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import docx # Importing the required module for DOCX extraction
from datasketch import MinHash, MinHashLSH # Importing MinHash and LSH from datasketch
import gradio as gr # Importing Gradio for creating the web interface
# Function to extract text from DOCX files
def extract_text_from_docx(docx_path):
try:
doc = docx.Document(docx_path) # Open the DOCX file
text = "\n".join([para.text for para in doc.paragraphs]) # Extract the text from paragraphs
return text
except Exception as e:
print(f"Error extracting text from DOCX: {str(e)}")
return ""
# Function to calculate MinHash-based similarity between two texts
def calculate_similarity(doc1, doc2):
def text_to_shingles(text, k=5):
# Split the text into k-grams (shingles) of length k
shingles = set()
for i in range(len(text) - k + 1):
shingles.add(text[i:i + k])
return shingles
# Generate shingles for both documents
shingles1 = text_to_shingles(doc1)
shingles2 = text_to_shingles(doc2)
# Compute MinHash signatures
minhash1 = MinHash(num_perm=128)
minhash2 = MinHash(num_perm=128)
for shingle in shingles1:
minhash1.update(shingle.encode('utf8'))
for shingle in shingles2:
minhash2.update(shingle.encode('utf8'))
# Compute Jaccard similarity using MinHash
similarity_score = minhash1.jaccard(minhash2)
return similarity_score
# Function to interpret similarity scores
def interpret_similarity(score):
if score == 1.0:
return "Exact Match! The documents are identical."
elif 0.8 <= score < 1.0:
return "High Similarity: The documents are very similar."
elif 0.5 <= score < 0.8:
return "Moderate Similarity: The documents share some content."
elif 0.2 <= score < 0.5:
return "Low Similarity: The documents have limited overlap."
else:
return "Very Low Similarity: The documents are mostly different."
# Function to handle the similarity calculation
def similarity(doc1, doc2, file1=None, file2=None):
text1 = ""
text2 = ""
# Check for file uploads
if file1 is not None and file1.name.endswith('.docx'):
text1 = extract_text_from_docx(file1.name)
elif doc1:
text1 = doc1
else:
return "Please provide either a DOCX file or paste the text for Document 1."
if file2 is not None and file2.name.endswith('.docx'):
text2 = extract_text_from_docx(file2.name)
elif doc2:
text2 = doc2
else:
return "Please provide either a DOCX file or paste the text for Document 2."
score = calculate_similarity(text1, text2)
return f"Similarity Score: {score:.2f}\n{interpret_similarity(score)}"
# Create a Gradio interface
with gr.Blocks() as demo:
gr.Markdown("## 📄 Document Similarity Checker")
gr.Markdown(
"Compare two documents by uploading DOCX files or pasting text. The app calculates similarity using MinHash and provides an interpretative score.")
with gr.Row():
with gr.Column():
gr.Markdown("### Document 1")
file1 = gr.File(label="Upload DOCX File")
doc1 = gr.Textbox(label="Or Paste Text Here", lines=10, placeholder="Paste document text...")
with gr.Column():
gr.Markdown("### Document 2")
file2 = gr.File(label="Upload DOCX File")
doc2 = gr.Textbox(label="Or Paste Text Here", lines=10, placeholder="Paste document text...")
output = gr.Textbox(label="Result", lines=3)
submit = gr.Button("Check Similarity", variant="primary")
submit.click(fn=similarity, inputs=[doc1, doc2, file1, file2], outputs=output)
# Launch the Gradio app
demo.launch() |