Chengfang Lu
7c43b44c57
Huaxu Sentinel Active Safety Platform with embedded algorithm code, Docker Compose setup, and vendored dataset scaffolds for clone-and-run. Co-authored-by: Cursor <cursoragent@cursor.com>
87 lines
2.5 KiB
Python
87 lines
2.5 KiB
Python
"""LangChain 风格 Tool 注册（纯 Python + 可选 langchain）。"""
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from __future__ import annotations
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from typing import Any, Callable
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from as_platform.audit.queue import submit_approval
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from as_platform.data.core import get_catalog, get_pending_report, load_wf
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from as_platform.jobs.queue import get_job, list_jobs
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import yaml
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from pathlib import Path
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WORKSPACE = Path(__file__).resolve().parents[2]
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def list_pending_batches() -> dict[str, Any]:
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return get_pending_report()
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def get_dataset_catalog() -> dict[str, Any]:
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return get_catalog()
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def submit_build_for_batch(task: str, batch: str, pack: str = "dms_v2", submitted_by: str | None = None) -> dict:
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return submit_approval(
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"build_dms",
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{"task": task, "pack": pack, "batch": batch},
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submitted_by=submitted_by,
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note=f"agent build {batch}",
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)
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def submit_train_job(project: str, task: str, track: str = "platform", submitted_by: str | None = None) -> dict:
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action = "train_dms" if project == "dms" else "train_lane"
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params: dict[str, Any] = {"track": track}
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if project == "dms":
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params["task"] = task
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return submit_approval(action, params, submitted_by=submitted_by, note=f"agent train {project}/{task}")
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def get_job_status(job_id: str) -> dict[str, Any] | None:
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return get_job(job_id)
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def get_model_versions(task: str) -> dict[str, Any]:
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root = WORKSPACE / "datasets/dms/manifests/train_versions.yaml"
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if not root.is_file():
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return {}
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data = yaml.safe_load(root.read_text(encoding="utf-8"))
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return data.get(task, {})
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TOOL_REGISTRY: dict[str, Callable[..., Any]] = {
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"list_pending_batches": list_pending_batches,
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"get_dataset_catalog": get_dataset_catalog,
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"submit_build_for_batch": submit_build_for_batch,
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"submit_train_job": submit_train_job,
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"get_job_status": get_job_status,
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"get_model_versions": get_model_versions,
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}
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def invoke_tool(name: str, **kwargs: Any) -> Any:
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fn = TOOL_REGISTRY.get(name)
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if not fn:
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raise ValueError(f"未知 tool: {name}")
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return fn(**kwargs)
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def as_langchain_tools() -> list[Any]:
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try:
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from langchain_core.tools import tool
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except ImportError:
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return []
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@tool
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def t_list_pending_batches() -> dict:
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"""列出待处理批次与送标状态。"""
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return list_pending_batches()
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@tool
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def t_get_dataset_catalog() -> dict:
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"""获取 DMS/Lane 数据目录统计。"""
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return get_dataset_catalog()
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return [t_list_pending_batches, t_get_dataset_catalog]
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