#!/usr/bin/env python3 -m pytest
import io
import os
import shutil

import pytest
import requests

from warnings import catch_warnings, resetwarnings

from markitdown import MarkItDown

skip_remote = (
    True if os.environ.get("GITHUB_ACTIONS") else False
)  # Don't run these tests in CI


# Don't run the llm tests without a key and the client library
skip_llm = False if os.environ.get("OPENAI_API_KEY") else True
try:
    import openai
except ModuleNotFoundError:
    skip_llm = True

# Skip exiftool tests if not installed
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",
]

XLS_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",
]

MSG_TEST_STRINGS = [
    "# Email Message",
    "**From:** test.sender@example.com",
    "**To:** test.recipient@example.com",
    "**Subject:** Test Email Message",
    "## Content",
    "This is the body of the test email message",
]

DOCX_COMMENT_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",
    "This is a test comment. 12df-321a",
    "Yet another comment in the doc. 55yiyi-asd09",
]

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",
    "a3f6004b-6f4f-4ea8-bee3-3741f4dc385f",  # chart title
    "2003",  # chart value
]

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",
]


RSS_TEST_STRINGS = [
    "The Official Microsoft Blog",
    "In the case of AI, it is absolutely true that the industry is moving incredibly fast",
]


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",
]

CSV_CP932_TEST_STRINGS = [
    "名前,年齢,住所",
    "佐藤太郎,30,東京",
    "三木英子,25,大阪",
    "髙橋淳,35,名古屋",
]

LLM_TEST_STRINGS = [
    "5bda1dd6",
]

JSON_TEST_STRINGS = [
    "5b64c88c-b3c3-4510-bcb8-da0b200602d8",
    "9700dc99-6685-40b4-9a3a-5e406dcb37f3",
]


# --- Helper Functions ---
def validate_strings(result, expected_strings, exclude_strings=None):
    """Validate presence or absence of specific strings."""
    text_content = result.text_content.replace("\\", "")
    for string in expected_strings:
        assert string in text_content
    if exclude_strings:
        for string in exclude_strings:
            assert string not in text_content


@pytest.mark.skipif(
    skip_remote,
    reason="do not run tests that query external urls",
)
def test_markitdown_remote() -> None:
    markitdown = MarkItDown()

    # By URL
    result = markitdown.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 = markitdown.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 = markitdown.convert(YOUTUBE_TEST_URL)
    # for test_string in YOUTUBE_TEST_STRINGS:
    #     assert test_string in result.text_content


def test_markitdown_local() -> None:
    markitdown = MarkItDown()

    # Test XLSX processing
    result = markitdown.convert(os.path.join(TEST_FILES_DIR, "test.xlsx"))
    validate_strings(result, XLSX_TEST_STRINGS)

    # Test XLS processing
    result = markitdown.convert(os.path.join(TEST_FILES_DIR, "test.xls"))
    for test_string in XLS_TEST_STRINGS:
        text_content = result.text_content.replace("\\", "")
        assert test_string in text_content

    # Test DOCX processing
    result = markitdown.convert(os.path.join(TEST_FILES_DIR, "test.docx"))
    validate_strings(result, DOCX_TEST_STRINGS)

    # Test DOCX processing, with comments
    result = markitdown.convert(
        os.path.join(TEST_FILES_DIR, "test_with_comment.docx"),
        style_map="comment-reference => ",
    )
    validate_strings(result, DOCX_COMMENT_TEST_STRINGS)

    # Test DOCX processing, with comments and setting style_map on init
    markitdown_with_style_map = MarkItDown(style_map="comment-reference => ")
    result = markitdown_with_style_map.convert(
        os.path.join(TEST_FILES_DIR, "test_with_comment.docx")
    )
    validate_strings(result, DOCX_COMMENT_TEST_STRINGS)

    # Test PPTX processing
    result = markitdown.convert(os.path.join(TEST_FILES_DIR, "test.pptx"))
    validate_strings(result, PPTX_TEST_STRINGS)

    # Test HTML processing
    result = markitdown.convert(
        os.path.join(TEST_FILES_DIR, "test_blog.html"), url=BLOG_TEST_URL
    )
    validate_strings(result, BLOG_TEST_STRINGS)

    # Test ZIP file processing
    result = markitdown.convert(os.path.join(TEST_FILES_DIR, "test_files.zip"))
    validate_strings(result, XLSX_TEST_STRINGS)

    # Test Wikipedia processing
    result = markitdown.convert(
        os.path.join(TEST_FILES_DIR, "test_wikipedia.html"), url=WIKIPEDIA_TEST_URL
    )
    text_content = result.text_content.replace("\\", "")
    validate_strings(result, WIKIPEDIA_TEST_STRINGS, WIKIPEDIA_TEST_EXCLUDES)

    # Test Bing processing
    result = markitdown.convert(
        os.path.join(TEST_FILES_DIR, "test_serp.html"), url=SERP_TEST_URL
    )
    text_content = result.text_content.replace("\\", "")
    validate_strings(result, SERP_TEST_STRINGS, SERP_TEST_EXCLUDES)

    # Test RSS processing
    result = markitdown.convert(os.path.join(TEST_FILES_DIR, "test_rss.xml"))
    text_content = result.text_content.replace("\\", "")
    for test_string in RSS_TEST_STRINGS:
        assert test_string in text_content

    ## Test non-UTF-8 encoding
    result = markitdown.convert(os.path.join(TEST_FILES_DIR, "test_mskanji.csv"))
    validate_strings(result, CSV_CP932_TEST_STRINGS)

    # Test MSG (Outlook email) processing
    result = markitdown.convert(os.path.join(TEST_FILES_DIR, "test_outlook_msg.msg"))
    validate_strings(result, MSG_TEST_STRINGS)

    # Test JSON processing
    result = markitdown.convert(os.path.join(TEST_FILES_DIR, "test.json"))
    validate_strings(result, JSON_TEST_STRINGS)

    # Test input with leading blank characters
    input_data = b"   \n\n\n<html><body><h1>Test</h1></body></html>"
    result = markitdown.convert_stream(io.BytesIO(input_data))
    assert "# Test" in result.text_content


@pytest.mark.skipif(
    skip_exiftool,
    reason="do not run if exiftool is not installed",
)
def test_markitdown_exiftool() -> None:
    # Test the automatic discovery of exiftool throws a warning
    # and is disabled
    try:
        with catch_warnings(record=True) as w:
            markitdown = MarkItDown()
            result = markitdown.convert(os.path.join(TEST_FILES_DIR, "test.jpg"))
            assert len(w) == 1
            assert w[0].category is DeprecationWarning
            assert result.text_content.strip() == ""
    finally:
        resetwarnings()

    # Test explicitly setting the location of exiftool
    which_exiftool = shutil.which("exiftool")
    markitdown = MarkItDown(exiftool_path=which_exiftool)
    result = markitdown.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

    # Test setting the exiftool path through an environment variable
    os.environ["EXIFTOOL_PATH"] = which_exiftool
    markitdown = MarkItDown()
    result = markitdown.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


@pytest.mark.skipif(
    skip_llm,
    reason="do not run llm tests without a key",
)
def test_markitdown_llm() -> None:
    client = openai.OpenAI()
    markitdown = MarkItDown(llm_client=client, llm_model="gpt-4o")

    result = markitdown.convert(os.path.join(TEST_FILES_DIR, "test_llm.jpg"))

    for test_string in LLM_TEST_STRINGS:
        assert test_string in result.text_content

    # This is not super precise. It would also accept "red square", "blue circle",
    # "the square is not blue", etc. But it's sufficient for this test.
    for test_string in ["red", "circle", "blue", "square"]:
        assert test_string in result.text_content.lower()


if __name__ == "__main__":
    """Runs this file's tests from the command line."""
    # test_markitdown_remote()
    # test_markitdown_local()
    test_markitdown_exiftool()
    # test_markitdown_deprecation()
    # test_markitdown_llm()
