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.gitignore

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+__pycache__/

app.py

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+# app.py
+import gradio as gr
+import spacy
+import language_tool_python
+from transformers import pipeline
+
+# --- load lightweight models once ---
+nlp = spacy.load("en_core_web_sm")
+tool = language_tool_python.LanguageTool('en-US')
+para = pipeline("text2text-generation", model="Vamsi/T5_Paraphrase_Paws")
+
+def humanize(text, tone, strength, freeze):
+    # detect entities to lock
+    locked = [(ent.text, ent.label_) for ent in nlp(text).ents] if freeze else []
+    # paraphrase
+    paraphrased = para(text, max_length=512, do_sample=True, temperature=0.7 * strength / 10)[0]['generated_text']
+    # grammar fix
+    paraphrased = tool.correct(paraphrased)
+    # restore locked entities
+    for ent, label in locked:
+        paraphrased = re.sub(re.escape(ent), ent, paraphrased, flags=re.IGNORECASE)
+    return paraphrased
+
+# --- Gradio interface ---
+import re
+iface = gr.Interface(
+    fn=humanize,
+    inputs=[
+        gr.Textbox(label="Paste or type your text here", lines=10, placeholder="Type or paste your AI text…"),
+        gr.Dropdown(["Casual", "Academic", "Marketing", "Legal", "Creative"], value="Casual", label="Tone"),
+        gr.Slider(1, 10, value=5, label="Humanize Strength (1 = subtle, 10 = aggressive)"),
+        gr.Checkbox(label="Lock facts / dates / names")
+    ],
+    outputs=gr.Textbox(label="Humanized text", lines=10),
+    title="AI Humanizer – 100 % Free & Unlimited",
+    description="Zero sign-up, zero cost. Paste, choose options, click “Submit”."
+)
+
+iface.launch()

requirements.txt

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+gradio==4.8
+spacy==3.7.2
+language-tool-python
+transformers
+torch
+sentencepiece
+nltk
+re