text-geo-map 2025.12.21225445

text-geo-map turns plain text location descriptions into standardized geospatial data for interactive maps.

Package Title

Transforming Text Descriptions to Structured Geospatial Data

About the Package

A new Python package that converts plain text descriptions of locations into structured geospatial data. The package extracts and validates key details such as coordinates, addresses, or landmarks from the text and outputs the information in a standardized format.

Installing

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Install the package via pip:

pip install text_geo_map

Using the Package

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from text_geo_map import text_geo_map

user_input = "The Eiffel Tower in Paris, France"
response = text_geo_map(user_input)
print(response)

Parameters

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The text_geo_map function accepts the following parameters:

• user_input: The text description of a location.
• llm: An instance of the LangChain BaseChatModel to use for LL7 queries (default is ChatLLM7 from langchain_llm7).
• api_key: The API key for LLM7 (default is None, which will use the LLM7_API_KEY environment variable).

You can also pass your own instance of a LangChain chat model by using the llm parameter. For example:

import os

from langchain OpenAI import ChatOpenAI
from text_geo_map import text_geo_map

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

Example to use the Anthropics:

import os

from langchain_anthropic import ChatAnthropic
from text_geo_map import text_geo_map

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

Example to use the Google generative ai:

import os

from langchain_google_genai import ChatGoogleGenerativeAI
from text_geo_map import text_geo_map

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

Note: The default rate limits for LLM7 free tier should be sufficient for most use cases of this package. If you need higher rate limits, you can pass your own API key via the environment variable LLM7_API_KEY or directly as the api_key parameter.

You can obtain a free API key by registering on https://token.llm7.io/.

Documentation

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More information can be found on the GitHub repository at: https://github.com/chigwell/

Author

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This package was created by Eugene Evstafev and can be reached at [e-mail].