tech-discriptor 2025.12.21161904

A new package designed to transform technical descriptions of hardware or software solutions into structured summaries and feature lists. It takes detailed textual inputs about various systems like Ro

Tech-Discriptor

Transform technical descriptions into structured summaries and feature lists

Overview

A new package designed to transform technical descriptions of hardware or software solutions into structured summaries and feature lists.

Installation

pip install tech_discriptor

Example Usage

from tech_discriptor import tech_discriptor

user_input = "Romforth—an ultra-portable, small, bare-metal Forth implementation for multiple processors—"
response = tech_discriptor(user_input)

print(response)

Input Parameters

• user_input: str - the user input text to process
• llm: Optional[BaseChatModel] - the langchain llm instance to use, if not provided the default ChatLLM7 will be used.
• api_key: Optional[str] - the api key for llm7, if not provided the default ChatLLM7 will be used.

Supported LLMs

You can safely pass your own llm instance (based on https://docs.langchain.io/docs/guides/get-started-with-a-model) if you want to use another LLM, via passing it like tech_discriptor(user_input, llm=their_llm_instance).

Examples

OpenAI

from langchain_openai import ChatOpenAI
from tech_discriptor import tech_discriptor

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

Anthropic

from langchain_anthropic import ChatAnthropic
from tech_discriptor import tech_discriptor

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

Google Generative AI

from langchain_google_genai import ChatGoogleGenerativeAI
from tech_discriptor import tech_discriptor

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

API Key for LLM7

The default ChatLLM7 LLM is used if no custom LLM is provided. The free tier rate limits are generally sufficient. For higher rate limits with ChatLLM7, you can:

• Set the LLM7_API_KEY environment variable.
• Pass the API key directly: tech_discriptor(user_input, api_key="your_api_key") You can obtain a free API key by registering at https://token.llm7.io/

Contributing

Contributions are welcome! Please refer to the GitHub repository for details.

License

This project is licensed under the MIT License.

Author

• Eugene Evstafev ([e-mail])

Contact

For issues or questions, please visit the GitHub issues page: https://github.com/chigwell/tech-discriptor/