houhuan/orc-order-v2
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Refactor processing logic and enhance error handling

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- Cleaned up code in processing.py by removing inline semicolons and improving readability.
- Updated upsert_file_relation calls to ensure consistent handling of file relations.
- Enhanced query_file_relations in db_schema.py to support filtering by file existence.
- Improved API error handling in index.ts with user-friendly messages for 401 and 403 errors.
- Added online/offline status tracking in Layout.vue.
- Implemented debounced search functionality across multiple views to optimize performance.
- Introduced loading skeletons in Dashboard.vue for better user experience during data fetching.
- Enhanced file preview cleanup logic in Images.vue, Orders.vue, and Tables.vue to prevent memory leaks.
- Updated global styles to include new loading and notification animations.
This commit is contained in:
侯欢
2026-05-12 18:37:23 +08:00
parent 81bafaf557
commit e441ac82a8
20 changed files with 455 additions and 76 deletions
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web/backend/routers/memory.py
+7
View File
@@ -53,6 +53,7 @@ class MemoryListResponse(BaseModel):
total: int
page: int
page_size: int
stats: Optional[Dict] = None
def _get_db():
@@ -96,11 +97,17 @@ async def list_memory(
start = (page - 1) * page_size
page_items = results[start:start + page_size]
# Compute confidence stats from all results (not just current page)
high = sum(1 for r in results if r.get("confidence", 0) > 50)
medium = sum(1 for r in results if 10 <= r.get("confidence", 0) <= 50)
low = sum(1 for r in results if r.get("confidence", 0) < 10)
return MemoryListResponse(
items=[_row_to_item(r) for r in page_items],
total=total,
page=page,
page_size=page_size,
stats={"high": high, "medium": medium, "low": low, "total": total},
)
web/backend/routers/processing.py
+16 -9
View File
@@ -265,7 +265,7 @@ async def ocr_batch(
for ext in ['.xlsx', '.xls']:
candidate = _output_dir / f"{out_stem}{ext}"
if candidate.exists():
upsert_file_relation(input_image=f.name, output_excel=candidate.name, status='ocr_done'); _add_result_file(candidate.name)
upsert_file_relation(input_image=f.name, output_excel=candidate.name, status='ocr_done')
_add_result_file(candidate.name)
break
tm.add_log(task.id, f"[OCR] 完成: {f.name}")
@@ -317,7 +317,8 @@ async def process_excel(
result_path = _result_dir / result_name
if result_path.exists():
tm.add_log(task.id, f"[跳过] {f.name} 已处理过 → {result_name}")
upsert_file_relation(output_excel=f.name, result_purchase=result_name, status='done'); _add_result_file(result_name)
upsert_file_relation(output_excel=f.name, result_purchase=result_name, status='done')
_add_result_file(result_name)
continue
tm.update_progress(task.id, int((i / total) * 100), f"正在处理: {f.name}")
@@ -326,7 +327,7 @@ async def process_excel(
svc.process_excel(str(f))
# Find result file
if result_path.exists():
upsert_file_relation(output_excel=f.name, result_purchase=result_name, status='done'); _add_result_file(result_name)
upsert_file_relation(output_excel=f.name, result_purchase=result_name, status='done')
_add_result_file(result_name)
tm.add_log(task.id, f"[Excel] 完成: {f.name}")
# Learn products into memory from purchase order result
@@ -430,7 +431,8 @@ async def full_pipeline(
for ext in ['.xlsx', '.xls']:
candidate = _output_dir / f"{out_stem}{ext}"
if candidate.exists():
upsert_file_relation(input_image=f.name, output_excel=candidate.name, status='ocr_done'); _add_result_file(candidate.name)
upsert_file_relation(input_image=f.name, output_excel=candidate.name, status='ocr_done')
_add_result_file(candidate.name)
break
tm.add_log(task.id, f"[OCR] 完成: {f.name}")
out_file = _output_dir / f"{out_stem}.xlsx"
@@ -456,7 +458,8 @@ async def full_pipeline(
result_path = _result_dir / result_name
if result_path.exists():
tm.add_log(task.id, f"[跳过] {f.name} 已处理过 → {result_name}")
upsert_file_relation(output_excel=f.name, result_purchase=result_name, status='done'); _add_result_file(result_name)
upsert_file_relation(output_excel=f.name, result_purchase=result_name, status='done')
_add_result_file(result_name)
tm.update_progress(task.id, pct, f"跳过: {f.name}")
continue
@@ -464,7 +467,8 @@ async def full_pipeline(
try:
order_svc.process_excel(str(f))
if result_path.exists():
upsert_file_relation(output_excel=f.name, result_purchase=result_name, status='done'); _add_result_file(result_name)
upsert_file_relation(output_excel=f.name, result_purchase=result_name, status='done')
_add_result_file(result_name)
tm.add_log(task.id, f"[Excel] 完成: {f.name}")
if result_path.exists():
_learn_products_from_excel(result_path, tm, task.id, source='ocr')
@@ -515,7 +519,8 @@ async def ocr_single(
for ext in ['.xlsx', '.xls']:
candidate = _output_dir / f"{stem}{ext}"
if candidate.exists():
upsert_file_relation(input_image=body.filename, output_excel=candidate.name, status='ocr_done'); _add_result_file(candidate.name)
upsert_file_relation(input_image=body.filename, output_excel=candidate.name, status='ocr_done')
_add_result_file(candidate.name)
break
tm.add_log(task.id, f"[OCR] 完成: {body.filename}")
result_files = list(getattr(_tlocal, 'result_files', []))
@@ -598,13 +603,15 @@ async def pipeline_single(
if out_xlsx.exists() or out_xls.exists():
out_name = out_xlsx.name if out_xlsx.exists() else out_xls.name
tm.add_log(task.id, f"[跳过] 已OCR过 → {out_name}")
upsert_file_relation(input_image=body.filename, output_excel=out_name, status='ocr_done'); _add_result_file(out_name)
upsert_file_relation(input_image=body.filename, output_excel=out_name, status='ocr_done')
_add_result_file(out_name)
else:
ocr_svc.process_image(str(file_path))
for ext in ['.xlsx', '.xls']:
candidate = _output_dir / f"{stem}{ext}"
if candidate.exists():
upsert_file_relation(input_image=body.filename, output_excel=candidate.name, status='ocr_done'); _add_result_file(candidate.name)
upsert_file_relation(input_image=body.filename, output_excel=candidate.name, status='ocr_done')
_add_result_file(candidate.name)
break
tm.add_log(task.id, f"[OCR] 完成")