import gradio as gr import requests import os import PIL from PIL import Image from PIL import ImageDraw from PIL import ImageFont ##Bloom API_URL = "https://api-inference.huggingface.co/models/bigscience/bloom" HF_TOKEN = os.environ["HF_TOKEN"] headers = {"Authorization": f"Bearer {HF_TOKEN}"} prompt1 = """ 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: """ prompt2 = """ Q: Joy has 5 balls. He buys 2 more cans of balls. Each can has 3 balls. How many balls he has now? A: Joy had 5 balls. 2 cans of 3 balls each is 6 balls. 5 + 6 = 11. Answer is 11. Q: Jane has 16 balls. Half balls are golf balls, and half golf balls are red. How many red golf balls are there? A: """ prompt3 = """Q: A juggler can juggle 16 balls. Half of the balls are golf balls, and half of the golf balls are blue. How many blue golf balls are there? A: Let’s think step by step. """ #Complete below sentence in fun way. prompt = """Distracted from: hubble by: james webb Distracted from: homework by: side project Distracted from: goals by: new goals Distracted from: """ def write_on_image(final_solution): print("************ Inside write_on_image ***********") image_path0 = "./distracted0.jpg" image0 = Image.open(image_path0) I1 = ImageDraw.Draw(image0) myfont = ImageFont.truetype('./font1.ttf', 30) I1.text((613, 89), "girlfriend",font=myfont, fill =(255, 255, 255)) I1.text((371, 223), "ME", font=myfont, fill =(255, 255, 255)) I1.text((142, 336), "new girl",font=myfont, fill =(255, 255, 255)) return image0 def meme_generate(img): #prompt, generated_txt): #, input_prompt_sql ): #, input_prompt_dalle2): print(f"*****Inside meme_generate - Prompt is :{prompt}") json_ = {"inputs": prompt, "parameters": { #"top_p": 0.95, "top_p": 0.90, #"top_k":0, "max_new_tokens": 250, "temperature": 1.1, #"num_return_sequences": 3, "return_full_text": True, "do_sample": True, }, "options": {"use_cache": True, "wait_for_model": True, },} response = requests.post(API_URL, headers=headers, json=json_) print(f"Response is : {response}") output = response.json() print(f"output is : {output}") output_tmp = output[0]['generated_text'] print(f"output_tmp is: {output_tmp}") solution = output_tmp.split("\nQ:")[0] print(f"Final response after splits is: {solution}") if '\nOutput:' in solution: final_solution = solution.split("\nOutput:")[0] print(f"Response after removing output is: {final_solution}") elif '\n\n' in solution: final_solution = solution.split("\n\n")[0] print(f"Response after removing new line entries is: {final_solution}") else: final_solution = solution meme_image = write_on_image(final_solution) return meme_image #final_solution #display_output, new_prompt #generated_txt+prompt demo = gr.Blocks() with demo: gr.Markdown("

Testing

") gr.Markdown( """Work In Progress""" ) with gr.Row(): #example_prompt = gr.Radio( ["Q: A juggler can juggle 16 balls. Half of the balls are golf balls, and half of the golf balls are blue. How many blue golf balls are there?\nA: Let’s think step by step.\n"], label= "Choose a sample Prompt") #example_prompt = gr.Radio( [ #"Instruction: Given an input question, respond with syntactically correct PostgreSQL\nInput: How many users signed up in the past month?\nPostgreSQL query: ", #"Instruction: Given an input question, respond with syntactically correct PostgreSQL\nInput: Create a query that displays empfname, emplname, deptid, deptname, location from employee table. Results should be in the ascending order based on the empfname and location.\nPostgreSQL query: ", #"Instruction: Given an input question, respond with syntactically correct PostgreSQL. Only use tables called 'employees'.\nInput: What is the total salary paid to all the employees?\nPostgreSQL query: ", #"Instruction: Given an input question, respond with syntactically correct PostgreSQL. Only use tables called 'employees'.\nInput: List names of all the employees whose name end with 'r'.\nPostgreSQL query: ", #"Instruction: Given an input question, respond with syntactically correct PostgreSQL. Only use tables called 'employees'.\nInput: What are the number of employees in each department?\nPostgreSQL query: ", #"Instruction: Given an input question, respond with syntactically correct PostgreSQL. Only use table called 'employees'.\nInput: Select names of all theemployees who have third character in their name as 't'.\nPostgreSQL query: ", #"Instruction: Given an input question, respond with syntactically correct PostgreSQL. Only use table called 'employees'.\nInput: Select names of all the employees who are working under 'Peter'\nPostgreSQL query: ", ], label= "Choose a sample Prompt") #"Dalle Prompt: Cyberwave vaporpunk art of a kneeling figure, looking up at a glowing neon book icon, smoke and mist, pink and blue lighting, cybernetic sci-fi render\nNew Dalle Prompt: " ], label= "Choose a sample Prompt") #with gr.Row(): in_image = gr.Image(value="./distracted0.jpg") #input_prompt = gr.Textbox(label="Write some text to get started...", lines=3) #input_prompt_sql #input_prompt_dalle2 = gr.Textbox(label="Or Write sample Dalle2 prompts to get more Prompt ideas...") #input_prompt2 = gr.Textbox(label="Write some text to get started...", lines=3, visible=False) #input_prompt_sql #input_word = gr.Textbox(placeholder="Enter a word here to generate text ...") #with gr.Row(): #generated_txt = gr.Textbox(lines=7, visible = True) output_image = gr.Image() #type="filepath", shape=(256,256)) b1 = gr.Button("Generate") #b2 = gr.Button("Generate Image") b1.click(meme_generate, inputs=in_image, outputs=output_image) #input_word #input_prompt_dalle2 #input_prompt_sql #example_prompt #b2.click(poem_to_image, poem_txt, output_image) #examples=examples demo.launch(enable_queue=True, debug=True)