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https://github.com/dreamingtulpa/replicate-ruby
Replicate Ruby client
https://github.com/dreamingtulpa/replicate-ruby
Last synced: 3 months ago
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Replicate Ruby client
- Host: GitHub
- URL: https://github.com/dreamingtulpa/replicate-ruby
- Owner: dreamingtulpa
- Created: 2022-10-13T15:42:24.000Z (about 2 years ago)
- Default Branch: master
- Last Pushed: 2024-02-17T20:10:15.000Z (9 months ago)
- Last Synced: 2024-07-05T15:01:19.347Z (4 months ago)
- Language: Ruby
- Size: 44.9 KB
- Stars: 60
- Watchers: 1
- Forks: 6
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
Awesome Lists containing this project
- awesome-replicate - replicate-ruby - A Ruby client for Replicate. (Client libraries)
README
# Replicate Ruby client
This is a Ruby client for [Replicate](https://replicate.com/). It lets you run models from your Ruby code and do various other things on Replicate.
## Installation
Add this line to your application's Gemfile:
```ruby
gem 'replicate-ruby'
```
## Usage
Grab your token from replicate.com/account and authenticate by configuring `api_token`:
```ruby
Replicate.configure do |config|
config.api_token = "your_api_token"
end
```
You can retrieve a model:
```ruby
# Latest version
model = Replicate.client.retrieve_model("stability-ai/stable-diffusion")
version = model.latest_version
# List of versions
version = Replicate.client.retrieve_model("stability-ai/stable-diffusion", version: :all)
# Specific version
version = Replicate.client.retrieve_model("stability-ai/stable-diffusion", version: "")
```
And then run predictions on it:
```ruby
prediction = version.predict(prompt: "a handsome teddy bear")
# manually refetch the prediction status
prediction = prediction.refetch
# or cancel a running prediction
prediction = prediction.cancel
# and if a prediction returns with status succeeded, you can retrieve the output
output = prediction.output
# Optionally you can submit a webhook url for replicate to send a POST request once a prediction has completed
prediction = version.predict(prompt: "a handsome teddy bear", "https://webhook.url/path") # call predict
id = prediction.id # store prediction id in your backend
prediction = Replicate.client.retrieve_prediction(id) # retrieve prediction during webhook with id from backend
```
## Dreambooth
There is support for the [experimental dreambooth endpoint](https://replicate.com/blog/dreambooth-api).
First, upload your training dataset:
```ruby
upload = Replicate.client.upload_zip('tmp/data.zip') # replace with the path to your zip file
```
Then start training a new model using, for instance:
```ruby
training = Replicate.client.create_training(
input: {
instance_prompt: "zwx style",
class_prompt: "style",
instance_data: upload.serving_url,
max_train_steps: 5000
},
model: 'yourusername/yourmodel'
)
```
As soon as the model has finished training, you can run predictions on it:
```ruby
prediction = Replicate.client.create_prediction(
input: {
prompt: 'your prompt, zwx style'
},
version: training.version
)
```
You can also download the `output.zip` file from the dreambooth training prediction, unzip it, and then convert the trained model to a Stable Diffusion checkpoint with [convert_diffusers_to_sd.py](https://gist.github.com/jachiam/8a5c0b607e38fcc585168b90c686eb05).
```bash
python ./convert_diffusers_to_sd.py --model_path ~/Downloads/output --checkpoint_path ~/Downloads/output.ckpt
```
## Development
After checking out the repo, run `bin/setup` to install dependencies. Then, run `rake test` to run the tests. You can also run `bin/console` for an interactive prompt that will allow you to experiment.