- Split AIConfig into separate LLMConfig and embedding config structs
- Update create_site.rs to use config.llm instead of config.ai
- Improve config loading comments in bootstrap manager
- Add new LLM-related environment variables with defaults
- Maintain backward compatibility with existing config loading
- Clean up unused AIConfig struct and related code
The change better organizes the AI-related configuration by separating LLM and embedding configurations, making the code more maintainable and flexible for future AI service integrations.
- Replace direct database connection establishment with shared `establish_pg_connection` utility
- Add "llm" to required components list in bootstrap manager
- Lower default RUST_LOG level from debug to info in VSCode config
- Clean up imports and connection error messages
- Remove hardcoded database URL strings in favor of centralized connection handling
The changes improve code maintainability by centralizing database connection logic and adding support for the new LLM component in the bootstrap process.
Add logic to automatically upload an initial `config.csv` to the default S3 bucket during bootstrap. Enhance S3 operator creation by ensuring endpoint formatting, setting default bucket and region, and enabling path style. Improve template upload flow by validating bucket existence and creating it if missing. Also include debug logging for better traceability.
Eliminates the `s3_bucket` field from `AppConfig` and deletes related initialization code in `main.rs`. This simplifies configuration management since S3 bucket handling is no longer required or used in the application.
- Removed unused Tauri dependencies and replaced aws-sdk-s3 with opendal for S3 services.
- Cleaned up feature flags in Cargo.toml.
- Simplified the welcome message logic in start.bas and removed redundant comments.
- Introduced AWS SDK dependencies for S3 and CSV handling.
- Implemented logic to check and update the default bot configuration in S3 after component installation.
- Added a new configuration CSV template for bot settings.
- Refactored package manager to register cache component with updated download URL and binary name.
- Updated README and Cargo files to reflect new dependencies and configuration options.
- Derive bot_id from BOT_GUID env var
- Guard concurrent runs with Redis
- Read CACHE_URL for Redis connection
- Extend bot memory keyword to accept comma as separator
- Increase LLM timeouts to 180s (local and legacy)
- Update templates to use bot memory (GET_BOT_MEMORY/SET_BOT_MEMORY)
- Fix start script path to announcements.gbai
- 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
Remove unnecessary async spawn in TALK handling and use `try_send` on
the WebSocket channel. Acquire `response_channels` with `try_lock` and
spawn an async task only when falling back to the web adapter. Clean up
debug logs and add missing `env` import. Also delete an extra blank line
in the announcement start script.
- Strip content up to the “final<|message|>” token in OpenAI responses.
- Replace the text‑based connection‑status indicator with a small
flashing circle.
- Simplify updateConnectionStatus to take only the status argument.
- Remove special handling of the initial assistant message and
streamline empty‑state removal.
- Clean up stray blank lines in the announcement template.
- Execute GET requests in a dedicated thread with its own Tokio runtime,
add timeout handling and clearer error messages.
- Tighten `is_safe_path` checks and simplify HTTP/S3 logic.
- Change `llm_keyword` to accept `Arc<AppState>`, add prompt builder,
run LLM generation in an isolated thread with timeout.
- Update keyword registration call in `basic/mod.rs`.
- Convert template script to use `let` declarations and return a
boolean.
- Introduce connection‑status indicator in the web UI with styles,
automatic reconnection attempts, and proper WS/WSS handling for voice.
- Replace async task spawning with `block_in_place` to simplify GET
handling
- Add detailed safety checks for file paths and organization prefixes
- Introduce timeout and keep‑alive settings for HTTP client
- Improve S3 bucket access with existence check, timeouts, and richer
logging
- Switch tracing logs to debug and add warning logs where appropriate
- Update announcement template to retrieve a PDF, generate a resume via
LLM, and set context for subsequent queries.
- Extract LLM generation into `execute_llm_generation` and simplify
keyword handling.
- Prepend system prompt and session context to LLM prompts in
`BotOrchestrator`.
- Parse incoming WebSocket messages as JSON and use the `content` field.
- Add async `get_session_context` and stop injecting Redis context into
conversation history.
- Change default LLM URL to `http://48.217.66.81:8080` throughout the
project.
- Use the existing DB pool instead of creating a separate custom
connection.
- Update `start.bas` to call LLM and set a new context string.
- Refactor web client message handling: separate event processing,
improve streaming logic, reset streaming state on thinking end, and
remove unused test functions.
- Use `tokio::spawn` to run Redis SET for `SET_CONTEXT` in a background
task with detailed tracing.
- Move context retrieval from `BotOrchestrator` to `SessionManager`,
inserting it as a system message in conversation history.
- Remove redundant Redis fetch logic from `BotOrchestrator`.
- Update `DEV.md` to install `valkey-cli`, reorder cargo tools, and
adjust apt commands.
- Add a `SET_CONTEXT "azul bolinha"` example to the announcements
template.
