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| import gradio as gr | |
| import re | |
| import textstat | |
| from transformers import pipeline | |
| from langdetect import detect | |
| # Load a summarization model | |
| summarizer = pipeline("summarization") | |
| # Load a text generation model from Hugging Face | |
| text_generator = pipeline("text-generation", model="gpt2") | |
| def text_analysis(text): | |
| # Analyze text: word count, character count, language detection, and readability | |
| words = re.findall(r'\w+', text.lower()) | |
| sentences = re.split(r'[.!?]+', text) | |
| num_sentences = len(sentences) - 1 | |
| num_words = len(words) | |
| num_chars = len("".join(words)) | |
| reading_ease = textstat.flesch_reading_ease(text) | |
| language = detect(text) | |
| # Format the results | |
| return { | |
| "Language": language, | |
| "Sentences": num_sentences, | |
| "Words": num_words, | |
| "Characters": num_chars, | |
| "Readability (Flesch Reading Ease)": reading_ease | |
| } | |
| def text_summarization(text): | |
| # Summarize text using the transformer model | |
| summary = summarizer(text, max_length=130, min_length=30, do_sample=False)[0]['summary_text'] | |
| return summary | |
| def generate_text(prompt): | |
| # Generate text using the loaded Hugging Face model | |
| generated_text = text_generator(prompt, max_length=50, num_return_sequences=1)[0]['generated_text'] | |
| return generated_text | |
| # Define interfaces for text analysis, text summarization, and text generation | |
| text_analysis_interface = gr.Interface(fn=text_analysis, | |
| inputs=gr.Textbox(lines=4, placeholder="Type something here..."), | |
| outputs=gr.JSON(label="Text Analysis")) | |
| text_summarization_interface = gr.Interface(fn=text_summarization, | |
| inputs=gr.Textbox(lines=4, placeholder="Type something here..."), | |
| outputs="text") | |
| text_generation_interface = gr.Interface(fn=generate_text, | |
| inputs=gr.Textbox(lines=4, placeholder="Type a prompt..."), | |
| outputs="text") | |
| # Launch the interfaces | |
| if __name__ == "__main__": | |
| text_analysis_interface.launch() | |
| text_summarization_interface.launch() | |
| text_generation_interface.launch() | |