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AnyParse

AnyParse is a powerful multimodal document parsing and understanding engine designed to seamlessly convert complex files into structured Markdown and JSON formats. Whether it's basic text processing, professional document conversion, or advanced Vision-Language Models (VLM) and OCR recognition, AnyParse provides a comprehensive, one-stop solution.

Core Capabilities

• Multimodal Document Understanding: Supports cross-modal parsing of images and documents. By combining OCR and VLM technologies, it accurately extracts unstructured data.
• Comprehensive Format Coverage: Easily parses office documents, web pages, spreadsheets, e-books, and emails with a single tool.
• Structured Output: Transforms complex files into standardized Markdown and JSON, streamlining downstream data processing and Large Language Model (LLM) applications.

Key Features

• Documents & Layouts: PDF, DOCX, PPTX, XLSX, EPUB, IPYNB
• Text & Markup: TXT, MD, RST, HTML/XHTML/HTM/SHTML
• Spreadsheets & Data: CSV, TSV
• Images & Multimedia: PNG, JPEG/JPG
• Others: EML (Emails)
• Built-in CLI, FastAPI
• Supports running in a pure CPU environment, and also supports GPU
• Output text in human reading order, suitable for single-column, multi-column and complex layouts
• Retain the original document structure, including titles, paragraphs, lists, etc.
• Extract images, image descriptions, tables, table titles and footnotes
• Automatically identify and convert formulas in documents to LaTeX format
• Automatically identify and convert tables in documents to HTML format

resources

• docs: AnyParse docs
• pypi: anyparse-python
• ModelScope Skills
• SkillHub
• ClawHub

Insduction

Installation

pip install anyparse-python

# or

pip install -e .

anyparse all models infer by transformers+pytorch, if you want to use gpu, please install pytorch+cuda

Usage

please download config/config.yaml into your project directory.

Download Models

# use modelscope (default)
export ANYPARSE_MODEL_MIRROR="modelscope"

# use huggingface
export ANYPARSE_MODEL_MIRROR="huggingface"

# download models
anyparse-cli download --config config/config.yaml --model

Models Hub

• AnyParse Models Hub ModelScope
• AnyParse Models Hub HuggingFace

Python

# Sync
from anyparse import AnyParser

model = AnyParser(config="config/config.yaml")
res = model.invoke(file = "/path/to/your_file")



# or Async
from anyparse import AsyncAnyParser

model = AsyncAnyParser(config="config/config.yaml")
res = await model.ainvoke(file = "/path/to/your_file")

CLI

# help

anyparse-cli --help

# parse file
anyparse-cli parse --config config/config.yaml --file /path/to/your_file

# start api server
anyparse-cli api --config config/config.yaml

# see allowed file types
anyparse-cli allow --config config/config.yaml

# see commands help
anyparse-cli [COMMAND] --help

API

• start api server

# start fastapi server and openai proxy
## use restful api or openai client call
anyparse-cli api --config config/config.yaml --host 0.0.0.0 --port 18007 --seckey 'your_custom_secret_key'

• call api

# openai
from openai import OpenAI

client = OpenAI(
    base_url = "http://localhost:18007/anyparse/openai/v1",
    api_key = "your_custom_secret_key",
)
## get model id and allowed file types
print(client.models.list())



## parse file
import base64

with open("1.pdf", "r", encoding="utf-8") as f:
    text_content = f.read()

encoded_bytes = base64.b64encode(text_content.encode('utf-8'))
base64_str = encoded_bytes.decode('utf-8')

response = client.chat.completions.create(
    model="anyparse",
    messages=[
        {
            "role": "user",
            "content": [
                {
                    "type": "file",
                    "file": {
                        "file_data": f"data:application/pdf;base64,{base64_str}"
                    }
                }
            ]
        }
    ],  # data:application/pdf;base64 prefix follow: client.models.list().data[0].allow_mimetypes
    # extra_body={
    #     "runtimes_args": {
    #         "use_doc_layout": True
    #     }
    # }
)

print(response.choices[0].message.content)



# or restful
import requests as rq

headers = {
    "Authorization": "Bearer your_custom_secret_key"
}

url = "http://localhost:18007/anyparse/invoke/v1"

args = {
    "use_doc_cls": False,
    "use_doc_rectifier": False,
    "use_doc_layout": True
}

file = '/path/to/your_file'

files = {
    'file': open(file,'rb')
}

res = rq.post(url, files = files, data = args, headers = headers)
print(res.json())

• call api by skills: see skills folder

Details and Documentation see docs

TODO LIST

• audio transcription
• video transcription

All Thanks To Our Contributors

Sponsors

As the project scales, ongoing financial support is essential to sustain its maintenance and development. The immense effort required to maintain this extensive ecosystem and build new features is made possible only by the generous backing of our sponsors.

支付宝或微信打赏 (Alipay reward or WeChat reward)

Commercial Support

• Docker Deployment
• Domestic Hardware Support
• Enhanced Parsing with anyparse-pro
• Custom Development

Contact us: Email

License Information

This repository is licensed under the AnyParse Open Source License, based on Apache 2.0 with additional conditions.

Acknowledgments

• MinerU
• PaddleOCR
• GLM-OCR
• pypdfium2