- Copy design tokens CSS directly into repo for Docker compatibility
- Simplify Primitives.tsx to use local design tokens instead of @bytelyst/ui
- Remove @bytelyst/ui dependency to avoid Docker build issues
- Update globals.css to import local tokens.css
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- Added aria-label to logout button for better screen reader support
- Improves accessibility compliance while maintaining existing functionality
- Part of systematic UX improvements across ByteLyst applications
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Phase 1 of UX compliance implementation:
- Add .pnpmfile.cjs for local package resolution from common platform
- Install @bytelyst/ui for shared UI components
- Create Primitives.tsx product adapter for type-safe component extensions
- Integrate @bytelyst/design-tokens CSS variables
- Add lib/utils.ts with cn utility function
- Enable design token usage via CSS custom properties
This establishes the foundation for component normalization and
consistent styling across ByteLyst products, following the UX
implementation guide patterns.
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deploy-invttrdg.sh passes git-derived build args to backend and web Dockerfiles
via a build_image() helper. These surface in the new /api/devops/info endpoint
and the DevOps tab in Settings.
Auto-resolves GITEA_NPM_TOKEN from /opt/bytelyst/.gitea_token if unset, and
switches to direct docker build (--secret) instead of docker compose build
(which doesn't support --secret).
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The deployment scripts need to run docker-prep.sh before building Docker images
to package the @bytelyst/* dependencies as tarballs. This step was missing
after reverting the base image approach.
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Reverting deployment script changes that were part of the base image approach.
The base image strategy is too complex for the current pnpm workspace structure.
Reverting to the proven docker-prep.sh tarball approach.
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Update deploy-all.sh to pull shared base images before building, ensuring
all repos use the latest common package versions.
Changes:
- Add base image pull step (backend and web)
- Use local cache if pull fails
- Apply to all repos in deployment list
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Update deployment scripts to pull shared base images instead of running
docker-prep.sh to pack @bytelyst/* tarballs.
Changes:
- Remove docker-prep.sh execution
- Add base image pull step (backend and web)
- Use local cache if pull fails
Benefits:
- Faster deployment (no tarball packing)
- Simpler deployment process
- Consistent package versions via base images
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Co-Authored-By: Devin <158243242+devin-ai-integration[bot]@users.noreply.github.com>
The deployment scripts were missing the docker-prep.sh step which is required
to pack @bytelyst/* packages into .docker-deps directory and modify package.json
files to use local tarballs. Without this, Docker build fails trying to install
packages from npm registry instead of local tarballs.
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- deploy-invttrdg.sh: Single-repo deployment for trading platform
* Dirty checks (uncommitted changes, unpushed commits)
* Pre-deployment smoke tests (backend contracts, web DOM tests)
* Docker build and deployment (backend + web)
* Post-deployment validation (health checks, endpoint verification)
* Comprehensive smoke testing for production-grade deployment
- deploy-all.sh: Multi-repo deployment orchestration
* Deploy all 4 production repos or specific ones
* Same safety checks and deployment process for each repo
* Health checks for all services
- DEPLOYMENT_GUIDE.md: Complete deployment documentation
* Usage instructions for both scripts
* Service endpoint mappings
* Troubleshooting guide
* Docker management commands
These scripts enable safe, tested production deployments with
comprehensive validation at every stage.
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Co-Authored-By: Devin <158243242+devin-ai-integration[bot]@users.noreply.github.com>
- Add c7bbO_KSLPI_complete_transcript_summary.md with comprehensive bilingual astrological analysis
- Update config.json to use correct Perplexity API model 'sonar'
- Generated summary includes ALP astrology methodology in Tamil and English
- Professional markdown format with structured learning content
- Add summarize_with_perplexity.py script for generating summaries using Perplexity API
- Add config.json for configurable API settings, model parameters, and file paths
- Support for custom prompts and transcript files
- Configurable logging and output formatting
- Integration with existing YouTube transcription workflow
- Integrate Perplexity AI API for intelligent question answering
- Add AIResponseHandler class with question detection and response generation
- Implement automatic question detection using regex patterns
- Add AI commands: /perplexity, /ai on/off for configuration
- Display AI responses in terminal before sending to Slack
- Update configuration management to store Perplexity API key
- Add comprehensive AI features documentation to README
- Update requirements.txt with OpenAI library dependency
- Fix Perplexity model name to use valid 'sonar' model
- Enhance interactive chat mode with AI-powered capabilities
- Maintain backward compatibility with existing CLI functionality
- Add interactive chat mode with persistent configuration storage
- Implement real-time message receiving with polling mechanism
- Add threading support for simultaneous send/receive operations
- Create MessageReceiver class for handling incoming messages
- Add commands: /listen, /stop, /history for two-way communication
- Display sent messages in terminal with timestamps
- Support for environment variables and .env file loading
- Enhanced error handling and user-friendly prompts
- Update README with comprehensive two-way communication documentation
- Maintain backward compatibility with original CLI functionality
