Update app.py

app.py

@@ -4,27 +4,25 @@ import os
 from huggingface_hub import login
 import torch
 
-# Authenticate with Hugging Face
+# Authenticate with Hugging Face token
 HUGGINGFACE_TOKEN = os.getenv("HF_TOKEN")
 login(token=HUGGINGFACE_TOKEN)
 
-# Load Phi-4 Mini
-phi_model_id = "microsoft/phi-4-mini-instruct"
-phi_tokenizer = AutoTokenizer.from_pretrained(phi_model_id, token=HUGGINGFACE_TOKEN)
-phi_model = AutoModelForCausalLM.from_pretrained(
-    phi_model_id, torch_dtype="auto", device_map="auto", token=HUGGINGFACE_TOKEN
-)
+# Load Phi-4 Mini for grammar/tone/fluency
+phi_id = "microsoft/phi-4-mini-instruct"
+phi_tokenizer = AutoTokenizer.from_pretrained(phi_id, token=HUGGINGFACE_TOKEN)
+phi_model = AutoModelForCausalLM.from_pretrained(phi_id, torch_dtype="auto", device_map="auto", token=HUGGINGFACE_TOKEN)
 phi_pipe = pipeline("text-generation", model=phi_model, tokenizer=phi_tokenizer)
 
-# Load T5 for paraphrasing
+# Load updated T5 model for paraphrasing
 t5_pipe = pipeline("text2text-generation", model="google-t5/t5-base")
 
-# Load AI detector
-ai_model_id = "openai-community/roberta-base-openai-detector"
-ai_tokenizer = AutoTokenizer.from_pretrained(ai_model_id)
-ai_model = AutoModelForSequenceClassification.from_pretrained(ai_model_id)
+# Load updated AI detector
+detector_id = "openai-community/roberta-base-openai-detector"
+detector_tokenizer = AutoTokenizer.from_pretrained(detector_id)
+detector_model = AutoModelForSequenceClassification.from_pretrained(detector_id)
 
-# Chunking helper
+# Text chunking
 def chunk_text(text, max_tokens=300):
     paragraphs = text.split("\n\n")
     chunks, current = [], ""
@@ -38,7 +36,7 @@ def chunk_text(text, max_tokens=300):
         chunks.append(current.strip())
     return chunks
 
-# Phi prompt-based generation
+# Prompt handling
 def generate_phi_prompt(text, instruction):
     chunks = chunk_text(text)
     outputs = []
@@ -51,36 +49,7 @@ def generate_phi_prompt(text, instruction):
             outputs.append(result.strip())
     return "\n\n".join(outputs)
 
-# AI detection logic
-def detect_ai_text(text):
-    inputs = ai_tokenizer(text, return_tensors="pt", truncation=True, padding=True)
-    with torch.no_grad():
-        logits = ai_model(**inputs).logits
-        probs = torch.softmax(logits, dim=1).squeeze()
-    return probs[0].item(), probs[1].item()  # human, ai
-
-# Auto-rewrite if AI > 50%
-def auto_rewrite_for_human(text):
-    rewritten = generate_phi_prompt(
-        text,
-        "Rewrite the following text so that it is indistinguishable from human writing and avoids AI detection. Be natural and fluent:"
-    )
-    human_score, ai_score = detect_ai_text(rewritten)
-    if ai_score < 0.05:
-        return rewritten, f"✅ Rewritten to pass detection. AI Likelihood: {round(ai_score * 100, 2)}%"
-    else:
-        return rewritten, f"⚠️ Rewritten, but AI Likelihood is still high: {round(ai_score * 100, 2)}%"
-
-# Smart detection & rewrite combo
-def check_and_rewrite(text):
-    human_score, ai_score = detect_ai_text(text)
-    if ai_score > 0.5:
-        rewritten, message = auto_rewrite_for_human(text)
-        return rewritten, {"Likely Human": round(human_score, 2), "Likely AI-Generated": round(ai_score, 2)}, message
-    else:
-        return text, {"Likely Human": round(human_score, 2), "Likely AI-Generated": round(ai_score, 2)}, "✅ Text is human-like. No rewrite needed."
-
-# Tool functions
+# Writing tools
 def fix_grammar(text):
     return generate_phi_prompt(text, "Correct all grammar and punctuation errors in the following text. Provide only the corrected version:")
 
@@ -98,7 +67,22 @@ def paraphrase(text):
         outputs.append(output)
     return "\n\n".join(outputs)
 
-# File utilities
+# AI Detection
+def detect_ai_percent(text):
+    inputs = detector_tokenizer(text, return_tensors="pt", truncation=True, padding=True)
+    with torch.no_grad():
+        logits = detector_model(**inputs).logits
+        probs = torch.softmax(logits, dim=1).squeeze()
+    return {
+        "Likely Human": round(probs[0].item() * 100, 2),
+        "Likely AI-Generated": round(probs[1].item() * 100, 2)
+    }
+
+# Rewrite to lower AI score
+def rewrite_to_human(text):
+    return generate_phi_prompt(text, "Rewrite the following text so that it is indistinguishable from human writing and avoids AI detection. Be natural and fluent:")
+
+# File I/O
 def load_file(file_obj):
     if file_obj is None:
         return ""
@@ -110,15 +94,15 @@ def save_file(text):
         f.write(text)
     return path
 
-# Gradio UI
+# UI
 with gr.Blocks() as demo:
-    gr.Markdown("# ✍️ AI Writing Assistant + AI Detector & Auto-Rewriter")
-    gr.Markdown("Fix grammar, improve tone, paraphrase, detect AI content, and automatically rewrite if needed.")
+    gr.Markdown("# ✍️ AI Writing Assistant + Detector")
+    gr.Markdown("Detect AI likelihood first. Rewrite manually if high. Fix grammar, tone, fluency, paraphrase, upload/download text.")
 
     with gr.Row():
         file_input = gr.File(label="📂 Upload .txt File", file_types=[".txt"])
         load_btn = gr.Button("���� Load Text")
-        input_text = gr.Textbox(lines=12, label="Or Paste Text")
+        input_text = gr.Textbox(lines=12, label="Input Text")
 
     load_btn.click(fn=load_file, inputs=file_input, outputs=input_text)
 
@@ -127,20 +111,26 @@ with gr.Blocks() as demo:
         btn_tone = gr.Button("🎯 Improve Tone")
         btn_fluency = gr.Button("🔄 Improve Fluency")
         btn_paraphrase = gr.Button("🌀 Paraphrase")
-        btn_detect = gr.Button("🕵️ Detect + Rewrite if AI")
 
     output_text = gr.Textbox(lines=12, label="Output")
-    ai_output = gr.Label(label="AI Detection Result")
-    rewrite_status = gr.Textbox(label="Status Message", interactive=False)
 
     btn_grammar.click(fn=fix_grammar, inputs=input_text, outputs=output_text)
     btn_tone.click(fn=improve_tone, inputs=input_text, outputs=output_text)
     btn_fluency.click(fn=improve_fluency, inputs=input_text, outputs=output_text)
     btn_paraphrase.click(fn=paraphrase, inputs=input_text, outputs=output_text)
-    btn_detect.click(fn=check_and_rewrite, inputs=input_text, outputs=[output_text, ai_output, rewrite_status])
+
+    gr.Markdown("## 🕵️ AI Detection")
+    detect_btn = gr.Button("Detect AI Probability")
+    ai_output = gr.Label(label="AI Detection Result")
+    detect_btn.click(fn=detect_ai_percent, inputs=input_text, outputs=ai_output)
+
+    gr.Markdown("## 🔁 Rewrite to Sound Human")
+    rewrite_btn = gr.Button("Rewrite to Reduce AI Likelihood")
+    rewritten_text = gr.Textbox(lines=12, label="Rewritten Text")
+    rewrite_btn.click(fn=rewrite_to_human, inputs=input_text, outputs=rewritten_text)
 
     gr.Markdown("## 📤 Download Output")
-    download_btn = gr.Button("💾 Download as .txt")
+    download_btn = gr.Button("💾 Download")
     download_file = gr.File(label="Click to download", interactive=True)
     download_btn.click(fn=save_file, inputs=output_text, outputs=download_file)