#!/usr/bin/env python3 -m pytest import io import os import shutil import pytest import requests from autogen_magentic_one.markdown_browser import MarkdownConverter 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() -> None: 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 # TODO: This test randomly fails for some reason. Haven't been able to repro it yet. Disabling until I can debug the issue # 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() -> None: mdconvert = MarkdownConverter() # Test XLSX processing result = mdconvert.convert(os.path.join(TEST_FILES_DIR, "test.xlsx")) for test_string in XLSX_TEST_STRINGS: text_content = result.text_content.replace("\\", "") assert test_string in text_content # Test DOCX processing result = mdconvert.convert(os.path.join(TEST_FILES_DIR, "test.docx")) for test_string in DOCX_TEST_STRINGS: text_content = result.text_content.replace("\\", "") assert test_string in text_content # Test PPTX processing result = mdconvert.convert(os.path.join(TEST_FILES_DIR, "test.pptx")) for test_string in PPTX_TEST_STRINGS: text_content = result.text_content.replace("\\", "") assert test_string in 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: text_content = result.text_content.replace("\\", "") assert test_string in text_content # Test Wikipedia processing result = mdconvert.convert(os.path.join(TEST_FILES_DIR, "test_wikipedia.html"), url=WIKIPEDIA_TEST_URL) text_content = result.text_content.replace("\\", "") for test_string in WIKIPEDIA_TEST_EXCLUDES: assert test_string not in text_content for test_string in WIKIPEDIA_TEST_STRINGS: assert test_string in text_content # Test Bing processing result = mdconvert.convert(os.path.join(TEST_FILES_DIR, "test_serp.html"), url=SERP_TEST_URL) text_content = result.text_content.replace("\\", "") for test_string in SERP_TEST_EXCLUDES: assert test_string not in text_content for test_string in SERP_TEST_STRINGS: assert test_string in text_content @pytest.mark.skipif( skip_exiftool, reason="do not run if exiftool is not installed", ) def test_mdconvert_exiftool() -> None: 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()