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