
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)
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registry.register(
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name="query_knowledge",
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description="查询指定知识库项目台账中的项目状态、待办、风险、指标、决策、完成事项和最近会议更新。",
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parameters={
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"type": "object",
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"properties": {
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"query": {"type": "string", "description": "用户查询。"},
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"knowledge_base_id": {
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"type": "string",
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"description": "知识库ID，对应 data/ 下的文件夹名。用户未说明时可以省略；工具会在只有一个知识库时自动使用该库。",
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},
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"team_id": {
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"type": "string",
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"description": "兼容旧参数：等同于 knowledge_base_id。新代码优先使用 knowledge_base_id。",
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},
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"limit": {"type": "integer", "description": "最多返回多少条命中。", "minimum": 1, "maximum": 20},
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},
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"required": ["query"],
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"additionalProperties": False,
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},
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handler=lambda ctx, args: _query_knowledge(meeting_service, ctx, args),
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)
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registry.register(
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name="list_knowledge_bases",
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description="列出 data/ 下已有的知识库ID，用于让用户或Web界面选择要查询的库。",
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parameters={"type": "object", "properties": {}, "additionalProperties": False},
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handler=lambda ctx, args: _list_knowledge_bases(meeting_service, ctx, args),
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)
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return registry
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def _resolve_knowledge_base_arg(ctx: ToolContext, args: dict[str, Any]) -> str:
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return str(
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args.get("knowledge_base_id")
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or args.get("team_id")
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or ctx.session.get("last_knowledge_base_id")
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or ctx.session.get("last_team_id")
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or "default_team"
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)
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def _import_meeting(service: MeetingKnowledgeService, ctx: ToolContext, args: dict[str, Any]) -> dict[str, Any]:
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file_path = str(args["file_path"])
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knowledge_base_id = _resolve_knowledge_base_arg(ctx, args)
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meeting_date = args.get("meeting_date")
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live_event_sink = ctx.session.get("_live_event_sink")
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def progress_callback(payload: dict[str, Any]) -> None:
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if callable(live_event_sink):
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live_event_sink({"kind": "subagent_progress", "payload": payload})
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def should_cancel() -> bool:
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return bool(ctx.session.get("_cancel_requested"))
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result = service.import_meeting_transcript(
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file_path=file_path,
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knowledge_base_id=knowledge_base_id,
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meeting_date=meeting_date,
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progress_callback=progress_callback,
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should_cancel=should_cancel,
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)
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ctx.session["last_knowledge_base_id"] = result.get("knowledge_base_id") or knowledge_base_id
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ctx.session["last_team_id"] = result.get("knowledge_base_id") or knowledge_base_id
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ctx.session["last_ledger_path"] = result.get("ledger_path")
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return result
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def _query_knowledge(service: MeetingKnowledgeService, ctx: ToolContext, args: dict[str, Any]) -> dict[str, Any]:
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knowledge_base_id = _resolve_knowledge_base_arg(ctx, args)
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limit = int(args.get("limit") or 8)
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result = service.query_knowledge(query=str(args["query"]), knowledge_base_id=knowledge_base_id, limit=limit)
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if result.get("knowledge_base_id"):
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ctx.session["last_knowledge_base_id"] = result["knowledge_base_id"]
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ctx.session["last_team_id"] = result["knowledge_base_id"]
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return result
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def _list_knowledge_bases(service: MeetingKnowledgeService, ctx: ToolContext, args: dict[str, Any]) -> dict[str, Any]:
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return service.list_knowledge_bases()
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