import gradio as gr import requests import os # GPT-J-6B API API_URL = "https://api-inference.huggingface.co/models/EleutherAI/gpt-j-6B" HF_TOKEN = os.environ["HF_TOKEN"] headers = {"Authorization": f"Bearer {HF_TOKEN}"} prompt = """ word: risk poem using word: And then the day came, when the risk to remain tight in a bud was more painful than the risk it took to blossom. word: bird poem using word: She sights a bird, she chuckles She flattens, then she crawls She runs without the look of feet Her eyes increase to Balls. word: """ examples = [["river"], ["night"], ["trees"],["table"],["laughs"]] def poem_generate(word): p = prompt + word.lower() + "\n" + "poem using word: " print(f"*****Inside poem_generate - Prompt is :{p}") json_ = {"inputs": p, "parameters": { "top_p": 0.9, "temperature": 1.1, "max_new_tokens": 50, "return_full_text": False }} response = requests.post(API_URL, headers=headers, json=json_) output = response.json() print(f"If there was an error? Reason is : {output}") output_tmp = output[0]['generated_text'] print(f"GPTJ response without splits is: {output_tmp}") #poem = output[0]['generated_text'].split("\n\n")[0] # +"." if "\n\n" not in output_tmp: if output_tmp.find('.') != -1: idx = output_tmp.find('.') poem = output_tmp[:idx+1] else: idx = output_tmp.rfind('\n') poem = output_tmp[:idx] else: poem = output_tmp.split("\n\n")[0] # +"." poem = poem.replace('?','') print(f"Poem being returned is: {poem}") return poem def poem_to_image(poem): print("*****Inside Poem_to_image") poem = " ".join(poem.split('\n')) poem = poem + " oil on canvas." steps, width, height, images, diversity = '50','256','256','1',15 img = gr.Interface.load("spaces/multimodalart/latentdiffusion")(poem, steps, width, height, images, diversity)[0] return img demo = gr.Blocks() with demo: gr.Markdown("

Generate Short Poem along with an Illustration

") gr.Markdown( """Enter a single word you would want GPTJ-6B to write Poetry 🎤 on. A Space by [Yuvraj Sharma](https://huggingface.co/ysharma).""" ) gr.Markdown("""
Generate an illustration 🎨 provided by Latent Diffusion model.
GPJ-6B is a 6 Billion parameter autoregressive language model. It generates the Poem based on how it has been 'prompt-engineered' 🤗 The complete text of generated poem then goes in as a prompt to the amazing Latent Diffusion Art space by Multimodalart.
Please note that some of the Poems/Illustrations might not look at par, and well, this is what happens when you can't 'cherry-pick' and post 😁
Some of the example words that you can use are 'river', 'night', 'trees', 'table', 'laughs' or maybe on similar lines to get best results!""" ) with gr.Row(): input_word = gr.Textbox(placeholder="Enter a word here to create a Poem on..") poem_txt = gr.Textbox(lines=7) output_image = gr.Image(type="filepath", shape=(256,256)) b1 = gr.Button("Generate Poem") b2 = gr.Button("Generate Image") b1.click(poem_generate, input_word, poem_txt) b2.click(poem_to_image, poem_txt, output_image) #examples=examples demo.launch(enable_queue=True, debug=True)