preact-codegen 2025.12.21144856

A new package that helps developers quickly set up Preact applications without needing a complex build configuration. Users can describe their application requirements in plain text, including desired

Preact Codegen

Overview

Preact Codegen is a package that helps developers quickly set up Preact applications without needing a complex build configuration. Users can describe their application requirements in plain text, including desired routing and signal management features. The package processes this input to generate a structured, ready-to-use Preact application code snippet.

Key Features

• Generate Preact application code from user input in plain text
• Supports routing and signal management features
• Easy to integrate and expand
• Simple and fast setup

Installation

pip install preact_codegen

Usage

from preact_codegen import preact_codegen

user_input = "Describe your Preact application requirements here..."
api_key = "your_api_key_here"  # Optional, if not provided, the default LLM7 will be used

response = preact_codegen(
    user_input=user_input,
    api_key=api_key,
)
print(response)

Parameters

• user_input: The user input text to process (type: str)
• llm: The langchain LLM instance to use (optional, type: Optional[BaseChatModel]), defaults to ChatLLM7 from langchain_llm7
• api_key: The API key for LLM7 (optional, type: Optional[str]), defaults to os.getenv("LLM7_API_KEY") or None

Notes

• The package uses ChatLLM7 from langchain_llm7 by default. You can safely pass your own LLM instance (based on langchain) if you want to use another LLM.

  Example for ChatOpenAI:

  from langchain_openai import ChatOpenAI
  from preact_codegen import preact_codegen
  
  llm = ChatOpenAI()
  response = preact_codegen(
      user_input=user_input,
      llm=llm,
  )
  

  Example for ChatAnthropic:

  from langchain_anthropic import ChatAnthropic
  from preact_codegen import preact_codegen
  
  llm = ChatAnthropic()
  response = preact_codegen(
      user_input=user_input,
      llm=llm,
  )
  

  Example for ChatGoogleGenerativeAI:

  from langchain_google_genai import ChatGoogleGenerativeAI
  from preact_codegen import preact_codegen
  
  llm = ChatGoogleGenerativeAI()
  response = preact_codegen(
      user_input=user_input,
      llm=llm,
  )
  

• The default rate limits for LLM7 free tier are sufficient for most use cases of this package. If you want higher rate limits for LLM7, you can pass your own API_KEY via environment variable LLM7_API_KEY or directly like preact_codegen(api_key="your_api_key").

• You can get a free API key by registering at LLM7.

Links

• GitHub issues: GitHub Issues
• Author name: Eugene Evstafev
• Author email: [e-mail]