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text2structured-summary generates structured summaries from unstructured text using an LLM.

Project description

text2structured_summary

PyPI version License: MIT Downloads LinkedIn

Generate structured summaries from unstructured text using an LLM.

Installation

pip install text2structured_summary

Usage

from text2structured_summary import text2structured_summary

# Basic usage with default LLM7
response = text2structured_summary(
    user_input="Your unstructured text here..."
)

# With custom LLM (e.g., OpenAI)
from langchain_openai import ChatOpenAI
from text2structured_summary import text2structured_summary

llm = ChatOpenAI()
response = text2structured_summary(
    user_input="Your unstructured text...",
    llm=llm
)

# With custom API key (LLM7)
response = text2structured_summary(
    user_input="Your unstructured text...",
    api_key="your_llm7_api_key"
)

Parameters

  • user_input (str): The unstructured text to be summarized
  • api_key (Optional[str]): LLM7 API key (defaults to environment variable LLM7_API_KEY)
  • llm (Optional[BaseChatModel]): Custom LangChain LLM instance (defaults to ChatLLM7)

Features

  • Uses LLM7 by default (free tier sufficient for most use cases)
  • Supports custom LLMs via LangChain interface
  • Returns structured summaries matching predefined pattern
  • Automatic API key fallback from environment variables

Getting Started

  1. Install the package
  2. Call text2structured_summary() with your text
  3. Get structured output matching the package's pattern

Notes

  • For LLM7, register at https://token.llm7.io/ for your API key
  • The default pattern ensures structured output format
  • Custom LLMs must implement LangChain's BaseChatModel interface

Issues

Report issues at: https://github.com/chigwell/text2structured-summary/issues

Author

Eugene Evstafev (hi@euegne.plus)

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