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| from flask import Flask, render_template, request | |
| from transformers import pipeline | |
| import logging | |
| logging.basicConfig(level=logging.DEBUG) | |
| app = Flask(__name__, static_folder='static') | |
| def generate_gpt3_text(text): | |
| generator = pipeline(task='text-generation', model='EleutherAI/gpt-neo-2.7B') | |
| generated_text = generator(text, max_length=200, num_return_sequences=1, truncation=True) | |
| return generated_text[0]['generated_text'] | |
| def generate_gpt2_text(prompt, max_length): | |
| generator = pipeline('text-generation', model='gpt2') | |
| generated_text = generator(prompt, max_length=max_length, num_return_sequences=1, truncation=True) | |
| return generated_text[0]['generated_text'] | |
| def translate_text_t5(prompt): | |
| translator = pipeline('translation_en_to_fr', model='t5-small') | |
| translated_text = translator(prompt, max_length=100)[0]['translation_text'] | |
| return translated_text | |
| def translate_text_english_to_hindi(prompt): | |
| translator = pipeline('translation_en_to_hi', model='Helsinki-NLP/opus-mt-en-hi') | |
| translated_text = translator(prompt, max_length=100)[0]['translation_text'] | |
| logging.debug(f'Generated text from GPT-3: {translated_text}') | |
| print('Translated Text (English to French):', translated_text) | |
| return translated_text | |
| def translate_text_hindi_to_english(prompt): | |
| translator = pipeline('translation_hi_to_en', model='Helsinki-NLP/opus-mt-hi-en') | |
| translated_text = translator(prompt, max_length=100)[0]['translation_text'] | |
| return translated_text | |
| def translate_text_spanish_to_english(prompt): | |
| translator = pipeline('translation_es_to_en', model='Helsinki-NLP/opus-mt-es-en') | |
| translated_text = translator(prompt, max_length=100)[0]['translation_text'] | |
| return translated_text | |
| def translate_text_german_to_english(prompt): | |
| translator = pipeline('translation_de_to_en', model='Helsinki-NLP/opus-mt-de-en') | |
| translated_text = translator(prompt, max_length=100)[0]['translation_text'] | |
| return translated_text | |
| def translate_text_french_to_english(prompt): | |
| translator = pipeline('translation_fr_to_en', model='Helsinki-NLP/opus-mt-fr-en') | |
| translated_text = translator(prompt, max_length=100)[0]['translation_text'] | |
| return translated_text | |
| def translate_text_chinese_to_english(prompt): | |
| translator = pipeline('translation_zh_to_en', model='Helsinki-NLP/opus-mt-zh-en') | |
| translated_text = translator(prompt, max_length=100)[0]['translation_text'] | |
| return translated_text | |
| def generate_long_content(input_text): | |
| summarizer = pipeline('summarization', model='t5-small') | |
| input_format = "summarize: {}".format(input_text) | |
| generated_summary = summarizer(input_format, max_length=210, num_return_sequences=1, truncation=True) | |
| output_summary = generated_summary[0]['summary_text'] | |
| return output_summary | |
| def generate_text_bert(prompt): | |
| generator = pipeline('fill-mask', model='bert-base-uncased') | |
| generated_text = generator(prompt) | |
| generated_sequences = [result['sequence'] for result in generated_text] | |
| return generated_sequences | |
| def home(): | |
| generated_text = '' | |
| if request.method == 'POST': | |
| try: | |
| prompt = request.form['prompt'] | |
| model_type = request.form['model_type'] | |
| logging.debug(f'Prompt received: {prompt}') | |
| logging.debug(f'Model type selected: {model_type}') | |
| if model_type == 'gpt3': | |
| generated_text = generate_gpt3_text(prompt) | |
| logging.debug(f'Generated text from GPT-3: {generated_text}') | |
| elif model_type == 'gpt2': | |
| max_length = int(request.form['max_length']) | |
| generated_text = generate_gpt2_text(prompt, max_length) | |
| logging.debug(f'Generated text from GPT-2: {generated_text}') | |
| elif model_type == 'translation_en_to_fr': | |
| max_length = int(request.form['max_length']) | |
| generated_text = translate_text_t5(prompt) | |
| logging.debug(f'Generated text from GPT-2: {generated_text}') | |
| elif model_type == 'translation_en_to_hi': | |
| generated_text = translate_text_english_to_hindi(prompt) | |
| logging.debug(f'Generated text from GPT-2: {generated_text}') | |
| elif model_type == 'translation_hi_to_en': | |
| generated_text = translate_text_hindi_to_english(prompt) | |
| logging.debug(f'Generated text from GPT-2: {generated_text}') | |
| elif model_type == 'translation_es_to_en': | |
| generated_text = translate_text_spanish_to_english(prompt) | |
| logging.debug(f'Generated text from GPT-2: {generated_text}') | |
| elif model_type == 'translation_de_to_en': | |
| generated_text = translate_text_german_to_english(prompt) | |
| logging.debug(f'Generated text from GPT-2: {generated_text}') | |
| elif model_type == 'translation_fr_to_en': | |
| generated_text = translate_text_french_to_english(prompt) | |
| logging.debug(f'Generated text from GPT-2: {generated_text}') | |
| elif model_type == 'translation_zh_to_en': | |
| generated_text = translate_text_chinese_to_english(prompt) | |
| logging.debug(f'Generated text from GPT-2: {generated_text}') | |
| elif model_type == 'summarization': | |
| generated_text = generate_long_content(prompt) | |
| logging.debug(f'Generated text from T5: {generated_text}') | |
| elif model_type == 'Text_bert': | |
| generated_text = generate_text_bert(prompt) | |
| logging.debug(f'Generated text from BERT: {generated_text}') | |
| except Exception as e: | |
| logging.error(f'An error occurred: {str(e)}') | |
| return render_template('index.html', prompt=prompt, generated_text=generated_text) | |
| return render_template('index.html', generated_text=generated_text) | |
| if __name__ == '__main__': | |
| app.run(debug=True) |