63 lines
1.6 KiB
Python
63 lines
1.6 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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LlmModeDecision,
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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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skill_policy: dict[str, Any],
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tool_summaries: list[dict[str, Any]],
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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 decide_execution_mode(
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self,
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*,
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text: str,
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params: dict[str, Any],
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intent: str,
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strategy: ExecutionStrategy,
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allowed_modes: list[str],
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tool_summaries: list[dict[str, Any]],
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) -> LlmModeDecision:
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"""决定进入固定 runtime 还是 agentic skill 模式。"""
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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，并给出是否允许继续执行的建议。"""
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...
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