import gradio as gr
import requests
from bs4 import BeautifulSoup
from nltk import download, sent_tokenize
import google.generativeai as genai
import os
import re
import tempfile

# Download NLTK tokenizer data
download('punkt')

# Set your Gemini API key
api_key = os.environ.get("GEMINI_API_KEY")
if not api_key:
    raise ValueError("GEMINI_API_KEY not found in environment variables")

genai.configure(api_key=api_key)
model = genai.GenerativeModel("gemini-pro")

# Helper functions
def extract_text_from_url(url):
    try:
        response = requests.get(url, timeout=10)
        soup = BeautifulSoup(response.text, "html.parser")

        for script in soup(["script", "style", "header", "footer", "nav"]):
            script.decompose()

        paragraphs = soup.find_all("p")
        blog_text = "\n".join(p.get_text() for p in paragraphs if len(p.get_text()) > 40)

        return blog_text.strip()
    except Exception as e:
        return f"Error extracting content: {str(e)}"

def review_blog(blog_text):
    prompt = f"""
You are a professional AI blog reviewer and sensitive content analyst.

Carefully analyze the following blog content for:
1. Grammar, spelling, and clarity improvements
2. Crude, harsh, or unprofessional language
3. Sensitive, biased, offensive, or policy-violating content

Provide detailed suggestions and highlight what should be improved.

BLOG:
\"\"\"
{blog_text}
\"\"\"
"""
    response = model.generate_content(prompt)
    return response.text

def process_input(text_input, url_input):
    if url_input:
        blog_content = extract_text_from_url(url_input)
    else:
        blog_content = text_input

    if not blog_content or blog_content.strip() == "":
        return "Please provide blog content or a valid URL.", None

    analysis = review_blog(blog_content)

    # Create a temporary file with the markdown review
    with tempfile.NamedTemporaryFile(mode="w", delete=False, suffix=".md") as tmp_file:
        tmp_file.write(analysis)
        file_path = tmp_file.name

    return analysis, file_path

# Gradio UI
with gr.Blocks(theme=gr.themes.Soft()) as demo:
    gr.Markdown("# 🧠 Blog Checker AI")
    gr.Markdown("Review blogs for grammar, clarity, and policy issues using Gemini AI.")

    with gr.Row(equal_height=True):
        with gr.Column(scale=3):
            with gr.Tabs():
                with gr.TabItem("✍️ Text Input"):
                    text_input = gr.Textbox(
                        label="Paste Your Blog Content",
                        placeholder="Write or paste your blog text here...",
                        lines=12
                    )
                with gr.TabItem("🔗 URL Input"):
                    url_input = gr.Textbox(
                        label="Enter Blog URL",
                        placeholder="https://example.com/blog"
                    )
        with gr.Column(scale=2):
            gr.Markdown("""
### 🚀 How It Works
1. **Input**: Paste your blog text or provide a blog URL  
2. **Analysis**: Gemini AI checks for grammar, legal violations, and sensitive content  
3. **Report**: Instantly download a structured Markdown review
            """)
            status_button = gr.Button("🧠 Review Blog")

    output_text = gr.Textbox(label="Review Summary", lines=20)
    download_button = gr.File(label="Download Markdown Review")

    status_button.click(
        fn=process_input,
        inputs=[text_input, url_input],
        outputs=[output_text, download_button]
    )

demo.launch()