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 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] print(f"What is the last character of sentence? : {temp_text[0]}") if temp_text[1] == '.': first_period_loc = temp_text[2:].find('.') + 1 print(f"Location of last Period is: {first_period_loc}") new_prompt = display_output[-first_period_loc:-1] print(f"Not sending blank as prompt so new prompt for next cycle is : {new_prompt}") else: print("HERE") first_period_loc = temp_text.find('.') print(f"Location of last Period is : {first_period_loc}") new_prompt = display_output[-first_period_loc:-1] print(f"Not sending blank as prompt so new prompt for next cycle is : {new_prompt}") display_output = display_output[:-1] return display_output, new_prompt #generated_txt+prompt #final_solution demo = gr.Blocks() with demo: gr.Markdown("

Bloom

") gr.Markdown( """Testing Bloom for SQL generation """ ) 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(): 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 Text") #b2 = gr.Button("Generate Image") b1.click(text_generate, inputs=[input_prompt, generated_txt], outputs=[generated_txt, input_prompt]) #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)