84 lines
2.9 KiB
Python
84 lines
2.9 KiB
Python
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"""独立候选回放：多轮 user 链式调用 LLM，不走路由 WS / ChatOrchestrator。"""
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from __future__ import annotations
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import time
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from typing import Any
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from app.core.logging import get_logger
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logger = get_logger(__name__)
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def _system_prompt_for_eval(version_config: dict | None) -> str:
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cfg = version_config or {}
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extra = (cfg.get("system_prompt_suffix") or "").strip()
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base = """你是「岁月留书」老年友好访谈员。语气温暖、耐心，先承接情绪再 gently 追问事实与感受；回答简洁分段，避免术语。"""
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if extra:
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return f"{base}\n\n{extra}"
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return base
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def _model_override(version_config: dict | None) -> str | None:
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if not version_config:
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return None
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m = version_config.get("model")
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return str(m).strip() if m else None
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class EvalCandidateRunner:
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"""使用 LangChain Chat 模型回放用户轮次。"""
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def __init__(self, llm: Any) -> None:
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self._llm = llm
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async def replay_utterances(
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self,
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utterances: list[str],
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*,
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version_config: dict | None = None,
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temperature: float = 0.7,
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) -> tuple[list[str], list[int]]:
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"""返回每轮 assistant 回复与耗时 ms。"""
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if not self._llm:
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raise RuntimeError(" replay: llm 未配置")
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from langchain_core.messages import AIMessage, HumanMessage, SystemMessage
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sys_prompt = _system_prompt_for_eval(version_config)
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model = _model_override(version_config)
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lc_messages: list = [SystemMessage(content=sys_prompt)]
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replies: list[str] = []
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latencies: list[int] = []
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bound = (
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self._llm.bind(model=model, temperature=temperature)
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if model
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else self._llm.bind(temperature=temperature)
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)
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for u in utterances:
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text = (u or "").strip()
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if not text:
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continue
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lc_messages.append(HumanMessage(content=text))
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t0 = time.perf_counter()
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result = await bound.ainvoke(lc_messages)
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elapsed_ms = int((time.perf_counter() - t0) * 1000)
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reply = str(getattr(result, "content", "") or "").strip()
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replies.append(reply)
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latencies.append(elapsed_ms)
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lc_messages.append(AIMessage(content=reply))
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return replies, latencies
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def simple_memoir_from_transcript(utterances: list[str], replies: list[str]) -> str:
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"""轻量成稿：供评审用占位（非生产叙事管线）。"""
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lines = ["# 访谈摘录整理（评测占位稿）", ""]
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for i, u in enumerate(utterances):
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lines.append(f"## 片段 {i + 1}")
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lines.append("")
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lines.append(f"**用户：** {u.strip()}")
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if i < len(replies):
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lines.append("")
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lines.append(f"**访谈者：** {replies[i].strip()}")
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lines.append("")
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return "\n".join(lines)
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