- forked this repo from Peter Kaminski
- expanded to include different LLM models
- these Python programs use the direct REST interface provided by
the PyPI `requests` module and do not require the `pip`
installation of LLM specific modules.
- each LLM does require an API key
- `-h` or `--help` provides argument descriptions
-
salamander.py
is the original program written to provide OpenAI text output in response to an input file that contains some prompt text. -
gecko.py
is a similar program that uses Anthropic's Claude-3-sonnet model. Specify a model name ("opus", "sonnet", "haiku") with the-m
argument. -
iguana.py
uses Google's Gemini-Pro model.
- One way to use these programs is to set up a local Python virtual
environment and run them in the terminal:
- initial setup:
python3 -m venv venv
source venv/bin/activate
pip install -U pip
pip install -r requirements.txt
-
My working practice is to activate the virtual environment
($ source venv/bin/activate
)
before running any code and deactivating ($ deactivate
) when done. -
run these programs (using a simple "why is the sky blue?" prompt):
- first set up API keys: see
env.sh-template
for an example of how to do this.
- first set up API keys: see
./salamander.py -i prompts/skybluePrompt.md
./gecko.py -i prompts/skybluePrompt.md
./iguana.py -i prompts/skybluePrompt.md
- The code generation prompt that was fed to "ChatGPT Plus" to create
the first sample of
salamander.py
is found inprompts/salamanderPrompt.md
. It can be used to compare how OpenAI, Claude, and Gemini respond to a prompt like this.
-
experiment with some summarization and topic extraction prompts
- two examples in the
prompts/
directory
- two examples in the
-
experiment with using the previous response as part of a topic and summarization conversation
Please post issues.