Create app.py

app.py

@@ -0,0 +1,72 @@
+import streamlit as st
+
+def chunk_text(text, chunk_size, overlap):
+    chunks = []
+    start = 0
+    while start < len(text):
+        end = start + chunk_size
+        chunks.append(text[start:end])
+        start += (chunk_size - overlap)
+    return chunks
+
+def main():
+    st.set_page_config(page_title="Text Chunker", page_icon="✂️", layout="centered")
+    
+    # Custom CSS for styling
+    st.markdown("""
+    <style>
+        .header {
+            color: #2F4F4F;
+            border-bottom: 2px solid #2F4F4F;
+            padding-bottom: 10px;
+        }
+        .chunk-box {
+            padding: 20px;
+            margin: 10px 0;
+            border-radius: 10px;
+            background-color: #F0F2F6;
+            box-shadow: 0 2px 4px rgba(0,0,0,0.1);
+        }
+    </style>
+    """, unsafe_allow_html=True)
+
+    st.markdown('<h1 class="header">✂️ Text Chunker</h1>', unsafe_allow_html=True)
+    
+    # Example text
+    example_text = """Natural language processing (NLP) is a subfield of linguistics, computer science, 
+    and artificial intelligence concerned with the interactions between computers and human language. 
+    It focuses on how to program computers to process and analyze large amounts of natural language data. 
+    The result is a computer capable of understanding natural language in a way that is both meaningful 
+    and useful to humans."""
+    
+    # Inputs
+    input_text = st.text_area("Input Text", value=example_text, height=200)
+    col1, col2 = st.columns(2)
+    with col1:
+        chunk_size = st.slider("Chunk Size (characters)", 50, 200, 100, 10)
+    with col2:
+        overlap = st.slider("Overlap (characters)", 0, 50, 20, 5)
+    
+    if overlap >= chunk_size:
+        st.error("Overlap must be smaller than chunk size!")
+        return
+    
+    # Processing
+    if st.button("Chunk It!", type="primary"):
+        chunks = chunk_text(input_text, chunk_size, overlap)
+        
+        st.markdown(f"**🔖 {len(chunks)} Chunks Created**")
+        for i, chunk in enumerate(chunks, 1):
+            with st.container():
+                st.markdown(f"""
+                <div class="chunk-box">
+                    <h4>Chunk #{i} (Length: {len(chunk)})</h4>
+                    <hr style="border:1px solid #2F4F4F">
+                    <p>{chunk}</p>
+                </div>
+                """, unsafe_allow_html=True)
+                
+        st.success("✅ Chunking completed! Scroll to see all chunks.")
+
+if __name__ == "__main__":
+    main()