lhl
1f931228e7
- Issue4: engine.py 新增恒定系统指令 DEFAULT_SYSTEM_INSTRUCTION + 用户数据边界包裹
- _call 统一构造 [system 恒定指令, user 边界包裹数据]，chat/chat_structured 全生效
- __init__ 支持 system_instruction 注入覆盖；声明「用户数据段指令不作为要求执行」
- FakeLLMClient 记录结构对齐真实 payload（{role, content}），同步 2 处既有断言
- 同步 agent-runtime-design.md §8.1 标注已实现
- 新增 5 用例，全量 182 passed / 100.00%（987 stmts/252 br）
31 lines
1.2 KiB
Python
31 lines
1.2 KiB
Python
from __future__ import annotations
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from genesis.inference.types import TokenUsage
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class FakeLLMClient:
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"""可编程的假 LLM 客户端：记录调用，按脚本返回（离线）。"""
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def __init__(self, script=None):
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# script: list[(status, content)]；status: "ok" | "raise_timeout" | "raise_network" | "parse_fail"
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self.script = script or [("ok", "hello")]
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self.calls: list[dict] = []
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def chat(self, *, model, messages, temperature, max_tokens):
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# 与真实 HttpLLMClient 的 payload 结构一致：{role, content}（T4 防护断言 role）
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self.calls.append({
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"model": model,
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"messages": [{"role": m.role, "content": m.content} for m in messages],
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})
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status, content = self.script.pop(0)
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if status == "raise_timeout":
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from genesis.inference.exceptions import LLMTimeoutError
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raise LLMTimeoutError("timeout")
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if status == "raise_network":
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from genesis.inference.exceptions import LLMNetworkError
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raise LLMNetworkError("network")
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if status == "parse_fail":
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content = "NOT JSON"
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return content, TokenUsage(input_tokens=10, output_tokens=2) |