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A new package that allows users to write SQL queries using a simplified, Tailwind CSS-like syntax. It takes natural language or abbreviated input from the user and converts it into valid, structured S

Project description

Tailwind-SQL

PyPI version License: MIT Downloads LinkedIn

Write SQL queries with Tailwind CSS-like simplicity

Tailwind-SQL lets you generate SQL queries using a natural language or utility-first approach inspired by Tailwind CSS. Perfect for developers and analysts who want to write database queries intuitively without deep SQL expertise.


🚀 Features

  • Utility-first SQL: Write queries using a simplified, intuitive syntax
  • LLM-powered: Uses advanced language models to convert natural language into valid SQL
  • Flexible: Works with any LangChain-compatible LLM (default: LLM7)
  • Type-safe: Returns structured SQL output ready for execution

📦 Installation

pip install tailwind_sql

🔧 Usage

Basic Usage (with default LLM7)

from tailwind_sql import tailwind_sql

# Simple query generation
response = tailwind_sql("Show me all users from New York with active status")
print(response)

Custom LLM Integration

You can use any LangChain-compatible LLM by passing it as the llm parameter:

With OpenAI

from langchain_openai import ChatOpenAI
from tailwind_sql import tailwind_sql

llm = ChatOpenAI()
response = tailwind_sql("Select top 10 customers ordered by purchase amount", llm=llm)

With Anthropic

from langchain_anthropic import ChatAnthropic
from tailwind_sql import tailwind_sql

llm = ChatAnthropic()
response = tailwind_sql("Find all inactive users from last quarter", llm=llm)

With Google Generative AI

from langchain_google_genai import ChatGoogleGenerativeAI
from tailwind_sql import tailwind_sql

llm = ChatGoogleGenerativeAI()
response = tailwind_sql("Calculate monthly revenue by product category", llm=llm)

🔑 API Key Configuration

Default (LLM7)

  • Uses LLM7's free tier by default
  • API key can be set via environment variable:
    export LLM7_API_KEY="your_api_key"
    
  • Or passed directly:
    from tailwind_sql import tailwind_sql
    response = tailwind_sql("Query example", api_key="your_api_key")
    

Custom LLM

For other LLMs, simply pass your configured LLM instance as shown in the examples above.


📝 Input Parameters

Parameter Type Description
user_input str The natural language or utility-style query input
llm Optional[BaseChatModel] Custom LangChain LLM instance (optional)
api_key Optional[str] LLM7 API key (optional, defaults to environment variable)

📊 Example Queries

Natural Language Input

tailwind_sql("Find all customers who made purchases over $1000 in 2023")

Utility-Style Input (Tailwind-like)

tailwind_sql("select * from users where status='active' and location='New York' order by created_at desc limit 100")

🔄 Rate Limits

  • LLM7 Free Tier: Sufficient for most use cases
  • Custom LLM: No rate limits (depends on your provider)
  • Upgrade: For higher LLM7 limits, pass your own API key

📜 License

MIT


📢 Support & Issues

For support or to report issues, please open a GitHub issue: https://github.com/chigwell/tailwind-sql/issues


👤 Author

Eugene Evstafev 📧 hi@euegne.plus 🔗 @chigwell


📚 Related Projects

  • LLM7 - Default LLM provider
  • LangChain - Framework for LLM integration
  • Tailwind CSS - Inspiration for utility-first approach

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