An experiment for the remarkable2 that watches what you write and, when prompted either with a gesture or some on-screen content, can write back to the screen. This is an exploration of various interacts through this handwriting+screen medium.
You need an OPENAI_API_KEY
environment variable set. I did this by adding it to my ~/.bashrc file on the remarkable:
# In the remarkable's ~/.bashrc or before you run ghostwriter
export OPENAI_API_KEY=your-key-here
Install by getting the binary to your remarkable. On your not-remarkable:
wget https://github.com/awwaiid/ghostwriter/releases/latest/download/ghostwriter
# Replace this ip address with your remarkable ip address
scp ghostwriter [email protected]:
Then you have to ssh over and run it. Here is how to install and run (run these on the remarkable):
# Make it executable after the initial copy
chmod +x ./ghostwriter
./ghostwriter --help # Get the options
./ghostwriter text-assist # Start a text/keyboard-replying session
Draw some stuff on your screen, and then trigger the assistant by touching/tapping the upper-right corner with your finger. In the ssh session you'll see other touch-detections and there is a log of what happens while it is processing. You should see some dots drawn during processing and then a typewritten or drawn response!
- 2024-10-06 - Bootstrapping
- Basic proof of concept works!!!
- Drawing back on the screen doesn't work super well; it takes the SVG output from ChatGPT and rasterizes it and then tries to draw lots of individual dots on the screen. The Remarkable flips out a bit ... and when the whole screen is a giant black square it really freaks out and doesn't complete
- Things that worked at least once:
- Writing "Fill in the answer to this math problem... 3 + 7 ="
- "Draw a picture of a chihuahua. Use simple line-art"
- 2024-10-07 - Loops are the stuff of souls
- I got a rudimentary gesture and status display!
- So now you can touch in the upper-right and you get an "X" drawn. Then as the input is processed you get further crosses through the X. You have to erase it yourself though :)
- 2024-10-10 - Initial virtual keyboard setup
- I've started to learn about using the Remarkable with a keyboard, something that I hadn't done before. It's surprisingly limited ... there is basicaly one large textarea for each page with some very basic formatting
- To write in that I have to make a pretend keyboard, which we can do via rM-input-devices, and I've done basic validation that it works!
- So now I want to introduce a mode where it always writes back to the text layer and recognizes that text comes from Machine and hadwriting from Human. Not sure that I'll like this mode
- 2024-10-20 - Text output and other modes
- Slowly starting to rework the code to be less scratch-work, organized a bit
- Now introduced
./ghostwriter text-assist
mode, uses a virtual keyboard to respond!
- 2024-10-21 - Binary release build
- Got a github action all set to do binary builds
- 2024-10-23 - Code shuffle
- Doing a bit of refactoring, grouping utilities into separate files
- Yesterday a new Anthropic model came out (3.5-sonnet-new) which might be better at spacial awareness on the screen, so next up is to try that out in drawing-mode
- In any case, next I want to set it up with
tools
so that it can contextually give back an SVG or text or start to trigger external scripts, like for TODO list management
- 2024-11-02 - Tool Time
- Switch to providing some tools -- draw_text and draw_svg
- This should make it more compatible with Anthropic?
- More immediately, this means now there is the one overall assistant and it decides to draw back keyboard text or SVG drawing
- 2024-11-07 - Claude! (Anthropic)
- More shuffling to start to isolate the API
- ... and now I added Claude/Anthropic!
- It is able to use an almost identical tool-use setup, so I should be able to merge the two
- So far it seems to like drawing a bit more, but it is not great at drawing and not much better at spacial awareness
- Maybe next on the queue will be augmenting spacial awareness through some image pre-processing and result positioning. Like detect bounding boxes, segments, etc, feed that into the model, and have the model return an array of svgs and where they should be positioned. Maybe.
- 2024-11-22 - Manual Evaluations
- Starting to sketch out how an evaluation might work
- First I've added a bunch of parameters for recording input/output
- Then I use that to record a sample input and output on the device
- Then I added support to run ghostwriter on my laptop using the pre-captured input
- Next I will build some tooling around iterating on examples given different prompts or pre-processing
- And then if I can get enough examples maye I'll have to make an AI judge to scale :)
- To help with that ... on idea is to make overlay the original input with the output but make the output a different color to make it differentiable by the judge
- So far this technique is looking good for SVG output, but it'd be nice to somehow render keyboard output locally too. That is tricker since the keyboard input rendering is done by the reMarkable app
- [DONE] Matt showed me his iOS super calc that just came out, take inspiration from that!
- This already kinda works, try writing an equation
- [DONE] A gesture or some content to trigger the request
- like an x in a certain place
- or a hover circle -- doesn't need to be an actual touch event per se
- [DONE] Take a screenshot, feed it into a vision model, get some output, put the output back on the screen somehow
- [DONE] Like with actual writing; or heck it can draw a million dots on the screen if it does it fast
- [DONE] OK ... we can also send keyboard events! That means we can use the Remarkable text area. This is an awkward and weird text area that lives on a different layer from the drawing
- So maybe we can say drawing = human, text = machine
- Probably a lot easier to erase too...
- Prompt library
- There is already the start of this in prompts/
- The idea is to give a set of tools (maybe actual llm "tools") that can be configured in the prompt
- But also could put in there some other things ... like an external command that gets run for the tool
- Example: a prompt that is good at my todo list management. It would look for "todo", extract that into a todo, and then run
add-todo.sh
or something- (which would in turn ssh somewhere to add something to taskwarrior)
- Initial config
- On first run, maybe create a config file
- Could prompt for openai key and then write it into the file
- Maybe an auto-start, auto-recovery?
- Generate Diagrams
- Let one of the outputs be plantuml and/or mermaid, and then turn that into an SVG/png that it then outputs to the screen
- External stuff
- Let it look things up
- Let it send me stuff ... emails, slacks
- Evaluation
- Create a set of screenshots for inputs
- Represent different use-cases
- Some of these, such as TODO-extraction, might have specific expectations for output or execution, but most of them won't
- Run through the system to get example output -- text, svg, actions
- Write a test suite to judge the results .... somewhat human powered? Separate VLM judge?
- Adapted screen capture from reSnap
- Techniques for screen-drawing inspired from rmkit lamp
- Super cool SVG-to-png done with resvg
- Make the keyboard input device even without a keyboard via rM-input-devices
- Not quite the same, but I recently found reMarkableAI that does OCR→OpenAI→PDF→Device
# Initial dependencies install (also ... rust)
rustup target add armv7-unknown-linux-gnueabihf
sudo apt-get install gcc-arm-linux-gnueabihf
cargo install cross
# Then to build
cross build --release --target=armv7-unknown-linux-gnueabihf
# And deploy by scp'ing the binary over and run it on the device!
scp target/armv7-unknown-linux-gnueabihf/release/ghostwriter remarkable:
I got evtest by getting the ipkg from trotek and untaring it a few levels and then scping it over. Surprisingly it works!
Now I can see that /dev/input/event1 is pen input and /dev/input/event2 is touch input
You can detect distance. The value gets smaller as you get close to the screen with the tip of the pen or eraser
Event: time 1728139017.789746, type 3 (EV_ABS), code 25 (ABS_DISTANCE), value 105
EV_KEY 320 (BTN_TOOL_PEN) is for pen presence/range EV_KEY 330 (BTN_TOUCH) is for actual drawing
- https://github.com/rmkit-dev/rmkit/tree/master is great to learn from
- https://github.com/rmkit-dev/rmkit/blob/master/src/lamp/main.cpy -- they've already worked out some other pen-input-drawing! See if we can translate or learn about a reliable way to draw