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Kevin
2026-03-19 14:36:14 +08:00
parent 2f60858c9c
commit c6e07ce5ca
135 changed files with 2111 additions and 4510 deletions
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105
api/app/agents/chat/interview_agent.py
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@@ -2,6 +2,7 @@
InterviewAgent：正式访谈 Specialist
负责状态感知回复、开场白，不负责 Redis 持久化（由 Orchestrator 统一处理）
"""
from typing import Any, List
from app.core.dependencies import get_llm_provider
@@ -36,11 +37,81 @@ class InterviewAgent:
"""根据关键词检测用户正在谈论的人生阶段"""
message = user_message.lower()
stage_keywords = {
"childhood": ["童年", "小时候", "出生", "家乡", "小镇", "爸妈", "父亲", "母亲", "爷爷", "奶奶", "外公", "外婆", "幼儿园"],
"education": ["上学", "学校", "老师", "同学", "教育", "大学", "高中", "初中", "小学", "考试", "毕业", "读书", "高考", "课堂"],
"career": ["工作", "职业", "事业", "公司", "同事", "创业", "升职", "跳槽", "老板", "行业", "项目", "加班", "薪水", "面试"],
"family": ["伴侣", "孩子", "家庭", "家人", "结婚", "爱人", "老婆", "老公", "丈夫", "妻子", "儿子", "女儿", "婚礼", "恋爱"],
"belief": ["信念", "价值观", "座右铭", "坚持", "原则", "信仰", "意义", "感悟", "遗憾", "骄傲"],
"childhood": [
"童年",
"小时候",
"出生",
"家乡",
"小镇",
"爸妈",
"父亲",
"母亲",
"爷爷",
"奶奶",
"外公",
"外婆",
"幼儿园",
],
"education": [
"上学",
"学校",
"老师",
"同学",
"教育",
"大学",
"高中",
"初中",
"小学",
"考试",
"毕业",
"读书",
"高考",
"课堂",
],
"career": [
"工作",
"职业",
"事业",
"公司",
"同事",
"创业",
"升职",
"跳槽",
"老板",
"行业",
"项目",
"加班",
"薪水",
"面试",
],
"family": [
"伴侣",
"孩子",
"家庭",
"家人",
"结婚",
"爱人",
"老婆",
"老公",
"丈夫",
"妻子",
"儿子",
"女儿",
"婚礼",
"恋爱",
],
"belief": [
"信念",
"价值观",
"座右铭",
"坚持",
"原则",
"信仰",
"意义",
"感悟",
"遗憾",
"骄傲",
],
}
for stage, keywords in stage_keywords.items():
if any(word in message for word in keywords):
@@ -81,12 +152,16 @@ class InterviewAgent:
) -> List[str]:
"""生成状态感知的访谈回复，不持久化（由 Orchestrator 负责）"""
if not self.llm:
return ["抱歉，LLM 服务未配置。请设置 DEEPSEEK_API_KEY 或 LLM_API_KEY 环境变量。"]
return [
"抱歉，LLM 服务未配置。请设置 DEEPSEEK_API_KEY 或 LLM_API_KEY 环境变量。"
]
try:
empty_slots = memoir_state.empty_slots_for_current_stage()
filled_slots = {
key: value.snippet
for key, value in memoir_state.slots.get(memoir_state.current_stage, {}).items()
for key, value in memoir_state.slots.get(
memoir_state.current_stage, {}
).items()
if value.snippet
}
detected_user_stage = self._detect_user_stage(user_message)
@@ -110,8 +185,12 @@ class InterviewAgent:
history_string = format_history_string(history_messages)
full_prompt = f"{system_prompt}\n\n{history_string}\n\nHuman: {user_message}\n\nAssistant:"
response = await self.llm.ainvoke(full_prompt)
response_text = response.content if hasattr(response, "content") else str(response)
messages = [msg.strip() for msg in response_text.split("[SPLIT]") if msg.strip()]
response_text = (
response.content if hasattr(response, "content") else str(response)
)
messages = [
msg.strip() for msg in response_text.split("[SPLIT]") if msg.strip()
]
return messages[:3] if messages else [response_text]
except Exception as e:
logger.error("生成回应失败: %s", e)
@@ -138,8 +217,12 @@ class InterviewAgent:
)
full_prompt = f"{prompt}\n\nAssistant:"
response = await self.llm.ainvoke(full_prompt)
response_text = response.content if hasattr(response, "content") else str(response)
messages = [msg.strip() for msg in response_text.split("[SPLIT]") if msg.strip()]
response_text = (
response.content if hasattr(response, "content") else str(response)
)
messages = [
msg.strip() for msg in response_text.split("[SPLIT]") if msg.strip()
]
return messages[:2] if messages else [response_text]
except Exception as e:
logger.error("生成开场白失败: %s", e, exc_info=True)