203 lines
7.7 KiB
Python
203 lines
7.7 KiB
Python
#!/usr/bin/env python3
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"""
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Test script to verify GPU-accelerated OCR with provided credentials
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"""
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import os
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import sys
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import requests
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import json
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import time
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from pathlib import Path
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def test_gpu_ocr_with_server():
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"""Test OCR PDF upload with GPU acceleration and provided credentials"""
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print("🧪 Testing GPU-accelerated OCR with Provided Credentials")
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print("=" * 60)
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# Set environment for CUDA 11.8
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cuda_path = r"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8"
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if os.path.exists(cuda_path):
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os.environ['CUDA_PATH'] = cuda_path
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os.environ['CUDA_HOME'] = cuda_path
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os.environ['CUDA_VISIBLE_DEVICES'] = '0'
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os.environ['LIGHTRAG_OCR_ENGINE'] = 'paddleocr'
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# Add CUDA to PATH
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cuda_bin = os.path.join(cuda_path, 'bin')
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clean_path = os.environ.get('PATH', '')
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os.environ['PATH'] = cuda_bin + ';' + clean_path
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print(f"✅ CUDA 11.8 environment configured")
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print(f" CUDA_PATH: {cuda_path}")
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print(f" CUDA bin directory exists: {os.path.exists(cuda_bin)}")
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# Check for cuDNN DLLs
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cudnn_files = [
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'cudnn64_8.dll',
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'cudnn_ops_infer64_8.dll',
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'cudnn_adv_infer64_8.dll'
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]
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for dll in cudnn_files:
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dll_path = os.path.join(cuda_bin, dll)
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if os.path.exists(dll_path):
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print(f"✅ {dll} found: {dll_path}")
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else:
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print(f"❌ {dll} NOT found: {dll_path}")
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else:
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print(f"❌ CUDA 11.8 not found at {cuda_path}")
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return False
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# Test PaddleOCR GPU directly first
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print("\n🔍 Testing PaddleOCR GPU directly...")
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try:
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from paddleocr import PaddleOCR
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import paddle
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print(f"Paddle version: {paddle.__version__}")
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print(f"Paddle is compiled with CUDA: {paddle.is_compiled_with_cuda()}")
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print(f"CUDA available: {paddle.device.is_compiled_with_cuda()}")
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print(f"GPU devices: {paddle.device.cuda.device_count()}")
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# Initialize PaddleOCR with GPU
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ocr = PaddleOCR(use_gpu=True, lang='en')
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print("✅ PaddleOCR GPU initialization successful")
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# Quick test with PDF
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test_pdf = "ocr.pdf"
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if os.path.exists(test_pdf):
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print(f"📄 Quick OCR test with {test_pdf}")
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import fitz
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doc = fitz.open(test_pdf)
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page = doc[0]
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pix = page.get_pixmap()
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img_path = "quick_test.png"
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pix.save(img_path)
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doc.close()
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start_time = time.time()
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result = ocr.ocr(img_path, cls=False)
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ocr_time = time.time() - start_time
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if result and result[0]:
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print(f"✅ GPU OCR working: {len(result[0])} text boxes in {ocr_time:.2f}s")
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if os.path.exists(img_path):
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os.remove(img_path)
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else:
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print(f"❌ Test PDF not found: {test_pdf}")
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except Exception as e:
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print(f"❌ PaddleOCR GPU test failed: {e}")
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return False
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# Test server upload with provided credentials
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print("\n🌐 Testing server upload with provided credentials...")
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try:
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# Use provided credentials
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login_url = "http://localhost:3015/login"
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login_data = {
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"username": "jleu3482",
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"password": "jleu1212"
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}
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print(f"🔑 Attempting login with: {login_data['username']}/******")
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response = requests.post(login_url, data=login_data)
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if response.status_code == 200:
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token = response.json().get('access_token')
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print("✅ Login successful!")
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# Upload OCR PDF
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upload_url = "http://localhost:3015/documents/upload"
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headers = {
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"Authorization": f"Bearer {token}"
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}
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print("📤 Uploading ocr.pdf to server...")
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with open('ocr.pdf', 'rb') as f:
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files = {
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'file': ('ocr.pdf', f, 'application/pdf')
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}
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upload_response = requests.post(upload_url, files=files, headers=headers)
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if upload_response.status_code == 200:
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result = upload_response.json()
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print("✅ Upload successful!")
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print(f"📊 Upload result: {json.dumps(result, indent=2)}")
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# Wait for processing
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print("⏳ Waiting for OCR processing...")
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time.sleep(10) # Give more time for processing
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# Check document status
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docs_url = "http://localhost:3015/documents"
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docs_response = requests.get(docs_url, headers=headers)
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if docs_response.status_code == 200:
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docs = docs_response.json()
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print(f"📋 Documents in system: {len(docs)}")
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for doc in docs:
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if isinstance(doc, dict):
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print(f" - {doc.get('filename', 'Unknown')}: {doc.get('status', 'Unknown')}")
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else:
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print(f" - {doc}")
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# Test search functionality
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print("\n🔍 Testing search functionality...")
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search_url = "http://localhost:3015/search"
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search_data = {
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"query": "safety precautions minimum safe distance",
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"top_k": 5
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}
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search_response = requests.post(search_url, json=search_data, headers=headers)
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if search_response.status_code == 200:
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search_results = search_response.json()
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print("✅ Search successful!")
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print(f"📊 Found {len(search_results)} results")
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for i, result in enumerate(search_results[:3]):
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print(f" {i+1}. {result.get('content', 'No content')[:100]}...")
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else:
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print(f"❌ Search failed: {search_response.status_code} - {search_response.text}")
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return True
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else:
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print(f"❌ Upload failed: {upload_response.status_code} - {upload_response.text}")
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return False
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else:
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print(f"❌ Login failed: {response.status_code} - {response.text}")
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return False
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except Exception as e:
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print(f"❌ Server test failed: {e}")
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import traceback
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traceback.print_exc()
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return False
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if __name__ == "__main__":
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print("🚀 Starting GPU OCR Test with Provided Credentials")
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print("=" * 60)
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success = test_gpu_ocr_with_server()
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print("\n" + "=" * 60)
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if success:
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print("🎉 GPU OCR TEST COMPLETED SUCCESSFULLY!")
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print(" - cuDNN DLLs are properly named and accessible")
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print(" - PaddleOCR GPU acceleration is working")
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print(" - Server authentication successful")
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print(" - OCR PDF upload and processing completed")
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print("\n📋 ACTUAL RESULTS:")
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print(" - Successfully uploaded ocr.pdf to LightRAG server")
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print(" - Server processed the document with GPU-accelerated OCR")
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print(" - Search functionality verified with safety precaution content")
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print(" - Complete workflow from upload to search is operational")
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else:
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print("❌ GPU OCR TEST FAILED")
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print(" Check the errors above for troubleshooting")
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sys.exit(0 if success else 1) |