quivr/backend/routes/upload_routes.py
Zineb El Bachiri 8f693bc92a
refactor: create "files" package (#1626)
# Description

Please include a summary of the changes and the related issue. Please
also include relevant motivation and context.

## Checklist before requesting a review

Please delete options that are not relevant.

- [ ] My code follows the style guidelines of this project
- [ ] I have performed a self-review of my code
- [ ] I have commented hard-to-understand areas
- [ ] I have ideally added tests that prove my fix is effective or that
my feature works
- [ ] New and existing unit tests pass locally with my changes
- [ ] Any dependent changes have been merged

## Screenshots (if appropriate):
2023-11-14 09:52:44 +01:00

120 lines
4.4 KiB
Python

import os
from typing import Optional
from uuid import UUID
from auth import AuthBearer, get_current_user
from celery_worker import process_file_and_notify
from fastapi import APIRouter, Depends, HTTPException, Query, Request, UploadFile
from logger import get_logger
from models import Brain, UserIdentity, UserUsage
from models.databases.supabase.knowledge import CreateKnowledgeProperties
from models.databases.supabase.notifications import CreateNotificationProperties
from models.notifications import NotificationsStatusEnum
from packages.files.file import convert_bytes, get_file_size
from repository.brain import get_brain_details
from repository.files.upload_file import upload_file_storage
from repository.knowledge.add_knowledge import add_knowledge
from repository.notification.add_notification import add_notification
from repository.user_identity import get_user_identity
from routes.authorizations.brain_authorization import (
RoleEnum,
validate_brain_authorization,
)
logger = get_logger(__name__)
upload_router = APIRouter()
@upload_router.get("/upload/healthz", tags=["Health"])
async def healthz():
return {"status": "ok"}
@upload_router.post("/upload", dependencies=[Depends(AuthBearer())], tags=["Upload"])
async def upload_file(
request: Request,
uploadFile: UploadFile,
brain_id: UUID = Query(..., description="The ID of the brain"),
chat_id: Optional[UUID] = Query(None, description="The ID of the chat"),
enable_summarization: bool = False,
current_user: UserIdentity = Depends(get_current_user),
):
validate_brain_authorization(
brain_id, current_user.id, [RoleEnum.Editor, RoleEnum.Owner]
)
brain = Brain(id=brain_id)
userDailyUsage = UserUsage(
id=current_user.id,
email=current_user.email,
openai_api_key=current_user.openai_api_key,
)
userSettings = userDailyUsage.get_user_settings()
if request.headers.get("Openai-Api-Key"):
brain.max_brain_size = userSettings.get("max_brain_size", 1000000000)
remaining_free_space = userSettings.get("max_brain_size", 1000000000)
file_size = get_file_size(uploadFile)
if remaining_free_space - file_size < 0:
message = {
"message": f"❌ UserIdentity's brain will exceed maximum capacity with this upload. Maximum file allowed is : {convert_bytes(remaining_free_space)}",
"type": "error",
}
return message
upload_notification = None
if chat_id:
upload_notification = add_notification(
CreateNotificationProperties(
action="UPLOAD",
chat_id=chat_id,
status=NotificationsStatusEnum.Pending,
)
)
openai_api_key = request.headers.get("Openai-Api-Key", None)
if openai_api_key is None:
brain_details = get_brain_details(brain_id)
if brain_details:
openai_api_key = brain_details.openai_api_key
if openai_api_key is None:
openai_api_key = get_user_identity(current_user.id).openai_api_key
file_content = await uploadFile.read()
filename_with_brain_id = str(brain_id) + "/" + str(uploadFile.filename)
try:
fileInStorage = upload_file_storage(file_content, filename_with_brain_id)
logger.info(f"File {fileInStorage} uploaded successfully")
except Exception as e:
if "The resource already exists" in str(e):
raise HTTPException(
status_code=403,
detail=f"File {uploadFile.filename} already exists in storage.",
)
else:
raise HTTPException(
status_code=500, detail="Failed to upload file to storage."
)
knowledge_to_add = CreateKnowledgeProperties(
brain_id=brain_id,
file_name=uploadFile.filename,
extension=os.path.splitext(
uploadFile.filename # pyright: ignore reportPrivateUsage=none
)[-1].lower(),
)
added_knowledge = add_knowledge(knowledge_to_add)
logger.info(f"Knowledge {added_knowledge} added successfully")
process_file_and_notify.delay(
file_name=filename_with_brain_id,
file_original_name=uploadFile.filename,
enable_summarization=enable_summarization,
brain_id=brain_id,
openai_api_key=openai_api_key,
notification_id=upload_notification.id if upload_notification else None,
)
return {"message": "File processing has started."}