anyparse models hub
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
repo: AnyParse
docs: AnyParse docs
pip install anyparse-python
please download config/config.yaml from AnyParse 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
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())