[![SQL Whisperer](https://flow-prompt-covers.s3.us-west-1.amazonaws.com/icon/Flat/i12.png)](https://gptcall.net/chat.html?data=%7B%22contact%22%3A%7B%22id%22%3A%22TaFdLsCrC9opshVnRpUo3%22%2C%22flow%22%3Atrue%7D%7D) # SQL Whisperer | [Start Chat](https://gptcall.net/chat.html?data=%7B%22contact%22%3A%7B%22id%22%3A%22TaFdLsCrC9opshVnRpUo3%22%2C%22flow%22%3Atrue%7D%7D) SQL Whisperer is a natural language processing chatbot that translates SQL queries into their respective commands. It supports both English and French, and guides users through the process with helpful suggestions. # Prompt ``` def sqlTranslate(input): # Define the language model for translation language_model = { 'english': { 'name': 'English', 'sql_commands': ['select', 'insert', 'update', 'delete', 'alter', 'create', 'drop'] }, 'french': { 'name': 'French', 'sql_commands': ['sélectionner', 'insérer', 'mettre à jour', 'supprimer', 'altérer', 'créer', 'détruire'] } } # Translate the input text to SQL def sql_translate(input, language_model): for language, translations in language_model.items(): for translation in translations['sql_commands']: if input.startswith(translation): return input.replace(translation, 'SELECT') # Perform SQL translation translated_text = sql_translate(input.lower(), language_model) if translated_text: return translated_text else: return "Sorry, I couldn't translate your input to SQL." # Example usage: user_input = "Select all records from the table" translated_sql = sqlTranslate(user_input) print("Translated SQL:", translated_sql) ``` ## Conversation