- Added a new implementation plan for separating text moderation and voice recording configurations.
- Introduced new configuration keys for text and voice guild/channel IDs with backward compatibility.
- Updated moderation capture and backlog sync to filter based on the new text-specific settings.
- Split shared UI state into distinct text and voice fields, ensuring backward compatibility.
- Enhanced the static dashboard to support separate selections for text and voice channels.
- Created a new media subsystem for audio playback, allowing users to queue, play, skip, and stop audio sources.
- Defined API routes for media control and integrated with existing voice functionalities.
Separate text moderation and voice recording guild/channel state so each workflow can persist and operate independently.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Add Discord-video-stream as a vendored workspace dependency and wire it to use the local selfbot package for development.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Apply low-memory client options and point the workspace vendor package at the optimized selfbot internals for more stable long-running moderation capture.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
- Update submodule `discord.js-selfbot-v13` to latest commit.
- Create implementation plan for modernizing the vendored dependency, focusing on toolchain replacement with Biome and runtime dependency auditing.
- Establish a design document outlining goals, scope, approach, toolchain design, runtime dependency design, and validation steps.
- Ensure public API compatibility and maintain existing functionality during modernization efforts.
- Add `discord.js-selfbot-v13` as a git submodule in `vendor/`
- Update `pnpm-workspace.yaml` to include the new submodule path
- Modify `.gitmodules` to track the submodule repository
- Change `discord.js-selfbot-v13` dependency in `package.json` to use `workspace:*`
- Create implementation and design documents for the submodule integration
- Migrate validation.ts from class-transformer/class-validator to Zod
- Apply Biome auto-fixes (import sorting, nodejs protocol)
- Fix duplicate type identifier in validation.ts
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Check for public/app/index.html before falling back to the old
public/index.html so the React moderation dashboard is served at
the root in production while preserving the legacy frontend during
the transition period.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
- Updated .env to use PostgreSQL (neondb) instead of SQLite
- Updated drizzle.ts to support DATABASE_URL connection string
- Regenerated migrations for PostgreSQL syntax
- Bot successfully connects and operates with PostgreSQL
- All database operations working correctly
- Replace all raw SQL queries in messageStore.ts with Drizzle ORM queries
- Remove DatabaseAdapter dependency from messageStore functions
- Update all function signatures to be async and remove db parameter
- Functions now use getDatabase() internally for database access
- Update all call sites in messageCapture.ts, attachmentUploader.ts, aiAnalyzer.ts, webserver.ts, and index.ts
- All functions remain backward compatible in behavior
- TypeScript typecheck passes with no errors
- All tests pass (11 passed)
- Replace direct better-sqlite3 imports with DatabaseAdapter pattern
- Make all muxer-queue functions async to support both SQLite and PostgreSQL
- Update database initialization to use adapter's getDatabase()
- Export DatabaseAdapter as SqliteDatabase for backward compatibility
- Update index.ts to handle async database initialization
- Update webserver.ts to await async database operations
- All functions now work with both SQLite and PostgreSQL backends
- Tests pass, no TypeScript errors
Reduce effective AI batch size so streaming requests finish before timeout. Keep token-based batching but cap each request to 80 messages or about 9k content tokens, and recursively split failed batches instead of marking the whole batch failed.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Batch AI moderation by estimated token budget instead of fixed message count. Send as many messages as fit within an 80k token request budget while keeping one concurrent API request. Include message metadata and chronological conversation context so the model can judge provocation and replies from surrounding discussion.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
MythEclipse