rankextractplus 2025.12.21231046

rankextractplus extracts and structures ranked info from text, organizing data for easier comparison and analysis.

RankExtractPlus

RankExtractPlus is a Python package designed to extract and structure ranked information from unstructured text inputs. It leverages the power of large language models (LLMs) to process text and return structured, ranked outputs.

Features

• Extracts and ranks information from unstructured text
• Uses llmatch-messages to ensure structured and consistent outputs
• Supports custom LLMs for flexible integration
• Easy-to-use interface with minimal setup

Installation

To install RankExtractPlus, simply run:

pip install rankextractplus

Usage

Basic Usage

from rankextractplus import rankextractplus

user_input = "Text about the best countries at math..."
response = rankextractplus(user_input)
print(response)

Advanced Usage with Custom LLM

You can use any LLM compatible with LangChain. Here are examples with different LLMs:

Using OpenAI

from langchain_openai import ChatOpenAI
from rankextractplus import rankextractplus

llm = ChatOpenAI()
response = rankextractplus(user_input, llm=llm)
print(response)

Using Anthropic

from langchain_anthropic import ChatAnthropic
from rankextractplus import rankextractplus

llm = ChatAnthropic()
response = rankextractplus(user_input, llm=llm)
print(response)

Using Google

from langchain_google_genai import ChatGoogleGenerativeAI
from rankextractplus import rankextractplus

llm = ChatGoogleGenerativeAI()
response = rankextractplus(user_input, llm=llm)
print(response)

Using LLM7 API Key

By default, RankExtractPlus uses ChatLLM7 from langchain_llm7. If you want to use a custom API key, you can pass it directly or set it as an environment variable:

from rankextractplus import rankextractplus

# Using environment variable
import os
os.environ["LLM7_API_KEY"] = "your_api_key"
response = rankextractplus(user_input)

# Or passing it directly
response = rankextractplus(user_input, api_key="your_api_key")

Parameters

• user_input (str): The unstructured text input 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 environment variable LLM7_API_KEY will be used.

Rate Limits

The default rate limits for LLM7's free tier are sufficient for most use cases. If you need higher rate limits, you can obtain a free API key by registering at LLM7.

Contributing

If you encounter any issues or have suggestions, please open an issue on GitHub.

Author

• Eugene Evstafev
• Email: [e-mail]
• GitHub: chigwell

License

This project is licensed under the MIT License. See the LICENSE file for details.