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import uuid
from app.configs.database import firebase_bucket, firebase_db
from app.configs.qdrant_db import qdrant_client
from app.configs.qdrant_db import models
from app.modules.question_tests_retrieval.models.text2vector import text2vector
# CRUD operation
def upload_file_question_tests(file):
re_name_file = str(uuid.uuid4()).replace("-","_") + "_" + file.filename
# upload file to firebase storage
blob = firebase_bucket.blob(re_name_file)
blob.upload_from_file(file.file)
# return gs link
return f"gs://{firebase_bucket.name}/{re_name_file}"
def remove_file_question_tests(file_url):
# remove file from firebase storage using "gs://" link
blob = firebase_bucket.blob(file_url.split(f"gs://{firebase_bucket.name}/")[1])
blob.delete()
return True
def get_all_question_tests():
# Get all documents from the collection
docs = firebase_db.collection("question_tests").stream()
data = []
for doc in docs:
doc_data = doc.to_dict()
doc_data["id"] = doc.id
data.append(doc_data)
return data
def get_question_test_by_id(id):
# Get a document by id
doc = firebase_db.collection("question_tests").document(id).get()
return doc.to_dict()
def get_question_test_url_by_description(description):
# Get a question_tests_url where question_tests_description is equal to description
docs = firebase_db.collection("question_tests").where("question_tests_description", "==", description).stream()
for doc in docs:
return doc.to_dict()["question_tests_url"]
return False
def create_question_test(data):
# get file_question_tests
file_question_tests = data["question_tests_url"]
# upload file to firebase storage
file_url = upload_file_question_tests(file_question_tests)
# add file url to data
data["question_tests_url"] = file_url
question_tests_des = data["question_tests_description"]
# Create a new document
document_ref = firebase_db.collection("question_tests").add(data)
document_id = document_ref[1].id
# Upload vector to Qdrant
collection_info = qdrant_client.get_collection('question_tests')
points_count = collection_info.points_count
description_vector = text2vector(question_tests_des)
payload = {"id": document_id}
point = models.PointStruct(id=points_count+1, payload=payload, vector=description_vector)
qdrant_client.upsert(collection_name="question_tests", points=[point])
return True
def update_question_test(id, data):
# Update a document by id
firebase_db.collection("question_tests").document(id).update(data)
return True
def delete_question_test(id):
# Delete a file from firebase storage
file_url = get_question_test_by_id(id)["question_tests_url"]
remove_file_question_tests(file_url)
# Delete a document by id
firebase_db.collection("question_tests").document(id).delete()
return True
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