I'm having trouble to retrieve attributes from my vector store, it fails at the retrieve. The same code works with OpenAI. I'm using 2025_03_02-preview API version.

Code:
import os

import sys

import tempfile

import time

from openai import AzureOpenAI, APIError, NotFoundError

from dotenv import load_dotenv

load_dotenv()

API_KEY = os.getenv("AZURE_OPENAI_API_KEY")

ENDPOINT = os.getenv("AZURE_OPENAI_API_BASE")

API_VERSION = os.getenv("AZURE_OPENAI_API_VERSION", "2025-03-01-preview")

if not API_KEY or not ENDPOINT:

print("Missing AZURE_OPENAI_API_KEY or AZURE_OPENAI_API_BASE in environment.")

sys.exit(1)

client = AzureOpenAI(api_key=API_KEY, api_version=API_VERSION, azure_endpoint=ENDPOINT)

VECTOR_STORE_NAME = f"debug_vs_{int(time.time())}"

TEST_ATTRIBUTE = {"test_key": "test_value"}

SAMPLE_TEXT = "This is a test file for vector store attribute debugging."

try:

1. Create vector store with metadata

print(f"Creating vector store: {VECTOR_STORE_NAME}")

vs = client.vector_stores.create(name=VECTOR_STORE_NAME, metadata=TEST_ATTRIBUTE)

vs_id = vs.id

print(f"Created vector store with ID: {vs_id}")

print(f"Vector store metadata: {getattr(vs, 'metadata', None)}")

2. Create a temp file and upload

with tempfile.NamedTemporaryFile(mode='w+', encoding='utf-8', suffix=".txt", delete=False) as temp_f:

temp_f.write(SAMPLE_TEXT)

temp_file_path = temp_f.name

print(f"Uploading file: {temp_file_path}")

with open(temp_file_path, "rb") as file_to_upload:

file_obj = client.files.create(file=file_to_upload, purpose="assistants")

file_id = file_obj.id

print(f"Uploaded file with ID: {file_id}")

3. Add file to vector store with attribute

print(f"Adding file to vector store with attributes: {TEST_ATTRIBUTE}")

vs_file = client.vector_stores.files.create(

vector_store_id=vs_id,

file_id=file_id,

attributes=TEST_ATTRIBUTE

)

vs_file_id = vs_file.id

print(f"Added file to vector store. VSFile ID: {vs_file_id}")

Wait for file to be processed (status 'completed')

print("Waiting for file to be processed (status 'completed')...")

max_wait = 60 # seconds

wait_time = 0

poll_interval = 3

while wait_time < max_wait:

retrieved_vs_file = client.vector_stores.files.retrieve(vector_store_id=vs_id, file_id=file_id)

status = getattr(retrieved_vs_file, 'status', None)

print(f" Status: {status} (waited {wait_time}s)")

if status == 'completed':

break

time.sleep(poll_interval)

wait_time += poll_interval

else:

print("Timeout waiting for file to be processed. Exiting test.")

raise RuntimeError("File did not reach 'completed' status in time.")

4. Retrieve file from vector store and check attribute

print("Retrieving file from vector store...")

print(f"Full retrieved_vs_file object: {repr(retrieved_vs_file)}")

if hasattr(retrieved_vs_file, 'dict'):

print(f"retrieved_vs_file.dict: {retrieved_vs_file.dict}")

attrs = getattr(retrieved_vs_file, 'attributes', None)

print(f"Retrieved attributes: {attrs}")

if attrs and attrs.get("test_key") == "test_value":

print("PASS: Attribute was correctly stored and retrieved.")

else:

print("FAIL: Attribute was not correctly stored or retrieved.")

except Exception as e:

print(f"Error during test: {e}")

finally:

Cleanup: delete file and vector store

try:

print("Cleaning up: deleting file and vector store...")

if 'file_id' in locals():

client.files.delete(file_id=file_id)

if 'vs_id' in locals():

client.vector_stores.delete(vector_store_id=vs_id)

if 'temp_file_path' in locals() and os.path.exists(temp_file_path):

os.remove(temp_file_path)

except Exception as cleanup_e:

print(f"Cleanup error: {cleanup_e}")