Database Schema v7.0.0:
- Create new 'gb' schema with PostgreSQL ENUMs instead of VARCHAR for all domain values
- Add sharding infrastructure (shard_config, tenant_shard_map tables)
- Implement partitioned tables for sessions, messages, and analytics (monthly partitions)
- Add Snowflake-like ID generation for distributed systems
- Design for billion-user scale with proper indexing strategies
Rust Enums:
- Add comprehensive enum types in core/shared/enums.rs
- Implement ToSql/FromSql for Diesel ORM integration
- Include: ChannelType, MessageRole, MessageType, LlmProvider, ContextProvider
- Include: TaskStatus, TaskPriority, ExecutionMode, RiskLevel, ApprovalStatus, IntentType
- All enums stored as SMALLINT for efficiency
Other fixes:
- Fix hardcoded gpt-4 model in auto_task modules to use bot config
- Add vector_db to required bootstrap components
- Add Qdrant health check before KB indexing
- Change verbose START messages to trace level
- Fix episodic memory role handling in Claude client
- Disable auth for /api routes during development
This is a DESTRUCTIVE migration - only for fresh installations.
- Fix match arms with identical bodies by consolidating patterns
- Fix case-insensitive file extension comparisons using eq_ignore_ascii_case
- Fix unnecessary Debug formatting in log/format macros
- Fix clone_from usage instead of clone assignment
- Fix let...else patterns where appropriate
- Fix format! append to String using write! macro
- Fix unwrap_or with function calls to use unwrap_or_else
- Add missing fields to manual Debug implementations
- Fix duplicate code in if blocks
- Add type aliases for complex types
- Rename struct fields to avoid common prefixes
- Various other clippy warning fixes
Note: Some 'unused async' warnings remain for functions that are
called with .await but don't contain await internally - these are
kept async for API compatibility.
- Add BOTSERVER_INSTALLERS_PATH env var to use local installers without downloading
- Replace hardcoded ./botserver-stack paths with configurable stack_path
- Add stack_dir() and vault_bin() helper methods in BootstrapManager
- Add Port: 8300 to Zitadel config to fix port binding issue
- Start Directory service before setup_directory() call
- Add SKIP_LLM_SERVER env var to skip local LLM in tests
- Update template loading to check ../bottemplates and botserver-templates paths
Instead of downloading pre-built binaries (which may require AVX2),
compile llama.cpp from source during installation. This ensures:
- Works on older CPUs (Sandy Bridge, Haswell, etc.)
- Uses GGML_NATIVE=ON to optimize for the current CPU
- Binary path updated to build/bin/llama-server
Reverts the AVX2 detection that was incorrectly disabling LLM.
- Add cpu_supports_avx2() function to check /proc/cpuinfo for AVX2 flag
- Skip LLM binary download on CPUs without AVX2 (pre-built llama.cpp requires it)
- Add runtime check for llama-server binary compatibility (catches 'Illegal instruction')
- Provide helpful error messages about alternatives (compile from source or use external API)
- Sandy Bridge (2nd gen i7) and older CPUs now gracefully skip local LLM
When llm-server=false in bot_configuration, the code now skips
attempting to start local llama-server processes. This prevents
the 60-attempt timeout error when using external LLM endpoints
or when local LLM serving is intentionally disabled.
- Add email-read-pixel config parameter to enable/disable tracking
- Implement tracking pixel injection in HTML emails
- Add sent_email_tracking table with migration
- Create 4 new API endpoints:
- GET /api/email/tracking/pixel/{id} - serve pixel & record read
- GET /api/email/tracking/status/{id} - get email read status
- GET /api/email/tracking/list - list all tracked emails
- GET /api/email/tracking/stats - get aggregate statistics
- Store tracking data: read_at, read_count, IP, user_agent
- Integrate with send_email() to auto-inject pixel when enabled
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
The commit adds a complete example environment configuration file
documenting all available settings for BotServer, including logging,
database, server, drive, LLM, Redis, email, and feature flags.
Also removes hardcoded environment variable usage throughout the
codebase, replacing them with configuration via config.csv or
appropriate defaults. This includes:
- WhatsApp, Teams, Instagram adapter configurations
- Weather API key handling
- Email and directory service configurations
- Console feature conditionally compiles monitoring code
- Improved logging configuration with library suppression
The sqlx database library has been removed from the project along with
associated database-specific code that was no longer being used. This
includes removal of various sqlx-related dependencies from Cargo.lock
and cleanup of database connection pool references.
Added actix-files and its dependencies (http-range, mime_guess, unicase, v_htmlescape) to enable static file functionality in the botserver. This will allow serving static assets and files through the web server. The change includes all required transitive dependencies for proper file handling and MIME type detection.
Removed commented-out code for deprecated LLM server arguments (n_moe, parallel, cont_batching, etc.) since these are no longer used. Also cleaned up the model arguments string by removing --jinja and --flash-attn flags which were moved to TODO comments for future config implementation. The change simplifies the server startup code while maintaining core functionality.
Added the --jinja flag to the LLM server startup arguments to enable Jinja template support. This allows for more flexible prompt formatting when using the local LLM server. The change maintains all existing functionality while adding the new feature.
Removed the redundant `--verbose` flag from Windows command since it's not needed. Standardized log file names to `llm-stdout.log` and `llmembd-stdout.log` for consistency across platforms. This makes log management simpler and more predictable.
Added the `--flash-attn on` flag to the LLM server startup arguments to enable flash attention optimization. This improves performance while maintaining existing parameters (top_p, temp, repeat-penalty). A TODO was added to move these parameters to config for better maintainability.
Updated the parameter name from 'n-ctx-size' to 'ctx-size' in both config lookup and argument formatting for consistency. This change aligns with the naming convention used elsewhere in the codebase and makes the parameter name more concise while maintaining clarity. The functionality remains unchanged.
Changed the config key 'llm-server-n_ctx_size' to 'llm-server-n-ctx-size' in local.rs to maintain consistent hyphen-separated naming convention across configuration parameters. This improves code readability and aligns with existing naming patterns.
Added support for configuring the context window size (n_ctx_size) when starting the local LLM server. The parameter is read from config with a default value of 4096 if not specified. This allows for better control over the model's memory usage and performance characteristics.
- Remove trace logs in compact_prompt.rs that were cluttering logs without adding value
- Simplify LLM server args in local.rs by removing redundant --reasoning-format parameter
- Add ID to float menu div in index.html for better DOM targeting
- Clean up code by removing unnecessary debug logging while maintaining functionality
Added diesel_migrations crate (v2.3.0) to enable database migration functionality. Updated Cargo.toml and Cargo.lock to include the new dependency along with its required sub-dependencies (migrations_internals and migrations_macros). Also made minor cleanups in the codebase:
- Removed unused UI code from platform README
- Cleaned up LLM server initialization code
- Added additional build dependencies in documentation
Include retrieval and passing of `llm-key` from configuration to LLM provider methods for secure authentication. Also refine role naming in compact prompts and remove unused logging import.
Include model parameter in LLM provider calls across automation, bot, and keyword modules to ensure correct model selection based on configuration. This improves flexibility and consistency in LLM usage.
Removed the legacy TABLES_SERVER environment variable check and related database connection logic. Simplified the bootstrap process to always generate new credentials and write them to .env file. Also updated drive monitor log message to use "Drive" instead of "S3" for consistency. #464
Refactored the prompt construction in compact_prompt.rs to use a single formatted string instead of multiple JSON messages. The conversation is now built as a single string with clear formatting markers, and the role names are more readable (User/Bot instead of user/bot). Also removed a trailing slash from the OpenAI API endpoint URL in llm/mod.rs for consistency.
The changes improve readability of the prompt structure and ensure consistent API endpoint formatting. The summarization request is more clearly formatted for the LLM while maintaining the same functionality.
Refactored the compact_prompt_for_bots function to use structured JSON messages instead of plain text formatting. Removed unused execute_compact_prompt method and related code from automation service as the functionality is now handled elsewhere. The changes include:
- Using serde_json to structure messages for LLM
- Improved error handling and fallback mechanism
- Cleaned up obsolete compact prompt execution code
Added parse_messages method to handle structured prompt input for OpenAI API. The method converts human/bot/compact prefixes to appropriate OpenAI roles (user/assistant/system) and properly formats multi-line messages. This enables more complex conversation structures in prompts while maintaining compatibility with the OpenAI API format.
Removed the direct prompt-to-message conversion in generate and generate_stream methods, replacing it with the new parse_messages utility. Also reorganized the impl blocks for better code organization.
- 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.
