Major additions:
- Video editing engine with AI features (transcription, captions, TTS, scene detection)
- RBAC middleware and organization management
- Security enhancements (MFA, passkey, DLP, encryption, audit)
- Billing and subscription management
- Contacts management
- Dashboards module
- Learn/LMS module
- Social features
- Compliance (SOC2, SOP middleware, vulnerability scanner)
- New migrations for RBAC, learn, and video tables
- Move app_generator, intent_classifier, intent_compiler, autotask_api, designer_ai, ask_later, auto_task, safety_layer to src/auto_task/
- Create auto_task/mod.rs with exports and route configuration
- Update imports in moved files
- Update main.rs to use auto_task::configure_autotask_routes
- Keep table_definition in keywords (shared utility)
- Add execute_task_handler for POST /api/autotask/:task_id/execute
- Add get_task_logs_handler for GET /api/autotask/:task_id/logs
- Add apply_recommendation_handler for POST /api/autotask/recommendations/:rec_id/apply
- Update route configuration in mod.rs
- New mcp_directory.rs: McpCsvLoader to load MCP servers from mcp.csv
- CSV format: name,type,command,args,description,enabled,auth_type,auth_env
- Support for stdio, http, websocket, tcp connection types
- Support for api_key and bearer authentication
- Updated sources/mod.rs with MCP management API endpoints
- New sources/mcp.rs with helper functions
- MCP tools available to Tasks like BASIC keywords
- intent_compiler.rs: LLM-to-BASIC translation engine
- auto_task.rs: Auto-executing task data structures
- mcp_client.rs: Model Context Protocol server integration
- safety_layer.rs: Constraints, simulation, audit trail
- autotask_api.rs: HTTP API handlers for Auto Task UI
- Updated mod.rs with new modules and keyword list
This commit introduces comprehensive documentation and implementation
for multi-agent orchestration capabilities:
- Add IMPLEMENTATION-PLAN.md with 4-phase roadmap
- Add Kubernetes deployment manifests (deployment.yaml, hpa.yaml)
- Add database migrations for multi-agent tables (6.1.1, 6.1.2)
- Implement A2A protocol for agent-to-agent communication
- Implement user memory keywords for cross-session persistence
- Implement model routing for dynamic L
update and code refactoring focused on:
1. Adding new documentation pages to the table of contents
2. Restructuring the bot templates documentation
3. Changing keyword syntax from underscore format to space format (e.g.,
`SET_BOT_MEMORY` → `SET BOT MEMORY`)
4. Updating compiler and keyword registration to support the new
space-based syntax
5. Adding new keyword modules (social media, lead scoring, templates,
etc.)
Refactor BASIC keywords to use spaces instead of underscores
Change keyword syntax from underscore format (SET_BOT_MEMORY) to more
natural space-separated format (SET BOT MEMORY) throughout the codebase.
Key changes:
- Update Rhai custom syntax registration to use space tokens
- Simplify compiler preprocessing (fewer replacements needed)
- Update all template .bas files to use new syntax
- Expand documentation with consolidated examples and new sections
- Add new keyword modules: social_media, lead_scoring, send_template,
core_functions, qrcode, sms, procedures, import_export, llm_macros,
on_form_submit
Add flate2 and tar dependencies for archive extraction support in file
operations. Update documentation with:
- New BASIC keywords: SWITCH/CASE, WEBHOOK, INSTR, IS_NUMERIC
- HTTP operations: POST, PUT, PATCH, DELETE_HTTP, GRAPHQL, SOAP
- Data operations: SAVE, INSERT, UPDATE, DELETE, MERGE, FILTER, etc.
- File operations: READ, WRITE, COMPRESS, EXTRACT, GENERATE_PDF, etc.
Simplify README and add appendices for external services and environment
variables. Add monitoring dashboard and player UI docs.
Introduces IMAGE, VIDEO, AUDIO, and SEE keywords for BASIC scripts that
connect to the botmodels service for AI-powered media generation and
vision/captioning capabilities.
- Add BotModelsClient for HTTP communication with botmodels service
- Implement BASIC keywords: IMAGE, VIDEO, AUDIO (generation), SEE
(captioning)
- Support configuration via config.csv for models
Changed incorrect references to .vbs files to .bas and corrected
USE_WEBSITE keyword naming. Also added missing fields to API response
structure and clarified that start.bas is optional for bots.
- Renamed `execute_compact_prompt` to `compact_prompt_for_bots` and simplified logic
- Removed redundant comments and empty lines in test files
- Consolidated prompt compaction threshold handling
- Cleaned up UI logging implementation by removing unnecessary whitespace
- Improved code organization in ui_tree module
The changes focus on code quality improvements, removing clutter, and making the prompt compaction logic more straightforward. Test files were cleaned up to be more concise.
Removed several unused dependencies from Cargo.lock including:
- auto_generate_cdp
- headless_chrome
- scraper
- cssparser and related crates
- dtoa and dtoa-short
- string_cache and related crates
- tendril
- tungstenite 0.27.0
Also updated ureq dependency to single version (removed duplicate entry). This cleanup reduces the dependency tree and removes unused code.
Added tracking of previously scheduled scripts using a `HashSet` and initialized it in `BasicCompiler::new`. Updated `compile_file` and `preprocess_basic` to require mutable access, allowing schedule cleanup before processing. Implemented logic to delete existing scheduled automations for a script using Diesel queries, ensuring old schedules are removed when a script is recompiled without a `SET_SCHEDULE`. Added necessary Diesel imports and `TriggerKind` reference. This prevents duplicate or orphaned scheduled tasks.
- Simplified auth module by removing unused imports and code
- Cleaned up shared models by removing unused structs (Organization, User, Bot, etc.)
- Updated add-req.sh to comment out unused directories
- Modified LLM fallback strategy in README with additional notes about model behaviors
The changes focus on removing unused code and improving documentation while maintaining existing functionality. The auth module was significantly reduced by removing redundant code, and similar cleanup was applied to shared models. The build script was adjusted to reflect currently used directories.
Updated references from `redis_client`, `s3_client`, and `custom_conn` to unified names `cache`, `drive`, and `conn` for consistency across modules. Adjusted `add_suggestion_keyword` to use clearer parameter naming and enhanced custom syntax registration for better readability and maintainability.
Added new `add_suggestion` module to support suggestion handling logic.
Updated `index.html` to include a dynamic suggestions container that fetches and displays context suggestions.
This improves user experience by enabling quick context changes through interactive suggestion buttons.
- Rename script_name to param in automation flow and DB schema
- Add BotMemory model and bot_memories table
- Remove script_name field from automation
- Enable sqlite support via rusqlite and related crates (optional)
- Update prompts and queries to use param instead of script_name
- Remove deprecated annoucements GBai templates and align add-req.sh
- Refactor main to initialize automation service and simplify startup
