refactor(rag): 梳理文档入库与检索服务结构

This commit is contained in:
2026-05-30 00:44:52 +08:00
parent f68b44f325
commit ccfe5eb667
6 changed files with 284 additions and 103 deletions

View File

@@ -1,7 +1,7 @@
from pathlib import Path
from zipfile import BadZipFile, ZipFile
import re
import xml.etree.ElementTree as ET
from zipfile import BadZipFile, ZipFile
from agent_core.rag.ingest import ingest_document
@@ -9,7 +9,13 @@ from .models import UploadedDocument
def create_uploaded_document(scenario_id: str, uploaded_file) -> UploadedDocument:
extension = Path(uploaded_file.name).suffix.lower().lstrip(".")
"""
保存上传文件的元数据记录。
Documents 模块只记录文件与场景关系、原始名称、类型和大小,
真正的入库动作由用户后续主动触发,避免上传阶段就耦合 RAG 流程。
"""
extension = _detect_extension(uploaded_file.name)
return UploadedDocument.objects.create(
scenario_id=scenario_id,
original_name=uploaded_file.name,
@@ -21,6 +27,14 @@ def create_uploaded_document(scenario_id: str, uploaded_file) -> UploadedDocumen
def extract_text(document: UploadedDocument) -> str:
"""
根据文档类型选择合适的文本抽取策略。
V1 的目标是“可演示且稳定”,因此:
- `.txt` / `.md` 直接按文本读取
- `.pdf` 优先走 pypdf失败时回退为二进制容错读取
- `.docx` 优先解析 Word XML失败时回退为二进制容错读取
"""
path = Path(document.file.path)
extension = f".{document.file_type.lower().lstrip('.')}"
if extension == ".pdf":
@@ -30,7 +44,47 @@ def extract_text(document: UploadedDocument) -> str:
return _read_text_file(path)
def index_document(document: UploadedDocument) -> UploadedDocument:
"""
触发单个文档入库,并把成功/失败状态回写到 UploadedDocument。
这里故意不抛业务异常给 View
View 层只需要知道“最终状态是什么”,而错误信息统一落到模型字段中,
便于页面重试和演示。
"""
try:
text = extract_text(document)
ingest_result = ingest_document(
document_id=document.id,
scenario_id=document.scenario_id,
source_file=document.original_name,
text=text,
collection=document.scenario_id,
)
_apply_ingest_result(document, ingest_result.success, ingest_result.error)
except Exception as exc:
_apply_ingest_result(document, success=False, error=str(exc))
document.save(update_fields=["status", "error_message", "updated_at"])
return document
def _apply_ingest_result(document: UploadedDocument, success: bool, error: str = "") -> None:
"""把入库结果映射为 UploadedDocument 的稳定状态字段。"""
if success:
document.status = UploadedDocument.STATUS_INDEXED
document.error_message = ""
return
document.status = UploadedDocument.STATUS_FAILED
document.error_message = error
def _detect_extension(file_name: str) -> str:
"""统一将扩展名转成小写且去掉前导点,便于模型字段存储。"""
return Path(file_name).suffix.lower().lstrip(".")
def _read_text_file(path: Path) -> str:
"""优先按 UTF-8 读取;失败时回退到系统默认编码。"""
try:
return path.read_text(encoding="utf-8")
except UnicodeDecodeError:
@@ -38,6 +92,7 @@ def _read_text_file(path: Path) -> str:
def _extract_pdf_text(path: Path) -> str:
"""优先使用 pypdf 抽取 PDF 文本,失败时回退到容错方案。"""
try:
import pypdf
@@ -48,6 +103,7 @@ def _extract_pdf_text(path: Path) -> str:
def _extract_docx_text(path: Path) -> str:
"""提取 Word XML 中的可见文字内容,不追求保留样式。"""
try:
with ZipFile(path) as archive:
document_xml = archive.read("word/document.xml")
@@ -60,30 +116,12 @@ def _extract_docx_text(path: Path) -> str:
def _read_binary_text_fallback(path: Path) -> str:
"""
当结构化抽取失败时,退回到“尽可能保留纯文本”的保底方案。
该方案不保证版式,但足以支撑 V1 入库和演示。
"""
data = path.read_bytes()
text = data.decode("utf-8", errors="ignore")
text = re.sub(r"[\x00-\x08\x0b\x0c\x0e-\x1f]+", " ", text)
return text.strip()
def index_document(document: UploadedDocument) -> UploadedDocument:
try:
text = extract_text(document)
result = ingest_document(
document_id=document.id,
scenario_id=document.scenario_id,
source_file=document.original_name,
text=text,
collection=document.scenario_id,
)
if result.success:
document.status = UploadedDocument.STATUS_INDEXED
document.error_message = ""
else:
document.status = UploadedDocument.STATUS_FAILED
document.error_message = result.error
except Exception as exc:
document.status = UploadedDocument.STATUS_FAILED
document.error_message = str(exc)
document.save(update_fields=["status", "error_message", "updated_at"])
return document