Blame for app.py

mport gradio as gr
import os
import requests

GROK_KEY = os.getenv("GROK_KEY")
GROK_URL = "https://api.grokapi.com/v1/generate"

def call_grok(prompt, max_tokens=300):
    headers = {"Authorization": f"Bearer {GROK_KEY}"}
    payload = {
        "prompt": prompt,
        "max_tokens": max_tokens,
        "temperature": 0.2
    }
    response = requests.post(GROK_URL, headers=headers, json=payload)
    if response.status_code == 200:
        return response.json()["text"]
    else:
        return f"Error: {response.status_code} - {response.text}"

def css_lexiscan_final(text_input):
    if not text_input.strip():
        return "⚠️ Please enter some text.", "⚠️ Please enter some text."

    import re

    precis_prompt = f"""
Summarize the text below following PASI rules (CSS exam):
- One-third length
- Suitable title
- Third-person pronouns
- No personal opinions/examples
- Condensed meaning
Output format:
<<<TITLE>>>
<Title here>
<<<PRECIS>>>
<Precis here>
Text:
{text_input}
"""

    precis_raw = call_grok(precis_prompt, max_tokens=300)

    title_match = re.search(r'<<<TITLE>>>\s*(.?)\s<<<PRECIS>>>', precis_raw, re.DOTALL)
    precis_match = re.search(r'<<<PRECIS>>>\s*(.*)', precis_raw, re.DOTALL)

    title_text = title_match.group(1).strip() if title_match else ""
    precis_text = precis_match.group(1).strip() if precis_match else ""

    final_precis = f"{title_text}\n{precis_text}"

    vocab_prompt = f"""
Extract 5-7 difficult or uncommon words from the following text and give their meanings in simple English.
Use numbered list format:
1. example_word: meaning
2. another_word: meaning
3. yet_another_word: meaning
Only include words actually present in the text. Output ONLY the list.
Text:
{text_input}
"""

    vocab_raw = call_grok(vocab_prompt, max_tokens=250)
    vocab_clean = vocab_raw.replace(text_input, "").strip()

    return final_precis, vocab_clean


# ----------------------------- GRADIO UI -----------------------------
custom_css = """
<style>
body {background-color: #1E1E2F; color: #FFFFFF; font-family: 'Poppins', sans-serif;}
.gradio-container {border-radius: 20px; padding: 20px;}
.gr-button {background-color: #FF6B6B !important; color: white !important; font-weight: bold;}
textarea {font-size: 18px !important; min-height: 180px !important;}
label {font-size: 20px !important; font-weight: bold !important;}
h1 {color: #FFD93D;}
h2 {color: #6BCB77;}
</style>
"""

with gr.Blocks() as demo:
    gr.HTML(custom_css)

    gr.Markdown("<h1>✨ CSS LexiScan MVP ✨</h1>")
    gr.Markdown("<h2>Enter text & get PASI-style precis + vocabulary</h2>")

    with gr.Row():
        with gr.Column():
            text_input = gr.Textbox(label="Enter Editorial / Paragraph",
                                    placeholder="Paste your text here...",
                                    lines=8)
            submit_btn = gr.Button("Analyze Text")

        with gr.Column():
            precis_output = gr.Textbox(label="📜 Precis Output", lines=10)
            vocab_output = gr.Textbox(label="📝 Difficult Words + Meanings", lines=10)

    submit_btn.click(css_lexiscan_final,
                     inputs=text_input,
                     outputs=[precis_output, vocab_output])

demo.launch()