* feat(telegram): implement Telegram channel and attachment handling - Added `TelegramChannel` struct for managing Telegram Bot API interactions, including user management and message handling. - Introduced attachment parsing with `TelegramAttachment` and `TelegramAttachmentKind` to support various media types. - Implemented functions for parsing attachment markers and validating URLs, enhancing message processing capabilities. - Created a new module structure for Telegram, including `attachments`, `channel`, and `text` for better organization and maintainability. * feat(skills): implement skills registry management and E2E testing - Added functionality for fetching, searching, installing, and uninstalling skills from a remote registry. - Introduced new modules for registry operations and types, enhancing the skills management system. - Implemented E2E tests for skills registry interactions, ensuring robust functionality and integration. - Updated documentation to reflect new skills registry features and usage instructions. * refactor(coreRpcClient): remove socket RPC handling and streamline HTTP request logging - Eliminated socket-based RPC handling to simplify the core RPC client logic. - Updated logging to use a unified debug logger for both HTTP requests and errors. - Improved error handling for HTTP responses to ensure clarity in error reporting. * feat(skills): enhance skill setup handling and improve error management - Updated SkillActionButton to directly open the setup modal for skills requiring OAuth, bypassing the QuickJS runtime. - Enhanced SkillSetupWizard to handle OAuth configuration more effectively, ensuring smoother transitions during skill setup. - Improved error handling during skill startup and setup processes, providing clearer logging for failures. - Refactored skills loading logic in the Skills page to prioritize registry-based skill fetching, with fallback to runtime discovery. - Added skill installation handling in the Skills page, allowing for better user feedback during installation processes. * feat(deep-link): enhance OAuth handling and streamline token management - Updated desktopDeepLinkListener to improve skill connection handling after OAuth completion. - Introduced setSkillSetupComplete action to mark skills as connected immediately post-OAuth. - Refactored token fetching logic to ensure encrypted tokens are stored correctly, enhancing error handling and reducing redundant checks. - Added new permissions in default.json for improved window management capabilities. * feat(skills): enhance skill management with global engine and runtime controllers - Added global engine management for skill runtime access, allowing RPC handlers to interact with the runtime engine. - Introduced new runtime controllers for skills, including start, stop, status, setup_start, list_tools, sync, and call_tool, enhancing skill lifecycle management. - Updated schemas to include new skill controller functionalities, improving the overall skills management system. - Enhanced documentation and comments for clarity on new features and usage. * refactor(skills): update global engine management and enhance documentation - Replaced OnceLock with RwLock for the global RuntimeEngine, allowing for better testability and flexibility in engine management. - Updated the global_engine and require_engine functions to return cloned Arc references, improving usability. - Enhanced documentation comments for clarity on the global engine's usage and behavior in production and testing scenarios. * chore(todos): update TODO list with removal of Tauri from Rust core - Added a new item to the TODO list indicating the need to remove Tauri from the OpenHuman Rust core, streamlining the project structure. * feat(onboarding): revamp onboarding steps and introduce local AI model consent - Replaced the PrivacyStep with a new ScreenPermissionsStep to handle accessibility permissions. - Added LocalAIStep for user consent on local AI model usage and download initiation. - Introduced SkillsStep and ToolsStep for selecting skills and enabling tools during onboarding. - Updated onboarding state management to include local model consent, download status, and enabled tools. - Enhanced the overall onboarding flow with new components and improved user experience. * feat(onboarding): enhance onboarding flow with new WelcomeStep and updated LocalAIStep - Introduced a new WelcomeStep to guide users through the onboarding process. - Updated LocalAIStep to clarify local AI model usage and consent, including improved messaging on privacy and resource impact. - Enhanced ScreenPermissionsStep to emphasize local processing of accessibility data. - Adjusted total steps in onboarding to reflect the addition of the WelcomeStep, improving user experience. * refactor(tray): remove tray integration and related functionalities - Deleted the tray module and its associated operations, streamlining the project structure. - Removed references to Tauri app handle in various components, transitioning to a memory client for skill data persistence. - Updated skill instances and event loops to eliminate dependencies on tray functionalities, enhancing modularity. - Improved documentation to reflect the removal of tray-related features and clarify the new architecture. * feat(onboarding): introduce OnboardingOverlay and enhance onboarding flow - Added OnboardingOverlay component to display the onboarding process as a full-screen overlay when the user is not onboarded. - Updated the Onboarding component to include a new MnemonicStep for recovery phrase management. - Enhanced onboarding state management to track workspace onboarding flags and user onboarding status. - Refactored AppRoutes to streamline routing and integrate the new onboarding flow. - Removed deprecated onboarding logic from previous steps, improving overall user experience. * refactor(sidebar): simplify hidden paths and update ProtectedRoute tests - Removed '/onboarding' from the hiddenPaths in MiniSidebar to streamline route visibility. - Updated ProtectedRoute tests to reflect changes in onboarding handling, ensuring children render correctly when authenticated. * chore: format, fix E2E lint, and onboarding step polish Made-with: Cursor * style(onboarding): update background color for onboarding steps - Changed background color from black/30 to stone-900 for improved visual consistency across LocalAIStep, MnemonicStep, ScreenPermissionsStep, SkillsStep, ToolsStep, and WelcomeStep components. - Enhanced overall aesthetics of the onboarding flow. * fix(tests): update variable naming and comment out unused JavaScript content - Renamed workspace variable to `_ws` to indicate it is unused in the `test_registry_cache_ttl_expired` test. - Commented out the `js_content` variable to prevent unused variable warnings in the test setup. * refactor(tests): streamline JSON-RPC test setup and remove unused backend URL handling - Updated the JSON-RPC end-to-end test to always use the in-process Axum mock for backend settings, ensuring consistent test behavior. - Removed the conditional logic for external backend URLs, simplifying the test setup. - Ensured proper cleanup of mock join handles after test execution. * refactor(runtime): update skill startup process to use core RPC - Replaced the direct call to `runtimeStartSkill` with a `callCoreRpc` method for starting skills, enhancing the integration with the core RPC system. - Updated comments to reflect the new implementation details. - Made minor adjustments to the schema organization in Rust for better clarity on runtime controllers.
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todo
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allow skills to be downloaded from the web
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allow skills to be written as text formatted files like SKILL.md
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skills need to specific via JSON-rpc the state changes they make to their state and data files in memory
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skills need to be able to download custom mcp servers from the web
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integrate the payments flow properly, skip the connect account page and goto the home page
[] - allow for new skills to be coded on their own [] - allow for multiple instances of a skill to be loaded [] - add a local model that can read through the screen and also go through voice using an API like whisper [] - add a screener recorder that goes through the intefaces in the screen and locally summarizes what is happening and brings more assitance to the user [] clean up the core so that we can run it as a binary on a server or as docker
[x] Separate the binary from the tauri codebase [] Integrate our custom memory engine into core - sanil [] Integrate our skills registry into core - steve [x] Integrate accessibility service installation [] Add as a step and setting in the UI - cyrus [x] Remove mentions of zeroclaw from the codebaes [x] Integrate local LLM into core [x] Handle process/deamon properly [x] install the linux philosophy of few modules that do their own thing really well sort of.. [x] Remove android / ios support from the codebase. [x] e2e test to check if daemon and sidecar loading works properly [x] Find a better way to structure the cargo files [x] fix all the rust and cargo issues [] Add icon and app name to the various permission settings - mithil [] add self update based on github release. create a update action on the cli - aniketh [] for each skill show information on how much data has been synced locally and information on how much syncs have happened so far etc.. - mithil/elvin [x] redo the docs once everything is done. [x] remove unwanted feature flags from the rust binary [] fix the config properly - mithil [] Allow for Migrating from OpenClaw - steve done - to be tested [] allow users to choose which version of LLM model they'd like to choose based on their CPU. better ram and gpu means higher parameter model can be used. - mithil [x] in the client side app, make console.log follow a logger style logging where there's a namespace for every logger (like python) - steve [ ] - currently we bundle tauri in the openhumany rust core but that shouldn't really have to be there. it can be completely removed.
--- e2e tests to write up
- connecting a channel like telegram/discord works properly