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| 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() |