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