[Python] Gemini Vertex AI Error upon uploading large file: 400 Precondition check failed

I am trying to upload files to Google's Gemini 1.5 Model via Vertex AI from google cloud. Despite the file limit being 30 mbs, a 11 mbs file raises this following error: 400 Precondition check failed

This is literally all the information google gives me in return. Could someone please help me troubleshoot and identify what the issue is?

async def async_get_model_output(prompt, filepaths, content_type):

vertexai.init(project=os.getenv("PROJECT_ID"), location="us-central1")
model = GenerativeModel(model_name="gemini-1.5-flash-001")
#Figure
parts = [Part.from_uri(filepath["gcs_link"], mime_type=filepath["mimetype"]) for filepath in filepaths]
parts.append(prompt)
# Create a GenerationConfig object with the specified parameters
generation_config = GenerationConfig(
temperature=0.3,
top_p=0.3,
max_output_tokens = 5000
# You can add other parameters here as needed
)
#BLOCK_ONLY_HIGH
safety_settings = [
SafetySetting(
category=HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT,
threshold=HarmBlockThreshold.BLOCK_ONLY_HIGH,
),
SafetySetting(
category=HarmCategory.HARM_CATEGORY_HARASSMENT,
threshold=HarmBlockThreshold.BLOCK_ONLY_HIGH,
),
SafetySetting(
category=HarmCategory.HARM_CATEGORY_HATE_SPEECH,
threshold=HarmBlockThreshold.BLOCK_ONLY_HIGH,
),
SafetySetting(
category=HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT,
threshold=HarmBlockThreshold.BLOCK_ONLY_HIGH,
),
# Add other categories as needed
]

for attempt in range(3):
print(f'Attempt {attempt + 1} to get model output')
try:
token_count = model.count_tokens(parts)
print(f"Token count: {token_count}")
print(f"##{content_type}## DEBUG: INVOKING VERTEX AI")
response = await asyncio.to_thread(
model.generate_content,
parts,
generation_config=generation_config,
safety_settings=safety_settings
)
logger.debug(f"Received response: {response}")
json_match = re.search(r'\{[\s\S]*\}', response.text)

if json_match:
json_string = json_match.group(0)
try:
study_guide_data = json.loads(json_string)
print(f"##{content_type}## DEBUG CONTENT SUCCESS: Successfully Generated content and parsed JSON")
return json_string
except json.JSONDecodeError as e:
print(f"##{content_type}##JSON decode error: {e}")
print(f"##{content_type}##Extracted JSON string:", json_string)
# Continue to next attempt
else:
print(f"##{content_type}## No JSON object found in the response")
except Exception as e:
error_message = str(e)
truncated_message = error_message[:197] + "..." if len(error_message) > 200 else error_message
print(f"##{content_type}## Unexpected error during attempt {attempt + 1}: {error_message}")

# If we reach here, the current attempt failed. We'll continue to the next one.
print(f"##{content_type}## Attempt {attempt + 1} failed. Moving to next attempt.")


if attempt < 2: # Don't sleep after the last attempt
print(f"##{content_type}## Waiting 1 seconds before next attempt...")
await asyncio.sleep(1)
# If we've exhausted all attempts without success
raise Exception(f"##{content_type}## Failed to get valid JSON after 3 attempts")


Above is my code, please let me know if you all need anything else

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