Phrame generates captivating and unique art by listening to conversations around it, transforming spoken words and emotions into visually stunning masterpieces. Unleash your creativity and transform the soundscape around you.
Phrame relies on the SpeechRecognition interface of the Web Speech API to transform audio into text. This text is processed by OpenAI, producing a condensed summary. The summary is then combined with the configured generative AI image services and the final images are saved.
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- Create unique AI-generated artwork from spoken conversations
- Automatic, manual or voice-activated summary generation for on-demand art
- User-friendly UI, optimized for both desktop and mobile
- Real-time updates and remote control via WebSockets
- Integrated config editor for customization
- Support for multiple generative AI image services
- Voice commands for image generation and navigation
- Manage your gallery effortlessly: browse, favorite, delete images, and navigate using keyboard shortcuts
- Access and manage logs for efficient troubleshooting
- amd64
- arm64
* Midjourney currently uses an unofficial third party package. Use this integration at your own risk.
Activate the microphone to interact with Phrame using the following voice commands.
| Command | Action |
|---|---|
Hey Phrame |
Wake word to generate images on demand |
Next Image |
Advance to next image |
Previous Image |
Advance to previous image |
Last Image |
Advance to previous image |
Phrame has a responsive UI available at localhost:3000.
| Path | Name |
|---|---|
/ |
Controller |
/phrame?mic |
Phrame with microphone support |
/phrame |
Phrame without microphone support |
/gallery |
Gallery |
/config |
Config |
/logs |
Logs |
Speech recognition in Phrame is managed by the browser. The handling of audio data for speech recognition depends on the specific browser used. For instance, Chrome takes the audio and sends it to Google's servers to perform the transcription. It is encouraged to review the privacy policy of your chosen browser to fully understand how speech data is handled.
Once transcribed, Phrame saves these transcriptions into a local database. They are then processed by OpenAI to generate a summary, and immediately after, the original transcriptions are deleted. This summary is used in conjunction with the configured generative AI image services and the final pieces of art are saved locally.
It's important to clarify that Phrame does not retain or transmit your transcripts beyond the local device, except for the brief period required for generating the summary through OpenAI. Apart from these specific instances, no personal data is used, stored, or transmitted for any other purposes.
Phrame operates as a single Docker container and is easily accessible using any modern browser, even without a microphone.
To take advantage of the speech recognition feature, a compatible browser and microphone are required. At this time Chrome and Safari are the only browsers that support speech recognition.
Artwork within Phrame is displayed according to the image.order value. The latest summary and any favorite images are seamlessly merged, providing an evolving canvas of unique AI-generated art. As new images are created, they are instantly displayed by Phrame.
- Start Phrame
- Go to localhost:3000/config
- Add your OpenAI API key and save
- Verify OpenAI shows as configured with a green circle
- In a new window go to localhost:3000/phrame?mic and follow the on screen instructions
- Go to localhost:3000 and verify the microphone and speech recognition are working
docker run -d --restart=unless-stopped --name=phrame -v phrame:/.storage -p 3000:3000 jakowenko/phrameversion: '3.9'
volumes:
phrame:
services:
phrame:
container_name: phrame
image: jakowenko/phrame
restart: unless-stopped
volumes:
- phrame:/.storage
ports:
- 3000:3000Modern browsers require a user click to access the microphone. To automatically start Phrame on boot, you can use the following script. This requires ydotool or xdotool (depending on your display server) to be installed which allows you to simulate keyboard input and mouse activity.
The script will wait 15 seconds for the Docker Engine and Phrame to start before launching Chrome. You can adjust the delay by changing the sleep value. After launching the browser, the script will wait 5 seconds before sending a click to get microphone access and start speech recognition.
Depending on your system, you may need to adjust the path to Chrome.
ydotool
#!/bin/bash
export YDOTOOL_SOCKET=/tmp/.ydotool_socket
# wait for the desktop and docker to be fully loaded
sleep 15s
# launch chrome in kiosk mode for microphone access
/usr/bin/google-chrome-stable --kiosk --no-first-run --hide-crash-restore-bubble --password-store=basic "http://localhost:3000/phrame?mic" &
# wait for chrome and phrame to load
sleep 5s
# move the mouse to the coordinates and click the left mouse button
ydotool mousemove --absolute 0 0
ydotool click 0xC0xdotool
#!/bin/bash
# wait for the desktop and docker to be fully loaded
sleep 15s
# launch chrome in kiosk mode for microphone access
/usr/bin/google-chrome-stable --kiosk --no-first-run --hide-crash-restore-bubble --password-store=basic "http://localhost:3000/phrame?mic" &
# wait for chrome and phrame to load
sleep 5s
# move the mouse to the coordinates and click the left mouse button
xdotool mousemove --sync 0 0 click 1Configurable options are saved to /.storage/config/config.yml and are editable via the UI at localhost:3000/config.
Note: Default values do not need to be specified in configuration unless they need to be overwritten.
# image settings (default: shown below)
image:
# time in seconds between image transitions
interval: 60
# order of images to display: random, recent
order: recentImages can be automatically generated by creating random summaries. This can be scheduled with a cron expression. Keywords can be passed to help guide the summary.
# autogen settings (default: shown below)
autogen:
# schedule as a cron expression for processing transcripts (at every 15th and 45th minute)
cron: '15,45 * * * *'
prompt: Provide a random short description to describe a picture. It should be no more than one or two sentences. If keywords are provided select a couple at random to help guide the description.
# keywords to guide the summary
keywords: []Images are generated by processing transcripts. This can be scheduled with a cron expression. All of the transcripts within X minutes will then be processed by OpenAI using openai.summary.prompt to summarize the transcripts.
# transcript settings (default: shown below)
transcript:
# schedule as a cron expression for processing transcripts (at every 30th minute)
cron: '*/30 * * * *'
# how many minutes of files to look back for (process the last 30 minutes of transcripts)
minutes: 30
# minimum number of transcripts required to process
minimum: 5To configure OpenAI, obtain an API key and add it to your config like the following. All other default settings found bellow will also be applied. You can overwrite the settings by updating your config.yml file.
# openai settings (default: shown below)
openai:
# api key
key:
summary:
# model name (https://platform.openai.com/docs/models/overview)
model: gpt-3.5-turbo
# prompt used to generate a summary from transcripts
prompt: You will be given a string of random conversations and need to pull out a few keywords and topics that were talked about. You will then turn this into a short description to describe a picture. It should be no more than two or three sentences.
# prompt used to generate a random summary
random: Provide a random short description to describe a picture. It should be no more than two or three sentences.
image:
# enable or disable image generation
enable: true
# trim letterbox and pillarbox images
trim: false
# size of the generated images: 256x256, 512x512, or 1024x1024
size: 512x512
# number of images to generate for each style
n: 1
# used with summary to guide the image model towards a particular style
style:
- cinematicMidjourney currently uses an unofficial third party package. Use this integration at your own risk.
To configure Midjourney, you will need the following:
- Discord Server ID and Channel ID
- Obtain by going to your Discord channel in a browser which should follow this pattern -
https://discord.com/channels/SERVER_ID/CHANNEL_ID
- Obtain by going to your Discord channel in a browser which should follow this pattern -
- Invite Midjourney bot to your server
- While not necessary, it is also recommended to use a Hugging Face token for security prompts
All other default settings found bellow will also be applied. You can overwrite the settings by updating your config.yml file.
# midjourney settings (default: shown below)
midjourney:
# discord server id
server_id:
# discord channel id
channel_id:
# discord token (https://linuxhint.com/get-discord-token)
token:
# hugging face token (https://huggingface.co/docs/hub/security-tokens)
hugging_face_token:
image:
# enable or disable image generation
enable: true
# trim letterbox and pillarbox images
trim: false
# options added to a prompt that change how an image generates (https://docs.midjourney.com/docs/parameter-list)
parameters: --chaos 80 --no text
# upscale options (false, random, 1,2,3,4)
upscale: random
# used with summary to guide the image model towards a particular style
style:
- cinematicTo configure Stability AI, obtain an API key and add it to your config like the following. All other default settings found bellow will also be applied. You can overwrite the settings by updating your config.yml file.
# stabilityai settings (default: shown below)
stabilityai:
# api key
key:
image:
# enable or disable image generation
enable: true
# trim letterbox and pillarbox images
trim: false
# number of seconds before the request times out and is aborted
timeout: 30
# engined used for image generation
engine_id: stable-diffusion-512-v2-1
# width of the image in pixels, must be in increments of 64
width: 512
# height of the image in pixels, must be in increments of 64
height: 512
# how strictly the diffusion process adheres to the prompt text (higher values keep your image closer to your prompt)
cfg_scale: 7
# number of images to generate for each style
samples: 1
# number of diffusion steps to run
steps: 50
# image model style (https://platform.stability.ai/rest-api#tag/v1generation/operation/textToImage)
style:
- cinematicTo configure DeepAI, obtain an API key and add it to your config like the following. All other default settings found bellow will also be applied. You can overwrite the settings by updating your config.yml file.
# deepai settings (default: shown below)
deepai:
# api key
key:
image:
# enable or disable image generation
enable: true
# trim letterbox and pillarbox images
trim: false
# number of seconds before the request times out and is aborted
timeout: 30
# 1 returns one image and 2 returns four images
grid_size: 1
# width of the image in pixels, between 128 and 1536
width: 512
# height of the image in pixels, between 128 and 1536
height: 512
# indicate what you want to be removed from the image
negative_prompt:
# image model style (https://deepai.org/machine-learning-model/text2img)
style:
- text2imgTo configure Dream, obtain an API key and add it to your config like the following. All other default settings found bellow will also be applied. You can overwrite the settings by updating your config.yml file.
# dream settings (default: shown below)
dream:
# api key
key:
image:
# enable or disable image generation
enable: true
# trim letterbox and pillarbox images
trim: false
# number of seconds before the request times out and is aborted
timeout: 30
# width of the image in pixels
width: 512
# height of the image in pixels
height: 512
# image model style (https://api.luan.tools/api/styles)
style:
- buliojourney v2To configure Leonardo.Ai, obtain an API key and add it to your config like the following. All other default settings found bellow will also be applied. You can overwrite the settings by updating your config.yml file.
# leonardoai settings (default: shown below)
leonardoai:
# api key
key:
image:
# enable or disable image generation
enable: true
# trim letterbox and pillarbox images
trim: false
# number of seconds before the request times out and is aborted
timeout: 30
# indicate what you want to be removed from the image
negative_prompt:
# model id used for the image generation, if not provided uses sd_version to determine the version of stable diffusion to use
model_id: 6bef9f1b-29cb-40c7-b9df-32b51c1f67d3
# base version of stable diffusion to use if not using a custom model
sd_version: v2
# number of images to generate for each style
num_images: 1
# width of the image in pixels, must be between 32 and 1024 and be a multiple of 8
width: 512
# height of the image in pixels, must be between 32 and 1024 and be a multiple of 8
height: 512
# number of inference steps to use for the generation, must be between 30 and 60
num_inference_steps:
# how strongly the generation should reflect the prompt, must be between 1 and 20.
guidance_scale: 7
# scheduler to generate images with
scheduler:
# style to generate images with
preset_style: LEONARDO
# whether the generated images should tile on all axis
tiling:
# whether the generated images should show in the community feed
public:
# enable to use prompt magic
prompt_magic:
# used with summary to guide the image model towards a particular style
style:
- cinematic# time settings (default: shown below)
time:
# defaults to iso 8601 format with support for token-based formatting
# https://github.com/moment/luxon/blob/master/docs/formatting.md#table-of-tokens
format:
# time zone used in logs
timezone: UTC# log settings (default: shown below)
logs:
# options: silent, error, warn, info, http, verbose, debug, silly
level: info# telemetry settings (default: shown below)
# self hosted version of plausible.io
# 100% anonymous, used to help improve project
# no cookies and fully compliant with GDPR, CCPA and PECR
telemetry: true| Service | Command | URL |
|---|---|---|
| UI | npm run local:frontend |
localhost:8080 |
| API | npm run local:api |
localhost:3000 |
./.develop/build