Update app.py

app.py

@@ -0,0 +1,49 @@
+import gradio as gr
+from newspaper import Article
+from transformers import pipeline
+
+# Load small LLM
+reviewer = pipeline("text2text-generation", model="google/flan-t5-base")
+
+# Step 1: Extract blog content
+def extract_text_from_url(url):
+    try:
+        article = Article(url)
+        article.download()
+        article.parse()
+        return article.text
+    except Exception as e:
+        return f"Error: {e}"
+
+# Step 2: Review content
+def review_blog(text):
+    prompt = f"""Please review the following blog content. Fix grammar, crude/offensive language, or policy-violating parts. Suggest replacements:
+
+{text}"""
+    result = reviewer(prompt, max_new_tokens=300)[0]['generated_text']
+    return result
+
+# Step 3: Finalize after approval
+def finalize_text(original_text, reviewed_suggestions):
+    # For simplicity, we'll just return reviewed version for now
+    # Later you can implement side-by-side diff + selective replacement
+    return reviewed_suggestions
+
+# Gradio UI
+with gr.Blocks() as app:
+    gr.Markdown("## 🧠 BlogChecker AI")
+    
+    url = gr.Textbox(label="Enter Blog URL")
+    blog_content = gr.Textbox(label="Extracted Blog Text", lines=10)
+    reviewed = gr.Textbox(label="Suggested Revisions", lines=10)
+    final_output = gr.Textbox(label="Final Clean Blog", lines=10)
+
+    extract_btn = gr.Button("1️⃣ Extract Blog Text")
+    review_btn = gr.Button("2️⃣ Review Content")
+    approve_btn = gr.Button("3️⃣ Approve and Finalize")
+
+    extract_btn.click(fn=extract_text_from_url, inputs=url, outputs=blog_content)
+    review_btn.click(fn=review_blog, inputs=blog_content, outputs=reviewed)
+    approve_btn.click(fn=finalize_text, inputs=[blog_content, reviewed], outputs=final_output)
+
+app.launch()