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185 lines
6.3 KiB
Python
185 lines
6.3 KiB
Python
#!/usr/bin/env python3 -m pytest
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import io
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import os
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import shutil
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import pytest
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import requests
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from markitdown import MarkItDown
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skip_remote = os.environ.get("GITHUB_ACTIONS") # Don't run these tests in CI
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skip_exiftool = shutil.which("exiftool") is None
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TEST_FILES_DIR = os.path.join(os.path.dirname(__file__), "test_files")
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JPG_TEST_EXIFTOOL = {
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"Author": "AutoGen Authors",
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"Title": "AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation",
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"Description": "AutoGen enables diverse LLM-based applications",
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"ImageSize": "1615x1967",
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"DateTimeOriginal": "2024:03:14 22:10:00",
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}
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PDF_TEST_URL = "https://arxiv.org/pdf/2308.08155v2.pdf"
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PDF_TEST_STRINGS = [
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"While there is contemporaneous exploration of multi-agent approaches"
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]
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YOUTUBE_TEST_URL = "https://www.youtube.com/watch?v=V2qZ_lgxTzg"
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YOUTUBE_TEST_STRINGS = [
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"## AutoGen FULL Tutorial with Python (Step-By-Step)",
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"This is an intermediate tutorial for installing and using AutoGen locally",
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"PT15M4S",
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"the model we're going to be using today is GPT 3.5 turbo", # From the transcript
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]
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XLSX_TEST_STRINGS = [
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"## 09060124-b5e7-4717-9d07-3c046eb",
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"6ff4173b-42a5-4784-9b19-f49caff4d93d",
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"affc7dad-52dc-4b98-9b5d-51e65d8a8ad0",
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]
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DOCX_TEST_STRINGS = [
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"314b0a30-5b04-470b-b9f7-eed2c2bec74a",
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"49e168b7-d2ae-407f-a055-2167576f39a1",
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"## d666f1f7-46cb-42bd-9a39-9a39cf2a509f",
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"# Abstract",
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"# Introduction",
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"AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation",
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]
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PPTX_TEST_STRINGS = [
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"2cdda5c8-e50e-4db4-b5f0-9722a649f455",
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"04191ea8-5c73-4215-a1d3-1cfb43aaaf12",
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"44bf7d06-5e7a-4a40-a2e1-a2e42ef28c8a",
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"1b92870d-e3b5-4e65-8153-919f4ff45592",
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"AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation",
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]
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BLOG_TEST_URL = "https://microsoft.github.io/autogen/blog/2023/04/21/LLM-tuning-math"
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BLOG_TEST_STRINGS = [
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"Large language models (LLMs) are powerful tools that can generate natural language texts for various applications, such as chatbots, summarization, translation, and more. GPT-4 is currently the state of the art LLM in the world. Is model selection irrelevant? What about inference parameters?",
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"an example where high cost can easily prevent a generic complex",
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]
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WIKIPEDIA_TEST_URL = "https://en.wikipedia.org/wiki/Microsoft"
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WIKIPEDIA_TEST_STRINGS = [
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"Microsoft entered the operating system (OS) business in 1980 with its own version of [Unix]",
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'Microsoft was founded by [Bill Gates](/wiki/Bill_Gates "Bill Gates")',
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]
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WIKIPEDIA_TEST_EXCLUDES = [
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"You are encouraged to create an account and log in",
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"154 languages",
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"move to sidebar",
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]
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SERP_TEST_URL = "https://www.bing.com/search?q=microsoft+wikipedia"
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SERP_TEST_STRINGS = [
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"](https://en.wikipedia.org/wiki/Microsoft",
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"Microsoft Corporation is **an American multinational corporation and technology company headquartered** in Redmond",
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"1995–2007: Foray into the Web, Windows 95, Windows XP, and Xbox",
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]
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SERP_TEST_EXCLUDES = [
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"https://www.bing.com/ck/a?!&&p=",
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"data:image/svg+xml,%3Csvg%20width%3D",
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]
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@pytest.mark.skipif(
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skip_remote,
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reason="do not run tests that query external urls",
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)
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def test_markitdown_remote() -> None:
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markitdown = MarkItDown()
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# By URL
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result = markitdown.convert(PDF_TEST_URL)
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for test_string in PDF_TEST_STRINGS:
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assert test_string in result.text_content
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# By stream
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response = requests.get(PDF_TEST_URL)
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result = markitdown.convert_stream(
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io.BytesIO(response.content), file_extension=".pdf", url=PDF_TEST_URL
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)
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for test_string in PDF_TEST_STRINGS:
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assert test_string in result.text_content
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# Youtube
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# TODO: This test randomly fails for some reason. Haven't been able to repro it yet. Disabling until I can debug the issue
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# result = markitdown.convert(YOUTUBE_TEST_URL)
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# for test_string in YOUTUBE_TEST_STRINGS:
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# assert test_string in result.text_content
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def test_markitdown_local() -> None:
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markitdown = MarkItDown()
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# Test XLSX processing
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result = markitdown.convert(os.path.join(TEST_FILES_DIR, "test.xlsx"))
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for test_string in XLSX_TEST_STRINGS:
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text_content = result.text_content.replace("\\", "")
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assert test_string in text_content
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# Test DOCX processing
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result = markitdown.convert(os.path.join(TEST_FILES_DIR, "test.docx"))
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for test_string in DOCX_TEST_STRINGS:
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text_content = result.text_content.replace("\\", "")
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assert test_string in text_content
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# Test PPTX processing
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result = markitdown.convert(os.path.join(TEST_FILES_DIR, "test.pptx"))
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for test_string in PPTX_TEST_STRINGS:
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text_content = result.text_content.replace("\\", "")
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assert test_string in text_content
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# Test HTML processing
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result = markitdown.convert(
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os.path.join(TEST_FILES_DIR, "test_blog.html"), url=BLOG_TEST_URL
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)
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for test_string in BLOG_TEST_STRINGS:
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text_content = result.text_content.replace("\\", "")
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assert test_string in text_content
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# Test Wikipedia processing
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result = markitdown.convert(
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os.path.join(TEST_FILES_DIR, "test_wikipedia.html"), url=WIKIPEDIA_TEST_URL
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)
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text_content = result.text_content.replace("\\", "")
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for test_string in WIKIPEDIA_TEST_EXCLUDES:
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assert test_string not in text_content
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for test_string in WIKIPEDIA_TEST_STRINGS:
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assert test_string in text_content
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# Test Bing processing
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result = markitdown.convert(
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os.path.join(TEST_FILES_DIR, "test_serp.html"), url=SERP_TEST_URL
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)
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text_content = result.text_content.replace("\\", "")
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for test_string in SERP_TEST_EXCLUDES:
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assert test_string not in text_content
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for test_string in SERP_TEST_STRINGS:
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assert test_string in text_content
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@pytest.mark.skipif(
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skip_exiftool,
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reason="do not run if exiftool is not installed",
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)
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def test_markitdown_exiftool() -> None:
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markitdown = MarkItDown()
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# Test JPG metadata processing
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result = markitdown.convert(os.path.join(TEST_FILES_DIR, "test.jpg"))
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for key in JPG_TEST_EXIFTOOL:
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target = f"{key}: {JPG_TEST_EXIFTOOL[key]}"
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assert target in result.text_content
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if __name__ == "__main__":
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"""Runs this file's tests from the command line."""
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test_markitdown_remote()
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test_markitdown_local()
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test_markitdown_exiftool()
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