import gradio as gr import requests import os ##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. """ def text_generate(prompt, generated_txt): #, input_prompt_sql ): #, input_prompt_dalle2): print(f"*****Inside text_generate - Prompt is :{prompt}") #if input_prompt_sql != '': # prompt = input_prompt_sql #"Instruction: Given an input question, respond with syntactically correct PostgreSQL\nInput: " +input_prompt_sql + "\nPostgreSQL query: " #elif input_prompt_dalle2 !='': # prompt = "Dalle Prompt: " + input_prompt_dalle2 + "\nNew Dalle Prompt: " json_ = {"inputs": prompt, "parameters": { "top_p": 0.9, "temperature": 1.1, "max_new_tokens": 250, "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 #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}") if len(generated_txt) == 0 : display_output = final_solution else: display_output = generated_txt[:-len(prompt)] + final_solution new_prompt = final_solution[len(prompt):] print(f"new prompt for next cycle is : {new_prompt}") print(f"display_output for printing on screen is : {display_output}") if len(new_prompt) == 0: temp_text = display_output[::-1] if temp_text[0] == '.': first_period_loc = temp_text[1:].find('.') new_prompt = display_output[-first_period_loc:] print(f"Not sending blank as prompt so new prompt for next cycle is : {new_prompt}") else: first_period_loc = temp_text.find('.') new_prompt = display_output[-first_period_loc:] print(f"Not sending blank as prompt so new prompt for next cycle is : {new_prompt}") return display_output, new_prompt #generated_txt+prompt #final_solution demo = gr.Blocks() with demo: gr.Markdown("