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Steven EnamakelandGitHub
244702d349
* Enhance autocomplete functionality and settings panel
- Added a new AutocompletePanel component for managing inline autocomplete settings, including options for enabling/disabling, debounce timing, and style configurations.
- Integrated autocomplete status tracking and logging within the panel to provide real-time feedback on the autocomplete engine's state.
- Updated settings navigation to include the new autocomplete settings route, improving user accessibility to autocomplete features.
- Introduced new Tauri commands for managing autocomplete operations, including start, stop, and current status retrieval, enhancing interaction with the autocomplete engine.
- Refactored existing code to streamline autocomplete-related functionalities and improve overall maintainability.
* Update TypeScript configuration and add new assets
- Modified `tsconfig.json` to adjust path aliases and include directories for improved module resolution.
- Added new SVG and image assets to the public directory, enhancing the application's visual resources.
- Introduced multiple Lottie animation JSON files for dynamic UI elements, expanding the application's animation capabilities.
* Update project structure and paths for Tauri integration
- Adjusted paths in the pull request template and various workflow files to reflect the new project structure, moving Tauri-related files under the `app` directory.
- Updated commands in the build and release workflows to ensure compatibility with the new file locations.
- Enhanced the test workflow to create the necessary `.env` file in the correct directory for end-to-end testing.
- Added new markdown files for agent prompts and configuration, establishing a foundation for OpenHuman's AI capabilities.
* Refactor project paths and update configurations for Tauri integration
- Adjusted script paths in package.json to reflect the new project structure, ensuring compatibility with the updated directory layout.
- Modified tsconfig.json to correct path aliases and include directories for improved module resolution.
- Introduced a new utility for resolving development paths, enhancing the ability to locate the `rust-core/ai` directory across different project structures.
- Updated Cargo.toml and tauri.conf.json to align with the new directory structure, ensuring proper resource and dependency management.
- Added a new dev_paths module to streamline path resolution logic, improving maintainability and clarity in the codebase.
* Refactor project structure and update configurations for Tauri integration
- Adjusted paths in .gitignore, Cargo.toml, and various scripts to reflect the new directory layout, moving Tauri-related files under the `app` directory.
- Introduced a new package.json file to manage workspace scripts and dependencies effectively.
- Updated end-to-end build and run scripts to ensure compatibility with the new project structure.
- Enhanced documentation in CONTRIBUTING.md to guide contributors on the updated project organization and Tauri command usage.
* Refactor Tauri command invocations to use dedicated utility functions
- Replaced direct `invoke` calls with utility functions from `tauriCommands` for improved readability and maintainability across multiple components.
- Updated `SkillsGrid`, `Skills`, `SkillProvider`, and `SkillManager` to utilize the new command structure, enhancing consistency in Tauri command handling.
- Introduced a new `coreRpcClient` for managing core RPC relay requests, streamlining error handling and request processing.
- Added a new `core_rpc_relay` command in the Tauri backend to facilitate communication with the core service, ensuring better service management and error reporting.
* Refactor Tauri command invocations in intelligence stats and memory manager
- Replaced direct `invoke` calls with utility functions from `tauriCommands` in `useIntelligenceStats` and `MemoryManager` for improved readability and maintainability.
- Updated the `aiListMemoryFiles`, `aiReadMemoryFile`, and `aiWriteMemoryFile` functions to utilize the new command structure, enhancing consistency in Tauri command handling.
- Introduced new command handling in the Rust backend for `ai.list_memory_files`, `ai.read_memory_file`, and `ai.write_memory_file`, streamlining communication with the core service.
* Refactor SkillsGrid and remove SelfEvolveModal component
- Removed the SelfEvolveModal component to streamline the SkillsGrid functionality.
- Updated the SkillsGrid to utilize the runtimeDiscoverSkills function for loading skills, replacing the previous invoke method.
- Simplified the skill entry normalization process by integrating it directly into the skills loading logic.
- Enhanced error handling during skill loading to improve robustness and user feedback.
* Refactor Tauri command invocations to use coreRpcClient
- Replaced direct `invoke` calls with `callCoreRpc` in various components, including `useIntelligenceStats`, `MemoryManager`, `SessionManager`, and `transcript` functions, enhancing code readability and maintainability.
- Updated the Rust backend to handle new command structures for memory and session management, streamlining communication with the core service.
- Improved consistency in handling Tauri commands across the application.
* Refactor Tauri command invocations to utilize coreRpcClient
- Replaced direct `invoke` calls with `callCoreRpc` in `tauriCommands.ts` and `tauriSocket.ts`, enhancing code readability and maintainability.
- Updated the Rust backend to support new command structures for authentication and session management, streamlining communication with the core service.
- Removed legacy socket reporting methods in `tauriSocket.ts`, reflecting a shift towards event-driven socket state management.
- Improved consistency in handling Tauri commands across the application, aligning with recent refactoring efforts.
* Remove pre-commit hook and update TODO list with completed tasks and new objectives. This includes separating the binary from the Tauri codebase, integrating accessibility service installation, and removing Android/iOS support from the codebase.
* Add core server functionality with dispatch and RPC handling
- Introduced new modules for core server operations, including dispatching RPC requests and handling various AI and memory-related commands.
- Implemented a robust structure for managing authentication, configuration, and session states through the `openhuman` namespace.
- Added helper functions for loading configurations, managing memory files, and processing authentication profiles.
- Established a new routing system using Axum for handling HTTP requests, including health checks and RPC endpoints.
- Enhanced error handling and logging throughout the new functionalities to improve maintainability and user feedback.
* Implement core server CLI and modular structure
- Introduced a new CLI module for the core server, enabling various commands for server management, health checks, and configuration settings.
- Established a modular structure for core server functionalities, including dispatching RPC requests and managing settings for models, memory, and runtime.
- Added comprehensive tests to validate the functionality of accessibility and autocomplete commands, ensuring robust error handling and schema compliance.
- Enhanced the overall organization of the core server codebase, improving maintainability and readability.
* Implement AI RPC dispatch functionality
- Introduced a new `ai_rpc` module for handling various AI-related commands, including memory file operations and session management.
- Enhanced the `try_dispatch` function to support commands such as listing, reading, writing memory files, and managing session states.
- Updated the core server dispatch module to integrate the new AI RPC functionality, improving modularity and maintainability.
- Refactored existing code to ensure consistent parameter parsing and error handling across AI commands.
* Update TODO list and refactor Rust core server files
- Added new tasks to the TODO list for documentation updates and feature flag cleanup.
- Introduced `Arc` import in `cli.rs` for improved concurrency handling.
- Cleaned up imports in `helpers.rs` and added conditional compilation for `tauri-host`.
- Removed unused `value_only` function in `types.rs` and added `#[allow(dead_code)]` to `SocketConnectParams` and `SocketEmitParams`.
- Enhanced `try_dispatch` function in `dispatch/mod.rs` for non-tauri-host scenarios.
- Updated `try_dispatch` in `openhuman/platform.rs` to correctly handle session parameters.
- Modified `screen_intelligence` configuration in tests to include new properties for better session management.
* Refactor import statements and enhance code readability
- Cleaned up import statements across multiple files for improved organization and consistency.
- Reformatted code in `cli.rs`, `helpers.rs`, and various dispatch modules to enhance readability.
- Ensured consistent parameter handling in `try_dispatch` functions, improving maintainability.
- Removed unnecessary whitespace and adjusted formatting for better code clarity.
* Refactor project structure and enhance AI memory management
- Consolidated the `openhuman-core` package into a single `Cargo.toml` file, removing the previous `rust-core` directory.
- Introduced new modules for AI memory management, including filesystem-based storage and encryption functionalities.
- Added Tauri commands for initializing memory and session management, enhancing user interaction with memory files.
- Implemented JSON-based storage for memory chunks and session transcripts, improving data accessibility and organization.
- Updated dependencies and features in `Cargo.toml` to support new functionalities and ensure compatibility.
* Update build and release workflows to reflect project structure changes
- Adjusted paths in GitHub Actions workflows to accommodate the consolidation of the `openhuman-core` package into a single `Cargo.toml`.
- Updated import statements in various files to point to the new locations of markdown resources.
- Modified the Tauri configuration to reflect the new resource paths, ensuring proper access to AI prompts.
- Enhanced the staging script to build the standalone binary from the updated project structure.
* Refactor AI directory resolution and update documentation
- Updated the logic for resolving AI directory paths to reflect the new project structure, replacing references to `rust-core/ai` with `src/ai/prompts`.
- Enhanced the `find_ai_directory` function across multiple modules to utilize the new path resolution methods.
- Updated documentation comments to clarify the new directory structure and fallback mechanisms for loading AI prompts.
* Rename `openhuman-core` to `openhuman` across the project
- Updated package names in `Cargo.toml` and `Cargo.lock` to reflect the new naming convention.
- Adjusted references in GitHub Actions workflows and scripts to use the new package name.
- Modified CLI command names and error messages to align with the updated naming.
- Ensured consistency in executable file names and paths throughout the codebase.
* Refactor project commands and update package scripts
- Updated package.json to change workspace references from `openhuman` to `app` for build, compile, dev, format, lint, and test scripts.
- Removed outdated memory and chat command files to streamline the codebase and improve maintainability.
- Adjusted the `lib.rs` file to reflect changes in memory command handling, transitioning to use `callCoreRpc` for Neocortex memory operations.
- Cleaned up the commands module by removing unused imports and consolidating functionality.
* Add Tauri host support and new daemon configuration
- Introduced new modules for Tauri host functionality, including `desktop` and `daemon_host`.
- Added static variables and initialization functions for managing the desktop app handle and resource directory.
- Updated import paths for `HeartbeatEngine` to improve clarity and organization.
- Implemented configuration loading and saving for daemon UI preferences, enhancing user experience.
* Update package names in project configuration
- Changed workspace references in package.json from `app` to `openhuman-app` for consistency.
- Updated the name field in the app's package.json to reflect the new naming convention.
* Remove Tauri host feature flags from core server modules
- Eliminated conditional compilation for Tauri host in `lib.rs`, `helpers.rs`, and `dispatch` modules.
- Streamlined socket management functions and dispatch logic by removing unused code related to Tauri host.
- Improved code clarity and maintainability by consolidating socket-related functionality.
* Enhance Tauri host feature integration and update dependencies
- Added `tauri-host` as a default feature in `Cargo.toml` to streamline feature management.
- Removed explicit feature flag from `openhuman` dependency in `app/src-tauri/Cargo.toml` for cleaner configuration.
- Updated Tauri command attributes in various modules to conditionally compile with the `tauri-host` feature, improving modularity.
- Expanded TODO list to include migration support from OpenClaw, indicating future development focus.
* Refactor authentication and credential management in OpenHuman
- Introduced new modules for handling authentication profiles and tokens, including `anthropic_token`, `openai_oauth`, and `profiles`.
- Removed unused Tauri host-related code from core server modules, enhancing clarity and maintainability.
- Updated `Cargo.toml` and `Cargo.lock` to reflect the removal of the `rquickjs` dependency and other package adjustments.
- Streamlined memory client initialization in dispatch logic to utilize the new `local_memory` module.
- Enhanced code organization by consolidating credential management functionalities and improving the overall structure of the OpenHuman module.
* Enhance Rust core RPC structure and streamline helper functions
- Introduced a dedicated `rpc.rs` file for each domain in the Rust core to manage JSON-RPC and CLI behavior, improving code organization and clarity.
- Refactored helper functions to utilize `rpc_invocation_from_outcome` for consistent handling of RPC responses across various modules.
- Removed unused authentication and credential management functions from `helpers.rs`, consolidating relevant logic into the new RPC structure.
- Updated dispatch logic in multiple modules to leverage the new RPC functions, enhancing maintainability and reducing code duplication.
* Enhance Rust core RPC structure and streamline helper functions
- Introduced a dedicated `rpc.rs` file for each domain in the Rust core to manage JSON-RPC and CLI behavior, improving code organization and clarity.
- Refactored helper functions to utilize `rpc_invocation_from_outcome` for consistent handling of RPC responses across various modules.
- Removed unused authentication and credential management functions from `helpers.rs`, consolidating relevant logic into the new RPC structure.
- Updated dispatch logic in multiple modules to leverage the new RPC functions, enhancing maintainability and reducing code duplication.
* Refactor OpenHuman configuration loading and enhance onboarding RPC
- Replaced the `load_openhuman_config` function with a new `load_config_with_timeout` method to improve timeout handling during configuration loading.
- Consolidated configuration loading logic across various modules, reducing redundancy and enhancing maintainability.
- Introduced new RPC functions for applying settings related to models, memory, screen intelligence, gateway, tunnel, runtime, and browser, streamlining the update process.
- Added onboarding helpers in a new `onboard` module, including a JSON-RPC controller for model refresh operations, improving onboarding flow management.
* Refactor CLI and configuration management in OpenHuman
- Consolidated CLI-related functionality by introducing new modules for settings and credentials management, enhancing code organization.
- Removed redundant functions and streamlined the configuration loading process, improving maintainability.
- Added new CLI helpers for screenshot tools and workspace initialization, facilitating better user experience and onboarding.
- Enhanced JSON-RPC responses to be more compatible with CLI requirements, ensuring consistent output across various commands.
* Remove gateway settings and related functionality from OpenHuman
- Eliminated the GatewaySettingsUpdate interface and associated functions from the codebase, streamlining configuration management.
- Removed references to gateway settings in the CLI and configuration modules, enhancing clarity and maintainability.
- Deleted the gateway module and its related components, including rate limiting and client handling, to simplify the architecture.
- Updated Cargo.toml and Cargo.lock to reflect the removal of dependencies related to gateway functionality.
* Update documentation and improve clarity in OpenHuman
- Revised comments in the `mod.rs`, `traits.rs`, and `pairing.rs` files to enhance clarity and accuracy.
- Updated descriptions related to security policy, long-running processes, and pairing functionality for better understanding.
* Refactor loading prop in TauriCommandsPanel for cleaner code
- Simplified the loading prop assignment in the TauriCommandsPanel component by removing unnecessary line breaks, enhancing readability and maintainability.
* Add OpenSSL dependency and implement OAuth authentication features
- Added OpenSSL as a dependency in `Cargo.toml` to support cryptographic operations.
- Introduced new OAuth-related structures and parameters in `types.rs` for handling authentication flows.
- Implemented OAuth connection and integration token fetching in `auth_socket.rs`, enhancing the authentication capabilities of the OpenHuman module.
- Created new modules for managing authentication profiles and responses, improving the organization of authentication-related code.
- Removed deprecated `anthropic_token` and `openai_oauth` modules to streamline credential management.
- Updated `Cargo.lock` to reflect the addition of the OpenSSL dependency.
* Refactor OpenHuman module and update dependencies
- Added OpenHuman integration entry in the registry for improved backend inference handling.
- Updated various files to enhance code clarity and organization, including adjustments to OAuth client methods and integration tests.
- Refactored import statements and removed unnecessary line breaks for better readability.
- Updated `Cargo.lock` to reflect changes in dependencies and ensure consistency across the project.
* Implement desktop host features and refactor runtime handling
- Introduced new modules for memory management, socket handling, and command definitions to support desktop host functionality.
- Refactored QuickJS runtime initialization to log errors when the engine is not linked, improving clarity on runtime status.
- Added placeholder commands for chat and model interactions, indicating unavailability in the desktop build while maintaining structure for future integration.
- Enhanced organization of the codebase by creating dedicated files for runtime and utility functions, streamlining the development process.
- Updated documentation to reflect new modules and their purposes, ensuring better understanding for future contributors.
* Add CLI banner and print function to enhance user experience
- Introduced a new CLI banner with branding and GitHub link for user engagement.
- Implemented a `print_cli_banner` function to display the banner when running the CLI, improving visibility and user interaction.
- Updated the CLI entry point to call the new banner function, ensuring it appears at startup.
* Add API integration and update dependencies
- Introduced new API modules for handling HTTP requests and WebSocket connections to the TinyHumans backend.
- Added `ureq` dependency for simplified HTTP client functionality, updating `Cargo.toml` and `Cargo.lock` accordingly.
- Implemented configuration and JWT handling in the new `api` module, enhancing session management and API interactions.
- Refactored existing code to utilize the new API helpers, improving code organization and maintainability.
- Updated documentation to reflect new API functionalities and usage guidelines.
* Refactor settings fetching and update dependencies
- Removed the `ureq` dependency and associated functions for fetching settings, streamlining the codebase.
- Updated the `fetch_settings` method to utilize `reqwest` for HTTP requests, enhancing consistency and reliability in API interactions.
- Adjusted the `Cargo.toml` to reflect the removal of `ureq`, ensuring dependencies are up to date.
* Update `ureq` dependency to version 3.3.0 in `Cargo.lock`
- Removed the specific version constraint for `ureq`, allowing for more flexibility in dependency resolution.
- Updated the `Cargo.lock` to reflect the new version of `ureq`, ensuring compatibility with recent changes in the codebase.
* Enhance JSON-RPC logging and CLI initialization
- Introduced a new `rpc_log` module for structured logging of JSON-RPC requests and responses, including redaction of sensitive parameters.
- Updated `execute_core_cli` to initialize logging with a default level and timestamp format.
- Enhanced logging in `rpc_handler` and `dispatch` functions to provide detailed insights into method calls and their execution times.
- Improved error handling logging to capture method failures with context, aiding in debugging and monitoring.
* Refactor HTTP server setup and add integration tests
- Introduced a new `build_core_http_router` function to encapsulate the HTTP routing logic, improving code organization and readability.
- Updated the `run_server` function to utilize the new router function, streamlining server initialization.
- Added comprehensive integration tests for the JSON-RPC API, ensuring robust functionality and error handling in real-world scenarios.
* Enhance OpenHuman backend integration and refactor provider handling
- Added support for the OpenHuman backend in the TauriCommandsPanel, including default configurations and validation for API keys.
- Introduced a new REPL command in the CLI for interactive RPC communication, allowing for dynamic mode switching and message handling.
- Refactored provider creation logic to streamline the integration of the OpenHuman backend, removing deprecated provider overrides and ensuring consistent usage across the codebase.
- Updated various components to improve error handling and user feedback related to provider selection and API interactions.
* Refactor provider handling and update default model settings
- Removed provider override states from the AgentChatPanel and TauriCommandsPanel components, simplifying state management.
- Updated local storage handling to exclude provider overrides, ensuring cleaner data storage.
- Changed default model settings across various components and backend configurations to use "neocortex-mk1" as the new default model.
- Enhanced error handling and validation logic in the TauriCommandsPanel, focusing on model and temperature settings.
- Streamlined integration tests and removed deprecated provider validation logic to improve code clarity and maintainability.
* Refactor code for improved readability and consistency
- Adjusted formatting in several files to enhance code clarity, including consistent parameter passing and alignment.
- Simplified match statement syntax in the `run_models` function for better readability.
- Streamlined assertions in tests to maintain consistency in error handling checks.
- Updated default model name handling in the `AgentBuilder` for cleaner initialization.
* Refactor API URL handling and enhance error reporting
- Updated the `effective_api_url` function to improve clarity in resolving the API base URL, incorporating environment variable checks.
- Enhanced diagnostics in the configuration check to provide clearer messages regarding the API URL status.
- Introduced new error formatting functions to improve the clarity of error messages related to API transport issues.
- Refactored error handling in the OpenAiCompatibleProvider to utilize the new error formatting, ensuring consistent and informative error reporting.
* Refactor API client initialization for consistency
- Updated the instantiation of `BackendOAuthClient` to consistently pass the API URL by reference across multiple functions.
- Simplified the match statement in the `run_models_refresh` function for improved readability.
* Enhance REPL command handling and add fallback mechanisms
- Improved error handling in the REPL command processing, providing clearer feedback for command execution failures.
- Introduced a fallback mechanism for the `agent_chat` RPC call, allowing for graceful degradation to a simpler chat method or a direct backend curl transport if the primary call fails.
- Added a new `backend_chat_via_curl` function to handle chat requests using curl as a last resort, ensuring continued functionality in case of RPC issues.
- Updated the `agent_chat_simple` function to support model overrides and temperature settings, enhancing flexibility in chat interactions.
* Update default Ollama model settings for consistency
- Changed the default Ollama model and vision model to "gemma3:4b-it-qat" for improved alignment across configurations.
- Ensured consistent model naming to enhance clarity in model usage within the local AI module.
* Implement login token consumption and enhance error handling
- Added functionality to consume login tokens via a new API endpoint, returning a JWT for authenticated sessions.
- Improved error handling in the Conversations component, introducing a fallback mechanism for chat interactions when the primary method is unavailable.
- Updated UserProvider to restore session tokens automatically, enhancing user experience during authentication.
- Refactored thread API to support the new login token consumption logic, ensuring seamless integration with the backend.
* Update HTTP client configuration to use Rustls TLS
- Replaced the HTTP/1.1 only setting with Rustls TLS in the OpenAiCompatibleProvider's client builder for enhanced security.
- Ensured consistent application of the new TLS setting across multiple client instances.
* Add Local AI command support and enhance error handling
- Introduced a new `LocalAi` command in the CLI for managing local AI runtime operations, including status checks, asset downloads, and prompt handling.
- Added detailed argument structures for various local AI functionalities, improving command usability.
- Enhanced error reporting in the `LocalAiService` by including response details in error messages for better debugging and user feedback.
- Refactored existing error handling to provide clearer context on failures during API interactions.
* Add local AI module with Ollama integration and model management
- Introduced a new local AI module that includes functionality for automatic installation of the Ollama runtime across different operating systems (Windows, macOS, Linux).
- Implemented model ID resolution and management, providing default settings for various AI models and ensuring compatibility with user configurations.
- Added HTTP API structures and request handling for Ollama, enabling interaction with the local AI service for generating responses and managing assets.
- Developed utility functions for parsing model outputs and managing workspace paths, enhancing the overall structure and usability of the local AI service.
- Established a comprehensive service layer for managing local AI operations, including status tracking and error handling for improved user experience.
* Refactor local AI service structure and enhance asset management
- Simplified the local AI module by reorganizing the service structure, introducing new modules for model IDs, paths, and asset management.
- Added comprehensive asset status tracking for various AI models, including chat, vision, embedding, STT, and TTS, with improved error handling.
- Implemented methods for downloading models and assets, ensuring better management of local AI resources.
- Updated visibility of service methods to enhance encapsulation and maintainability within the local AI service.
* Enhance local AI module with new download progress tracking and unit tests
- Added new structures for tracking download progress of various AI models, including detailed status and metrics.
- Implemented unit tests for model ID resolution, parsing suggestions, and asset path resolution to ensure robust functionality.
- Refactored service methods to improve encapsulation and maintainability, enhancing the overall structure of the local AI service.
- Updated existing tests to cover new functionalities and ensure consistent behavior across the module.
* Implement new local AI download functionalities and refactor model management
- Added support for downloading all local AI assets and tracking download progress, enhancing user experience and resource management.
- Introduced new RPC methods for fetching download progress and managing asset states, improving the overall functionality of the local AI module.
- Refactored existing model management code to utilize the new model catalog, ensuring better organization and maintainability.
- Updated relevant tests to cover new functionalities and ensure consistent behavior across the local AI service.
* Add new interfaces and functions for local AI download progress tracking
- Introduced `LocalAiDownloadProgressItem` and `LocalAiDownloadsProgress` interfaces to structure download progress data for various AI models.
- Implemented `openhumanLocalAiDownloadAllAssets` and `openhumanLocalAiDownloadsProgress` functions to facilitate downloading all assets and tracking their progress.
- Enhanced error handling for Tauri environment checks in new functions, ensuring robust operation within the local AI module.
* Refactor agent loop structure and introduce modular components
- Deleted the `loop_.rs` file and reorganized the agent loop into multiple modules for better maintainability and clarity.
- Introduced new files for handling credentials, history management, tool instructions, memory context, and parsing logic.
- Implemented functions for scrubbing sensitive credentials, managing conversation history, and building tool instructions.
- Enhanced the overall structure of the agent loop to facilitate easier testing and future development.
* Refactor authentication structure and migrate to credentials module
- Moved authentication-related functionality from `auth_profiles` to a new `credentials` module for better organization and clarity.
- Updated references in the API and core server to reflect the new module structure.
- Introduced new data structures and methods for managing authentication profiles, including session support and response handling.
- Removed the obsolete `auth_profiles` module to streamline the codebase and enhance maintainability.
* Add screen intelligence module with capture and context management
- Introduced new modules for screen capture and context management, specifically targeting macOS.
- Implemented functionality to capture screen images and retrieve foreground application context.
- Added data structures for managing application context and window bounds.
- Established limits for screenshot sizes and context character counts to ensure efficient resource management.
- Enhanced helper functions for input action validation and vision summary processing.
- Set up a modular structure for better maintainability and future enhancements.
* Refactor screen intelligence module and remove obsolete components
- Deleted unused files related to screen intelligence, including context and permissions management, to streamline the codebase.
- Refactored the capture functionality to improve organization and maintainability.
- Updated function signatures for better clarity and consistency.
- Enhanced the overall structure of the screen intelligence module for future development and testing.
* Enhance autocomplete CLI functionality and refactor related code
- Added new options for the autocomplete command in the CLI, allowing users to run the autocomplete loop in the current process or spawn a detached process.
- Introduced `AutocompleteStartCliOptions` struct to encapsulate the new command-line arguments.
- Refactored the `autocomplete_start_cli` function to handle the new options and improve process management for the autocomplete service.
- Updated documentation in `CLAUDE.md` to clarify the separation of concerns between routing and controller logic in the codebase.
* Enhance autocomplete error handling and improve focused text context retrieval
- Added a new function to identify "no text candidate" errors, improving error management in the autocomplete engine.
- Refactored the `focused_text_context` and `focused_text_context_verbose` functions to enhance clarity and reliability in retrieving application context.
- Updated the return format of the `focused_text_context_verbose` function to use a separator for better data parsing.
- Added a new TODO item for allowing users to select LLM model versions based on their CPU capabilities.
* Remove Docker, Native, and WASM runtime implementations along with related traits and tests
- Deleted the DockerRuntime, NativeRuntime, and WasmRuntime implementations to streamline the codebase.
- Removed associated traits and factory functions for runtime creation.
- Eliminated all related tests to ensure a clean removal of unused components.
- This refactor aims to simplify the runtime management and prepare for future enhancements.
* Add quickjs-runtime feature and introduce runtime module
- Added a new feature flag for `quickjs-runtime` in `Cargo.toml` to enable its usage.
- Created a new `runtime.rs` module to implement `NativeRuntime` and `DockerRuntime` with associated traits for runtime management.
- Updated the `skills` module to reference the correct path for `SkillConfig`.
- Removed the obsolete `skillforge` module from the `openhuman` namespace to streamline the codebase.
- Enhanced the `skills` module with new structures and functions for managing skills, including initialization and loading logic.
* Refactor autocomplete configuration to remove legacy disabled apps
- Updated the default configuration for `AutocompleteConfig` to remove the legacy disabled apps ('terminal' and 'code'), allowing for broader usage of Codex/CLI.
- Introduced a migration function to handle legacy disabled apps during configuration loading, ensuring custom user preferences remain intact.
- This change enhances the flexibility of the autocomplete feature by preventing unnecessary restrictions on application usage.
* Update rquickjs dependencies in Cargo.lock
- Updated the rquickjs and rquickjs-core dependencies to versions 0.11.0 and 0.9.0 respectively, ensuring compatibility with the latest features and fixes.
- Added new entries for rquickjs-sys and its corresponding version 0.9.0 to the dependency list, enhancing the project's runtime capabilities.
- This update improves the overall stability and performance of the application by leveraging the latest improvements in the rquickjs ecosystem.
* Add terminal application detection to autocomplete logic
- Introduced a new function `is_terminal_app` to identify terminal applications based on their names, enhancing the autocomplete feature's context awareness.
- Updated the `focused_text_context_verbose` function to allow terminal applications to bypass text role checks when the input value is not empty, improving user experience in terminal environments.
- This change aims to provide better support for terminal-based applications in the autocomplete system.
* Add terminal input context extraction and noise line detection
- Introduced functions to identify terminal-like buffers and filter out noise lines in terminal input, enhancing the autocomplete engine's context awareness.
- Updated the `focused_text_context` logic to utilize the new terminal context extraction, improving the handling of text in terminal applications.
- Enhanced the `focused_text_context_verbose` function to better retrieve static text values from UI elements, ensuring accurate context representation in terminal environments.
- These changes aim to improve user experience and functionality for terminal-based applications in the autocomplete system.
* Enhance autocomplete engine state management and error handling
- Added new fields `last_escape_down` and `last_overlay_signature` to `EngineState` for improved state tracking.
- Implemented `try_reject_via_escape` method to handle escape key interactions, allowing users to reject suggestions more intuitively.
- Updated error handling to display notifications for different states (ready, accepted, rejected, error) using `show_overflow_badge`.
- Refactored state updates to ensure consistent management of suggestion and phase transitions, enhancing overall user experience in the autocomplete system.
* Implement periodic status logging in autocomplete service
- Added a polling mechanism to log the status of the autocomplete engine at regular intervals.
- Enhanced logging to capture changes in phase, application name, suggestions, and errors, improving visibility during service execution.
- Refactored the `autocomplete_start_cli` function to integrate the new logging functionality, ensuring a more informative user experience while the service is running.
* Refactor memory dispatch logic and remove local memory implementation
- Updated the memory dispatch functions to utilize the new `memory_rpc` module, enhancing the handling of memory operations such as document management and namespace queries.
- Removed the local memory implementation, including database interactions and related functions, to streamline the codebase and improve maintainability.
- Introduced new RPC calls for document operations (put, list, delete) and context queries, ensuring a more efficient and consistent approach to memory management.
- This refactor aims to enhance the overall architecture and performance of the memory handling system.
* Remove macOS-specific overflow badge functionality and related helper functions
- Deleted the `show_overflow_badge` and `escape_applescript_string` functions, which were specific to macOS, to streamline the codebase.
- Refactored the `show_overflow_badge` function to provide a no-op implementation for non-macOS platforms, enhancing cross-platform compatibility.
- This change simplifies the autocomplete module by removing platform-dependent code, improving maintainability and clarity.
* Enhance text application logic in autocomplete module
- Updated the `apply_text_to_focused_field` function to improve interaction with focused UI elements on macOS.
- The new implementation retrieves the current value of the focused element and appends the provided text, ensuring better handling of text input.
- Enhanced error reporting to include stderr output when applying suggestions fails, improving debugging capabilities.
- These changes aim to provide a more robust and user-friendly experience in the autocomplete functionality.
* Refactor Landlock feature configuration for Linux support
- Moved the `landlock` and `rppal` dependencies under a conditional target configuration for Linux in both `Cargo.toml` files, ensuring they are only included when building for Linux.
- Updated the `landlock.rs` module to check for both the `sandbox-landlock` feature and the Linux target OS, improving the conditional compilation logic.
- This change enhances cross-platform compatibility and ensures that Landlock functionality is only available on supported systems.
* Update dependencies and enhance Tauri integration
- Updated the Tauri dependency in `Cargo.toml` to include the `tray-icon` feature, enabling system tray support.
- Introduced a new `rust-toolchain.toml` file to pin the Rust version to 1.93.0, ensuring compatibility with the matrix-sdk.
- Modified GitHub workflows to use the specified Rust version from `rust-toolchain.toml` instead of the stable version, improving build consistency.
- Refactored Tauri commands to utilize a new `wrapCommandResult` function for better response handling.
- Added a new `tray` module in `openhuman` for managing system tray functionality, enhancing the desktop experience.
- Updated various command implementations to streamline service management and improve error handling.
* Refactor core process handling and enhance encryption features
- Removed the `openhuman` dependency from `Cargo.lock` and `Cargo.toml`, streamlining the project structure.
- Updated the core process handling to fall back to a child process when in-process execution is unavailable, improving error handling and logging.
- Introduced new encryption commands (`ai_init_encryption`, `ai_encrypt`, `ai_decrypt`) to enhance security features, utilizing AES-GCM for data protection.
- Added a new `tray` module for managing system tray functionality, improving user experience on desktop platforms.
- Refactored various command implementations to improve service management and error handling, ensuring a more robust application architecture.
* Remove unused modules and refactor daemon host configuration
- Deleted the `daemon_host_config`, `memory`, `models`, `openhuman_daemon`, `tray`, `chat`, `conscious_loop`, and `runtime` modules to streamline the codebase.
- Refactored the daemon host configuration logic into the `openhuman` module, consolidating related functionality.
- Updated command implementations to utilize the new configuration methods, ensuring consistent handling of daemon host settings.
- This cleanup enhances maintainability and reduces complexity in the project structure.
* Refactor memory management and update Tauri dependencies
- Removed the `tray-icon` feature from the Tauri dependency in `Cargo.toml` to streamline the configuration.
- Deleted the `core:tray:default` capability from the default capabilities JSON, simplifying the capabilities structure.
- Refactored memory handling in tests to utilize `UnifiedMemory` instead of `SqliteMemory`, enhancing consistency across memory operations.
- Updated memory store, recall, and forget functionalities to support a global namespace, improving memory management and retrieval processes.
- Enhanced error handling and logging in memory operations to provide clearer feedback during execution.
* Remove AI encryption commands and related functionality
- Deleted the `ai_init_encryption`, `ai_encrypt`, and `ai_decrypt` functions to streamline the codebase and remove unused features.
- Updated the command registration in the `run` function to reflect the removal of these encryption commands, enhancing maintainability and reducing complexity.
* Add OAuth integration token handling and channel connection management
- Introduced functions to fetch and encrypt integration tokens using OAuth, enhancing security for token management.
- Updated the channel connections API to support OAuth integration, including listing, connecting, and disconnecting channels.
- Implemented checks for supported channels and authentication modes, improving the robustness of channel connection handling.
- Enhanced error handling for integration token retrieval to ensure required fields are present before proceeding.
* Refactor project structure and update documentation
- Renamed the project from "Outsourced" to "OpenHuman" and revised the project summary to reflect its focus on AI-powered assistance for crypto communities.
- Restructured the repository layout, detailing the purpose of each directory and its contents.
- Updated runtime scope to clarify platform support and Tauri's desktop-only focus.
- Enhanced documentation across various files, including architecture, services, and routing, to improve clarity and usability for contributors.
- Removed outdated sections and streamlined commands for development and production builds, ensuring consistency in the documentation.
* Implement REPL session management and multimodal support
- Introduced a new REPL session management system, allowing for session-specific interactions with agents.
- Added functions for starting, chatting, resetting, and ending REPL sessions, enhancing user experience and control.
- Implemented multimodal message handling, enabling the processing of images alongside text in user messages.
- Updated the project structure to include new modules for identity and multimodal functionalities, improving organization and maintainability.
- Enhanced error handling and logging for session operations, providing clearer feedback during execution.
* Refactor memory store implementation and introduce unified memory management
- Removed the legacy memory store implementation and replaced it with a new unified memory management system.
- Introduced a `MemoryClient` for handling document storage, retrieval, and namespace management.
- Added support for key-value storage and graph data structures within the unified memory framework.
- Enhanced the `UnifiedMemory` struct with methods for document upsertion, querying, and namespace operations.
- Updated the project structure to include new modules for memory types, factories, and traits, improving organization and maintainability.
- Improved error handling and logging across memory operations for clearer feedback during execution.
* Implement QuickJS skill instance management
- Removed the previous QjsSkillInstance implementation and replaced it with a new modular structure.
- Introduced separate modules for event loop management, instance handling, JavaScript handlers, and utility functions.
- Enhanced the event loop to efficiently manage QuickJS runtime tasks, including timer callbacks and message processing.
- Added support for asynchronous tool calls and lifecycle management within the QuickJS context.
- Improved error handling and logging throughout the new implementation for better debugging and user feedback.
- Updated documentation to reflect the new structure and functionality of the QuickJS skill instance.
284 lines
9.6 KiB
JavaScript
284 lines
9.6 KiB
JavaScript
/** @type {import('tailwindcss').Config} */
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module.exports = {
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darkMode: 'class',
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content: [
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"./src/index.html",
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"./src/**/*.{js,ts,jsx,tsx}",
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],
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theme: {
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extend: {
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// Premium font stack optimized for crypto professionals
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fontFamily: {
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'sans': ['Inter', '-apple-system', 'BlinkMacSystemFont', 'Segoe UI', 'Helvetica', 'Arial', 'sans-serif'],
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'display': ['Cabinet Grotesk', 'Inter', '-apple-system', 'system-ui', 'sans-serif'],
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'mono': ['JetBrains Mono', 'SF Mono', 'Consolas', 'Liberation Mono', 'Courier', 'monospace'],
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'serif': ['Newsreader', 'Georgia', 'Cambria', 'Times New Roman', 'Times', 'serif'],
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},
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// Elevated color system - Calm, trustworthy, and sophisticated
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colors: {
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// Canvas - Background layers with subtle warmth
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canvas: {
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50: '#FAFAF9', // Base background
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100: '#F5F5F4', // Secondary background
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150: '#EDEDEC', // Tertiary background
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200: '#E5E5E3', // Card background
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300: '#D4D4D1', // Hover states
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},
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// Primary - Premium ocean blue with depth (optimized for dark backgrounds)
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primary: {
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50: '#F0F7FF',
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100: '#E0EFFF',
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200: '#C7E2FF',
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300: '#A5D0FF',
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400: '#7AB5FF',
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500: '#4A83DD', // Main brand - darker blue for dark backgrounds
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600: '#3D6DC4', // Hover state
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700: '#345A9F', // Active state
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800: '#2D4B7F',
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900: '#1E3052',
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950: '#0F1A2E',
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},
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// Sage - Success and growth (sophisticated green)
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sage: {
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50: '#F7FDF9',
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100: '#ECFAEF',
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200: '#D4F4DC',
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300: '#AEEAC1',
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400: '#72D892',
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500: '#4DC46F', // Main success - refined green
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600: '#3BA858',
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700: '#318B48',
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800: '#2B6F3C',
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900: '#255933',
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950: '#14371E',
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},
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// Amber - Attention and caution (warm, muted)
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amber: {
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50: '#FEFDF8',
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100: '#FEF8E7',
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200: '#FDEEC8',
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300: '#FBDF9A',
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400: '#F7C960',
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500: '#E8A838', // Main warning - sophisticated amber
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600: '#D18B1F',
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700: '#B06F1A',
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800: '#8D581B',
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900: '#744919',
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950: '#4A2B0B',
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},
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// Coral - Errors and dangers (soft, professional)
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coral: {
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50: '#FFF5F5',
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100: '#FFEBEB',
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200: '#FFD6D6',
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300: '#FFB3B3',
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400: '#FF8585',
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500: '#F56565', // Main error - soft coral red
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600: '#E84855',
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700: '#D13742',
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800: '#B02937',
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900: '#922330',
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950: '#5C1419',
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},
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// Stone - Neutral scale with subtle warmth
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stone: {
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50: '#FAFAF9',
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100: '#F5F5F4',
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200: '#E7E5E4',
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300: '#D6D3D1',
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400: '#A8A29E',
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500: '#78716C',
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600: '#57534E',
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700: '#44403C',
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800: '#292524',
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900: '#1C1917',
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950: '#0C0A09',
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},
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// Slate - Cool grays for data and charts
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slate: {
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50: '#F8FAFC',
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100: '#F1F5F9',
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200: '#E2E8F0',
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300: '#CBD5E1',
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400: '#94A3B8',
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500: '#64748B',
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600: '#475569',
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700: '#334155',
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800: '#1E293B',
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900: '#0F172A',
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950: '#020617',
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},
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// Market colors - For crypto specific UI
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market: {
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bullish: '#4DC46F', // Green for gains
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bearish: '#F56565', // Red for losses
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neutral: '#94A3B8', // Gray for no change
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bitcoin: '#F7931A', // Bitcoin orange
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ethereum: '#627EEA', // Ethereum purple
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stablecoin: '#5B9BF3', // Blue for stables
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},
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// Accent colors for special elements
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accent: {
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lavender: '#9B8AFB', // Premium features
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mint: '#6EE7B7', // Achievements
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sky: '#7DD3FC', // Notifications
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rose: '#FDA4AF', // Alerts
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gold: '#FCD34D', // Rewards
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}
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},
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// Refined spacing scale for elegant layouts
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spacing: {
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'4.5': '1.125rem',
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'13': '3.25rem',
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'15': '3.75rem',
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'17': '4.25rem',
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'18': '4.5rem',
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'22': '5.5rem',
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'30': '7.5rem',
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'34': '8.5rem',
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'42': '10.5rem',
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'68': '17rem',
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'76': '19rem',
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'84': '21rem',
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'88': '22rem',
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'92': '23rem',
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'128': '32rem',
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'144': '36rem',
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},
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// Sophisticated typography scale
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fontSize: {
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'micro': ['0.625rem', { lineHeight: '0.75rem', letterSpacing: '0.02em' }],
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'xs': ['0.75rem', { lineHeight: '1rem', letterSpacing: '0.01em' }],
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'sm': ['0.875rem', { lineHeight: '1.25rem', letterSpacing: '0' }],
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'base': ['1rem', { lineHeight: '1.5rem', letterSpacing: '-0.01em' }],
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'lg': ['1.125rem', { lineHeight: '1.75rem', letterSpacing: '-0.01em' }],
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'xl': ['1.25rem', { lineHeight: '1.875rem', letterSpacing: '-0.02em' }],
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'2xl': ['1.5rem', { lineHeight: '2rem', letterSpacing: '-0.02em' }],
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'3xl': ['1.875rem', { lineHeight: '2.25rem', letterSpacing: '-0.02em' }],
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'4xl': ['2.25rem', { lineHeight: '2.5rem', letterSpacing: '-0.03em' }],
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'5xl': ['3rem', { lineHeight: '3.5rem', letterSpacing: '-0.03em' }],
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'6xl': ['3.75rem', { lineHeight: '4rem', letterSpacing: '-0.04em' }],
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'7xl': ['4.5rem', { lineHeight: '4.75rem', letterSpacing: '-0.04em' }],
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},
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// Smooth border radius system
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borderRadius: {
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'xs': '0.25rem',
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'sm': '0.375rem',
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'md': '0.5rem',
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'lg': '0.625rem',
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'xl': '0.75rem',
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'2xl': '1rem',
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'3xl': '1.25rem',
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'4xl': '1.5rem',
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'5xl': '2rem',
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},
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// Sophisticated shadow system for depth
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boxShadow: {
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'glow': '0 0 20px rgba(91, 155, 243, 0.15)',
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'glow-lg': '0 0 40px rgba(91, 155, 243, 0.2)',
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'inner-glow': 'inset 0 0 20px rgba(91, 155, 243, 0.08)',
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'subtle': '0 1px 2px 0 rgba(0, 0, 0, 0.03), 0 1px 3px 0 rgba(0, 0, 0, 0.04)',
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'soft': '0 2px 8px -2px rgba(0, 0, 0, 0.08), 0 4px 12px -4px rgba(0, 0, 0, 0.08)',
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'medium': '0 4px 12px -2px rgba(0, 0, 0, 0.08), 0 8px 16px -4px rgba(0, 0, 0, 0.08)',
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'large': '0 8px 24px -4px rgba(0, 0, 0, 0.10), 0 16px 32px -8px rgba(0, 0, 0, 0.10)',
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'float': '0 12px 32px -8px rgba(0, 0, 0, 0.12), 0 24px 48px -12px rgba(0, 0, 0, 0.12)',
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'crisp': '0 0 0 1px rgba(0, 0, 0, 0.05), 0 2px 4px rgba(0, 0, 0, 0.08)',
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},
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// Premium animations for polished interactions
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animation: {
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'fade-in': 'fadeIn 0.5s cubic-bezier(0.4, 0, 0.2, 1)',
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'fade-up': 'fadeUp 0.5s cubic-bezier(0.4, 0, 0.2, 1)',
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'slide-in': 'slideIn 0.3s cubic-bezier(0.4, 0, 0.2, 1)',
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'slide-right': 'slideRight 0.3s cubic-bezier(0.25, 0.46, 0.45, 0.94)',
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'scale-in': 'scaleIn 0.3s cubic-bezier(0.4, 0, 0.2, 1)',
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'shimmer': 'shimmer 2s linear infinite',
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'glow-pulse': 'glowPulse 2s cubic-bezier(0.4, 0, 0.6, 1) infinite',
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'float': 'float 3s ease-in-out infinite',
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'ticker': 'ticker 30s linear infinite',
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},
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keyframes: {
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fadeIn: {
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'0%': { opacity: '0' },
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'100%': { opacity: '1' },
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},
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fadeUp: {
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'0%': { opacity: '0', transform: 'translateY(10px)' },
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'100%': { opacity: '1', transform: 'translateY(0)' },
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},
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slideIn: {
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'0%': { transform: 'translateX(-100%)' },
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'100%': { transform: 'translateX(0)' },
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},
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slideRight: {
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'0%': { opacity: '0', transform: 'translateX(100%)' },
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'100%': { opacity: '1', transform: 'translateX(0)' },
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},
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scaleIn: {
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'0%': { transform: 'scale(0.95)', opacity: '0' },
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'100%': { transform: 'scale(1)', opacity: '1' },
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},
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shimmer: {
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'0%': { backgroundPosition: '-200% 0' },
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'100%': { backgroundPosition: '200% 0' },
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},
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glowPulse: {
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'0%, 100%': { opacity: '1' },
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'50%': { opacity: '0.5' },
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},
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float: {
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'0%, 100%': { transform: 'translateY(0)' },
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'50%': { transform: 'translateY(-10px)' },
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},
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ticker: {
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'0%': { transform: 'translateX(0)' },
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'100%': { transform: 'translateX(-50%)' },
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},
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},
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// Backdrop blur for glass morphism
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backdropBlur: {
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'xs': '2px',
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'sm': '4px',
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'md': '8px',
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'lg': '12px',
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'xl': '16px',
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'2xl': '24px',
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'3xl': '40px',
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},
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// Background patterns and gradients
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backgroundImage: {
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'gradient-radial': 'radial-gradient(var(--tw-gradient-stops))',
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'gradient-conic': 'conic-gradient(from 180deg at 50% 50%, var(--tw-gradient-stops))',
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'gradient-mesh': 'linear-gradient(to right, #5B9BF3 0%, #9B8AFB 25%, #6EE7B7 50%, #7DD3FC 75%, #5B9BF3 100%)',
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'noise': "url('data:image/svg+xml,%3Csvg xmlns=\"http://www.w3.org/2000/svg\" width=\"100\" height=\"100\"%3E%3Cfilter id=\"noise\"%3E%3CfeTurbulence type=\"fractalNoise\" baseFrequency=\"0.9\" numOctaves=\"4\" /%3E%3C/filter%3E%3Crect width=\"100\" height=\"100\" filter=\"url(%23noise)\" opacity=\"0.03\" /%3E%3C/svg%3E')",
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},
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// Extended transition duration for smooth animations
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transitionDuration: {
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'300': '300ms',
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'400': '400ms',
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},
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},
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},
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plugins: [
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require('@tailwindcss/forms'),
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require('@tailwindcss/typography'),
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],
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};
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