wisup_e2m 0.1.52

Everything to Markdown.

🚀 E2M: Everything to Markdown

Everything to Markdown

E2M is a Python library that can parse and convert various file types into Markdown format. By utilizing a parser-converter architecture, it supports the conversion of multiple file formats, including doc, docx, epub, html, htm, url, pdf, ppt, pptx, mp3, and m4a.

✨The ultimate goal of the E2M project is to provide high-quality data for Retrieval-Augmented Generation (RAG) and model training or fine-tuning.

📂 Supported File Types

• doc
• docx
• epub
• html
• htm
• url
• pdf
• pptx
• mp3
• m4a

📦 Installation

Create Environment:

conda create -n e2m python=3.10
conda activate e2m

Install E2M using pip:

# Option 1: Install via pip
pip install wisup_e2m
# Option 2: Install via git
pip install git+https://github.com/wisupai/e2m.git
# Option 3: Manual installation
git clone https://github.com/wisupai/e2m.git
pip install poetry
poetry build
pip install dist/wisup_e2m-0.1.41-py3-none-any.whl

⚡️ Parser Quick Start

Here's simple examples demonstrating how to use E2M Parsers:

📄 Pdf Parser

from wisup_e2m import PdfParser

pdf_path = "./test.pdf"
parser = PdfParser(engine="marker") # pdf engines: marker, unstructured, surya_layout
pdf_data = parser.parse(pdf_path)
print(pdf_data.text)

📝 Doc Parser

from wisup_e2m import DocParser

doc_path = "./test.doc"
parser = DocParser(engine="xml") # doc engines: xml
doc_data = parser.parse(doc_path)
print(doc_data.text)

📜 Docx Parser

from wisup_e2m import DocxParser

docx_path = "./test.docx"
parser = DocxParser(engine="xml") # docx engines: xml
docx_data = parser.parse(docx_path)
print(docx_data.text)

📚 Epub Parser

from wisup_e2m import EpubParser

epub_path = "./test.epub"
parser = EpubParser(engine="unstructured") # epub engines: unstructured
epub_data = parser.parse(epub_path)
print(epub_data.text)

🌐 Html Parser

from wisup_e2m import HtmlParser

html_path = "./test.html"
parser = HtmlParser(engine="unstructured") # html engines: unstructured
html_data = parser.parse(html_path)
print(html_data.text)

🔗 Url Parser

from wisup_e2m import UrlParser

url = "https://www.example.com"
parser = UrlParser(engine="jina") # url engines: jina
url_data = parser.parse(url)
print(url_data.text)

🖼️ Ppt Parser

from wisup_e2m import PptParser

ppt_path = "./test.ppt"
parser = PptParser(engine="unstructured") # ppt engines: unstructured
ppt_data = parser.parse(ppt_path)
print(ppt_data.text)

🖼️ Pptx Parser

from wisup_e2m import PptxParser

pptx_path = "./test.pptx"
parser = PptxParser(engine="unstructured") # pptx engines: unstructured
pptx_data = parser.parse(pptx_path)
print(pptx_data.text)

🎤 Voice Parser

from wisup_e2m import VoiceParser

voice_path = "./test.mp3"
parser = VoiceParser(
  engine="openai_whisper_local", # voice engines: openai_whisper_api, openai_whisper_local
  model="large" # available models: https://github.com/openai/whisper#available-models-and-languages
  )

voice_data = parser.parse(voice_path)
print(voice_data.text)

🔄 Converter Quick Start

Here's simple examples demonstrating how to use E2M Converters:

📝 Text Converter

from wisup_e2m import TextConverter

text = "Parsed text data from any parser"
converter = TextConverter(
  engine="litellm", # text engines: litellm
  model="deepseek/deepseek-chat",
  api_key="your api key",
  base_url="your base url"
  )
text_data = converter.convert(text)
print(text_data)

🖼️ Image Converter

from wisup_e2m import ImageConverter

images = ["./test1.png", "./test2.png"]
converter = ImageConverter(
  engine="litellm", # image engines: litellm
  model="gpt-4o",
  api_key="your api key",
  base_url="your base url"
  )
image_data = converter.convert(image_path)
print(image_data)

🆙 Next Level

🛠️ E2MParser

E2MParser is an integrated parser that supports multiple file types. It can be used to parse a wide range of file types into Markdown format.

from wisup_e2m import E2MParser

# Initialize the parser with your configuration file
ep = E2MParser.from_config("config.yaml")

# Parse the desired file
data = ep.parse(file_name="/path/to/file.pdf")

# Print the parsed data as a dictionary
print(data.to_dict())

🛠️ E2MConverter

E2MConverter is an integrated converter that supports text and image conversion. It can be used to convert text and images into Markdown format.

from wisup_e2m import E2MConverter

ec = E2MConverter.from_config("./config.yaml")

text = "Parsed text data from any parser"

ec.convert(text=text)

images = ["test.jpg", "test.png"]
ec.convert(images=images)

You can use a config.yaml file to specify the parsers and converters you want to use. Here is an example of a config.yaml file:

parsers:
    doc_parser:
        engine: "xml"
        langs: ["en", "zh"]
    docx_parser:
        engine: "xml"
        langs: ["en", "zh"]
    epub_parser:
        engine: "unstructured"
        langs: ["en", "zh"]
    html_parser:
        engine: "unstructured"
        langs: ["en", "zh"]
    url_parser:
        engine: "jina"
        langs: ["en", "zh"]
    pdf_parser:
        engine: "marker"
        langs: ["en", "zh"]
    pptx_parser:
        engine: "unstructured"
        langs: ["en", "zh"]
    voice_parser:
        # option 1: use openai whisper api
        # engine: "openai_whisper_api"
        # api_base: "https://api.openai.com/v1"
        # api_key: "your_api_key"
        # model: "whisper"

        # option 2: use local whisper model
        engine: "openai_whisper_local"
        model: "large" # available models: https://github.com/openai/whisper#available-models-and-languages

converter:
    text_converter:
        engine: "litellm"
        model: "deepseek/deepseek-chat"
        api_key: "your_api_key"
        # base_url: ""
    image_converter:
        engine: "litellm"
        model: "gpt-4o-mini"
        api_key: "your_api_key"
        # base_url: ""

❓ Q&A

• Resource xxx not found. Please use the NLTK Downloader to obtain the resource:

    import nltk
    nltk.download('all') # you can directly download all resources
  

• Resource wordnet not found.

  • Uninstall nltk completely: pip uninstall nltk
  • Reinstall nltk with the following command: pip install nltk
  • Download corpora/wordnet.zip manually and unzip it to the directory specified in the error message. Otherwise, you can download it using the following commands:
    • Windows: wget https://raw.githubusercontent.com/nltk/nltk_data/gh-pages/packages/corpora/wordnet.zip -O ~\AppData\Roaming\nltk_data\corpora\wordnet.zip and unzip ~\AppData\Roaming\nltk_data\corpora\wordnet.zip -d ~\AppData\Roaming\nltk_data\corpora\
    • Unix: wget https://raw.githubusercontent.com/nltk/nltk_data/gh-pages/packages/corpora/wordnet.zip -O ~/nltk_data/corpora/wordnet.zip and unzip ~/nltk_data/corpora/wordnet.zip -d ~/nltk_data/corpora/

📜 License

This project is licensed under the MIT License. See the LICENSE file for details.

📧 Contact

You can scan the QR code below to join our WeChat group:

For any questions or inquiries, please open an issue on GitHub or contact us at [e-mail].

🌟 Contributing