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Fix AI upload: process inline instead of background

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Background AI processing returned before results were ready,
leaving the UI showing "AI processing..." forever. Now AI
metadata generation runs inline (awaited) so results are
returned immediately in the upload response.

Background SSE-based processing can be re-enabled later for
large batch uploads (10+ files).

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
SamoilenkoVadym 2026-02-09 22:07:34 +00:00
parent b3bb2831a0
commit 3fe4ed0b4a
1 changed files with 12 additions and 40 deletions
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52
app/routers/upload.py
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@ -87,45 +87,23 @@ async def upload_files(
)
results = []
ai_pending = [] # Files needing background AI processing
for upload_file in files:
try:
filepath = await file_svc.save_upload(upload_file, user_id)
filename = Path(filepath).name
if metadata_source == "ai":
# For AI source: save files first, process AI in background
file_type = metadata_service.detect_file(filepath)
old_metadata = metadata_service.extract_metadata(filepath, file_type)
file_result = {
"success": True,
"filename": filename,
"file_type": file_type.value,
"current_metadata": old_metadata,
"suggested_metadata": {"title": "", "subject": "AI processing...", "keywords": ""},
"filepath": filepath,
"metadata_source": "ai",
"ai_status": "pending",
}
store.add_file_to_session(session_id, file_result)
ai_pending.append({
"file_index": len(results),
"filepath": filepath,
"filename": filename,
"file_type": file_type,
})
results.append(file_result)
else:
file_result = await metadata_service.process_uploaded_file(
filepath=filepath,
filename=filename,
metadata_source=metadata_source,
lookup=lookup,
import_map=import_map,
)
store.add_file_to_session(session_id, file_result)
results.append(file_result)
# Process file through the standard pipeline (including AI inline)
file_result = await metadata_service.process_uploaded_file(
filepath=filepath,
filename=filename,
metadata_source=metadata_source,
lookup=lookup,
import_map=import_map,
)
store.add_file_to_session(session_id, file_result)
results.append(file_result)
except ValueError as e:
results.append({"filename": upload_file.filename, "error": str(e)})
@ -133,16 +111,10 @@ async def upload_files(
logger.error(f"Upload error for {upload_file.filename}: {e}")
results.append({"filename": upload_file.filename, "error": str(e)})
# Start background AI processing if needed
if ai_pending:
import asyncio
from ..services.ai_service import process_bulk_ai
asyncio.create_task(process_bulk_ai(session_id, ai_pending, store, user_id))
# Strip server paths from client response
safe_results = [{k: v for k, v in r.items() if k != "filepath"} for r in results]
return {"success": True, "session_id": session_id, "files": safe_results, "ai_processing": bool(ai_pending)}
return {"success": True, "session_id": session_id, "files": safe_results}
@router.post("/upload-excel")