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| import gradio as gr | |
| import json | |
| def analyze_text(text: str) -> str: | |
| """Analyze text and return statistics. | |
| Args: | |
| text: The input text to analyze | |
| Returns: | |
| JSON string with analysis results | |
| """ | |
| words = text.split() | |
| chars = len(text) | |
| chars_no_spaces = len(text.replace(" ", "")) | |
| sentences = text.count(".") + text.count("!") + text.count("?") | |
| avg_word_length = round(chars_no_spaces / len(words), 2) if words else 0 | |
| avg_sentence_length = round(len(words) / max(sentences, 1), 2) | |
| return json.dumps({ | |
| "total_characters": chars, | |
| "characters_without_spaces": chars_no_spaces, | |
| "total_words": len(words), | |
| "total_sentences": max(sentences, 1), | |
| "average_word_length": avg_word_length, | |
| "average_sentence_length": avg_sentence_length | |
| }, indent=2) | |
| def extract_keywords(text: str, count: int = 5) -> str: | |
| """Extract keywords (most common words) from text. | |
| Args: | |
| text: The input text | |
| count: Number of keywords to return (default 5) | |
| Returns: | |
| JSON string with keywords and frequencies | |
| """ | |
| stopwords = { | |
| "the", "a", "an", "and", "or", "but", "in", "on", "at", "to", "for", | |
| "of", "with", "is", "are", "was", "were", "be", "been", "by", "from" | |
| } | |
| words = text.lower().split() | |
| filtered = [w.strip(".,!?;:") for w in words if w.lower() not in stopwords] | |
| from collections import Counter | |
| word_freq = Counter(filtered) | |
| top_words = word_freq.most_common(count) | |
| return json.dumps({ | |
| "keywords": [{"word": w, "frequency": f} for w, f in top_words] | |
| }, indent=2) | |
| def check_reading_level(text: str) -> str: | |
| """Estimate reading difficulty level. | |
| Args: | |
| text: The input text | |
| Returns: | |
| JSON string with reading level estimate | |
| """ | |
| sentences = max(text.count(".") + text.count("!") + text.count("?"), 1) | |
| words = len(text.split()) | |
| vowels = "aeiou" | |
| syllables = sum(1 for c in text.lower() if c in vowels) | |
| if words == 0: | |
| return json.dumps({"error": "No text to analyze"}) | |
| grade = max(0, (0.39 * (words / sentences)) + (11.8 * (syllables / words)) - 15.59) | |
| if grade < 6: | |
| level = "Elementary School" | |
| elif grade < 9: | |
| level = "Middle School" | |
| elif grade < 13: | |
| level = "High School" | |
| else: | |
| level = "College/Academic" | |
| return json.dumps({ | |
| "grade_level": round(grade, 1), | |
| "reading_level": level | |
| }, indent=2) | |
| # Create web UI | |
| with gr.Blocks(title="Text Processor") as demo: | |
| gr.Markdown("# Text Processing Tools") | |
| gr.Markdown("Analyze text statistics, extract keywords, and check reading difficulty.") | |
| with gr.Tab("Analyze Text"): | |
| text_input1 = gr.Textbox( | |
| label="Enter text", | |
| lines=8, | |
| placeholder="Paste your text here..." | |
| ) | |
| analysis_output = gr.Textbox(label="Analysis Results", lines=8) | |
| gr.Button("Analyze", size="lg").click(analyze_text, text_input1, analysis_output) | |
| with gr.Tab("Extract Keywords"): | |
| text_input2 = gr.Textbox(label="Enter text", lines=8) | |
| count_input = gr.Slider(1, 20, value=5, step=1, label="Number of keywords") | |
| keywords_output = gr.Textbox(label="Keywords", lines=8) | |
| gr.Button("Extract", size="lg").click( | |
| extract_keywords, | |
| [text_input2, count_input], | |
| keywords_output | |
| ) | |
| with gr.Tab("Reading Level"): | |
| text_input3 = gr.Textbox(label="Enter text", lines=8) | |
| level_output = gr.Textbox(label="Reading Level Analysis", lines=5) | |
| gr.Button("Check Level", size="lg").click(check_reading_level, text_input3, level_output) | |
| if __name__ == "__main__": | |
| demo.launch(mcp_server=True) |