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Steven EnamakelandGitHub
37991fc567
* chore: add Cargo.toml and Cargo.lock for rust-core workspace - Introduced a new workspace for the rust-core module with its own Cargo.toml. - Added Cargo.lock to manage dependencies for the rust-core module. - Updated .gitignore to exclude the target directory generated by Cargo. - Modified GitHub Actions workflow to build from the new rust-core path instead of src-tauri. * feat: enhance memory and authentication models in rust-core - Added new `memory` module to handle persistent memory operations for skills, including methods for storing and querying skill data. - Introduced `models` module with `auth` and `socket` submodules to manage user session and socket connection states. - Updated `lib.rs` to include new modules and ensure proper integration within the rust-core workspace. - Modified `eslint.config.js` to ignore target directories in linting processes. * feat: integrate Tauri and QuickJS support in rust-core - Added `tauri` and `rquickjs` as optional dependencies in `Cargo.toml` to enable Tauri integration and JavaScript execution. - Introduced `CronScheduler` and `PingScheduler` modules for managing scheduled tasks and health checks for skills. - Implemented `MemoryState` struct for shared app-state management in the memory client. - Updated the runtime module to include new schedulers and ensure proper integration with Tauri features. - Enhanced the skill registry to support new functionalities related to skill management and communication. * chore: update ESLint configuration and refactor Rust module imports - Added 'rust-core/**' to ESLint ignore list to streamline linting processes. - Refactored import paths in Rust modules to directly reference the `memory` module, enhancing clarity and maintainability. - Improved formatting in JavaScript files for better readability and consistency. * refactor: rename rust-core to openhuman-core and update dependencies - Renamed the `rust-core` module to `openhuman-core` across all files for consistency. - Updated `Cargo.lock` to include `openhuman-core` as a new dependency and removed `rust-core`. - Adjusted import paths in the codebase to reflect the new module name, ensuring all references are updated. - Enhanced the Tauri integration by modifying dependencies in `src-tauri/Cargo.toml` to point to `openhuman-core`. * refactor: simplify platform detection using match statements - Replaced multiple if-else statements with match expressions in `current_platform`, `get_platform`, and `register` functions for improved readability and maintainability. - Removed unnecessary conditional compilation for Android and iOS in the `SocketManager` and `tauri_bridge` modules, streamlining the codebase. - Enhanced the `send_notification` function to handle platform checks more efficiently. * refactor: update platform detection to use std::env::consts - Replaced `cfg!(target_os = "os_name")` checks with `std::env::consts::OS` for improved clarity and consistency across the codebase. - Added `rppal` as an optional dependency in `Cargo.toml` for Raspberry Pi support. - Cleaned up platform-specific code in various modules, enhancing maintainability. * refactor: streamline platform-specific code and improve readability - Replaced conditional compilation with `std::env::consts::OS` checks in various modules to enhance clarity and maintainability. - Simplified platform detection logic in `available_disk_space_mb`, `ensure_arduino_cli`, and `open_in_brave` functions. - Updated `screenshot_command_exists` test to conditionally skip based on the operating system. - Cleaned up unnecessary `#[cfg]` attributes, focusing on a more consistent approach across the codebase. * feat: introduce comprehensive AI configuration and memory management - Added multiple configuration files for OpenHuman AI, including `AGENTS.md`, `BOOTSTRAP.md`, `CONSCIOUS_LOOP.md`, `IDENTITY.md`, `MEMORY.md`, `README.md`, `SOUL.md`, `TOOLS.md`, and `USER.md` to define agent roles, onboarding processes, identity, memory management, and tool capabilities. - Implemented an encryption layer for AI memory storage in `encryption.rs`, utilizing AES-256-GCM for secure data handling. - Updated `lib.rs` to include the new AI module structure, enhancing the overall architecture and maintainability of the codebase. * refactor: update dependencies and configuration for improved structure - Removed `android_logger` and related packages from `Cargo.lock` and `Cargo.toml`, streamlining the dependency list. - Adjusted the `APP_IDENTIFIER` constant in `config.rs` to reflect the new application identifier. - Updated resource paths in `tauri.conf.json` for better organization. - Enhanced platform-specific dependency management in `Cargo.toml` for clarity and maintainability. * fix(core): gate ai module behind tauri-host feature * refactor: update AI loading mechanisms and improve platform handling - Refactored the AI configuration loading in `loader.ts` and `tools/loader.ts` to utilize Tauri commands for desktop environments, enhancing performance and reliability. - Updated paths for AI markdown files to reflect the new `rust-core` structure. - Introduced a new end-to-end test for Tauri command interactions in `tauriCoreBridge.e2e.test.ts`. - Cleaned up platform-specific code across various modules, ensuring a more consistent approach to handling desktop and web contexts. * feat: add sidecar core binary build and staging for Tauri bundler - Implemented build steps for the sidecar core binary in multiple workflows, targeting both x86_64-unknown-linux-gnu and aarch64-apple-darwin architectures. - Added staging steps to copy the built binaries into the Tauri resources directory, ensuring proper integration for application bundling. - Updated relevant workflows to enhance the build process and streamline artifact management. * refactor: enhance AI loading logic for Tauri integration - Updated `loader.ts` and `tools/loader.ts` to prioritize Tauri commands for loading configurations in desktop environments, with a fallback to bundled markdown files for web contexts. - Adjusted test mocks to reflect the new file paths for tools markdown. - Improved test setup to mock Tauri API behavior accurately. * docs: update CLAUDE.md and remove Android build scripts from package.json - Added a new section in CLAUDE.md detailing the runtime scope, clarifying that Tauri is desktop-only and should not include mobile or web branches. - Removed Android development and build scripts from package.json to streamline the project for desktop platforms only. * refactor: streamline import statements and enhance test mock structure - Reordered import statements in `loader.ts` and `tools/loader.ts` for consistency. - Simplified mock implementation in `tauriCoreBridge.e2e.test.ts` to improve readability and maintainability. - Added external binary configuration in `build.rs` to support resource management during local builds. * test: stabilize core/unit test paths and tauri build-test config * chore: update subproject commit reference in skills * chore: update Tauri build configuration to include custom environment variable - Modified the Tauri build command in the GitHub Actions workflow to set a custom configuration for updater artifacts, enhancing the build process for the x86_64-unknown-linux-gnu target.
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User Context and Adaptation
Target User Profiles
OpenHuman serves the crypto ecosystem. Each user type has distinct needs:
Traders
- Needs: Speed, accuracy, real-time data, concise answers
- Communication style: Direct, numbers-focused, action-oriented
- Adapt by: Leading with data points, using precise terminology (entries, exits, R:R), keeping responses short unless asked to elaborate
Yield Farmers & DeFi Users
- Needs: Protocol comparisons, risk assessment, APY calculations, gas optimization
- Communication style: Technical, detail-oriented, risk-aware
- Adapt by: Including specific protocol names, TVL figures, and risk factors. Always mention smart contract risks when relevant.
Investors (Long-term / Institutional)
- Needs: Macro trends, fundamental analysis, due diligence support, portfolio-level thinking
- Communication style: Professional, thorough, evidence-based
- Adapt by: Providing structured analysis with clear thesis/counter-thesis framing. Cite sources when possible.
Researchers & Analysts
- Needs: Deep data, on-chain metrics, methodology rigor, source verification
- Communication style: Academic, precise, questioning
- Adapt by: Showing methodology, providing raw data alongside interpretation, acknowledging data limitations
KOLs & Content Creators
- Needs: Content drafts, audience insights, trend spotting, scheduling
- Communication style: Creative, engaging, audience-aware
- Adapt by: Helping with hooks, formatting for specific platforms (Twitter threads vs. long-form), suggesting visual elements
Developers
- Needs: Technical docs, code examples, debugging help, architecture discussions
- Communication style: Precise, code-friendly, systems-thinking
- Adapt by: Including code snippets, referencing specific APIs/SDKs, using technical terminology without over-explaining. Leverage GitHub integration for repo context.
Complexity Detection
Adjust response depth based on signals:
- Beginner signals: Basic terminology questions, "what is," "how do I start," confusion about fundamentals
- Response: Explain concepts clearly, avoid jargon, provide step-by-step guidance
- Intermediate signals: Specific protocol questions, comparison requests, "which is better for"
- Response: Assume foundational knowledge, focus on trade-offs and practical advice
- Expert signals: Technical deep-dives, on-chain analysis requests, protocol-specific edge cases
- Response: Match their depth, skip basics, engage at a peer level
Personalization Boundaries
What to Remember
- User's stated role and experience level
- Platform preferences (which integrations they use)
- Communication style preferences (verbose vs. concise)
- Recurring topics and interests
- Timezone and scheduling preferences
What to Forget
- Specific wallet addresses (unless user explicitly asks to save)
- Trade details and portfolio positions
- Private conversations from connected platforms
- Any information the user asks to be forgotten
Privacy Rules
- Never proactively reference a user's financial details in conversation
- If recalling user context, make it clear: "Based on what you've told me before..."
- Users can ask "what do you know about me?" and get a transparent answer
- Users can request a full memory wipe at any time