Create app.py

app.py

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+import streamlit as st
+from docx import Document
+import io
+import os
+import re
+from transformers import pipeline, AutoTokenizer, AutoModelForSeq2SeqLM
+from gingerit.gingerit import GingerIt
+
+# Initialize counter
+if not os.path.exists("counter.txt"):
+    with open("counter.txt", "w") as f:
+        f.write("0")
+
+def get_counter():
+    with open("counter.txt", "r") as f:
+        return int(f.read())
+
+def increment_counter():
+    with open("counter.txt", "r+") as f:
+        count = int(f.read())
+        count += 1
+        f.seek(0)
+        f.write(str(count))
+        f.truncate()
+    return count
+
+# Load advanced paraphrasing model
+MODEL_NAME = "humarin/chatgpt_paraphraser_on_T5_base"
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+model = AutoModelForSeq2SeqLM.from_pretrained(MODEL_NAME)
+
+def grammar_check(text):
+    try:
+        parser = GingerIt()
+        result = parser.parse(text)
+        return result['result']
+    except Exception as e:
+        st.error(f"Grammar check failed: {str(e)}")
+        return text
+
+def improve_text(text):
+    # Preprocessing
+    text = re.sub(r'\s+', ' ', text).strip()
+    
+    # Split into manageable chunks
+    sentences = re.split(r'(?<=[.!?]) +', text)
+    chunks = []
+    current_chunk = []
+    char_count = 0
+    
+    for sentence in sentences:
+        if char_count + len(sentence) < 400:
+            current_chunk.append(sentence)
+            char_count += len(sentence)
+        else:
+            chunks.append(" ".join(current_chunk))
+            current_chunk = [sentence]
+            char_count = len(sentence)
+    if current_chunk:
+        chunks.append(" ".join(current_chunk))
+
+    # Process each chunk
+    improved_chunks = []
+    for chunk in chunks:
+        inputs = tokenizer(
+            f"paraphrase: {chunk}",
+            return_tensors="pt",
+            max_length=512,
+            truncation=True
+        )
+        
+        outputs = model.generate(
+            inputs["input_ids"],
+            max_length=512,
+            num_beams=5,
+            num_return_sequences=1,
+            temperature=1.2,
+            do_sample=True,
+            top_p=0.95,
+            early_stopping=True
+        )
+        
+        paraphrased = tokenizer.decode(outputs[0], skip_special_tokens=True)
+        improved_chunks.append(paraphrased)
+
+    # Post-processing
+    final_text = " ".join(improved_chunks)
+    final_text = grammar_check(final_text)
+    
+    # Ensure coherence
+    final_text = re.sub(r'\s+([.,!?])', r'\1', final_text)
+    final_text = re.sub(r'\s+', ' ', final_text)
+    
+    return final_text
+
+# Page configuration
+st.set_page_config(
+    page_title="⚡ Rapid Humanize AI",
+    page_icon="⚡",
+    layout="wide",
+    initial_sidebar_state="expanded"
+)
+
+# Custom CSS
+st.markdown("""
+<style>
+    @import url('https://fonts.googleapis.com/css2?family=Poppins:wght@400;600&display=swap');
+    html, body, [class*="css"]  {
+        font-family: 'Poppins', sans-serif;
+    }
+    .stTextArea textarea {min-height: 300px; border-radius: 10px; padding: 15px!important;}
+    .download-btn {margin-top: 20px;}
+    .counter {font-size: 1.4em; color: #FF4B4B; font-weight: 700; padding: 10px 20px; background: #FFE3E3; border-radius: 10px;}
+    .header {color: #2c3e50; border-bottom: 3px solid #FF4B4B; padding-bottom: 10px;}
+    .stButton button {background: #FF4B4B!important; color: white!important; border-radius: 8px!important; padding: 12px 24px!important;}
+    .stButton button:hover {background: #FF2B2B!important; color: white!important;}
+    .logo {text-align: center; margin-bottom: 30px;}
+    .logo h1 {color: #FF4B4B; font-size: 2.8em; margin-bottom: 0;}
+    .logo p {color: #6c757d; font-size: 1.2em;}
+</style>
+""", unsafe_allow_html=True)
+
+# Sidebar
+with st.sidebar:
+    st.markdown('<div class="header">⚙️ Settings</div>', unsafe_allow_html=True)
+    language = st.selectbox("Language Version", ["English (US)", "English (UK)", "English (AU)", "English (CA)"])
+    mode = st.radio("Processing Mode", ["Basic", "Advanced"])
+    st.markdown(f'<div class="counter">🚀 Total Conversions: {get_counter()}</div>', unsafe_allow_html=True)
+    st.markdown("---")
+    st.markdown("**Made with ❤️ by RHAI Team**")
+
+# Main content
+st.markdown("""
+<div class="logo">
+    <h1>⚡ Rapid Humanize AI</h1>
+    <p>Transform AI-generated text into undetectable human-like content</p>
+</div>
+""", unsafe_allow_html=True)
+
+col1, col2 = st.columns(2, gap="large")
+
+with col1:
+    st.markdown('<div class="header">📥 Input Section</div>', unsafe_allow_html=True)
+    uploaded_file = st.file_uploader("Upload DOC/DOCX File", type=["docx", "doc"], help="Max file size: 25MB")
+    
+    input_text = st.text_area("Paste your AI-generated text here:", height=400, 
+                            placeholder="Enter text or upload file... (No word limit)")
+    
+    if uploaded_file:
+        doc = Document(io.BytesIO(uploaded_file.getvalue()))
+        input_text = "\n".join([para.text for para in doc.paragraphs])
+
+with col2:
+    st.markdown('<div class="header">📤 Output Section</div>', unsafe_allow_html=True)
+    output_text = st.text_area("Humanized text will appear here:", 
+                             value=st.session_state.get("output_text", ""), 
+                             height=400, key="output")
+    
+    if output_text:
+        col_d1, col_d2 = st.columns(2)
+        with col_d1:
+            st.download_button(
+                label="📥 Download TXT",
+                data=output_text,
+                file_name="humanized_text.txt",
+                mime="text/plain",
+                use_container_width=True
+            )
+        with col_d2:
+            doc = Document()
+            doc.add_paragraph(output_text)
+            bio = io.BytesIO()
+            doc.save(bio)
+            st.download_button(
+                label="📥 Download DOCX",
+                data=bio.getvalue(),
+                file_name="humanized_text.docx",
+                mime="application/vnd.openxmlformats-officedocument.wordprocessingml.document",
+                use_container_width=True
+            )
+
+# Humanize Button
+if st.button("✨ HUMANIZE NOW", use_container_width=True, type="primary"):
+    if input_text.strip():
+        with st.spinner("🚀 Humanizing your text... (This usually takes 10-30 seconds)"):
+            output_text = improve_text(input_text)
+            st.session_state.output_text = output_text
+            increment_counter()
+            st.experimental_rerun()
+    else:
+        st.error("Please enter some text or upload a file to humanize")
+
+# Features Section
+with st.expander("🌟 Key Features", expanded=True):
+    col_f1, col_f2, col_f3 = st.columns(3)
+    with col_f1:
+        st.markdown("""
+        ### 🔒 AI Detection Proof
+        Advanced algorithms remove all AI patterns
+        """)
+    with col_f2:
+        st.markdown("""
+        ### 🌐 Multi-language Support
+        Process text in various English variants
+        """)
+    with col_f3:
+        st.markdown("""
+        ### ⚡ Instant Processing
+        Quick conversion with real-time preview
+        """)
+
+# Instructions
+with st.expander("📘 How to Use RHAI"):
+    st.markdown("""
+    1. **Input Method** - Paste text directly or upload Word document
+    2. **Settings** - Choose language variant and processing mode
+    3. **Humanize** - Click the HUMANIZE NOW button
+    4. **Review & Download** - Check output and download preferred format
+    """)
+
+st.markdown("""
+---
+> **Note**: Current version uses GingerIt for grammar checking. For enterprise solutions with enhanced checking, contact RHAI Team.
+""")