File size: 3,169 Bytes
09498fa | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 | #!/usr/bin/env python3
"""
Test script to verify all dependencies and PDF handling capabilities.
"""
import os
import sys
print("=== CogniChat Dependencies & PDF Handling Test ===")
# Test imports
try:
print("\nTesting core imports...")
from langchain_community.embeddings import HuggingFaceEmbeddings
from langchain_community.retrievers import BM25Retriever
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain_core.documents import Document
print("✓ Core LangChain imports successful!")
except ImportError as e:
print(f"✗ Import error: {e}")
if "rank_bm25" in str(e):
print(" → Missing dependency: pip install rank-bm25==0.2.2")
sys.exit(1)
# Test PDF loading capabilities
try:
print("\nTesting PDF loading capabilities...")
# Test PyPDF availability
try:
from langchain_community.document_loaders import PyPDFLoader
print("✓ PyPDFLoader available")
except ImportError:
print("✗ PyPDFLoader not available")
# Test PyMuPDF availability
try:
import fitz
print("✓ PyMuPDF (fitz) available - can handle corrupted PDFs")
except ImportError:
print("✗ PyMuPDF (fitz) not available")
# Test pdfplumber availability
try:
import pdfplumber
print("✓ pdfplumber available - additional PDF parsing method")
except ImportError:
print("✗ pdfplumber not available")
except Exception as e:
print(f"✗ Error testing PDF capabilities: {e}")
# Test BM25 Retriever
try:
print("\nTesting BM25 Retriever...")
# Create some test documents
test_docs = [
Document(page_content="This is the first test document about machine learning."),
Document(page_content="This is the second document discussing natural language processing."),
Document(page_content="The third document covers artificial intelligence topics."),
]
# Create BM25 retriever
bm25_retriever = BM25Retriever.from_documents(test_docs)
bm25_retriever.k = 2
# Test retrieval
query = "machine learning"
results = bm25_retriever.get_relevant_documents(query)
print(f"✓ BM25 retriever created and tested successfully!")
print(f"✓ Retrieved {len(results)} documents for query: '{query}'")
except Exception as e:
print(f"✗ Error testing BM25 retriever: {e}")
import traceback
traceback.print_exc()
sys.exit(1)
print("\n=== All tests completed successfully! ===")
print("\nThe application should now handle:")
print(" • Regular file uploads and processing")
print(" • Corrupted PDF files with multiple fallback methods")
print(" • BM25 and FAISS hybrid retrieval")
print(" • Proper error messages for failed file processing")
print("\nMake sure to install all dependencies with:")
print(" pip install -r requirements.txt")
# Display dependency summary
print("\n=== Key Dependencies Added/Updated ===")
print(" • rank-bm25==0.2.2 (for BM25 retrieval)")
print(" • pymupdf==1.23.26 (PDF fallback method)")
print(" • pdfplumber==0.10.3 (additional PDF parsing)") |