olmocr/tests/test_birrpipeline.py
2024-10-30 16:26:02 +00:00

247 lines
9.1 KiB
Python

import unittest
from unittest.mock import MagicMock, patch
import hashlib
import json
import os
import base64
from PIL import Image
# Adjust the import path to match where your code resides
from pdelfin.birrpipeline import build_dolma_doc, DatabaseManager, build_finetuning_prompt, build_page_query
class TestBuildDolmaDoc(unittest.TestCase):
@patch('pdelfin.birrpipeline.DatabaseManager')
@patch('pdelfin.birrpipeline.get_s3_bytes')
def test_build_dolma_doc_with_multiple_page_entries(self, mock_get_s3_bytes, mock_DatabaseManager):
# Mock DatabaseManager instance
mock_db_instance = MagicMock()
mock_DatabaseManager.return_value = mock_db_instance
# Define the PDF record
pdf_s3_path = 's3://bucket/pdf/test.pdf'
pdf = DatabaseManager.PDFRecord(s3_path=pdf_s3_path, num_pages=1, status='pending')
# Create multiple BatchInferenceRecord entries for page_num=1
entry_a = DatabaseManager.BatchInferenceRecord(
inference_s3_path='s3://bucket/inference/output1.jsonl',
pdf_s3_path=pdf_s3_path,
page_num=1,
round=0,
start_index=0,
length=100,
finish_reason='stop',
error=None
)
entry_b = DatabaseManager.BatchInferenceRecord(
inference_s3_path='s3://bucket/inference/output2.jsonl',
pdf_s3_path=pdf_s3_path,
page_num=1,
round=0,
start_index=0,
length=100,
finish_reason='stop',
error=None
)
entry_c = DatabaseManager.BatchInferenceRecord(
inference_s3_path='s3://bucket/inference/output3.jsonl',
pdf_s3_path=pdf_s3_path,
page_num=1,
round=0,
start_index=0,
length=100,
finish_reason='stop',
error=None
)
entry_d = DatabaseManager.BatchInferenceRecord(
inference_s3_path='s3://bucket/inference/output4.jsonl',
pdf_s3_path=pdf_s3_path,
page_num=1,
round=0,
start_index=0,
length=100,
finish_reason='stop',
error=None
)
# Set up mock_db_instance.get_index_entries to return all entries
mock_db_instance.get_index_entries.return_value = [entry_a, entry_b, entry_c, entry_d]
# Define get_s3_bytes side effect function
def get_s3_bytes_side_effect(s3_client, s3_path, start_index=None, end_index=None):
if s3_path == 's3://bucket/inference/output1.jsonl':
data = {
"custom_id": f"{pdf_s3_path}-1",
"outputs": [{"text": "{\"is_rotation_valid\": true, \"natural_text\": \"Short Text\"}"}],
"round": 0
}
elif s3_path == 's3://bucket/inference/output2.jsonl':
data = {
"custom_id": f"{pdf_s3_path}-1",
"outputs": [{"text": "{\"is_rotation_valid\": false, \"natural_text\": \"Very Long Text Here that is longer\"}"}],
"round": 0
}
elif s3_path == 's3://bucket/inference/output3.jsonl':
data = {
"custom_id": f"{pdf_s3_path}-1",
"outputs": [{"text": "{\"is_rotation_valid\": true, \"natural_text\": \"Medium Length Text\"}"}],
"round": 0
}
elif s3_path == 's3://bucket/inference/output4.jsonl':
data = {
"custom_id": f"{pdf_s3_path}-1",
"outputs": [{"text": "{\"is_rotation_valid\": true, \"natural_text\": \"The Longest Correct Text\"}"}],
"round": 0
}
else:
data = {}
line = json.dumps(data) + '\n'
content_bytes = line.encode('utf-8')
return content_bytes
mock_get_s3_bytes.side_effect = get_s3_bytes_side_effect
# Call build_dolma_doc
s3_workspace = 's3://bucket/workspace'
dolma_doc = build_dolma_doc(s3_workspace, pdf)
# Check that the resulting dolma_doc has the expected document_text
expected_text = 'The Longest Correct Text\n'
self.assertIsNotNone(dolma_doc)
self.assertEqual(dolma_doc['text'], expected_text)
# Additional assertions to ensure that the correct page was selected
self.assertEqual(dolma_doc['metadata']['Source-File'], pdf_s3_path)
self.assertEqual(dolma_doc['metadata']['pdf-total-pages'], 1)
self.assertEqual(len(dolma_doc['attributes']['pdf_page_numbers']), 1)
self.assertEqual(dolma_doc['attributes']['pdf_page_numbers'][0][2], 1)
# Ensure that the document ID is correctly computed
expected_id = hashlib.sha1(expected_text.encode()).hexdigest()
self.assertEqual(dolma_doc['id'], expected_id)
class TestBuildPageQuery(unittest.TestCase):
def testNotParsing(self):
file = os.path.join(
os.path.dirname(__file__),
"gnarly_pdfs",
"not_parsing.pdf"
)
for page in range(1,9):
query = build_page_query(file, "not_parsing.pdf", page, 1024, 6000)
print(query)
def testNotParsing2(self):
file = os.path.join(
os.path.dirname(__file__),
"gnarly_pdfs",
"not_parsing2.pdf"
)
for page in range(1,10):
query = build_page_query(file, "not_parsing2.pdf", page, 1024, 6000)
print(query)
def testNotParsingHugeMemoryUsage(self):
file = os.path.join(
os.path.dirname(__file__),
"gnarly_pdfs",
"failing_pdf_pg9.pdf"
)
print("Starting to parse bad pdf")
query = build_page_query(file, "failing_pdf_pg9.pdf", 9, 1024, 6000)
print(query)
def testRotation(self):
# First, generate and save the non-rotated image
query = build_page_query(os.path.join(
os.path.dirname(__file__),
"gnarly_pdfs",
"edgar.pdf"
), "edgar.pdf", 1, 1024, 6000, 0)
# Extract the base64 image from the query
image_content = query["chat_messages"][0]["content"][1]
self.assertEqual(image_content["type"], "image_url")
image_url = image_content["image_url"]["url"]
# Extract base64 string from the data URL
prefix = "data:image/png;base64,"
self.assertTrue(image_url.startswith(prefix))
image_base64 = image_url[len(prefix):]
# Decode the base64 string
image_data = base64.b64decode(image_base64)
# Define the output file path for the non-rotated image
output_image_path = os.path.join(os.path.dirname(__file__), "test_renders", "output_image.png")
# Save the non-rotated image to a file
with open(output_image_path, "wb") as image_file:
image_file.write(image_data)
# Now, generate and save the rotated image (90 degrees clockwise)
query_rotated = build_page_query(os.path.join(
os.path.dirname(__file__),
"gnarly_pdfs",
"edgar.pdf"
), "edgar.pdf", 1, 1024, 6000, 90)
# Extract the base64 image from the rotated query
image_content_rotated = query_rotated["chat_messages"][0]["content"][1]
self.assertEqual(image_content_rotated["type"], "image_url")
image_url_rotated = image_content_rotated["image_url"]["url"]
# Extract base64 string from the data URL for the rotated image
self.assertTrue(image_url_rotated.startswith(prefix))
image_base64_rotated = image_url_rotated[len(prefix):]
# Decode the base64 string for the rotated image
image_data_rotated = base64.b64decode(image_base64_rotated)
# Define the output file path for the rotated image
output_image_rotated_path = os.path.join(os.path.dirname(__file__), "test_renders", "output_image_rotated90.png")
# Save the rotated image to a file
with open(output_image_rotated_path, "wb") as image_file_rotated:
image_file_rotated.write(image_data_rotated)
# Verification Step: Ensure the rotated image is 90 degrees clockwise rotated
# Open both images using PIL
with Image.open(output_image_path) as original_image:
with Image.open(output_image_rotated_path) as rotated_image:
# Compare pixel by pixel
original_pixels = original_image.load()
rotated_pixels = rotated_image.load()
width, height = original_image.size
self.assertEqual(width, rotated_image.size[1])
self.assertEqual(height, rotated_image.size[0])
for x in range(width):
for y in range(height):
self.assertEqual(
original_pixels[x, y], rotated_pixels[height - 1 - y, x],
f"Pixel mismatch at ({x}, {y})"
)
print("Rotation verification passed: The rotated image is correctly rotated 90 degrees clockwise.")
# Run the test
if __name__ == '__main__':
unittest.main()