UnisMindMap/projects/multi_gpu_v2/README.md

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# MinerU v2.0 Multi-GPU Server
[简体中文](README_zh.md)
A streamlined multi-GPU server implementation.
## Quick Start
### 1. install MinerU
```bash
pip install --upgrade pip
pip install uv
uv pip install -U "mineru[core]"
uv pip install litserve aiohttp loguru
```
### 2. Start the Server
```bash
python server.py
```
### 3. Start the Client
```bash
python client.py
```
Now, pdf files under folder [demo](../../demo/) will be processed in parallel. Assuming you have 2 gpus, if you change the `workers_per_device` to `2`, 4 pdf files will be processed at the same time!
## Customize
### Server
Example showing how to start the server with custom settings:
```python
server = ls.LitServer(
MinerUAPI(output_dir='/tmp/mineru_output'),
accelerator='auto', # You can specify 'cuda'
devices='auto', # "auto" uses all available GPUs
workers_per_device=1, # One worker instance per GPU
timeout=False # Disable timeout for long processing
)
server.run(port=8000, generate_client_file=False)
```
### Client
The client supports both synchronous and asynchronous processing:
```python
import asyncio
import aiohttp
from client import mineru_parse_async
async def process_documents():
async with aiohttp.ClientSession() as session:
# Basic usage
result = await mineru_parse_async(session, 'document.pdf')
# With custom options
result = await mineru_parse_async(
session,
'document.pdf',
backend='pipeline',
lang='ch',
formula_enable=True,
table_enable=True
)
# Run async processing
asyncio.run(process_documents())
```
### Concurrent Processing
Process multiple files simultaneously:
```python
async def process_multiple_files():
files = ['doc1.pdf', 'doc2.pdf', 'doc3.pdf']
async with aiohttp.ClientSession() as session:
tasks = [mineru_parse_async(session, file) for file in files]
results = await asyncio.gather(*tasks)
return results
```