159 lines
7.1 KiB
Python
159 lines
7.1 KiB
Python
"""简历两阶段并行提取
|
||
|
||
第一阶段：5路并行提取主表短字段 + 各子表标识名（极快，输出极短）。
|
||
第二阶段：N+1路并行提取每条子表记录的短字段 + description，以及 profile 补充（skills/certificates/summary）。
|
||
description/summary 由 AI 直接按原文结构输出为字符串数组（不再返回行号区间），代码只做类型兜底与清理。
|
||
最终组装为与原方案一致的 dict 结构（description 为 list[str]，summary 为 str），上下游无感知。
|
||
"""
|
||
|
||
import asyncio
|
||
import time
|
||
|
||
from langchain_core.output_parsers import StrOutputParser
|
||
from langchain_core.prompts import ChatPromptTemplate
|
||
|
||
from app.ai.model_config import ResumeExtractorModel
|
||
from app.ai.resume_extractor.prompts import (
|
||
OVERVIEW_PROFILE_PROMPT, OVERVIEW_EDUCATION_PROMPT, OVERVIEW_WORK_PROMPT,
|
||
OVERVIEW_PROJECT_PROMPT, OVERVIEW_COMPETITION_PROMPT,
|
||
DETAIL_PROFILE_PROMPT, DETAIL_EDUCATION_PROMPT, DETAIL_WORK_PROMPT,
|
||
DETAIL_INTERNSHIP_PROMPT, DETAIL_PROJECT_PROMPT, DETAIL_COMPETITION_PROMPT,
|
||
)
|
||
from app.core.logger import log
|
||
from app.tool.json_helper import parse_llm_json
|
||
|
||
|
||
# ==================== LLM 调用工具 ====================
|
||
|
||
def _build_chain(prompt: str):
|
||
"""构建提取链：prompt → LLM → 文本输出"""
|
||
return ChatPromptTemplate.from_messages([("system", prompt), ("human", "{text}")]) | ResumeExtractorModel.PARSE | StrOutputParser()
|
||
|
||
|
||
async def _safe_invoke(chain, inp: dict, label: str):
|
||
"""单个链调用，记录耗时，失败返回空"""
|
||
start = time.perf_counter()
|
||
try:
|
||
raw = await chain.ainvoke(inp)
|
||
log.info(f"AI提取[{label}]完成，耗时: {time.perf_counter() - start:.2f}s")
|
||
return parse_llm_json(raw)
|
||
except Exception as e:
|
||
log.warning(f"AI提取[{label}]失败，耗时: {time.perf_counter() - start:.2f}s，错误: {e}")
|
||
return None
|
||
|
||
|
||
def _clean_str_list(value) -> list[str]:
|
||
"""将 AI 返回值规整为字符串数组：过滤非字符串与空白元素，去除首尾空白"""
|
||
if not isinstance(value, list):
|
||
return []
|
||
return [s.strip() for s in value if isinstance(s, str) and s.strip()]
|
||
|
||
|
||
# ==================== 第一阶段：概览 ====================
|
||
|
||
_overview_profile_chain = _build_chain(OVERVIEW_PROFILE_PROMPT)
|
||
_overview_education_chain = _build_chain(OVERVIEW_EDUCATION_PROMPT)
|
||
_overview_work_chain = _build_chain(OVERVIEW_WORK_PROMPT)
|
||
_overview_project_chain = _build_chain(OVERVIEW_PROJECT_PROMPT)
|
||
_overview_competition_chain = _build_chain(OVERVIEW_COMPETITION_PROMPT)
|
||
|
||
|
||
async def _extract_overview(text: str) -> dict:
|
||
"""第一阶段：5路并行提取概览信息"""
|
||
inp = {"text": text}
|
||
profile, edu_names, work_names, proj_names, comp_names = await asyncio.gather(
|
||
_safe_invoke(_overview_profile_chain, inp, "概览-个人信息"),
|
||
_safe_invoke(_overview_education_chain, inp, "概览-教育"),
|
||
_safe_invoke(_overview_work_chain, inp, "概览-工作实习"),
|
||
_safe_invoke(_overview_project_chain, inp, "概览-项目"),
|
||
_safe_invoke(_overview_competition_chain, inp, "概览-竞赛"),
|
||
)
|
||
return {
|
||
"profile": profile if isinstance(profile, dict) else {},
|
||
"education": edu_names if isinstance(edu_names, list) else [],
|
||
"work": work_names.get("work", []) if isinstance(work_names, dict) else [],
|
||
"internship": work_names.get("internship", []) if isinstance(work_names, dict) else [],
|
||
"project": proj_names if isinstance(proj_names, list) else [],
|
||
"competition": comp_names if isinstance(comp_names, list) else [],
|
||
}
|
||
|
||
|
||
# ==================== 第二阶段：详情 ====================
|
||
|
||
# 子表模块统一配置（单一数据源）：(模块键, 详情 prompt 模板, 日志标签)
|
||
# 概览/详情/组装/日志均复用此清单，新增子表只需在此追加一行。
|
||
_DETAIL_MODULES: tuple[tuple[str, str, str], ...] = (
|
||
("education", DETAIL_EDUCATION_PROMPT, "教育"),
|
||
("work", DETAIL_WORK_PROMPT, "工作"),
|
||
("internship", DETAIL_INTERNSHIP_PROMPT, "实习"),
|
||
("project", DETAIL_PROJECT_PROMPT, "项目"),
|
||
("competition", DETAIL_COMPETITION_PROMPT, "竞赛"),
|
||
)
|
||
_SUB_MODULES: tuple[str, ...] = tuple(m[0] for m in _DETAIL_MODULES)
|
||
|
||
|
||
async def _extract_detail(prompt_tpl: str, name: str, text: str, label: str) -> dict | None:
|
||
"""单条子表记录详情提取：用 name 替换 prompt 中的 {name}"""
|
||
chain = _build_chain(prompt_tpl.replace("{name}", name))
|
||
return await _safe_invoke(chain, {"text": text}, label)
|
||
|
||
|
||
async def _extract_all_details(overview: dict, text: str) -> dict:
|
||
"""第二阶段：根据概览结果，N+1路并行提取所有子表记录详情 + 个人信息补充"""
|
||
# 第 0 路固定为 profile 补充（skills/certificates/summary），其余按子表记录展开
|
||
tasks = [_extract_detail(DETAIL_PROFILE_PROMPT, "", text, "详情-个人信息补充")]
|
||
task_modules = ["profile_extra"]
|
||
for module, prompt_tpl, label in _DETAIL_MODULES:
|
||
for name in overview[module]:
|
||
tasks.append(_extract_detail(prompt_tpl, name, text, f"详情-{label}-{name}"))
|
||
task_modules.append(module)
|
||
|
||
results = await asyncio.gather(*tasks)
|
||
details: dict[str, list] = {"profile_extra": [], **{m: [] for m in _SUB_MODULES}}
|
||
for module, result in zip(task_modules, results):
|
||
details[module].append(result if isinstance(result, dict) else {})
|
||
return details
|
||
|
||
|
||
# ==================== 组装 ====================
|
||
|
||
def _assemble(overview: dict, details: dict) -> dict:
|
||
"""将两阶段结果组装为与原方案一致的 dict 结构（description 为 list[str]，summary 为 str）"""
|
||
profile = overview["profile"]
|
||
profile_extra = details.get("profile_extra", [{}])[0] if details.get("profile_extra") else {}
|
||
profile["skills"] = _clean_str_list(profile_extra.get("skills"))[:5]
|
||
profile["certificates"] = _clean_str_list(profile_extra.get("certificates"))
|
||
summary_paras = _clean_str_list(profile_extra.get("summary"))
|
||
profile["summary"] = "\n".join(summary_paras) if summary_paras else None
|
||
|
||
result = dict(profile)
|
||
for module in _SUB_MODULES:
|
||
items = []
|
||
for item in details.get(module, []):
|
||
item["description"] = _clean_str_list(item.get("description"))
|
||
items.append(item)
|
||
result[module] = items
|
||
return result
|
||
|
||
|
||
# ==================== 入口 ====================
|
||
|
||
async def extract_all(text: str) -> dict:
|
||
"""两阶段并行提取简历，返回与原方案完全一致的结构化数据
|
||
|
||
text: 简历纯文本全文（PyMuPDF/docx/txt 提取，保留原始换行）。
|
||
"""
|
||
log.info("第一阶段：5路并行概览提取")
|
||
overview = await _extract_overview(text)
|
||
log.info(
|
||
"概览完成 - " + " ".join(f"{label}:{len(overview[module])}" for module, _, label in _DETAIL_MODULES)
|
||
)
|
||
|
||
total = sum(len(overview[m]) for m in _SUB_MODULES)
|
||
log.info(f"第二阶段：{total + 1}路并行详情提取")
|
||
details = await _extract_all_details(overview, text)
|
||
|
||
result = _assemble(overview, details)
|
||
log.info("两阶段提取完成，数据组装完毕")
|
||
return result
|