lawhead-extractor 2025.12.21190602

lawhead-extractor parses legal headlines, extracting parties, claim type and outcome using an LLM with pattern matching for accuracy.

Lawhead Extractor

Extract structured information from legal case headlines

The Lawhead Extractor is a Python package that processes legal case headlines and extracts structured information such as the parties involved, the type of claim, and the outcome. It uses a Large Language Model (LLM) to analyze the text input and returns a consistent, formatted response with key details, ensuring accuracy through pattern matching and retries.

Installation

pip install lawhead_extractor

Usage

from lawhead_extractor import lawhead_extractor
import os

# default usage
response = lawhead_extractor(user_input="an example user input text")
print(response)

# usage with custom LLM instance (e.g. OpenAI)
from langchain_openai import ChatOpenAI
from lawhead_extractor import lawhead_extractor
llm = ChatOpenAI()
response = lawhead_extractor(user_input="user input text", llm=llm)

# usage with custom LLM instance (e.g. Anthropic)
from langchain_anthropic import ChatAnthropic
from lawhead_extractor import lawhead_extractor
llm = ChatAnthropic()
response = lawhead_extractor(user_input="user input text", llm=llm)

# usage with custom LLM instance (e.g. Google Generative AI)
from langchain_google_genai import ChatGoogleGenerativeAI
from lawhead_extractor import lawhead_extractor
llm = ChatGoogleGenerativeAI()
response = lawhead_extractor(user_input="user input text", llm=llm)

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 rate limits for LLM7 free tier will be used.

By default, the package uses the ChatLLM7 from langchain_llm7 <https://pypi.org/project/langchain_llm7/>. Developers can safely pass their own LLM instance (based on https://docs.langchain.com/docs/llm/how-to-use-another-llm) if they want to use another LLM, via passing it like lawhead_extractor(llm=their_llm_instance), for example to use the OpenAI https://docs.langchain.com/docs/openai/how-to-use-openai, Anthropic https://docs.langchain.com/docs/anthropic/how-to-use-anthropic, or Google Generative AI https://docs.langchain.com/docs/google/generative-ai/how-to-use-google-generative-ai.

The default rate limits for LLM7 free tier are sufficient for most use cases of this package. If developers want higher rate limits for LLM7, they can pass their own API key via environment variable LLM7_API_KEY or via passing it directly like lawhead_extractor(api_key="their_api_key"). Developers can get a free API key by registering at https://token.llm7.io/.

Issues

Find and report any issues with the package on our GitHub issues page: https://github.com/chigwell/lawhead_extractor

Author

The Lawhead Extractor package was created by Eugene Evstafev and is maintained by Eugene Evstafev.

Contact the author at: [e-mail]

Follow Chigwell on GitHub at: https://github.com/chigwell