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DocStrange Hugging Face Spaces API
Deploy this on Hugging Face Spaces to provide DocStrange extraction API
"""
import os
import sys
import tempfile
from pathlib import Path
from fastapi import FastAPI, File, UploadFile, HTTPException
from fastapi.responses import JSONResponse
from fastapi.middleware.cors import CORSMiddleware
import uvicorn
# Add docstrange to path
sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'docstrange'))
try:
from docstrange import DocumentExtractor
HAS_DOCTSTRANGE = True
except ImportError:
HAS_DOCTSTRANGE = False
app = FastAPI(
title="DocStrange Document Extractor API",
description="Extract structured data from documents using DocStrange AI",
version="1.0.0"
)
# Allow CORS for DataSync integration
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
# Global extractor instance
extractor = None
def get_extractor():
"""Get or create DocumentExtractor instance"""
global extractor
if extractor is None:
if not HAS_DOCTSTRANGE:
raise HTTPException(status_code=500, detail="DocStrange not installed")
# Use GPU if available, otherwise cloud mode
try:
import torch
gpu_mode = torch.cuda.is_available()
except:
gpu_mode = False
if gpu_mode:
extractor = DocumentExtractor(gpu=True)
else:
extractor = DocumentExtractor()
return extractor
@app.get("/")
def root():
"""Health check"""
return {
"status": "ok",
"service": "DocStrange API",
"version": "1.0.0",
"gpu_available": HAS_DOCTSTRANGE
}
@app.get("/health")
def health():
"""Health check"""
try:
import torch
gpu = torch.cuda.is_available()
vram = f"{torch.cuda.get_device_properties(0).total_mem/1024**3:.1f}GB" if gpu else "N/A"
except:
gpu = False
vram = "N/A"
return {
"status": "ok",
"gpu": gpu,
"vram": vram,
"docstrange": HAS_DOCTSTRANGE
}
@app.post("/extract")
async def extract_document(
file: UploadFile = File(...),
output_format: str = "markdown"
):
"""
Extract structured data from document
Args:
file: Document file (PDF, DOCX, XLSX, Images, etc.)
output_format: markdown, json, csv, html, text, flat-json, all
Returns: JSON with extracted data
"""
if not file.filename:
raise HTTPException(status_code=400, detail="No file provided")
supported_formats = ['.pdf', '.docx', '.xlsx', '.pptx', '.png', '.jpg', '.jpeg',
'.bmp', '.tiff', '.webp', '.gif', '.txt', '.html', '.md', '.csv']
ext = Path(file.filename).suffix.lower()
if ext not in supported_formats:
raise HTTPException(
status_code=400,
detail=f"Unsupported format: {ext}. Supported: {supported_formats}"
)
try:
# Save uploaded file temporarily
with tempfile.NamedTemporaryFile(delete=False, suffix=ext) as tmp:
content = await file.read()
tmp.write(content)
tmp_path = tmp.name
# Extract document
ext = get_extractor()
result = ext.extract_document(tmp_path, output_format=output_format)
# Build response
response = {
"success": True,
"file_name": file.filename,
"data": result.get('data', {}),
"format": result.get('format', output_format),
"metadata": {
"file_size": result.get('metadata', {}).get('file_size', 0),
"engine": "docstrange",
"gpu_mode": result.get('metadata', {}).get('gpu_mode', False)
}
}
# Cleanup
os.unlink(tmp_path)
return JSONResponse(content=response)
except Exception as e:
# Cleanup on error
if 'tmp_path' in locals():
try:
os.unlink(tmp_path)
except:
pass
raise HTTPException(status_code=500, detail=f"Extraction failed: {str(e)}")
@app.post("/extract/markdown")
async def extract_to_markdown(file: UploadFile = File(...)):
"""Extract document to markdown only (lightweight)"""
try:
with tempfile.NamedTemporaryFile(delete=False, suffix=Path(file.filename).suffix.lower()) as tmp:
content = await file.read()
tmp.write(content)
tmp_path = tmp.name
ext = get_extractor()
result = ext.extract_document(tmp_path, output_format='markdown')
os.unlink(tmp_path)
return {
"success": True,
"markdown": result.get('data', ''),
"file_name": file.filename
}
except Exception as e:
if 'tmp_path' in locals():
try:
os.unlink(tmp_path)
except:
pass
raise HTTPException(status_code=500, detail=str(e))
@app.post("/extract/tables")
async def extract_tables(file: UploadFile = File(...)):
"""Extract tables only from document"""
try:
with tempfile.NamedTemporaryFile(delete=False, suffix=Path(file.filename).suffix.lower()) as tmp:
content = await file.read()
tmp.write(content)
tmp_path = tmp.name
# Extract with JSON format to get structured tables
ext = get_extractor()
result = ext.extract_document(tmp_path, output_format='json')
data = result.get('data', {})
tables = data.get('tables', [])
os.unlink(tmp_path)
return {
"success": True,
"tables": tables,
"tables_count": len(tables),
"file_name": file.filename
}
except Exception as e:
if 'tmp_path' in locals():
try:
os.unlink(tmp_path)
except:
pass
raise HTTPException(status_code=500, detail=str(e))
if __name__ == "__main__":
print("="*60)
print("DocStrange Document Extractor API")
print("="*60)
print("URL: http://localhost:8080")
print("Docs: http://localhost:8080/docs")
print("="*60)
uvicorn.run(
"app:app",
host="0.0.0.0",
port=8080,
reload=True
)
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