text2design 2025.12.21154002

A new package that enables users to input textual descriptions of visual design, layout, or interface concepts and returns structured representations or annotations derived from the description. It le

text2design

A package for converting textual descriptions of visual design, layout, or interface concepts to structured representations or annotations.

Overview

This package enables users to input textual descriptions of visual design, layout, or interface concepts and returns structured representations or annotations derived from the description. It leverages language model interactions coupled with pattern matching to extract key elements such as components, relationships, and attributes, facilitating tasks like generating structured design tokens, verifying design specifications, or creating markup descriptions.

Installation

pip install text2design

Usage

from text2design import text2design

response = text2design(user_input="a description of the design")

You can also use a langchain LLM instance instead of the default ChatLLM7 instance:

from langchain_openai import ChatOpenAI
from text2design import text2design

llm = ChatOpenAI()
response = text2design(user_input="a description of the design", llm=llm)

Input Parameters

• user_input: str, the user input text to process
• llm: Optional[BaseChatModel], the langchain LLM instance to use, defaults to ChatLLM7
• api_key: Optional[str], the api key for LLM7, can be set via environment variable LLM7_API_KEY or passed directly

Supported LLMs

This package uses ChatLLM7 from langchain_llm7 by default. You can pass your own LLM instance, for example:

• OpenAI:

from langchain_openai import ChatOpenAI
from text2design import text2design

llm = ChatOpenAI()
response = text2design(user_input, llm=llm)

• Anthropic:

from langchain_anthropic import ChatAnthropic
from text2design import text2design

llm = ChatAnthropic()
response = text2design(user_input, llm=llm)

• Google Generative AI:

from langchain_google_genai import ChatGoogleGenerativeAI
from text2design import text2design

llm = ChatGoogleGenerativeAI()
response = text2design(user_input, llm=llm)

API Key and Rate Limits

The default free tier for LLM7 is sufficient for most use cases. For higher rate limits:

• Set your API key via environment variable LLM7_API_KEY
• Or pass it directly: text2design(user_input, api_key="your_api_key")

You can register for a free API key at https://token.llm7.io/.

Support and Issues

For issues or feature requests, please visit: https://github....

Author

• Eugene Evstafev ([e-mail])
• GitHub: chigwell