Files
MinerU/projects/multi_gpu/server.py
2024-10-27 01:11:36 +08:00

75 lines
2.3 KiB
Python

import os
import fitz
import torch
import base64
import litserve as ls
from uuid import uuid4
from fastapi import HTTPException
from filetype import guess_extension
from magic_pdf.tools.common import do_parse
from magic_pdf.model.doc_analyze_by_custom_model import ModelSingleton
class MinerUAPI(ls.LitAPI):
def __init__(self, output_dir='/tmp'):
self.output_dir = output_dir
def setup(self, device):
if device.startswith('cuda'):
os.environ['CUDA_VISIBLE_DEVICES'] = device.split(':')[-1]
if torch.cuda.device_count() > 1:
raise RuntimeError("Remove any CUDA actions before setting 'CUDA_VISIBLE_DEVICES'.")
model_manager = ModelSingleton()
model_manager.get_model(True, False)
model_manager.get_model(False, False)
print(f'Model initialization complete on {device}!')
def decode_request(self, request):
file = request['file']
file = self.to_pdf(file)
opts = request.get('kwargs', {})
opts.setdefault('debug_able', False)
opts.setdefault('parse_method', 'auto')
return file, opts
def predict(self, inputs):
try:
do_parse(self.output_dir, pdf_name := str(uuid4()), inputs[0], [], **inputs[1])
return pdf_name
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
finally:
self.clean_memory()
def encode_response(self, response):
return {'output_dir': response}
def clean_memory(self):
import gc
if torch.cuda.is_available():
torch.cuda.empty_cache()
torch.cuda.ipc_collect()
gc.collect()
def to_pdf(self, file_base64):
try:
file_bytes = base64.b64decode(file_base64)
file_ext = guess_extension(file_bytes)
with fitz.open(stream=file_bytes, filetype=file_ext) as f:
if f.is_pdf: return f.tobytes()
return f.convert_to_pdf()
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
if __name__ == '__main__':
server = ls.LitServer(
MinerUAPI(output_dir='/tmp'),
accelerator='cuda',
devices='auto',
workers_per_device=1,
timeout=False
)
server.run(port=8000)