modelscout 0.1.1

ModelScout: Find the best LLM for your needs.

ModelScout

ModelScout is a command-line tool designed to help users pick the best LLM for their needs. Modelscout uses a similar recommendation algorithm as to Macros On Demand a more in-depth example of my SWE work. While ModelScout is simple it serves as a useful stop-gap in the quickly evolving field of LLMs. As the name suggests ModelScout is simply a scout and should serve as the beginning, not the end of your LLM search.

Subjective metrics such as performance and the degree to which a model is supported are gathered from various sources and forums (ie. Benchmarks, Reddit, Google trends. etc) and are based largely on community sentiment so should be taken with a grain of salt. Further note the cost per million tokens for open source models are very rough estimates with varying accuracy.

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Installation

Ensure you have Python installed, then install ModelScout using pip:

pip install modelscout

Alternatively, clone the repository manually:

git clone https://github.com/Hadi-M-Ibrahim/ModelScout.git
cd ModelScout

For installation details, visit the ModelScout PyPI page.

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Command-Line Arguments

Argument	Description
file (Default: ./models.csv)	Path to the CSV file
--scout	Launch interactive mode for selecting filters (Recommended)
--top	Number of recommended models to display (5 by default)
--license	Ideal license (1 for open source, 0 for no preference)
--performance	Ideal performance rating (1.0-10.0)
--cost	Ideal cost per million tokens
--context_length	Ideal context length
--Support	Ideal API/tools availability (1.0-10.0)

For implemtion details, visit the ModelScout Github Repo.

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CSV format

Model Name,Company,Context Length,Cost per Million Tokens,Performance,license,Support