@casual-simulation/crypto - npm Package Versions

• The aspect ratio should be the width of the image divided by the height of the image.
• Negative aspect ratios can also be used to mirror the image horizontally.

• Key features:
  • The ability to join multiple chat rooms at once.
  • The ability to display camera/screen feeds on 3D bots.
  • Notification of when remote users join/leave.
  • Notification of when users are speaking.
  • The ability to control the quality that video tracks stream at.
• The following functions have been added:
  • os.joinRoom(roomName, options?)
  • os.leaveRoom(roomName, options?)
  • os.getRoomOptions(roomName)
  • os.setRoomOptions(roomName, options)
  • os.getRoomTrackOptions(roomName, trackAddress)
  • os.setRoomTrackOptions(roomName, trackAddress, options)
  • os.getRoomRemoteOptions(roomName, remoteId)
• The following listeners have been added:
  • @onRoomJoined - Sent whenever a room has been joined via os.joinRoom()
  • @onRoomLeave - Sent whenever a room has been exited via os.leaveRoom()
  • @onRoomStreaming - Sent whenever the local user has been connected or reconnected to a room.
  • @onRoomStreamLost - Sent whenever the local user has been disconnected from a room.
  • @onRoomTrackSubscribed - Sent whenever an audio/video track has been discovered inside a room.
  • @onRoomTrackUnsubscribed - Sent whenever an audio/video track has been removed from a room.
  • @onRoomRemoteJoined - Sent whenever a remote user has joined a room.
  • @onRoomRemoteLeave - Sent whenever a remote user has left a room.
  • @onRoomSpeakersChanged - Sent whenever the list of speaking users has changed in a room.
  • @onRoomOptionsChanged - Sent whenever the local room options have been changed.
• See the documentation for more detailed information.
• Also check out the rooms-example appBundle for an example.

• These functions are useful for tracking the history of an instance and debugging potential data loss problems.
• os.listInstUpdates() gets the list of updates that have occurred in the current instance.
• os.getInstStateFromUpdates() gets the bot state that is produced by the given list of updates.

Added the os.openImageClassifier(options) and os.closeImageClassifier() functions.

• These functions are useful for applying Machine Learning inside CasualOS to detect categories of things via the camera feed.
• Currently, the image classifier is only able to consume models generated with Teachable Machine.
  1. To create a model, go to https://teachablemachine.withgoogle.com/ and click "Get Started".
  2. Create an "Image Project" and choose "Standard image model".
  3. Add or record photos in each class.
  4. Click "Train".
  5. Once training is done you can get a model URL by clicking "Export Model".
  6. Under "Tensorflow.js", choose "Upload (shareable link)" and click "Upload". You can also optionally save the project to Google Drive.
  7. Once uploaded, copy the shareable link.
  8. Create a bot with an @onClick tag and put the following code in it (replacing MY_MODEL_URL with the shareable link):

     await os.openImageClassifier({
         modelUrl: 'MY_MODEL_URL',
     });
     

• options is an object with the following properties:
  • modelUrl - The sharable link that was generated from Teachable Machine.
  • modelJsonUrl - Is optional and can be used in advanced scenarios where you want to control where the model is stored.
  • modelMetadataUrl - Is optional and can be used in advanced scenarios where you want to control where the model is stored.
  • cameraType - Is optional and is the type of camera that should be preferred. Can be "front" or "rear".

Created the oai-1 appBundle.

• This appBundle is currently a simple ab that can query the OpenAI GPT-3 API via a shout.

• The ab has the following features:

  • A single manager bot in the oai-1 dimension and systemPortal as oai-1.manager.

  • @generateTextResponse is a listener that asks GPT-3 to respond to a given text prompt.

    • It takes the following parameters:

      • apiKey - The API key that should be used to access the API. You can get an API key at https://beta.openai.com/overview.
      • prompt - The text that the AI should respond to. An example is "Write a tagline for an ice cream shop.". Also see this guide: https://beta.openai.com/docs/guides/completion.
      • engine - The engine that should be used to process the prompt. Defaults to "text-davinci-001" if not specified. You can find a list of engines is available here: https://beta.openai.com/docs/engines.
      • options - An object that contains additional options for the request. You can find the documentation for these options here: https://beta.openai.com/docs/api-reference/completions/create.

    • It returns a promise that contains a list of generated choices.

    • Example:

      let oai = getBot('system', 'oai-1.manager');
      const response = await oai.generateTextResponse({
          apiKey: 'myAPIKey',
          prompt: 'Write a tagline for an ice cream shop.',
      });
      
      if (response.choices.length > 0) {
          os.toast('Best choice: ' + response.choices[0]);
      } else {
          os.toast('No choices.');
      }