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Merge pull request #72 from rishikanthc/feature/handle-thinking-field
Feature: Handle thinking field support and fix markdown rendering
2 parents cba7e16 + 7350a47 commit 3c17b74

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‎.dockerignore‎

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.dockerdata
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docker-compose.ollama.yaml
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Dockerfile
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Dockerfile-cuda128
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install_audiowaveform.sh
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samples
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scriberr_files
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scriberr
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install_aw.sh
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.prettier*
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venv
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node_modules
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*.env
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# Exclude version control files
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.git
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.gitignore
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.gitattributes
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# Docker-related files
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.dockerdata
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docker-compose*.yml
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docker-compose*.yaml
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Dockerfile*
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install_audiowaveform.sh
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install_aw.sh
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# Runtime data directories
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samples
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scriberr_files
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scriberr
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uploads
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temp
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.downloads
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# Development and build artifacts
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.prettier*
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venv
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.venv
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node_modules
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build
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dist
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.svelte-kit
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.eslintcache
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.npm
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npm-debug.log*
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# Environment variables and secrets
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*.env
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.env
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.env.*
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.ENV
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.env.local
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.env.development
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.env.test
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.env.production
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# IDE specific files
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.idea
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.vscode
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*.swp
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*.swo
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*.sublime-workspace
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*.sublime-project

‎.env‎

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# .env file
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# Docker image configuration
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IMAGE_TAG=main # Docker image tag to use for building the Docker image
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PORT=3000 # Port to use for running the web interface
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# Database configuration
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POSTGRES_PORT=5432 # Port to use for PostgreSQL database
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POSTGRES_USER=root # Username for PostgreSQL database
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POSTGRES_PASSWORD=mysecretpassword # Password for PostgreSQL database
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POSTGRES_DB=local # Database name
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DATABASE_URL=postgres://root:mysecretpassword@db:5432/local # Database URL for connection to PostgreSQL database with credentials from above
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# Application configuration
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ADMIN_USERNAME=admin # Username for admin user in web interface
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ADMIN_PASSWORD=password # Password for admin user in web interface
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# AI configuration
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# Default Model to use for transcription, can be set to any OpenAI model or Ollama model
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# For ollama connections, enter the model name and version number. EG: llama3.2:latest
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AI_MODEL="gpt-3.5-turbo"
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# Leave blank to use default (OpenAI API), otherwise set to the base URL of your OpenAI API compatible server
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# For ollama connections, enter the IP of the Ollama server, and then the port it is running on.
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# Include the /v1/ or /api/v1/ path if needed (OpenWeb UI uses /api/ and ollama uses /v1/
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# Example: http://192.168.1.5:11434 or http://host.docker.internal:11434
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# NOTE: host.docker.internal is only available on Windows and MacOS, use the IP address of the host machine on Linux
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# NOTE: localhost and 127.0.0.1 will not work, as they refer to the container itself, not the host machine
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OLLAMA_BASE_URL=""
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# API Keys
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# NOTE:
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# If using Ollama, you can leave these blank or set to a dummy value
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# If using OpenAI, you must set these to your API keys
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# If using a custom API compatible server, you must set these to your API keys
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OPENAI_API_KEY="" # Needed for retrieving models from OpenAI, for Ollama connections, this can be left blank or set to a dummy value
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HF_API_KEY="" # Needed for retrieving models from HuggingFace for Diarization
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# Diarization configuration
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# Default Model to use for Diarization, can be set to any HuggingFace model that supports diarization
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# NOTE: This model will be downloaded automatically if it is not already present in the models directory
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# NOTE: You can use any model that supports diarization, but the default model is pyannote/speaker-diarization
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# NOTE: You can find a list of models that support diarization here: https://huggingface.co/models?other=speaker-diarization
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DIARIZATION_MODEL=pyannote/speaker-diarization
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MODELS_DIR=/scriberr/models
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WORK_DIR=/scriberr/temp
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AUDIO_DIR=/scriberr/uploads
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# Server configuration
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BODY_SIZE_LIMIT=1G
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HARDWARE_ACCEL=cpu # Set to 'gpu' if you have a Nvidia GPU
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# .env file
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# Docker image configuration
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IMAGE_TAG=main # Docker image tag to use for building the Docker image
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PORT=3000 # Port to use for running the web interface
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# Database configuration
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POSTGRES_PORT=5432 # Port to use for PostgreSQL database
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POSTGRES_USER=root # Username for PostgreSQL database
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POSTGRES_PASSWORD=mysecretpassword # Password for PostgreSQL database
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POSTGRES_DB=local # Database name
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DATABASE_URL=postgres://root:mysecretpassword@db:5432/local # Database URL for connection to PostgreSQL database with credentials from above
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# Application configuration
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ADMIN_USERNAME=admin # Username for admin user in web interface
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ADMIN_PASSWORD=password # Password for admin user in web interface
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# AI configuration
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# Default Model to use for transcription, can be set to any OpenAI model or Ollama model
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# For ollama connections, enter the model name and version number. EG: llama3.2:latest
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AI_MODEL="deepseek-r1:8b"
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# Leave blank to use default (OpenAI API), otherwise set to the base URL of your OpenAI API compatible server
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# For ollama connections, enter the IP of the Ollama server, and then the port it is running on.
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# Include the /v1/ or /api/v1/ path if needed (OpenWeb UI uses /api/ and ollama uses /v1/
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# Example: http://192.168.1.5:11434 or http://host.docker.internal:11434
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# NOTE: host.docker.internal is only available on Windows and MacOS, use the IP address of the host machine on Linux
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# NOTE: localhost and 127.0.0.1 will not work, as they refer to the container itself, not the host machine
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OLLAMA_BASE_URL="http://192.168.50.5:11434/v1"
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# API Keys
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# NOTE:
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# If using Ollama, you can leave these blank or set to a dummy value
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# If using OpenAI, you must set these to your API keys
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# If using a custom API compatible server, you must set these to your API keys
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OPENAI_API_KEY="" # Needed for retrieving models from OpenAI, leave blank when using Ollama
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HF_API_KEY="" # Needed for retrieving models from HuggingFace for Diarization
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# Diarization configuration
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# Default Model to use for Diarization, can be set to any HuggingFace model that supports diarization
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# NOTE: This model will be downloaded automatically if it is not already present in the models directory
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# NOTE: You can use any model that supports diarization, but the default model is pyannote/speaker-diarization
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# NOTE: You can find a list of models that support diarization here: https://huggingface.co/models?other=speaker-diarization
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DIARIZATION_MODEL=pyannote/speaker-diarization
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MODELS_DIR=/scriberr/models
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WORK_DIR=/scriberr/temp
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AUDIO_DIR=/scriberr/uploads
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# Server configuration
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BODY_SIZE_LIMIT=1G
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HARDWARE_ACCEL=cpu # Set to 'gpu' if you have a Nvidia GPU

‎.github/workflows/Main Cuda Docker Build.yml‎

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name: Main CUDA Docker Build
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on:
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push:
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branches:
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- main # Only trigger on pushes to the main branch
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jobs:
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docker:
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runs-on: ubuntu-latest
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steps:
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- name: Delete huge unnecessary tools folder
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run: rm -rf /opt/hostedtoolcache
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- name: Set up QEMU
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uses: docker/setup-qemu-action@v3
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- name: Set up Docker Buildx
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uses: docker/setup-buildx-action@v3
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- name: Login to GHCR
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uses: docker/login-action@v3
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with:
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registry: ghcr.io
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username: ${{ github.repository_owner }}
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password: ${{ secrets.GITHUB_TOKEN }}
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- name: Build and push scriberr:main-gpu Docker image
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uses: docker/build-push-action@v6
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with:
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platforms: linux/amd64,linux/arm64
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push: true
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file: ./Dockerfile-cuda128
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tags: |
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ghcr.io/rishikanthc/scriberr:main-cuda128
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- name: Verify multi-platform image for scriberr:main-gpu
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run: |
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name: Main CUDA Docker Build
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on:
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push:
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branches:
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- main # Only trigger on pushes to the main branch
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jobs:
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docker:
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runs-on: ubuntu-latest
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steps:
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- name: Delete huge unnecessary tools folder
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run: rm -rf /opt/hostedtoolcache
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- name: Set up QEMU
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uses: docker/setup-qemu-action@v3
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- name: Set up Docker Buildx
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uses: docker/setup-buildx-action@v3
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- name: Login to GHCR
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uses: docker/login-action@v3
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with:
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registry: ghcr.io
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username: ${{ github.repository_owner }}
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password: ${{ secrets.GITHUB_TOKEN }}
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- name: Build and push scriberr:main-gpu Docker image
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uses: docker/build-push-action@v6
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with:
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platforms: linux/amd64,linux/arm64
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push: true
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file: ./Dockerfile-cuda128
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tags: |
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ghcr.io/rishikanthc/scriberr:main-cuda128
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- name: Verify multi-platform image for scriberr:main-gpu
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run: |
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docker buildx imagetools inspect ghcr.io/rishikanthc/scriberr:main-cuda128

‎.github/workflows/Main Docker Build.yml‎

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name: Main Docker Build
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on:
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push:
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branches:
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- main # Only trigger on pushes to the main branch
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jobs:
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docker:
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runs-on: ubuntu-latest
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steps:
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- name: Delete huge unnecessary tools folder
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run: rm -rf /opt/hostedtoolcache
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- name: Set up QEMU
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uses: docker/setup-qemu-action@v3
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- name: Set up Docker Buildx
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uses: docker/setup-buildx-action@v3
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- name: Login to GHCR
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uses: docker/login-action@v3
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with:
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registry: ghcr.io
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username: ${{ github.repository_owner }}
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password: ${{ secrets.GITHUB_TOKEN }}
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- name: Build and push scriberr:main Docker image
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uses: docker/build-push-action@v6
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with:
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platforms: linux/amd64,linux/arm64
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push: true
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file: ./Dockerfile
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tags: |
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ghcr.io/rishikanthc/scriberr:main
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- name: Verify multi-platform image for scriberr:main
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run: |
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docker buildx imagetools inspect ghcr.io/rishikanthc/scriberr:latest
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name: Main Docker Build
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on:
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push:
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branches:
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- main # Only trigger on pushes to the main branch
7+
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jobs:
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docker:
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runs-on: ubuntu-latest
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steps:
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- name: Delete huge unnecessary tools folder
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run: rm -rf /opt/hostedtoolcache
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- name: Set up QEMU
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uses: docker/setup-qemu-action@v3
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- name: Set up Docker Buildx
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uses: docker/setup-buildx-action@v3
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- name: Login to GHCR
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uses: docker/login-action@v3
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with:
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registry: ghcr.io
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username: ${{ github.repository_owner }}
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password: ${{ secrets.GITHUB_TOKEN }}
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- name: Build and push scriberr:main Docker image
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uses: docker/build-push-action@v6
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with:
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platforms: linux/amd64,linux/arm64
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push: true
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file: ./Dockerfile
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tags: |
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ghcr.io/rishikanthc/scriberr:main
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- name: Verify multi-platform image for scriberr:main
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run: |
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docker buildx imagetools inspect ghcr.io/rishikanthc/scriberr:latest

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