Update app.py

app.py

@@ -1,67 +1,80 @@
-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 handle the file upload and similarity calculation
-def similarity(file1, file2):
-    if file1.name.endswith('.docx'):
-        text1 = extract_text_from_docx(file1.name)
-    else:
-        return "File type not supported. Please upload a DOCX file."
-
-    if file2.name.endswith('.docx'):
-        text2 = extract_text_from_docx(file2.name)
-    else:
-        return "File type not supported. Please upload a DOCX file."
-
-    return calculate_similarity(text1, text2)
-
-# Create a Gradio interface
-with gr.Blocks() as demo:
-    gr.Markdown("## Document Similarity Checker for DOCX files")
-    file1 = gr.File(label="Upload Document 1 (DOCX)")
-    file2 = gr.File(label="Upload Document 2 (DOCX)")
-    output = gr.Textbox(label="Similarity Score")
-    submit = gr.Button("Submit")
-    
-    submit.click(fn=similarity, inputs=[file1, file2], outputs=output)
-
-# Launching the Streamlit app
-demo.launch()
+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 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."
+
+    return calculate_similarity(text1, text2)
+
+# Create a Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("## Document Similarity Checker")
+    with gr.Row():
+        with gr.Column():
+            file1 = gr.File(label="Upload Document 1 (DOCX)")
+            doc1 = gr.Textbox(label="Or Paste Text for Document 1", lines=10)
+        with gr.Column():
+            file2 = gr.File(label="Upload Document 2 (DOCX)")
+            doc2 = gr.Textbox(label="Or Paste Text for Document 2", lines=10)
+    output = gr.Textbox(label="Similarity Score")
+    submit = gr.Button("Submit")
+
+    submit.click(fn=similarity, inputs=[doc1, doc2, file1, file2], outputs=output)
+
+# Launch the Gradio app
+demo.launch()