# import gradio as gr # import requests # import os # ##Bloom # API_URL = "https://api-inference.huggingface.co/models/bigscience/bloom" # HF_TOKEN = "Bloom_Token" # headers = {"Authorization": f"Bearer {HF_TOKEN}"} # def sql_generate(prompt, input_prompt_sql ): # print(f"*****Inside SQL_generate - Prompt is :{prompt}") # print(f"length of input_prompt_sql is {len(input_prompt_sql)}") # print(f"length of prompt is {len(prompt)}") # if len(prompt) == 0: # prompt = input_prompt_sql # json_ = {"inputs": prompt, # "parameters": # { # "top_p": 0.9, # "temperature": 1.1, # "max_new_tokens": 64, # "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_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 # return final_solution # demo = gr.Blocks() # with demo: # gr.Markdown("

Zero Shot SQL by Bloom

") # gr.Markdown( # """[BigScienceW Bloom](https://twitter.com/BigscienceW) \n\n Large language models have demonstrated a capability of Zero-Shot SQL generation. Some might say — You can get good results out of LLMs if you know how to speak to them. This space is an attempt at inspecting this behavior/capability in the new HuggingFace BigScienceW [Bloom](https://huggingface.co/bigscience/bloom) model.\n\nThe Prompt length is limited at the API end right now, thus there is a certain limitation in testing Bloom's capability thoroughly.This Space might sometime fail due to inference queue being full and logs would end up showing error as *'queue full, try again later'*, in such cases please try again after few minutes. Please note that, longer prompts might not work as well and the Space could error out with Response code [500] or *'A very long prompt, temporarily not accepting these'* message in the logs. Still iterating over the app, might be able to improve it further soon.. \n\nThis Space is created by [Yuvraj Sharma](https://twitter.com/yvrjsharma) for Gradio EuroPython 2022 Demo.""" # ) # with gr.Row(): # 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 table 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 table 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 table 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") # #with gr.Column: # input_prompt_sql = gr.Textbox(label="Or Write text following the example pattern given below, to get SQL commands...", value="Instruction: Given an input question, respond with syntactically correct PostgreSQL. Use table called 'department'.\nInput: Select names of all the departments in their descending alphabetical order.\nPostgreSQL query: ", lines=6) # with gr.Row(): # generated_txt = gr.Textbox(lines=3) # b1 = gr.Button("Generate SQL") # b1.click(sql_generate,inputs=[example_prompt, input_prompt_sql], outputs=generated_txt) # with gr.Row(): # gr.Markdown("![visitor badge](https://visitor-badge.glitch.me/badge?page_id=europython2022_zero-shot-sql-by-bloom)") # demo.launch(enable_queue=True, debug=True) import gradio as gr gr.Interface.load("models/bigscience/bloom").launch()