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, input_prompt_sql, input_prompt_dalle2): print(f"*****Inside poem_generate - Prompt is :{prompt}") if input_prompt_sql != '': prompt = "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": False, }, "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}") output_tmp = output[0]['generated_text'] print(f"output_tmp is: {output_tmp}") solution = output_tmp.split("\nQ:")[0] #output[0]['generated_text'].split("Q:")[0] # +"." print(f"Final response after splits is: {solution}") final_solution = solution.split("\nOutput:")[0] print(f"Response after removing output is: {final_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}") return final_solution #solution #output #response #output_tmp #poem 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. 'employees' table columns are: emp_id (integer), emp_name (character varying), mgr_id (integer), hire_dt (timestamp), dept_id (character varying), and sal (integer). \nInput: What is total salary paid to employees?\nPostgreSQL query: ", "Instruction: Given an input question, respond with syntactically correct PostgreSQL. Only use tables called 'employees'.\nInput: List name of all the employees whose name ends with 'r'?\nPostgreSQL query: ", "Instruction: Given an input question, respond with syntactically correct PostgreSQL. Only use tables called 'employees' and 'department'.\nInput: What is 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 the name of the employees whose name's 3rd charactor is 't'.\nPostgreSQL query: ", "Instruction: Given an input question, respond with syntactically correct PostgreSQL. Only use table called 'employees'.\nInput: Select the name of all the employee 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") input_prompt_sql = gr.Textbox(label="Or Write text to get SQL commands...") input_prompt_dalle2 = gr.Textbox(label="Or Write sample Dalle2 prompts to get more Prompt ideas...") #input_word = gr.Textbox(placeholder="Enter a word here to generate text ...") generated_txt = gr.Textbox(lines=7) #output_image = gr.Image(type="filepath", shape=(256,256)) b1 = gr.Button("Generate SQL") #b2 = gr.Button("Generate Image") b1.click(text_generate,inputs=[example_prompt, input_prompt_sql, input_prompt_dalle2], outputs=generated_txt) #input_word #b2.click(poem_to_image, poem_txt, output_image) #examples=examples demo.launch(enable_queue=True, debug=True)