A collection of Python scripts to monitor the Elite Dangerous journal files and provide audio feedback using OpenRouter services.
This script is a work in progress, primarily for personal use, as a learning experience and to have fun with LLMs and ED. For something more complete and polished, I recommend checking out the COVAS:NEXT project.
The idea is to provide audio feedback for the most common events in the game, such as jumps, combat, docking, etc., while using the small and free LLMs from OpenRouter, that are usually limited in prompt size.
Since each event can have a personalized parser, post-processing and web content, such as EDSM data, can be injected before triggering the AI response. This also helps to reduce the size of the prompt.
I'm also keeping a small static ship-state.json
file for the ship fuel levels, last place visited, etc, that can be used to enrich the information on specific events.
You might need Python 3.x installed in the system.
- Install the requirements with
pip install -r requirements.txt
- Copy or rename the
config.py.example
file toconfig.py
- Open the
config.py
and paste your OpenRouter key on theLLM_API_KEY
variable. The script should work without any other modification, but take a look at the settings in case you want to change something. - To run the script use
python start.py
You can run the script right from the start or when ED: Dangerous is already working.
You want to create your own parsers? Just create a new file in the /parsers
directory using the exact name of the event you want to parse. I recommend copying another parser that provides a similar functionality to use as a template.
Do you want to use Cortana/Eva voice on Windows? Use the registry patch file included: Microsoft-Eva-Mobile.reg
to make that voice available.
- RatherRude - Elite Dangerous AI Integration
- Brian Wilson - EDDI