1e74ae3cd6
- 新增 OpenAI-compatible LLM client，支持 base_url、api_key、model 配置 - 固化意图识别、参数抽取、部署计划生成的结构化 JSON 提示词 - 增加 MCP client 配置读取和真实 session 接入说明 - 实现 checkpoint 自动保存、resume 断点续跑和已完成步骤跳过 - 实现人工确认流程，支持失败 IP 回滚 approve/reject - 新增 chat 常驻式 CLI 对话框，支持自然语言分析、参数设置、执行确认、状态查看、回滚确认和续跑 - 同步 README，补充 LLM、MCP、checkpoint、confirm/resume、chat 使用方式 - 增加相关单元测试，覆盖 LLM client、MCP 配置、确认/续跑和交互式 CLI
53 lines
1.6 KiB
Python
53 lines
1.6 KiB
Python
"""Business checkpoint JSON storage."""
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from __future__ import annotations
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import json
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from dataclasses import asdict, fields, is_dataclass
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from pathlib import Path
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from typing import Any
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from .constants import SENSITIVE_KEYS
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from .models import AgentState
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def redact_mapping(value: Any) -> Any:
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if isinstance(value, dict):
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result = {}
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for key, item in value.items():
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if str(key) in SENSITIVE_KEYS:
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result[key] = "***"
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else:
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result[key] = redact_mapping(item)
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return result
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if isinstance(value, list):
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return [redact_mapping(item) for item in value]
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return value
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def save_checkpoint(state: Any, path: str | Path, *, redact: bool = True) -> Path:
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checkpoint_path = Path(path)
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checkpoint_path.parent.mkdir(parents=True, exist_ok=True)
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payload = asdict(state) if is_dataclass(state) else state
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if redact:
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payload = redact_mapping(payload)
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checkpoint_path.write_text(
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json.dumps(payload, ensure_ascii=False, indent=2),
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encoding="utf-8",
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)
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return checkpoint_path
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def load_checkpoint(path: str | Path) -> dict[str, Any]:
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return json.loads(Path(path).read_text(encoding="utf-8"))
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def agent_state_from_mapping(payload: dict[str, Any]) -> AgentState:
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allowed_fields = {item.name for item in fields(AgentState)}
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state_payload = {key: value for key, value in payload.items() if key in allowed_fields}
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return AgentState(**state_payload)
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def load_agent_state(path: str | Path) -> AgentState:
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return agent_state_from_mapping(load_checkpoint(path))
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