ai-mysql-translator

Overview

A package enables AI systems to securely interact with MySQL databases by translating natural language queries into structured SQL commands. It processes user text input to generate safe, validated database operations, ensuring responses are consistent and free from injection risks. This allows AI assistants to perform data retrieval and manipulation without exposing sensitive database structures or requiring manual query writing.

Installation

pip install ai_mysql_translator

Usage

from ai_mysql_translator import ai_mysql_translator
user_input: str
api_key: Optional[str] = None
llm: Optional[BaseChatModel] = None

response = ai_mysql_translator(
    user_input, 
    api_key=api_key, 
    llm=llm 
)

You can safely pass your own llm instance (based on https://docs.langchain.com/) if you prefer to use a different LLM. For example, to use the OpenAI LLM, you can use:

from langchain_openai import ChatOpenAI
import ai_mysql_translator

llm = ChatOpenAI()
response = ai_mysql_translator(
    user_input,
    llm=llm
)

Or to use the Anthropic LLM, you can use:

from langchain_anthropic import ChatAnthropic
import ai_mysql_translator

llm = ChatAnthropic()
response = ai_mysql_translator(
    user_input,
    llm=llm
)

Or Google Generative AI LLM, use:

from langchain_google_genai import ChatGoogleGenerativeAI
import ai_mysql_translator

llm = ChatGoogleGenerativeAI()
response = ai_mysql_translator(
    user_input,
    llm=llm
)

The package uses the ChatLLM7 from langchain_llm7 (https://pypi.org/project/langchain-llm7/) by default.

If you need higher rate limits for LLM7, you can pass your own API key via environment variable LLM7_API_KEY or directly via api_key. You can obtain a free API key by registering at https://token.llm7.io/.

GitHub

• Project Repository: https://github.com/chigwell/ai-mysql-translator
• Issues: https://github.com/chigwell/ai-mysql-translator/issues

Author

• Eugene Evstafev - hi@eugevev.plus