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litellm/tests/ocr_tests/test_ocr_vertex_ai.py
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2025-12-19 23:53:17 +05:30

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Python

"""
Test OCR functionality with Vertex AI OCR APIs (Mistral and DeepSeek).
Note: Vertex AI OCR automatically converts URLs to base64 data URIs since
the Vertex AI endpoint doesn't have internet access.
"""
import os
import json
import tempfile
import pytest
from base_ocr_unit_tests import BaseOCRTest
def load_vertex_ai_credentials():
"""Load Vertex AI credentials for tests"""
# Define the path to the vertex_key.json file
print("loading vertex ai credentials")
filepath = os.path.dirname(os.path.abspath(__file__))
vertex_key_path = filepath + "/vertex_key.json"
# Read the existing content of the file or create an empty dictionary
try:
with open(vertex_key_path, "r") as file:
# Read the file content
print("Read vertexai file path")
content = file.read()
# If the file is empty or not valid JSON, create an empty dictionary
if not content or not content.strip():
service_account_key_data = {}
else:
# Attempt to load the existing JSON content
file.seek(0)
service_account_key_data = json.load(file)
except FileNotFoundError:
# If the file doesn't exist, create an empty dictionary
service_account_key_data = {}
# Update the service_account_key_data with environment variables
private_key_id = os.environ.get("VERTEX_AI_PRIVATE_KEY_ID", "")
private_key = os.environ.get("VERTEX_AI_PRIVATE_KEY", "")
private_key = private_key.replace("\\n", "\n")
service_account_key_data["private_key_id"] = private_key_id
service_account_key_data["private_key"] = private_key
# Create a temporary file
with tempfile.NamedTemporaryFile(mode="w+", delete=False) as temp_file:
# Write the updated content to the temporary files
json.dump(service_account_key_data, temp_file, indent=2)
# Export the temporary file as GOOGLE_APPLICATION_CREDENTIALS
os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = os.path.abspath(temp_file.name)
class TestVertexAIMistralOCR(BaseOCRTest):
"""
Test class for Vertex AI Mistral OCR functionality.
Inherits from BaseOCRTest and provides Vertex AI-specific configuration.
Note: For Vertex AI, LiteLLM will automatically convert URLs to base64 data URIs before
sending to the API, since Vertex AI OCR endpoint doesn't have internet access.
"""
def get_base_ocr_call_args(self) -> dict:
"""
Return the base OCR call args for Vertex AI Mistral OCR.
"""
load_vertex_ai_credentials()
return {
"model": "vertex_ai/mistral-ocr-2505",
"vertex_location": "us-central1",
}
class TestVertexAIDeepSeekOCR(BaseOCRTest):
"""
Test class for Vertex AI DeepSeek OCR functionality.
Inherits from BaseOCRTest and provides Vertex AI-specific configuration.
Note: DeepSeek OCR uses the chat completion API format through the openapi endpoint.
Note: DeepSeek OCR does not support PDF URLs - only image URLs and base64 data.
"""
def get_base_ocr_call_args(self) -> dict:
"""
Return the base OCR call args for Vertex AI DeepSeek OCR.
"""
load_vertex_ai_credentials()
return {
"model": "vertex_ai/deepseek-ocr-maas",
"vertex_location": "us-central1",
}
# Skip PDF URL tests for DeepSeek OCR as it doesn't support PDF URLs
@pytest.mark.skip(reason="DeepSeek OCR does not support PDF URLs")
async def test_basic_ocr_with_url(self, sync_mode):
"""Skip this test for DeepSeek OCR - PDF URLs not supported"""
pass
@pytest.mark.skip(reason="DeepSeek OCR does not support PDF URLs")
def test_ocr_response_structure(self):
"""Skip this test for DeepSeek OCR - PDF URLs not supported"""
pass
def test_vertex_ai_ocr_routing():
"""
Test that Vertex AI OCR routing correctly selects the right config based on model name.
"""
from litellm.llms.vertex_ai.ocr.common_utils import get_vertex_ai_ocr_config
from litellm.llms.vertex_ai.ocr.deepseek_transformation import VertexAIDeepSeekOCRConfig
from litellm.llms.vertex_ai.ocr.transformation import VertexAIOCRConfig
# Test DeepSeek OCR routing
deepseek_config = get_vertex_ai_ocr_config("vertex_ai/deepseek-ocr-maas")
assert isinstance(deepseek_config, VertexAIDeepSeekOCRConfig), \
"DeepSeek model should route to VertexAIDeepSeekOCRConfig"
# Test Mistral OCR routing (should use default VertexAIOCRConfig)
mistral_config = get_vertex_ai_ocr_config("vertex_ai/mistral-ocr-2505")
assert isinstance(mistral_config, VertexAIOCRConfig), \
"Mistral model should route to VertexAIOCRConfig"
# Test other DeepSeek variants
deepseek_variant = get_vertex_ai_ocr_config("vertex_ai/deepseek-ocr-maas")
assert isinstance(deepseek_variant, VertexAIDeepSeekOCRConfig), \
"DeepSeek variant should route to VertexAIDeepSeekOCRConfig"