添加agent优化简历接口

app/ai/job_agent/prompts.py

@@ -1,4 +1,4 @@
-"""求职助手 Agent 对话 Prompt 模板"""
+"""求职助手 Agent 对话 Prompt 模板 + 岗位简历优化 Prompt"""
 
 SYSTEM_PROMPT = """你是 OfferPie 求职助手，帮助用户找到合适的工作。
 
@@ -32,3 +32,42 @@ tool 可选值：
 5. 偏好描述要准确概括用户的岗位偏好，如"更偏技术方向的产品岗"、"大厂优先"
 6. 如果用户没有明确偏好，preference 填"无特殊偏好"
 """
+
+
+# ===== 岗位简历优化 Prompt =====
+
+RESUME_SUMMARY_OPTIMIZE_PROMPT = """你是一个求职投递助手。用户即将投递目标岗位，请针对该岗位优化用户的个人概述。
+
+【目标岗位】
+{job_title}
+
+【岗位职责与要求】
+{job_description}
+
+【原始个人概述】
+{original_summary}
+
+规则：
+1. 保持原文风格和主体内容不变
+2. 突出与目标岗位最相关的经验和能力
+3. 适当融入岗位要求中的关键词，但不要生硬堆砌
+4. 避免过度优化和编造内容，改动越少越好
+5. 直接输出优化后的文本，不要其他内容"""
+
+RESUME_EXPERIENCE_OPTIMIZE_PROMPT = """你是一个求职投递助手。用户即将投递目标岗位，请针对该岗位微调用户的经历描述。
+
+【目标岗位】
+{job_title}
+
+【岗位职责与要求】
+{job_description}
+
+【原始经历数据】
+{original_module_data}
+
+规则：
+1. 基本保持原文不变，只在可以优化的地方做轻微调整
+2. 突出与目标岗位最匹配的经历和成果
+3. 适当使用岗位要求中的关键词润色描述，但不要编造内容
+4. description 字段是 [{{"id": "xxx", "text": "xxx"}}] 格式：修改时保留原 id 只改 text，新增段落生成随机8位字符串作为 id，删除段落直接移除
+5. 返回修改后的完整模块数据（JSON 格式，与输入格式一致）"""

app/ai/job_agent/resume_optimizer.py

@@ -0,0 +1,55 @@
+"""求职助手 - 岗位简历优化 AI 引擎
+
+针对目标岗位并发优化简历（summary + 经历子表）。
+依赖：LLM 枚举、job_agent/prompts、parse_llm_json
+"""
+
+from langchain_core.output_parsers import StrOutputParser
+from langchain_core.prompts import ChatPromptTemplate
+
+from app.ai.job_agent.prompts import RESUME_SUMMARY_OPTIMIZE_PROMPT, RESUME_EXPERIENCE_OPTIMIZE_PROMPT
+from app.ai.models import LLM
+from app.core.logger import log
+from app.tool.json_helper import parse_llm_json
+
+# ===== summary 优化 =====
+
+_summary_chain = (
+    ChatPromptTemplate.from_messages([("system", RESUME_SUMMARY_OPTIMIZE_PROMPT), ("human", "请开始优化。")])
+    | LLM.JIAYU_CLAUDE_SONNET_4_5.create(temperature=0.3)
+    | StrOutputParser()
+)
+
+
+async def optimize_summary(job_title: str, job_description: str, original_summary: str) -> str:
+    """针对岗位优化个人概述"""
+    try:
+        return await _summary_chain.ainvoke({
+            "job_title": job_title, "job_description": job_description or "",
+            "original_summary": original_summary or "暂无",
+        })
+    except Exception as e:
+        log.warning(f"岗位简历summary优化失败: {e}")
+        return original_summary
+
+
+# ===== 经历优化 =====
+
+_experience_chain = (
+    ChatPromptTemplate.from_messages([("system", RESUME_EXPERIENCE_OPTIMIZE_PROMPT), ("human", "请开始优化。")])
+    | LLM.JIAYU_CLAUDE_SONNET_4_5.create(temperature=0.3)
+    | StrOutputParser()
+)
+
+
+async def optimize_experience(job_title: str, job_description: str, module_data: str) -> list | dict | None:
+    """针对岗位优化经历模块描述，返回修改后的完整模块数据"""
+    try:
+        raw = await _experience_chain.ainvoke({
+            "job_title": job_title, "job_description": job_description or "",
+            "original_module_data": module_data,
+        })
+        return parse_llm_json(raw)
+    except Exception as e:
+        log.warning(f"岗位简历经历优化失败: {e}")
+        return None

app/api/job_agent_chat.py

@@ -4,7 +4,7 @@ from fastapi import APIRouter
 
 from app.core.context import RequestContext
 from app.core.database import get_db
-from app.schemas.job_agent_chat import JobAgentChatParam
+from app.schemas.job_agent_chat import JobAgentChatParam, OptimizeResumeParam
 from app.services.job_agent_chat_service import JobAgentChatService
 
 router = APIRouter(prefix="/job-agent", tags=["求职助手agent"])
@@ -22,3 +22,13 @@ async def chat(param: JobAgentChatParam):
             param.job_categories, param.regions, param.industries,
         )
     return result
+
+
+@router.post("/optimize-resume", summary="针对岗位优化简历")
+async def optimize_resume(param: OptimizeResumeParam):
+    """根据目标岗位，AI并发优化简历（summary + 5张子表经历），存Redis并返回"""
+    user_id = RequestContext.user_id.get()
+    async for session in get_db():
+        service = JobAgentChatService(session)
+        result = await service.optimize_resume(user_id, param.resume_id, param.job_id)
+    return result

app/schemas/job_agent_chat.py

@@ -35,3 +35,8 @@ class JobAgentChatDto(BaseModel):
     tool_params: ToolParams | None = Field(default=None, alias="toolParams", description="工具参数")
 
     model_config = {"populate_by_name": True}
+
+
+class OptimizeResumeParam(BaseModel):
+    resume_id: int = Field(..., alias="resumeId", description="简历ID")
+    job_id: int = Field(..., alias="jobId", description="岗位ID")

app/services/customize_resume_store.py

@@ -1,11 +1,17 @@
-"""定制简历 Redis 存取模块
+"""定制简历 Redis 存取 + 数据转换模块
 
-提供定制简历的保存（自动回滚备份）、查询、回滚能力。
+提供定制简历的保存（自动回滚备份）、查询、回滚、从 ResumeDetail 构建能力。
 各 Service 统一复用，不直接操作 Redis key。
 """
 
+import random
+import string
+
 from app.core.redis import RedisManager
-from app.schemas.customize_resume import CustomizeResume
+from app.schemas.customize_resume import (
+    CustomizeResume, ResumeProfile, Education, Work, Internship, Project, Competition, Paragraph,
+)
+from app.services.resume_loader import ResumeDetail
 
 # Redis 常量
 KEY_PREFIX = "customize:resume:"
@@ -13,16 +19,59 @@ EXPIRE = 12 * 60 * 60  # 12小时
 ROLLBACK_KEY_PREFIX = "customize:resume:rollback:"
 ROLLBACK_EXPIRE = 30 * 60  # 30分钟
 
+_CHARS = string.ascii_letters + string.digits
+
+
+def _rand_id() -> str:
+    """生成随机8位字符串标识"""
+    return "".join(random.choices(_CHARS, k=8))
+
+
+def _build_paragraphs(description: list[dict] | None) -> list[Paragraph]:
+    """将数据库 description [{id, text}] 转为 Paragraph 列表"""
+    if not description:
+        return []
+    return [Paragraph(id=_rand_id(), text=item.get("text", "")) for item in description if isinstance(item, dict)]
+
+
+def build_from_detail(detail: ResumeDetail) -> CustomizeResume:
+    """从 ResumeDetail 组装 CustomizeResume"""
+    resume = detail.resume
+    profile = ResumeProfile(
+        avatarUrl=resume.avatar_url or "", name=resume.name or "", email=resume.email or "",
+        mobileNumber=resume.mobile_number or "", city=resume.city or "",
+        wechatNumber=resume.wechat_number or "", portfolioUrl=resume.portfolio_url or "",
+        skills=resume.skills or [], certificates=resume.certificates or [],
+        summary=resume.summary or "",
+    )
+    return CustomizeResume(
+        resume=profile,
+        education=[Education(id=_rand_id(), school=r.school or "", major=r.major or "",
+                             degree=r.degree or "", studyType=r.study_type or "",
+                             startDate=r.start_date or "", endDate=r.end_date or "",
+                             description=_build_paragraphs(r.description)) for r in detail.education],
+        work=[Work(id=_rand_id(), companyName=r.company_name or "", position=r.position or "",
+                   startDate=r.start_date or "", endDate=r.end_date or "",
+                   description=_build_paragraphs(r.description)) for r in detail.work],
+        internship=[Internship(id=_rand_id(), companyName=r.company_name or "", position=r.position or "",
+                               startDate=r.start_date or "", endDate=r.end_date or "",
+                               description=_build_paragraphs(r.description)) for r in detail.internship],
+        project=[Project(id=_rand_id(), companyName=r.company_name or "", projectName=r.project_name or "",
+                         role=r.role or "", startDate=r.start_date or "", endDate=r.end_date or "",
+                         description=_build_paragraphs(r.description)) for r in detail.project],
+        competition=[Competition(id=_rand_id(), competitionName=r.competition_name or "", award=r.award or "",
+                                 awardDate=r.award_date or "",
+                                 description=_build_paragraphs(r.description)) for r in detail.competition],
+    )
+
 
 async def save(user_id: int, cr: CustomizeResume) -> None:
     """保存定制简历，自动备份旧版本到回滚 key"""
     key = f"{KEY_PREFIX}{user_id}"
     rollback_key = f"{ROLLBACK_KEY_PREFIX}{user_id}"
-    # 备份旧数据
     old_data = await RedisManager.client.get(key)
     if old_data:
         await RedisManager.client.set(rollback_key, old_data, ex=ROLLBACK_EXPIRE)
-    # 存新数据
     await RedisManager.client.set(key, cr.model_dump_json(by_alias=True), ex=EXPIRE)
 
 

app/services/job_agent_chat_service.py

@@ -1,14 +1,23 @@
-"""求职助手 Agent 对话 Service
+"""求职助手 Agent 对话 + 岗位简历优化 Service
 
-主要功能：查询简历数据，调用 AI 模块完成对话。
+主要功能：查询简历数据，调用 AI 模块完成对话；针对岗位并发优化简历。
-依赖：resume_loader（简历统一查询）、job_agent.chat AI 模块
+依赖：resume_loader（简历统一查询）、customize_resume_store（定制简历存取+构建）、job_agent.chat AI 模块、job_agent.resume_optimizer（岗位简历优化）
-使用表：bg_user_resume + 5张子表（通过 resume_loader 查询）
+使用表：bg_user_resume + 5张子表（通过 resume_loader 查询）、bg_job（查岗位）
 """
 
+import asyncio
+import json
+
+from sqlalchemy import select
 from sqlalchemy.ext.asyncio import AsyncSession
 
 from app.ai.job_agent.chat import agent_chat
+from app.ai.job_agent.resume_optimizer import optimize_summary, optimize_experience
+from app.core.logger import log
+from app.models.job import Job
+from app.schemas.customize_resume import CustomizeResume, Education, Work, Internship, Project, Competition
 from app.services.resume_loader import ResumeDetail, load_resume_detail
+from app.services import customize_resume_store
 
 
 class JobAgentChatService:
@@ -60,3 +69,58 @@ class JobAgentChatService:
             for r in detail.competition:
                 parts.append(f"  - {r.competition_name or ''} {r.award or ''}")
         return "\n".join(parts) if parts else "暂无简历信息"
+
+    async def optimize_resume(self, user_id: int, resume_id: int, job_id: int) -> dict:
+        """针对岗位优化简历：查简历+岗位 → 构建定制简历 → 并发AI优化 → 存Redis → 返回"""
+        # 1. 查简历 + 岗位
+        detail = await load_resume_detail(self.session, resume_id, user_id)
+        job = await self._get_job(job_id)
+        # 2. 构建定制简历
+        cr = customize_resume_store.build_from_detail(detail)
+        # 3. 并发 AI 优化（summary + 5张子表经历）
+        tasks = []
+        job_desc = f"{job.description or ''}\n{job.requirement or ''}"
+        if cr.resume.summary:
+            tasks.append(("summary", optimize_summary(job.title or "", job_desc, cr.resume.summary)))
+        for name, items in [("education", cr.education), ("work", cr.work), ("internship", cr.internship),
+                            ("project", cr.project), ("competition", cr.competition)]:
+            if items:
+                rows_json = json.dumps([item.model_dump(by_alias=True) for item in items], ensure_ascii=False)
+                tasks.append((name, optimize_experience(job.title or "", job_desc, rows_json)))
+        # 执行并发
+        if tasks:
+            keys = [t[0] for t in tasks]
+            results = await asyncio.gather(*[t[1] for t in tasks], return_exceptions=True)
+            for key, result in zip(keys, results):
+                if isinstance(result, Exception):
+                    log.warning(f"岗位简历优化[{key}]失败: {result}")
+                    continue
+                self._apply_optimize_result(cr, key, result)
+        # 4. 存 Redis
+        await customize_resume_store.save(user_id, cr)
+        # 5. 返回
+        return cr.model_dump(by_alias=True)
+
+    async def _get_job(self, job_id: int) -> Job:
+        """查岗位"""
+        result = await self.session.execute(select(Job).where(Job.id == job_id))
+        job = result.scalar_one_or_none()
+        if not job:
+            raise ValueError("岗位不存在")
+        return job
+
+    @staticmethod
+    def _apply_optimize_result(cr: CustomizeResume, key: str, result) -> None:
+        """将 AI 优化结果应用到定制简历"""
+        if key == "summary" and isinstance(result, str):
+            cr.resume.summary = result
+        elif key == "education" and isinstance(result, list):
+            cr.education = [Education.model_validate(item) for item in result]
+        elif key == "work" and isinstance(result, list):
+            cr.work = [Work.model_validate(item) for item in result]
+        elif key == "internship" and isinstance(result, list):
+            cr.internship = [Internship.model_validate(item) for item in result]
+        elif key == "project" and isinstance(result, list):
+            cr.project = [Project.model_validate(item) for item in result]
+        elif key == "competition" and isinstance(result, list):
+            cr.competition = [Competition.model_validate(item) for item in result]

app/services/skill_gap_service.py

@@ -8,8 +8,6 @@
 
 import asyncio
 import json
-import random
-import string
 
 from sqlalchemy import select
 from sqlalchemy.ext.asyncio import AsyncSession
@@ -21,15 +19,13 @@ from app.ai.skill_gap_analyzer.analyzer import (
 from app.ai.skill_gap_analyzer.prompts import MODULE_SCHEMAS
 from app.core.logger import log
 from app.schemas.customize_resume import (
-    CustomizeResume, ResumeProfile, Education, Work, Internship, Project, Competition, Paragraph,
+    CustomizeResume, ResumeProfile, Education, Work, Internship, Project, Competition,
 )
 from app.models.job import Job
 from app.models.user_resume import UserResume
 from app.services.resume_loader import ResumeDetail, load_resume_detail, load_default_resume_detail
 from app.services import customize_resume_store
 
-_CHARS = string.ascii_letters + string.digits
-
 # 模块名 → 中文标签映射
 _MODULE_LABELS = {
     "resume": "个人简介",
@@ -41,18 +37,6 @@ _MODULE_LABELS = {
 }
 
 
-def _rand_id() -> str:
-    """生成随机8位字符串标识"""
-    return "".join(random.choices(_CHARS, k=8))
-
-
-def _build_paragraphs(description: list[dict] | None) -> list[Paragraph]:
-    """将数据库 description [{id, text}] 转为 Paragraph 列表，id 用随机8位替换"""
-    if not description:
-        return []
-    return [Paragraph(id=_rand_id(), text=item.get("text", "")) for item in description if isinstance(item, dict)]
-
-
 def _build_resume_json(detail: ResumeDetail) -> str:
     """拼装简历 JSON 字符串供 AI 使用"""
     resume = detail.resume
@@ -120,7 +104,7 @@ class SkillGapService:
         detail = await load_resume_detail(self.session, resume_id, user_id)
         job = await self._get_job(job_id)
         # 2. 组装基础定制简历
-        cr = self._build_customize_resume(detail)
+        cr = customize_resume_store.build_from_detail(detail)
         # 3. 并发 AI 优化
         tasks = []
         job_desc = f"{job.description or ''}\n{job.requirement or ''}"
@@ -339,34 +323,3 @@ class SkillGapService:
         if not job:
             raise ValueError("岗位不存在")
         return job
-
-    def _build_customize_resume(self, detail: ResumeDetail) -> CustomizeResume:
-        """从 ResumeDetail 组装 CustomizeResume"""
-        resume = detail.resume
-        profile = ResumeProfile(
-            avatarUrl=resume.avatar_url or "", name=resume.name or "", email=resume.email or "",
-            mobileNumber=resume.mobile_number or "", city=resume.city or "",
-            wechatNumber=resume.wechat_number or "", portfolioUrl=resume.portfolio_url or "",
-            skills=resume.skills or [], certificates=resume.certificates or [],
-            summary=resume.summary or "",
-        )
-        return CustomizeResume(
-            resume=profile,
-            education=[Education(id=_rand_id(), school=r.school or "", major=r.major or "",
-                                 degree=r.degree or "", studyType=r.study_type or "",
-                                 startDate=r.start_date or "", endDate=r.end_date or "",
-                                 description=_build_paragraphs(r.description)) for r in detail.education],
-            work=[Work(id=_rand_id(), companyName=r.company_name or "", position=r.position or "",
-                       startDate=r.start_date or "", endDate=r.end_date or "",
-                       description=_build_paragraphs(r.description)) for r in detail.work],
-            internship=[Internship(id=_rand_id(), companyName=r.company_name or "", position=r.position or "",
-                                   startDate=r.start_date or "", endDate=r.end_date or "",
-                                   description=_build_paragraphs(r.description)) for r in detail.internship],
-            project=[Project(id=_rand_id(), companyName=r.company_name or "", projectName=r.project_name or "",
-                             role=r.role or "", startDate=r.start_date or "", endDate=r.end_date or "",
-                             description=_build_paragraphs(r.description)) for r in detail.project],
-            competition=[Competition(id=_rand_id(), competitionName=r.competition_name or "", award=r.award or "",
-                                     awardDate=r.award_date or "",
-                                     description=_build_paragraphs(r.description)) for r in detail.competition],
-        )
-