├── .env.example ├── .gitignore ├── LICENSE ├── README.md ├── app.py ├── cli.py ├── docs └── demo.gif ├── prompts ├── graph.txt ├── idk.txt └── sql.txt ├── requirement.txt ├── schema.py └── tpl └── index.html /.env.example: -------------------------------------------------------------------------------- 1 | APP_PORT=5000 2 | DATABASE_URL=postgres://postgres:postgres@localhost:5432/postgres 3 | OPENAI_TOKEN=sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | .env 2 | __pycache__ 3 | .venv -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 3, 29 June 2007 3 | 4 | Copyright (C) 2007 Free Software Foundation, Inc. 5 | Everyone is permitted to copy and distribute verbatim copies 6 | of this license document, but changing it is not allowed. 7 | 8 | Preamble 9 | 10 | The GNU General Public License is a free, copyleft license for 11 | software and other kinds of works. 12 | 13 | The licenses for most software and other practical works are designed 14 | to take away your freedom to share and change the works. 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Interpretation of Sections 15 and 16. 613 | 614 | If the disclaimer of warranty and limitation of liability provided 615 | above cannot be given local legal effect according to their terms, 616 | reviewing courts shall apply local law that most closely approximates 617 | an absolute waiver of all civil liability in connection with the 618 | Program, unless a warranty or assumption of liability accompanies a 619 | copy of the Program in return for a fee. 620 | 621 | END OF TERMS AND CONDITIONS 622 | 623 | How to Apply These Terms to Your New Programs 624 | 625 | If you develop a new program, and you want it to be of the greatest 626 | possible use to the public, the best way to achieve this is to make it 627 | free software which everyone can redistribute and change under these terms. 628 | 629 | To do so, attach the following notices to the program. It is safest 630 | to attach them to the start of each source file to most effectively 631 | state the exclusion of warranty; and each file should have at least 632 | the "copyright" line and a pointer to where the full notice is found. 633 | 634 | 635 | Copyright (C) 636 | 637 | This program is free software: you can redistribute it and/or modify 638 | it under the terms of the GNU General Public License as published by 639 | the Free Software Foundation, either version 3 of the License, or 640 | (at your option) any later version. 641 | 642 | This program is distributed in the hope that it will be useful, 643 | but WITHOUT ANY WARRANTY; without even the implied warranty of 644 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 645 | GNU General Public License for more details. 646 | 647 | You should have received a copy of the GNU General Public License 648 | along with this program. If not, see . 649 | 650 | Also add information on how to contact you by electronic and paper mail. 651 | 652 | If the program does terminal interaction, make it output a short 653 | notice like this when it starts in an interactive mode: 654 | 655 | Copyright (C) 656 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. 657 | This is free software, and you are welcome to redistribute it 658 | under certain conditions; type `show c' for details. 659 | 660 | The hypothetical commands `show w' and `show c' should show the appropriate 661 | parts of the General Public License. Of course, your program's commands 662 | might be different; for a GUI interface, you would use an "about box". 663 | 664 | You should also get your employer (if you work as a programmer) or school, 665 | if any, to sign a "copyright disclaimer" for the program, if necessary. 666 | For more information on this, and how to apply and follow the GNU GPL, see 667 | . 668 | 669 | The GNU General Public License does not permit incorporating your program 670 | into proprietary programs. If your program is a subroutine library, you 671 | may consider it more useful to permit linking proprietary applications with 672 | the library. If this is what you want to do, use the GNU Lesser General 673 | Public License instead of this License. But first, please read 674 | . 675 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # GPT-3 SQL Query Generator and UI (And AI Chart Generator) 2 | 3 | This is simple python application to generate SQL Schema + prompt to ask GPT-3 to generate SQL queries. 4 | 5 | It also has a simple UI to show results in a table. And yes, **you can try to generate a chart from the results of query**. 6 | 7 | GPT-3 self choose the chart type and prepare the data for it (it is not perfect, but it is a good start). 8 | 9 | **It can generate a prompt for you, if you don't know what to ask GPT-3.** 10 | 11 | ![](https://github.com/Hormold/gpt-sql-box/blob/master/docs/demo.gif?raw=true) 12 | 13 | 14 | ## How it works: 15 | 1. Getting SQL schemas from PostgreSQL and compile prompt from SQL Schema 16 | 3. Wait for user input 17 | 4. Generate SQL query from prompt + user input 18 | 5. Show SQL query and ask user to confirm or edit if it is correct before executing it 19 | 6. Execute SQL query and show results in a table 20 | 21 | ## Environment 22 | - DATABASE_URL: PostgreSQL database URL 23 | - OPENAI_TOKEN: OpenAI API token (Not nessessary, you can set it in the UI) 24 | - APP_PORT: Port to run the application (default: 5000) 25 | - OPENAI_ENGINE: OpenAI engine to use (default: text-davinci-003, not nessessary). You can set some free to use model: text-chat-davinci-002-20221122 26 | 27 | ## How to run 28 | 1. It better to create a virtual environment using `python3 -m venv venv` 29 | 2. Install dependencies using `pip install -r requirements.txt` 30 | 3. Set environment variables in `.env` file in project root or in your system 31 | 4. Run the application using `python app.py` and open `http://localhost:5000` in your browser 32 | 33 | ## Contact 34 | If you have any questions, please contact me at [@define](https://t.me/define) in Telegram. 35 | -------------------------------------------------------------------------------- /app.py: -------------------------------------------------------------------------------- 1 | """Web app to generate SQL queries from user input using GPT-3""" 2 | import os 3 | import json 4 | import sys 5 | import time 6 | import psycopg2 7 | import openai 8 | from dotenv import load_dotenv 9 | from flask import Flask, request, render_template 10 | from schema import Schema 11 | 12 | app = Flask(__name__, template_folder='tpl') 13 | # Read .env file 14 | load_dotenv() 15 | OPENAI_ENGINE = os.getenv('OPENAI_ENGINE') or 'text-davinci-003' 16 | TEMPLATE_DIR = os.path.abspath('./tpl') 17 | PROMPT_DIR = os.path.abspath('./prompts') 18 | APP_PORT = os.getenv('APP_PORT') or 5000 19 | DATABASE_URL = os.getenv('DATABASE_URL') 20 | if not DATABASE_URL: 21 | print('Please set DATABASE_URL in .env file.') 22 | sys.exit(1) 23 | 24 | if os.getenv('OPENAI_TOKEN'): 25 | openai.api_key = os.getenv('OPENAI_TOKEN') 26 | 27 | if not openai.api_key: 28 | print('Please set OPENAI_TOKEN in .env file or set token in UI') # Not a critical error 29 | 30 | # Generate SQL Schema from PostgreSQL 31 | schema = Schema() 32 | sql_schema, json_data = schema.index() 33 | print('SQL data was generated successfully.') 34 | 35 | def load_prompt(name: str) -> str: 36 | """Load prompt from file""" 37 | with open(os.path.join(PROMPT_DIR, name + ".txt"), 'r', encoding='utf-8') as file: 38 | return file.read() 39 | 40 | # Middleware to check key in request or in .env file 41 | @app.before_request 42 | def get_key(): 43 | """Get API key from request or .env file""" 44 | if (request.content_type != 'application/json' 45 | or request.method != 'POST' 46 | or request.path == '/run'): 47 | return 48 | content = request.json 49 | if not content['api_key'] and not openai.api_key: 50 | return { 51 | 'success': False, 52 | 'error': 'Please set OPENAI_TOKEN in .env file or set token in UI' 53 | } 54 | 55 | if content and content['api_key']: 56 | request.api_key = content['api_key'] 57 | else: 58 | request.api_key = os.getenv('OPENAI_TOKEN') 59 | 60 | @app.get('/') 61 | def index(): 62 | """Show SQL Schema + prompt to ask GPT-3 to generate SQL queries""" 63 | normalized_json_data = json.dumps(json_data) 64 | return render_template( 65 | 'index.html', 66 | has_openai_key=bool(openai.api_key), 67 | sql_schema=sql_schema, 68 | json_data=normalized_json_data 69 | ) 70 | 71 | @app.post('/generate') 72 | def generate(): 73 | """Generate SQL query from prompt + user input""" 74 | try: 75 | content = request.json 76 | user_input = content['query'] 77 | query_temperture = content['temp'] 78 | selected = content['selected'] 79 | print('Selected tables:', selected) 80 | print('User input:', user_input) 81 | print('Query temperture:', query_temperture) 82 | 83 | openai.api_key = request.api_key 84 | regen_schema = schema.regen(selected) 85 | fprompt = load_prompt('sql').replace('{regen_schema}', regen_schema).replace('{user_input}', user_input) 86 | # Edit prompt on the fly by editing prompts/sql.txt 87 | print(f'Final prompt: {fprompt}') 88 | 89 | # Ask GPT-3 90 | gpt_response = openai.Completion.create( 91 | engine=OPENAI_ENGINE, 92 | prompt=fprompt, 93 | temperature=float(query_temperture), 94 | max_tokens=500, 95 | top_p=1, 96 | frequency_penalty=0, 97 | presence_penalty=0, 98 | stop=["\n\n"] 99 | ) 100 | 101 | used_tokens = gpt_response['usage']['total_tokens'] 102 | 103 | # Get SQL query 104 | sql_query = gpt_response['choices'][0]['text'] 105 | sql_query = sql_query.lstrip().rstrip() 106 | print('Generated SQL query:', sql_query) 107 | 108 | # Return json 109 | return { 110 | 'success': True, 111 | 'sql_query': sql_query, 112 | 'used_tokens': used_tokens, 113 | } 114 | except Exception as err: 115 | print(err) 116 | return { 117 | 'success': False, 118 | 'error': str(err) 119 | } 120 | 121 | @app.post('/run') 122 | def execute(): 123 | """Execute SQL query and show results in a table""" 124 | # Get SQL query 125 | try: 126 | ts_start = time.time() 127 | content = request.json 128 | sql_query = content['query'] 129 | print('Run SQL query:', sql_query) 130 | 131 | # Execute SQL query and show results in a table 132 | conn = psycopg2.connect(DATABASE_URL) 133 | cur = conn.cursor() 134 | cur.execute(sql_query) 135 | results = cur.fetchall() 136 | 137 | # Return json with all columns names and results 138 | columns = [desc[0] for desc in cur.description] 139 | results = [dict(zip(columns, row)) for row in results] 140 | seconds_elapsed = time.time() - ts_start 141 | return { 142 | 'success': True, 143 | 'columns': columns, 144 | 'results': results, 145 | 'seconds_elapsed': seconds_elapsed 146 | } 147 | except psycopg2.Error as err: 148 | print(err) 149 | return { 150 | 'success': False, 151 | 'error': str(err) 152 | } 153 | except Exception as err: 154 | print(err) 155 | return { 156 | 'success': False, 157 | 'error': str(err) 158 | } 159 | 160 | @app.post('/generate_prompt') 161 | def generate_prompt(): 162 | """Generate prompt from selected tables""" 163 | try: 164 | content = request.json 165 | selected = content['selected'] 166 | query_temperture = content['temp'] 167 | 168 | openai.api_key = request.api_key 169 | 170 | # Update prompt 171 | regen_schema = schema.regen(selected) 172 | final_prompt = load_prompt('idk').replace('{regen_schema}', regen_schema) 173 | print(f'Final prompt: {final_prompt}') 174 | 175 | gpt_response = openai.Completion.create( 176 | engine=OPENAI_ENGINE, 177 | prompt=final_prompt, 178 | temperature=float(query_temperture), 179 | max_tokens=500, 180 | top_p=1, 181 | frequency_penalty=0, 182 | presence_penalty=0, 183 | stop=["\n\n"] 184 | ) 185 | 186 | used_tokens = gpt_response['usage']['total_tokens'] 187 | 188 | # Get SQL query 189 | query = gpt_response['choices'][0]['text'].lstrip().rstrip() 190 | print('Generated prompt:', query) 191 | 192 | return { 193 | 'success': True, 194 | 'query': query, 195 | 'used_tokens': used_tokens, 196 | } 197 | except Exception as err: 198 | print(err) 199 | return { 200 | 'success': False, 201 | 'error': str(err) 202 | } 203 | 204 | @app.post('/generate_chart') 205 | def generate_chart(): 206 | """Generate chart from SQL query""" 207 | content = request.json 208 | csv_data = str(content['csv_data']) 209 | query_temperture = float(content['temp']) 210 | print('CSV data:', csv_data) 211 | print('Query temperture:', query_temperture) 212 | #chart_type = content['chart_type'] # bar, line, pie, scatter 213 | example_prompt = load_prompt('graph').replace('{csv_data}', csv_data) 214 | 215 | openai.api_key = request.api_key 216 | gpt_response = openai.Completion.create( 217 | engine=OPENAI_ENGINE, 218 | prompt=example_prompt, 219 | temperature=float(query_temperture), 220 | max_tokens=300, 221 | top_p=1, 222 | frequency_penalty=0, 223 | presence_penalty=0, 224 | stop=["\n\n"] 225 | ) 226 | 227 | used_tokens = gpt_response['usage']['total_tokens'] 228 | pseudo_code = gpt_response['choices'][0]['text'].lstrip().rstrip(); 229 | chart_type = pseudo_code.split('|')[0] 230 | chart_data = pseudo_code.split('|')[1] 231 | 232 | return { 233 | 'success': True, 234 | 'chart_type': chart_type, 235 | 'chart_data': chart_data, 236 | 'used_tokens': used_tokens, 237 | } 238 | 239 | # Run web app 240 | if __name__ == '__main__': 241 | app.run(debug=True, port=int(APP_PORT)) 242 | -------------------------------------------------------------------------------- /cli.py: -------------------------------------------------------------------------------- 1 | """CLI for GPT-3 SQL query generator.""" 2 | import sys 3 | import os 4 | import openai 5 | from schema import Schema 6 | from dotenv import load_dotenv 7 | 8 | load_dotenv() 9 | if not os.getenv('OPENAI_TOKEN'): 10 | print('Please set OPENAI_TOKEN in .env file') 11 | sys.exit(1) 12 | 13 | if __name__ == '__main__': 14 | openai.api_key = os.getenv('OPENAI_TOKEN') 15 | schema = Schema() 16 | sql_schema, _ = schema.index() 17 | sql_schema = schema.regen(['users']) # Remove this line to generate schema for all tables 18 | 19 | query_temperture = 0.5 20 | prompt = input('Enter prompt to generate SQL query: ') 21 | final_prompt = f'Given an input question, respond with syntactically correct PostgreSQL. Be creative but the SQL must be correct, not nessesary to use all tables.\n\n{sql_schema}\n\nInstructions: {prompt}\n\nSQL:\n' 22 | 23 | gpt_response = openai.Completion.create( 24 | engine="text-davinci-003", 25 | prompt=final_prompt, 26 | temperature=float(query_temperture), 27 | max_tokens=200, 28 | stop=["\n\n"] 29 | ) 30 | 31 | print(f'GPT-3 response:\n\n{gpt_response["choices"][0]["text"]}') 32 | -------------------------------------------------------------------------------- /docs/demo.gif: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Hormold/gpt-sql-box/38d90b1fb06ae20753d523e3633a615a7b18d397/docs/demo.gif -------------------------------------------------------------------------------- /prompts/graph.txt: -------------------------------------------------------------------------------- 1 | You are chart generator and your task is to generate chart from CSV data. 2 | You need to response with valid code following instructions in format: chart_type|chart_data. 3 | chart_type can be: line, bar, pie, scatter 4 | chart_data is data for chart is only VALID JSON, for example: 5 | Line chart: line|{'2017-01-01': 11, '2017-01-02': 6} 6 | Bar chart: bar|[["0",32],["1",46],["2",28]] 7 | Pie chart: pie|[["Blueberry",44],["Strawberry",23],["Banana",22]] 8 | Scatter chart: scatter|[[174.0, 80.0], [176.5, 82.3], [180.3, 73.6], [167.6, 74.1], [188.0, 85.9]] 9 | 10 | Example valid response: line|{"2021-02-10":11,"2021-02-11":6} 11 | 12 | Here is CSV data, first row is column names, next rows are data: 13 | {csv_data} 14 | 15 | Response: -------------------------------------------------------------------------------- /prompts/idk.txt: -------------------------------------------------------------------------------- 1 | Your task is create creative prompt, using this scheme of database: {regen_schema} 2 | Generate a prompt for database data extract, not project description. 3 | Do not generate SQL query, generate text based prompt. 4 | Result: -------------------------------------------------------------------------------- /prompts/sql.txt: -------------------------------------------------------------------------------- 1 | Given an input question, respond with syntactically correct PostgreSQL. Be creative but the SQL must be correct, not nessesary to use all tables. {regen_schema} 2 | 3 | Instructions: {user_input} 4 | 5 | SQL: -------------------------------------------------------------------------------- /requirement.txt: -------------------------------------------------------------------------------- 1 | psycopg2 2 | flask 3 | openai 4 | dotenv -------------------------------------------------------------------------------- /schema.py: -------------------------------------------------------------------------------- 1 | """Generate SQL Schema from PostgreSQL""" 2 | import os 3 | import sys 4 | from dotenv import load_dotenv 5 | import psycopg2 6 | 7 | # Read .env file 8 | load_dotenv() 9 | 10 | DATABASE_URL = os.getenv('DATABASE_URL') 11 | 12 | class Schema: 13 | """Generate SQL Schema from PostgreSQL""" 14 | 15 | def __init__(self, schema = 'public'): 16 | """Connect to PostgreSQL database""" 17 | self.schema = schema 18 | try: 19 | self.conn = psycopg2.connect(DATABASE_URL) 20 | except psycopg2.OperationalError as err: 21 | print(f'Unable to connect!\n{err}') 22 | sys.exit(1) 23 | else: 24 | print('Connected to PostgreSQL database successfully.') 25 | self.cur = self.conn.cursor() 26 | self.comments = [] 27 | self.tables = [] 28 | self.columns = [] 29 | 30 | def get_tables(self): 31 | """Get list of tables""" 32 | self.cur.execute("SELECT table_name FROM information_schema.tables WHERE table_schema = %s", (self.schema,)) 33 | tables = self.cur.fetchall() 34 | self.tables = tables 35 | return tables 36 | 37 | def get_all_comments(self): 38 | """Get list of all comments""" 39 | self.cur.execute('select c.table_schema, c.table_name, c.column_name, pgd.description from pg_catalog.pg_statio_all_tables as st inner join pg_catalog.pg_description pgd on (pgd.objoid = st.relid) inner join information_schema.columns c on (pgd.objsubid = c.ordinal_position and c.table_schema = st.schemaname and c.table_name = st.relname);') 40 | comments = self.cur.fetchall() 41 | self.comments = comments 42 | return comments 43 | 44 | def get_columns(self, table): 45 | """Get list of columns for a table""" 46 | self.cur.execute("SELECT column_name, data_type FROM information_schema.columns WHERE table_schema = %s AND table_name = %s", (self.schema, table)) 47 | columns = self.cur.fetchall() 48 | return columns 49 | 50 | def regen(self, selected): 51 | """Regenerate SQL Schema only for selected tables""" 52 | if len(selected) == 0: 53 | return 'No tables selected.' 54 | prompt = '' 55 | tables = self.tables 56 | comments = self.comments 57 | for table in tables: 58 | if table[0] in selected: 59 | columns = self.get_columns(table[0]) 60 | prompt += f'The "{table[0]}" table has columns: ' 61 | for column in columns: 62 | cmnt = '' 63 | for comment in comments: 64 | if comment[0] == self.schema and comment[1] == table[0] and comment[2] == column[0]: 65 | cmnt = comment[3] 66 | break 67 | if cmnt == '': 68 | prompt += f'{column[0]} ({column[1]}), ' 69 | else: 70 | prompt += f'{column[0]} ({column[1]} - {cmnt}), ' 71 | prompt = prompt[:-2] + '. ' 72 | return prompt 73 | 74 | def index(self): 75 | """Generate SQL Schema""" 76 | prompt = '' 77 | json_data = {} 78 | tables = self.get_tables() 79 | comments = self.get_all_comments() 80 | for table in tables: 81 | columns = self.get_columns(table[0]) 82 | prompt += f'The "{table[0]}" table has columns: ' 83 | json_data[table[0]] = [] 84 | for column in columns: 85 | cmnt = '' 86 | for comment in comments: 87 | if comment[0] == self.schema and comment[1] == table[0] and comment[2] == column[0]: 88 | cmnt = comment[3] 89 | break 90 | if cmnt == '': 91 | prompt += f'{column[0]} ({column[1]}), ' 92 | else: 93 | prompt += f'{column[0]} ({column[1]} - {cmnt}), ' 94 | json_data[table[0]].append({ 95 | 'name': column[0], 96 | 'type': column[1], 97 | 'comment': cmnt, 98 | "seleted": True 99 | }) 100 | prompt = prompt[:-2] + '. ' 101 | return prompt, json_data 102 | -------------------------------------------------------------------------------- /tpl/index.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | GPT SQL Query 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 30 | 31 | 32 | 33 | 34 | 35 | 36 | 37 |
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Chart generated by GPT-3

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Set OpenAI Token

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Looks like API token is not set in environment variable. Please enter your OpenAI API token below and it will be saved to browser localStorage

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105 | You can get your OpenAI API token here. 106 |
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GPT SQL Query: Configuation

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SQL Strucutre (select tables to use to generate query):

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175 | Adjusting OpenAI temperature will change the randomness of the generated 176 | query. Higher temperature will generate more random queries, while lower temperature will 177 | generate more predictable queries. Using the huge number of tables can increase the cost of query. 178 |
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Approve generate SQL query

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232 | Disclaimer: SQL is generated by OpenAI GPT-3. Please review the 233 | query before running. Query can be invalid. 234 |
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Results of SQL query

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Used SQL query: 279 | 280 | [[sql_query]] 281 | 282 |

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Execution time: [[seconds_elapsed]] seconds

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