LLMTextualAnswer 0.1.0

Find textual answers via an LLM.

LLMTextualAnswer

Python package for finding textual answers via LLMs. This is a Python port of the Wolfram Language LLMTextualAnswer function, focused on building prompts, wiring LangChain models, and parsing structured outputs.

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Install

pip install LLMTextualAnswer

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Usage

from LLMTextualAnswer import LLMTextualAnswer
from langchain_openai import ChatOpenAI

llm = ChatOpenAI(model="gpt-4o-mini")

text = (
    "Born and raised in the Austrian Empire, Tesla studied engineering and physics "
    "in the 1870s without receiving a degree."
)

questions = ["Where born?"]

result = LLMTextualAnswer(
    text,
    questions,
    llm=llm,
    form=dict,
)

print(result)

For more detailed examples see the notebook "./docs/Basic-usage.ipynb".

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Notes

• LLMTextualAnswer accepts LangChain chat/text models that support .invoke.
• Use prompt_style="chat" or prompt_style="text" if auto-detection is not desired.
• When you want only the prompt template, pass form="StringTemplate".