from transformers import pipeline, set_seed from flask import Flask, request, jsonify import random, re app = Flask(__name__) # Initialize the GPT-2 pipeline gpt2_pipe = pipeline('text-generation', model='Gustavosta/MagicPrompt-Stable-Diffusion', tokenizer='gpt2') with open("ideas.txt", "r") as f: lines = f.readlines() def generate_prompts(starting_text, num_prompts=1): response_list = [] for _ in range(num_prompts): for count in range(4): # Attempt up to 4 times to generate valid response seed = random.randint(100, 1000000) set_seed(seed) # Choose a random line from the file if the input text is empty if starting_text == "": starting_text = lines[random.randrange(0, len(lines))].strip().lower().capitalize() starting_text = re.sub(r"[,:\-–.!;?_]", '', starting_text) # Generate text response = gpt2_pipe(starting_text, max_length=random.randint(60, 90), num_return_sequences=1) generated_text = response[0]['generated_text'].strip() # Clean and check the generated response if generated_text != starting_text and len(generated_text) > (len(starting_text) + 4): cleaned_text = re.sub(r'[^ ]+\.[^ ]+', '', generated_text) # Remove strings like 'abc.xyz' cleaned_text = cleaned_text.replace("<", "").replace(">", "") response_list.append(cleaned_text) break # Stop trying further once a valid prompt is added return response_list[:num_prompts] # Define the API endpoint @app.route('/', methods=['GET']) def generate_api(): starting_text = request.args.get('text', default="", type=str) num_prompts = request.args.get('n', default=1, type=int) # Get the number of prompts to return, default is 1 # Generate the prompts results = generate_prompts(starting_text, num_prompts=num_prompts) return jsonify(results) if __name__ == '__main__': # Run the Flask app on port 7860 app.run(host='0.0.0.0', port=7860)