d01c4d3d06
- 新增 MCP client 配置加载，支持 CLI/chat 通过配置文件接入 MCP - 完善 chat 交互命令，支持参数查看、事件查看、checkpoint 列表与加载 - 增加 LLM action 后诊断能力，支持真实 LLM 和本地规则兜底 - 将 chat 人工确认点接入 LangGraph interrupt/checkpointer - 更新 README、流程图、待办文档和打包说明 - 补充相关单元测试
47 lines
1.1 KiB
Python
47 lines
1.1 KiB
Python
"""LLM client 需要实现的共享协议。"""
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from __future__ import annotations
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from typing import Any, Protocol
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from pam_deploy_graph.models import (
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ActionResult,
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ExecutionStrategy,
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LlmActionAnalysis,
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LlmDeployPlan,
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LlmIntentResult,
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LlmParamResult,
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)
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class LlmClient(Protocol):
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"""Agent 使用的最小 LLM 能力接口。"""
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def understand_request(self, text: str) -> LlmIntentResult:
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"""识别用户自然语言请求的意图。"""
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...
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def extract_params(self, text: str, base_params: dict[str, Any] | None = None) -> LlmParamResult:
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"""从自然语言中抽取部署参数。"""
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...
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def generate_plan(
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self,
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*,
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params: dict[str, Any],
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intent: str,
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strategy: ExecutionStrategy,
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) -> LlmDeployPlan:
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"""根据参数和意图生成部署计划。"""
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...
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def analyze_action_result(
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self,
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*,
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action: str,
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result: ActionResult,
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state_summary: dict[str, Any],
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) -> LlmActionAnalysis:
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"""分析 action 执行结果，并给出辅助诊断建议。"""
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...
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