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2383d51ea63c356a8b6038d6acc60b7cfe11d429
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Commits
| Author | SHA1 | Message | Date | |
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 sanil-23andGitHub
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2383d51ea6 |
revert: remove unnecessary prompt and parser changes from #156 (#169)
The actual fix in #156 was adding chat(ChatRequest) to ReliableProvider. The prompt changes in instructions.rs and the bracket tool call parser in parse.rs were added during investigation but are not needed — the model uses native tool calls when ReliableProvider properly delegates to the inner provider. |
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3c247a2439 |
Feat/humanlike replies (#168)
* fix(chat): prevent stacked socket listeners on reconnect subscribeChatEvents was declared async despite having no awaits, so the cleanup function was returned in a microtask after React's synchronous cleanup had already run. Each socket reconnect added another layer of listeners that were never removed, causing chat:done to fire N times and produce duplicate message bubbles. - Remove async keyword from subscribeChatEvents; return cleanup fn directly - Update useEffect call site to store cleanup synchronously and return it to React (eliminates the mounted/then race entirely) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * feat(local-ai): add multi-turn chat via Ollama /api/chat Expose openhuman.local_ai_chat RPC method so the UI can run full conversation-history chat directly through the bundled Ollama model without touching the cloud inference API. - ollama_api.rs: add OllamaChatMessage / OllamaChatRequest / OllamaChatResponse types for the /api/chat endpoint - service/public_infer.rs: add LocalAiService::chat_with_history() — sends multi-turn message array to Ollama, updates latency/TPS status on response - ops.rs: add LocalAiChatMessage struct and local_ai_chat async op - schemas.rs: register local_ai_chat controller (schema, handler, params) in all_controller_schemas + all_registered_controllers Zero cloud tokens are consumed on this path; the call never reaches the backend socket or the /openai/v1/chat/completions endpoint. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * feat(conversations): local-model chat gate with multi-bubble delivery When Ollama is ready (isLocalModelActive), handleSendMessage bypasses the cloud socket entirely and routes through openhumanLocalAiChat. Response is segmented and delivered as multiple typed bubbles with natural pauses — human-like reply behaviour at zero cloud token cost. UI / delivery - deliverLocalResponse(): segments full reply via segmentMessage(), dispatches each bubble with getSegmentDelay() pause between them; typing indicator (isDelivering) shows between segments - Socket-connected guard skipped on local path so offline local use works - Cloud socket path (chatSend → chat:done) fully unchanged Frontend RPC - tauriCommands: openhumanLocalAiChat(messages, maxTokens?) wraps openhuman.local_ai_chat via core RPC; LocalAiChatMessage type exported Tests (402 passing) - messageSegmentation: 4 new edge-case tests (whitespace, 80-char boundary, paragraph split, delay scaling) - localChatGating (new file): 9 tests — segmentation correctness, delay bounds [500, 1400] ms, sender→role mapping for message history build Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix(prompts): replace vague emoji guidance with explicit contextual rules The previous "Minimal — match the user's style" instruction was too loose, causing the model to stack decorative emojis on every message (e.g. "Hey! 😄 Just cooking up some AI magic! 🚀🔥✨"). SOUL.md — add Emoji Rules section: - Hard cap: one emoji maximum per message; none is always acceptable - Contextual, not decorative: emoji must reinforce the specific content (🔥 for exciting news, 🤔 for uncertainty, ✅ for confirmations) - Never open a sentence with an emoji - Skip entirely in error/warning/technical/long responses - Mirror the user's own emoji usage pattern - Concrete good/bad examples so the model can calibrate BOOTSTRAP.md — tighten the Communication Preferences entry to reference the same rules rather than the old vague one-liner. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * chore: scope PR_DESCRIPTION.md to feat/humanlike-replies only Remove unrelated package manager distribution content (was from a different branch). Description now covers only the 4 commits on this branch: socket listener fix, Rust local_ai_chat RPC, frontend local chat gate + multi-bubble delivery, and emoji prompt rules. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * refactor(local_ai): improve code formatting and readability in chat operations - Adjusted formatting in local_ai_chat function for better readability by adding line breaks. - Simplified the mapping of messages to OllamaChatMessage in ops.rs. - Streamlined the await syntax in schemas.rs for clarity. - Enhanced formatting in public_infer.rs for consistency in API request construction. * refactor(conversations): enhance code readability and structure in Conversations component - Improved formatting and consistency in the Conversations component, including better alignment of dispatch calls and message handling logic. - Removed redundant imports and streamlined the mapping of stored messages for clarity. - Adjusted conditional rendering for improved readability in the UI logic. --------- Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com> |
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YellowSnnowmannandGitHub
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6406ec2bc3 |
Feat:package manager channels (brew, apt, npm ) (#166)
* feat(release): upload versioned CLI tarballs in release workflow (#128) Package and upload non-Windows CLI tarballs with SHA-256 checksum companions during release builds so package managers can consume stable release artifacts. Made-with: Cursor * feat(packaging): add brew apt npm release channels automation (#128) Add post-release workflow and channel assets to publish Homebrew formula updates, signed apt repository metadata, and npm package releases with smoke validation. Made-with: Cursor * docs: add installation guide for OpenHuman across various package managers |
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sanil-23andGitHub
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305c58a6ec |
fix: reduce agent loop hallucination and improve tool call reliability (#156)
* fix: reduce agent loop hallucination and improve tool call reliability - Strengthen tool-use instructions with explicit anti-hallucination rules: "NEVER narrate tool use without emitting tags", "use exact tool names", "only respond without tool call when no tool is needed" - Wire context guard into tool loop: check utilization before each LLM call, abort on context exhaustion (>95% with circuit breaker tripped) - Add 120-second timeout on tool execution to prevent hangs - Add debug/warn/error logging at all loop boundaries: LLM request, response (with token counts), tool call parsing, tool execution, unknown tools, timeouts, and final response Closes #144 * fix: implement chat(ChatRequest) on ReliableProvider and add bracket tool call parser Root cause: ReliableProvider did not implement the chat(ChatRequest) trait method. The agent loop called provider.chat() which fell through to the default trait implementation — this used chat_with_history() which strips native tool support and sends raw tool-role messages without the required assistant tool_calls, causing the backend Jinja template to reject the request with "Message has tool role, but there was no previous assistant message with a tool call!" Fixes: - Add chat(ChatRequest) to ReliableProvider with full retry/failover logic, matching the existing chat_with_system/chat_with_history implementations. Delegates to inner provider's chat() which properly converts messages to native OpenAI format with tool_calls. - Add [TOOL_CALL]/[/TOOL_CALL] bracket format to the tool call parser (parse.rs) — some models emit this format instead of <tool_call> XML. - Add parse_bracket_tool_call() for the pseudo-syntax format: {tool => "name", args => { --key "value" }} Verified with real staging backend (agentic-v1 model): - Shell tool calls execute successfully - File read tool calls return real content - Knowledge questions return without tool calls - No Jinja template errors Closes #144 |
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YellowSnnowmannandGitHub
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64eb513071 |
feat(billing, team): add billing and team management RPC functionality (#159)
* feat(billing, team): add billing and team management RPC functionality - Introduced billing module with methods for fetching current plans, purchasing plans, creating portal sessions, and topping up credits. - Added team management module with methods for listing team members, creating invites, listing invites, removing members, and changing member roles. - Updated core registry to include new billing and team controllers and schemas, enhancing the overall functionality of the application. - Implemented comprehensive tests for billing and team RPC methods to ensure reliability and correctness. These additions improve the application's capabilities in managing billing and team functionalities, providing a more robust user experience. * refactor(billing, team): improve code readability and structure * fix(billing, team): enhance error handling and response structure - Improved error handling in to provide clearer error messages when reading response bodies. - Updated validation in to ensure is a finite number greater than zero. - Refined output schemas for billing and team functions to include more descriptive fields, enhancing API clarity. - Introduced a new function to standardize URL path construction, improving code maintainability. - Added tests to verify the correctness of new output structures and API path building. These changes enhance the robustness and usability of the billing and team management functionalities. * feat(billing, team): add gateway normalization and route redaction functionality - Introduced function to standardize payment gateway inputs, ensuring only valid options (stripe, coinbase) are accepted, with defaults and error handling. - Enhanced function to utilize the new gateway normalization logic, improving input validation. - Added function to obscure sensitive identifiers in API route paths, enhancing security in logging. - Implemented unit tests for both and to ensure correctness and reliability of the new features. These changes improve the robustness of billing operations and enhance security in route handling. |
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Cyrus GrayandGitHub
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ec6f954356 |
fix(onboarding): clear all onboarding state on logout so overlay reappears (#167)
* feat(onboarding): calmer onboarding with durable deferral + local AI download snackbar - Add persisted `onboardingDeferredByUser` state so "Set up later" survives across sessions (no more overlay nagging on every launch) - Add SetupBanner for non-intrusive "Finish setting up" reminder with resume path - Convert LocalAIStep to fire-and-forget download, advancing immediately - Add LocalAIDownloadSnackbar (bottom-left, collapsible) for persistent download progress that doesn't block the main chrome - Extract shared helpers (formatBytes, formatEta, progressFromStatus) to localAiHelpers.ts - Add Vitest tests for overlay gating, banner, and snackbar Closes #101 * fix(test): remove per-test config mock that overrode global setup exports The OnboardingOverlay test mocked utils/config with only DEV_FORCE_ONBOARDING, which shadowed the global mock from setup.ts and dropped IS_DEV — causing store/index.ts to fail on CI. * fix(tests): destructure build_agent_with tuple in agent tests Two tests called .history() and .turn() on the (Agent, TempDir) tuple instead of destructuring it first, causing compilation errors on CI. * fix(onboarding): clear all onboarding state on logout so overlay reappears On logout, `isOnboardedByUser` and `isAnalyticsEnabledByUser` were not reset in the `_clearToken` reducer, and the workspace `.skip_onboarding` flag file was never deleted. This caused the onboarding overlay to be permanently skipped after the first completion — even for new users on the same machine. - Clear `isOnboardedByUser` and `isAnalyticsEnabledByUser` in `_clearToken` - Call `openhumanWorkspaceOnboardingFlagSet(false)` on logout, clear-all, and auth recovery paths - Add 3s timeout fallback in OnboardingOverlay for slow user profile loads - Add unit test asserting `clearToken` resets all per-user fields Closes #117 * fix(onboarding): address CodeRabbit review feedback - Add console.warn in UserProvider catch block for workspace flag clear - Add inline comment explaining userLoadTimedOut stickiness is harmless Closes #117 |
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github-actions[bot]
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7fd45682eb | chore(release): v0.50.3 v0.50.3 | ||
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github-actions[bot]
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cf6f077502 | chore(release): v0.50.2 | ||
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github-actions[bot]
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c4b5474643 | chore(release): v0.50.1 | ||
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Steven Enamakel
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756f2c9c69 |
chore(release): disable Windows build notifications in release workflow
- Commented out the Windows build notification section in the release workflow to prevent errors during the release process. - Added a note indicating that the Windows build is currently disabled in the matrix, improving clarity for future updates. |
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github-actions[bot]
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270d0008e2 | chore(release): v0.50.0 | ||
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ed83cae117 |
feat(agent): multi-agent harness with 8 archetypes, DAG planning, and episodic memory (#155)
* refactor(agent): update default model configuration and pricing structure - Changed the default model name in `AgentBuilder` to use a constant `DEFAULT_MODEL` instead of a hardcoded string. - Introduced new model constants (`MODEL_AGENTIC_V1`, `MODEL_CODING_V1`, `MODEL_REASONING_V1`) in `types.rs` for better clarity and maintainability. - Refactored the pricing structure in `identity_cost.rs` to utilize the new model constants, improving consistency across the pricing definitions. These changes enhance the configurability and readability of the agent's model and pricing settings. * refactor(models): update default model references and suggestions - Replaced hardcoded model names with a constant `DEFAULT_MODEL` in multiple files to enhance maintainability. - Updated model suggestions in the `TauriCommandsPanel` and `Conversations` components to reflect new model names, improving user experience and consistency across the application. These changes streamline model management and ensure that the application uses the latest model configurations. * style: fix Prettier formatting for model suggestions Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat(agent): introduce multi-agent harness with archetypes and task DAG - Added a new module for the multi-agent harness, defining 8 specialized archetypes (Orchestrator, Planner, CodeExecutor, SkillsAgent, ToolMaker, Researcher, Critic, Archivist) to enhance task management and execution. - Implemented a Directed Acyclic Graph (DAG) structure for task planning, allowing the Planner archetype to create and manage task dependencies. - Introduced a session queue to serialize tasks within sessions, preventing race conditions and enabling parallelism across different sessions. - Updated configuration schema to support orchestrator settings, including per-archetype configurations and maximum concurrent agents. These changes significantly improve the agent's architecture, enabling more complex task management and execution strategies. * feat(agent): implement orchestrator executor and interrupt handling - Introduced a new `executor.rs` module for orchestrated multi-agent execution, enabling a structured run loop that includes planning, executing, reviewing, and synthesizing tasks. - Added an `interrupt.rs` module to handle graceful interruptions via SIGINT and `/stop` commands, ensuring running sub-agents can be cancelled and memory flushed appropriately. - Implemented a self-healing interceptor in `self_healing.rs` to automatically create polyfill scripts for missing commands, enhancing the robustness of tool execution. - Updated the `mod.rs` file to include new modules and functionalities, improving the overall architecture of the agent harness. These changes significantly enhance the agent's capabilities in managing multi-agent workflows and handling interruptions effectively. * feat(agent): implement orchestrator executor and interrupt handling - Introduced a new `executor.rs` module for orchestrated multi-agent execution, enabling a structured run loop that includes planning, executing, reviewing, and synthesizing tasks. - Added an `interrupt.rs` module to handle graceful interruptions via SIGINT and `/stop` commands, ensuring running sub-agents are cancelled and memory is flushed. - Implemented a `SelfHealingInterceptor` in `self_healing.rs` to automatically generate polyfill scripts for missing commands, enhancing the agent's resilience. - Updated the `mod.rs` file to include new modules and functionalities, improving the overall architecture of the agent harness. These changes significantly enhance the agent's ability to manage complex tasks and respond to interruptions effectively. * feat(agent): add context assembly module for orchestrator - Introduced a new `context_assembly.rs` module to handle the assembly of the bootstrap context for the orchestrator, integrating identity files, workspace state, and relevant memory. - Implemented functions to load archetype prompts and identity contexts, enhancing the orchestrator's ability to generate a comprehensive system prompt. - Added a `BootstrapContext` struct to encapsulate the assembled context, improving the organization and clarity of context management. - Updated `mod.rs` to include the new context assembly module, enhancing the overall architecture of the agent harness. These changes significantly improve the orchestrator's context management capabilities, enabling more effective task execution and user interaction. * style: apply cargo fmt to multi-agent harness modules Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: resolve merge conflict in config/mod.rs re-exports Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: address PR review findings — security, correctness, observability Inline fixes: - executor: wire semaphore to enforce max_concurrent_agents cap - executor: placeholder sub-agents now return success=false - executor: halt DAG when level has failed tasks after retries - self_healing: remove overly broad "not found" pattern - session_queue: fix gc() race with acquire() via Arc::strong_count check - skills_agent.md: reference injected memory context, not memory_recall tool - init.rs: run EPISODIC_INIT_SQL during UnifiedMemory::new() - ask_clarification: make "question" param optional to match execute() default - insert_sql_record: return success=false for unimplemented stub - spawn_subagent: return success=false for unimplemented stub - run_linter: reject absolute paths and ".." in path parameter - run_tests: catch spawn/timeout errors as ToolResult, fix UTF-8 truncation - update_memory_md: add symlink escape protection, use async tokio::fs::write Nitpick fixes: - archivist: document timestamp offset intent - dag: add tracing to validate(), hoist id_map out of loop in execution_levels() - session_queue: add trace logging to acquire/gc - types: add serde(rename_all) to ReviewDecision, preserve sub-second Duration - ORCHESTRATOR.md: add escalation rule for Core handoff - read_diff: add debug logging, simplify base_str with Option::map - workspace_state: add debug logging at entry and exit - run_tests: add debug logging for runner selection and exit status Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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00c7b01280 |
fix(skills): debug infrastructure + disconnect credential cleanup (#154)
* feat(debug): add skills debug script and E2E tests - Introduced a new script `debug-skill.sh` for running end-to-end tests on skills, allowing users to easily test specific skills with customizable parameters. - Added comprehensive integration tests in `skills_debug_e2e.rs` to validate the full lifecycle of skills, including discovery, starting, tool listing, and execution. - Enhanced logging and error handling in the tests to improve observability and debugging capabilities. These additions facilitate better testing and debugging of skills, improving the overall development workflow. * feat(tests): add end-to-end tests for Skills RPC over HTTP JSON-RPC - Introduced a new test file `skills_rpc_e2e.rs` to validate the full stack of skill operations via HTTP JSON-RPC. - Implemented comprehensive tests covering skill discovery, starting, tool listing, and execution, ensuring robust functionality. - Enhanced logging for better observability during test execution, facilitating easier debugging and validation of skill interactions. These tests improve the reliability and maintainability of the skills framework by ensuring all critical operations are thoroughly validated. * refactor(tests): update RPC method names in end-to-end tests for skills - Changed RPC method names in `skills_rpc_e2e.rs` to use the new `openhuman` prefix, reflecting the updated API structure. - Updated corresponding test assertions to ensure consistency with the new method names. - Enhanced logging messages to align with the new method naming conventions, improving clarity during test execution. These changes ensure that the end-to-end tests accurately reflect the current API and improve maintainability. * feat(debug): add live debugging script and corresponding tests for Notion skill - Introduced `debug-notion-live.sh` script to facilitate debugging of the Notion skill with a live backend, including health checks and OAuth proxy testing. - Added `skills_notion_live.rs` test file to validate the Notion skill's functionality using real data and backend interactions. - Enhanced logging and error handling in both the script and tests to improve observability and debugging capabilities. These additions streamline the debugging process and ensure the Notion skill operates correctly with live data. * feat(env): enhance environment configuration for debugging scripts - Updated `.env.example` to include a new `JWT_TOKEN` variable for session management in debugging scripts. - Modified `debug-notion-live.sh` and `debug-skill.sh` scripts to load environment variables from `.env`, improving flexibility and usability. - Enhanced error handling in the scripts to ensure required variables are set, providing clearer feedback during execution. These changes streamline the debugging process for skills by ensuring necessary configurations are easily managed and accessible. * feat(tests): add disconnect flow test for skills - Introduced a new end-to-end test `skill_disconnect_flow` to validate the disconnect process for skills, mirroring the expected frontend behavior. - The test covers the stopping of a skill, handling OAuth credentials, and verifying cleanup after a disconnect. - Enhanced logging throughout the test to improve observability and debugging capabilities. These additions ensure that the disconnect flow is properly validated, improving the reliability of skill interactions. * fix(skills): revoke OAuth credentials on skill disconnect disconnectSkill() was only stopping the skill and resetting setup_complete, leaving oauth_credential.json on disk. On restart the stale credential would be restored, causing confusing auth state. Now sends oauth/revoked RPC before stopping so the event loop deletes the credential file and clears memory. Also adds revokeOAuth() and disableSkill() to the skills RPC API layer. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * style: apply cargo fmt to skill debug tests Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * refactor(tests): improve skills directory discovery and error handling - Renamed `find_skills_dir` to `try_find_skills_dir`, returning an `Option<PathBuf>` to handle cases where the skills directory is not found. - Introduced a macro `require_skills_dir!` to simplify the usage of skills directory discovery in tests, providing clearer error messages when the directory is unavailable. - Updated multiple test functions to utilize the new macro, enhancing readability and maintainability of the test code. These changes improve the robustness of the skills directory discovery process and streamline the test setup. * refactor(tests): enhance skills directory discovery with improved error handling - Renamed `find_skills_dir` to `try_find_skills_dir`, returning an `Option<PathBuf>` to better handle cases where the skills directory is not found. - Introduced a new macro `require_skills_dir!` to streamline the usage of skills directory discovery in tests, providing clearer error messages when the directory is unavailable. - Updated test functions to utilize the new macro, improving code readability and maintainability. These changes enhance the robustness of the skills directory discovery process and simplify test setup. * fix(tests): skip skill tests gracefully when skills dir unavailable Tests that require the openhuman-skills repo now return early with a SKIPPED message instead of panicking when the directory is not found. Fixes CI failures where the skills repo is not checked out. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(skills): harden disconnect flow, test assertions, and secret redaction - disconnectSkill: read stored credentialId from snapshot and pass it to oauth/revoked for correct memory bucket cleanup; add host-side fallback to delete oauth_credential.json when the runtime is already stopped. - revokeOAuth: make integrationId required (no more "default" fabrication); add removePersistedOAuthCredential helper for host-side cleanup. - skills_debug_e2e: hard-assert oauth_credential.json is deleted after oauth/revoked instead of soft logging. - skills_notion_live: gate behind RUN_LIVE_NOTION=1; require all env vars (BACKEND_URL, JWT_TOKEN, CREDENTIAL_ID, SKILLS_DATA_DIR); redact JWT and credential file contents from logs. - skills_rpc_e2e: check_result renamed to assert_rpc_ok and now panics on JSON-RPC errors so protocol regressions fail fast. - debug-notion-live.sh: capture cargo exit code separately from grep/head to avoid spurious failures under set -euo pipefail. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * style: apply cargo fmt to skills_notion_live.rs Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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a1932408dd |
refactor(models): standardize to reasoning-v1, agentic-v1, coding-v1 (#152)
* refactor(agent): update default model configuration and pricing structure - Changed the default model name in `AgentBuilder` to use a constant `DEFAULT_MODEL` instead of a hardcoded string. - Introduced new model constants (`MODEL_AGENTIC_V1`, `MODEL_CODING_V1`, `MODEL_REASONING_V1`) in `types.rs` for better clarity and maintainability. - Refactored the pricing structure in `identity_cost.rs` to utilize the new model constants, improving consistency across the pricing definitions. These changes enhance the configurability and readability of the agent's model and pricing settings. * refactor(models): update default model references and suggestions - Replaced hardcoded model names with a constant `DEFAULT_MODEL` in multiple files to enhance maintainability. - Updated model suggestions in the `TauriCommandsPanel` and `Conversations` components to reflect new model names, improving user experience and consistency across the application. These changes streamline model management and ensure that the application uses the latest model configurations. * style: fix Prettier formatting for model suggestions Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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Steven Enamakel
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f0801e8a75 | Merge remote-tracking branch 'upstream/main' | ||
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Steven Enamakel
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4518e4c52a | Merge remote-tracking branch 'upstream/main' | ||
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35be5e99e8 |
feat(agent): architecture improvements — context guard, cost tracking, permissions, events (#151)
* chore(workflows): comment out Windows smoke tests in installer and release workflows * feat: add usage field to ChatResponse structure - Introduced a new `usage` field in the `ChatResponse` struct across multiple files to track token usage information. - Updated various test cases and response handling to accommodate the new field, ensuring consistent behavior in the agent's responses. - Enhanced the `Provider` trait and related implementations to include the `usage` field in responses, improving observability of token usage during interactions. * feat: introduce structured error handling and event system for agent loop - Added a new `AgentError` enum to provide structured error types, allowing differentiation between retryable and permanent failures. - Implemented an `AgentEvent` enum for a typed event system, enhancing observability during agent loop execution. - Created a `ContextGuard` to manage context utilization and trigger auto-compaction, preventing infinite retry loops on compaction failures. - Updated the `mod.rs` file to include the new `UsageInfo` type for improved observability of token usage. - Added comprehensive tests for the new error handling and event system, ensuring robustness and reliability in agent operations. * feat: implement token cost tracking and error handling for agent loop - Introduced a `CostTracker` to monitor cumulative token usage and enforce daily budget limits, enhancing cost management in the agent loop. - Added structured error types in `AgentError` to differentiate between retryable and permanent failures, improving error handling and recovery strategies. - Implemented a typed event system with `AgentEvent` for better observability during agent execution, allowing multiple consumers to subscribe to events. - Developed a `ContextGuard` to manage context utilization and trigger auto-compaction, preventing excessive resource usage during inference calls. These enhancements improve the robustness and observability of the agent's operations, ensuring better resource management and error handling. * style: apply cargo fmt formatting Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat(agent): enhance error handling and event structure - Updated `AgentError` conversion to attempt recovery of typed errors wrapped in `anyhow`, improving error handling robustness. - Expanded `AgentEvent` enum to include `tool_arguments` and `tool_call_ids` for better context in tool calls, and added `output` and `tool_call_id` to `ToolExecutionComplete` for enhanced event detail. - Improved `EventSender` to clamp channel capacity to avoid panics and added tracing for event emissions, enhancing observability during event handling. * fix(agent): correct error conversion in AgentError implementation - Updated the conversion logic in the `From<anyhow::Error>` implementation for `AgentError` to return the `agent_err` directly instead of dereferencing it. This change improves the clarity and correctness of error handling in the agent's error management system. * refactor(config): simplify default implementations for ReflectionSource and PermissionLevel - Added `#[derive(Default)]` to `ReflectionSource` and `PermissionLevel` enums, removing custom default implementations for cleaner code. - Updated error handling in `handle_local_ai_set_ollama_path` to streamline serialization of service status. - Refactored error mapping in webhook registration and unregistration functions for improved readability. * refactor(config): clean up LearningConfig and PermissionLevel enums - Removed unnecessary blank lines in `LearningConfig` and `PermissionLevel` enums for improved code readability. - Consolidated `#[derive(Default)]` into a single line for `PermissionLevel`, streamlining the code structure. --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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1b131baf70 |
feat(webhooks): webhook tunnel routing for skills + remove legacy tunnel module (#147)
* feat(webhooks): implement webhook management interface and routing - Added a new Webhooks page with TunnelList and WebhookActivity components for managing webhook tunnels and displaying recent activity. - Introduced useWebhooks hook for handling CRUD operations related to tunnels, including fetching, creating, and deleting tunnels. - Implemented a WebhookRouter in the backend to route incoming webhook requests to the appropriate skills based on tunnel UUIDs. - Enhanced the API for tunnel management, including the ability to register and unregister tunnels for specific skills. - Updated the Redux store to manage webhooks state, including tunnels, registrations, and activity logs. This update provides a comprehensive interface for managing webhooks, improving the overall functionality and user experience in handling webhook events. * refactor(tunnel): remove tunnel-related modules and configurations - Deleted tunnel-related modules including Cloudflare, Custom, Ngrok, and Tailscale, along with their associated configurations and implementations. - Removed references to TunnelConfig and related functions from the configuration and schema files. - Cleaned up the mod.rs files to reflect the removal of tunnel modules, streamlining the codebase. This refactor simplifies the project structure by eliminating unused tunnel functionalities, enhancing maintainability and clarity. * refactor(config): remove tunnel settings from schemas and controllers - Eliminated the `update_tunnel_settings` controller and its associated schema from the configuration files. - Streamlined the `all_registered_controllers` function by removing the handler for tunnel settings, enhancing code clarity and maintainability. This refactor simplifies the configuration structure by removing unused tunnel-related functionalities. * refactor(tunnel): remove tunnel settings and related configurations - Eliminated tunnel-related state variables and functions from the TauriCommandsPanel component, streamlining the settings interface. - Removed the `openhumanUpdateTunnelSettings` function and `TunnelConfig` interface from the utility commands, enhancing code clarity. - Updated the core RPC client to remove legacy tunnel method aliases, further simplifying the codebase. This refactor focuses on cleaning up unused tunnel functionalities, improving maintainability and clarity across the application. * style: apply prettier and cargo fmt formatting Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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Steven EnamakelGitHubClaude Opus 4.6coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com>CodeRabbit |
262390274d |
feat(auth): Telegram bot registration flow — /auth/telegram endpoint (#150)
* feat(auth): add /auth/telegram registration endpoint for bot-initiated login When a user sends /start register to the Telegram bot, the bot sends an inline button pointing to localhost:7788/auth/telegram?token=<token>. This new GET handler consumes the one-time login token via the backend, stores the resulting JWT as the app session, and returns a styled HTML success/error page. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * style: apply cargo fmt to telegram auth handler Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: apply CodeRabbit auto-fixes Fixed 1 file(s) based on 2 unresolved review comments. Co-authored-by: CodeRabbit <noreply@coderabbit.ai> * update format --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com> Co-authored-by: CodeRabbit <noreply@coderabbit.ai> |
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Steven EnamakelGitHubClaude Opus 4.6coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com>CodeRabbit |
684e784896 |
feat(agent): add self-learning subsystem with post-turn reflection (#149)
* feat(agent): add self-learning subsystem with post-turn reflection Integrate Hermes-inspired self-learning capabilities into the agent core: - Post-turn hook infrastructure (hooks.rs): async, fire-and-forget hooks that receive TurnContext with tool call records after each turn - Reflection engine: analyzes turns via local Ollama or cloud reasoning model, extracts observations/patterns/preferences, stores in memory - User profile learning: regex-based preference extraction from user messages (e.g. "I prefer...", "always use...") - Tool effectiveness tracking: per-tool success rates, avg duration, common error patterns stored in memory - tool_stats tool: lets the agent query its own effectiveness data - LearningConfig: master switch (default off), configurable reflection source (local/cloud), throttling, complexity thresholds - Prompt sections: inject learned context and user profile into system prompt when learning is enabled All storage uses existing Memory trait with Custom categories. All hooks fire via tokio::spawn (non-blocking). Everything behind config flags. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * style: apply cargo fmt formatting Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: apply CodeRabbit auto-fixes Fixed 6 file(s) based on 7 unresolved review comments. Co-authored-by: CodeRabbit <noreply@coderabbit.ai> * fix(learning): address PR review — sanitization, async, atomicity, observability Fixes all findings from PR review: 1. Sanitize tool output: Replace raw output_snippet with sanitized output_summary via sanitize_tool_output() — strips PII, classifies error types, never stores raw payloads in ToolCallRecord 2. Env var overrides: Add OPENHUMAN_LEARNING_* env vars in apply_env_overrides() — enabled, reflection_enabled, user_profile_enabled, tool_tracking_enabled, skill_creation_enabled, reflection_source (local/cloud), max_reflections_per_session, min_turn_complexity 3. Sanitize prompt injection: Pre-fetch learned context async in Agent::turn(), pass through PromptContext.learned field, sanitize via sanitize_learned_entry() (truncate, strip secrets) — no raw entry.content in system prompt 4. Remove blocking I/O: Replace std::thread::spawn + Handle::block_on in prompt sections with async pre-fetch in turn() + data passed via PromptContext.learned — fully non-blocking prompt building 5. Per-session throttling: Replace global AtomicUsize with per-session HashMap<String, usize> under Mutex, rollback counter on reflection or storage failure 6. Atomic tool stats: Add per-tool tokio::sync::Mutex to serialize read-modify-write cycles, preventing lost concurrent updates 7. Tool registration tracing: Add tracing::debug for ToolStatsTool registration decision in ops.rs 8. System prompt refresh: Rebuild system prompt on subsequent turns when learning is enabled, replacing system message in history so newly learned context is visible 9. Hook observability: Add dispatch-level debug logging (scheduling, start time, completion duration, error timing) to fire_hooks 10. tool_stats logging: Add debug logging for query filter, entry count, parse failures, and filter misses Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com> Co-authored-by: CodeRabbit <noreply@coderabbit.ai> |
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Steven EnamakelandGitHub
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bed15f0978 | Update issue templates (#148) | ||
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Steven Enamakel
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5cbec9f06c | Merge remote-tracking branch 'upstream/main' | ||
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58b8a0dd4d |
fix(skills): persist OAuth credentials and fix skill auto-start lifecycle (#146)
* refactor(deep-link): streamline OAuth handling and skill setup process - Removed the RPC call for persisting setup completion, now handled directly in the preferences store. - Updated comments in the deep link handler to clarify the sequence of operations during OAuth completion. - Enhanced the `set_setup_complete` function to automatically enable skills upon setup completion, improving user experience during skill activation. This refactor simplifies the OAuth deep link handling and ensures skills are automatically enabled after setup, enhancing the overall flow. * feat(skills): enhance SkillSetupModal and snapshot fetching with polling - Added a mechanism in SkillSetupModal to sync the setup mode when the setup completion status changes, improving user experience during asynchronous loading. - Updated the useSkillSnapshot and useAllSkillSnapshots hooks to include periodic polling every 3 seconds, ensuring timely updates from the core sidecar and enhancing responsiveness to state changes. These changes improve the handling of skill setup and snapshot fetching, providing a more seamless user experience. * fix(ErrorFallbackScreen): update reload button behavior to navigate to home before reloading - Modified the onClick handler of the reload button to first set the window location hash to '#/home' before reloading the application. This change improves user experience by ensuring users are directed to the home screen upon reloading. * refactor(intelligence-api): simplify local-only hooks and remove unused code - Refactored the `useIntelligenceApiFallback` hooks to focus on local-only implementations, removing reliance on backend APIs and mock data. - Streamlined the `useActionableItems`, `useUpdateActionableItem`, `useSnoozeActionableItem`, and `useChatSession` hooks to operate solely with in-memory data. - Updated comments for clarity on the local-only nature of the hooks and their intended usage. - Enhanced the `useIntelligenceStats` hook to derive entity counts from local graph relations instead of fetching from a backend API, improving performance and reliability. - Removed unused imports and code related to backend interactions, resulting in cleaner and more maintainable code. * feat(intelligence): add active tab state management for Intelligence component - Introduced a new `IntelligenceTab` type to manage the active tab state within the Intelligence component. - Initialized the `activeTab` state to 'memory', enhancing user experience by allowing tab-specific functionality and navigation. This update lays the groundwork for future enhancements related to tabbed navigation in the Intelligence feature. * feat(intelligence): implement tab navigation and enhance UI interactions - Added a tab navigation system to the Intelligence component, allowing users to switch between 'Memory', 'Subconscious', and 'Dreams' tabs. - Integrated conditional rendering for the 'Analyze Now' button, ensuring it is only displayed when the 'Memory' tab is active. - Updated the UI to include a 'Coming Soon' label for the 'Subconscious' and 'Dreams' tabs, improving user awareness of upcoming features. - Enhanced the overall layout and styling for better user experience and interaction. * refactor(intelligence): streamline UI text and enhance OAuth credential handling - Simplified text rendering in the Intelligence component for better readability. - Updated the description for subconscious and dreams sections to provide clearer context on functionality. - Refactored OAuth credential handling in the QjsSkillInstance to utilize a data directory for persistence, improving credential management and recovery. - Enhanced logging for OAuth credential restoration and persistence, ensuring better traceability of actions. * fix(skills): update OAuth credential handling in SkillManager - Modified the SkillManager to use `credentialId` instead of `integrationId` for OAuth notifications, aligning with the expectations of the JS bootstrap's oauth.fetch. - Enhanced the parameters passed during the core RPC call to include `grantedScopes` and ensure the provider defaults to "unknown" if not specified, improving the robustness of the skill activation process. * fix(skills): derive modal mode from snapshot instead of syncing via effect Avoids the react-hooks/set-state-in-effect lint warning by deriving the setup/manage mode directly from the snapshot's setup_complete flag. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * refactor(ErrorFallbackScreen): format reload button onClick handler for improved readability - Reformatted the onClick handler of the reload button to enhance code readability by adding line breaks. - Updated import order in useIntelligenceStats for consistency. - Improved logging format in event_loop.rs and js_helpers.rs for better traceability of OAuth credential actions. --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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3369454cbe |
fix(local-ai): Ollama bootstrap failure UX and auto-recovery (#142)
* feat(local-ai): enhance Ollama installation and path configuration - Added a new command to set a custom path for the Ollama binary, allowing users to specify a manually installed version. - Updated the LocalModelPanel and Home components to reflect the installation state, including progress indicators for downloading and installing. - Enhanced error handling to display detailed installation errors and provide guidance for manual installation if needed. - Introduced a new state for 'installing' to improve user feedback during the Ollama installation process. - Refactored related components and utility functions to accommodate the new installation flow and error handling. This update improves the user experience by providing clearer feedback during the Ollama installation process and allowing for custom binary paths. * feat(local-ai): enhance LocalAIDownloadSnackbar and Home component - Updated LocalAIDownloadSnackbar to display installation phase details and improve progress bar animations during the installation state. - Refactored the display logic to show 'Installing...' when in the installing phase, enhancing user feedback. - Modified Home component to present warnings in a more user-friendly format, improving visibility of local AI status warnings. These changes improve the user experience by providing clearer feedback during downloads and installations. * feat(onboarding): update LocalAIStep to integrate Ollama installation - Added Ollama SVG icon to the LocalAIStep component for visual representation. - Updated text to clarify that OpenHuman will automatically install Ollama for local AI model execution. - Enhanced privacy and resource impact descriptions to reflect Ollama's functionality. - Changed button text to "Download & Install Ollama" for clearer user action guidance. - Improved messaging for users who skip Ollama installation, emphasizing future setup options. These changes enhance user understanding and streamline the onboarding process for local AI model usage. * feat(onboarding): update LocalAIStep and LocalAIDownloadSnackbar for improved user experience - Modified the LocalAIStep component to include a "Setup later" button for user convenience and updated the messaging to clarify the installation process for Ollama. - Enhanced the LocalAIDownloadSnackbar by repositioning it to the bottom-right corner for better visibility and user interaction. - Updated the Ollama SVG icon to include a white background for improved contrast and visibility. These changes aim to streamline the onboarding process and enhance user understanding of the local AI installation and usage. * feat(local-ai): add diagnostics functionality for Ollama server health check - Introduced a new diagnostics command to assess the Ollama server's health, list installed models, and verify expected models. - Updated the LocalModelPanel to manage diagnostics state and display errors effectively. - Enhanced error handling for prompt testing to provide clearer feedback on issues encountered. - Refactored related components and utility functions to support the new diagnostics feature. These changes improve the application's ability to monitor and report on the local AI environment, enhancing user experience and troubleshooting capabilities. * feat(local-ai): add Ollama diagnostics section to LocalModelPanel - Introduced a new diagnostics feature in the LocalModelPanel to check the health of the Ollama server, display installed models, and verify expected models. - Implemented loading states and error handling for the diagnostics process, enhancing user feedback during checks. - Updated the UI to present diagnostics results clearly, including server status, installed models, and any issues found. These changes improve the application's monitoring capabilities for the local AI environment, aiding in troubleshooting and user experience. * feat(local-ai): implement auto-retry for Ollama installation on degraded state - Enhanced the Home component to include a reference for tracking auto-retry status during Ollama installation. - Updated the local AI service to retry the installation process if the server state is degraded, improving resilience against installation failures. - Introduced a new method to force a fresh install of the Ollama binary, ensuring that users can recover from initial setup issues more effectively. These changes enhance the reliability of the local AI setup process, providing a smoother user experience during installation and recovery from errors. * feat(local-ai): improve Ollama server management and diagnostics - Refactored the Ollama server management logic to include a check for the runner's health, ensuring that the server can execute models correctly. - Introduced a new method to verify the Ollama runner's functionality by sending a lightweight request, enhancing error handling for server issues. - Added functionality to kill any stale Ollama server processes before restarting with the correct binary, improving reliability during server restarts. - Updated the server startup process to streamline the handling of server health checks and binary resolution. These changes enhance the robustness of the local AI service, ensuring better management of the Ollama server and improved diagnostics for user experience. * style: apply prettier and cargo fmt formatting Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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c5e5ae170c |
ci: speed up GitHub Actions builds (~14m → ~3-5m warm) (#136)
* chore: add CI profile for faster compilation in Cargo.toml files - Introduced a new `[profile.ci]` section in both root and Tauri Cargo.toml files to optimize build settings for continuous integration. - Adjusted compilation parameters to prioritize speed over runtime performance, including reduced optimization level and enabled code generation units. * refactor(tests): update agent test setup to return temporary directory - Modified the `build_agent_with` function calls in the agent tests to return a temporary directory alongside the agent instance, improving resource management during tests. - Ensured consistency in test setup across multiple test functions. * chore: update .gitignore to include fastembed_cache - Added 'workflow' and '.fastembed_cache' to the .gitignore file to prevent unnecessary files from being tracked in the repository. * test: enhance dispatch routing tests with panic handling Updated the `dispatch_routes_memory_doc_ingest` test to use `AssertUnwindSafe` and `catch_unwind` for better handling of potential panics during execution. This ensures that the test verifies route existence even if the handler encounters a panic, improving robustness against shared state issues in concurrent tests. * ci: speed up builds with rust-cache, sccache, mold linker, and CI profile - Replace manual Cargo registry cache with Swatinem/rust-cache@v2 (caches target/ directories for both core and Tauri crates) - Add mozilla-actions/sccache for cross-branch compilation caching - Install mold linker on Linux for faster linking - Use --profile ci for sidecar build (opt-level 1, codegen-units 16) - Override release profile env vars for Tauri build with CI-tuned settings - Add --bundles none to CI build (skip unused deb/appimage packaging) - Restrict push triggers to main branch only (PRs already cover feature branches, preventing duplicate runs) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(ci): unset RUSTC_WRAPPER for cargo fmt to avoid sccache errors The sccache-action sets RUSTC_WRAPPER globally for the job. cargo fmt invokes rustc through sccache which fails if the GHA cache service is unavailable. Clear RUSTC_WRAPPER for fmt steps and remove redundant per-step env overrides (the action already sets them job-wide). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * refactor: implement Default trait for various structs and enums - Added Default implementations for ConnectionStatus, AgentBuilder, NativeRuntime, AutocompleteEngine, CliChannel, ActionTracker, SkillStatus, and ExtractionMode to streamline object initialization. - Simplified condition checks in several places by replacing map_or with is_some_and and is_none_or for better readability and performance. - Updated various instances of string handling in message sending to remove unnecessary conversions. This refactor enhances code clarity and consistency across the codebase. * style: clean up whitespace and improve code formatting - Removed unnecessary blank lines in several files to enhance code readability. - Simplified condition checks by consolidating method calls into single lines for better clarity. - Improved formatting in various functions to maintain consistency across the codebase. * fix(ci): use --bundles deb instead of unsupported none value Tauri CLI on this version doesn't support 'none' as a bundle type. Use 'deb' as the lightest single bundle to minimize packaging time. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat(ci): add Dockerfile and CI workflows for building and pushing Docker images - Introduced a Dockerfile to set up a CI environment with necessary dependencies for Tauri, Rust, Node.js, and sccache. - Created a new workflow to build and push the CI Docker image to GitHub Container Registry on main branch pushes. - Updated existing workflows to utilize the new Docker image for building and testing, enhancing consistency and efficiency in CI processes. * chore(ci): update container image references in CI workflows - Removed unnecessary permissions for packages in build, test, and typecheck workflows. - Updated container image references to use a specific digest instead of the latest tag for improved stability and reproducibility in CI processes. * fix(ci): use correct amd64 Docker image digest Previous digest was from arm64 build (Mac). Rebuilt with --platform linux/amd64 for GitHub Actions runners. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(ci): use tag instead of digest for Docker image reference GHCR doesn't support pulling OCI index manifests by digest reliably. Use the rust-1.93.0 tag which is pinned to a specific Rust version and resolves correctly on amd64 CI runners. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(ci): rename Docker package to openhuman_ci Move from nested ghcr.io/tinyhumansai/openhuman/ci-runner to ghcr.io/tinyhumansai/openhuman_ci to avoid GHCR nested package manifest resolution issues. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(ci): remove sccache env vars from container jobs sccache can't access the GHA cache API from inside a Docker container (missing ACTIONS_CACHE_URL/ACTIONS_RUNTIME_TOKEN). Swatinem/rust-cache already caches target/ which provides the main build speedup. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * chore: update installer smoke workflow to trigger on main branch pushes - Added a trigger for the installer smoke workflow to run on pushes to the main branch, enhancing CI coverage for mainline changes. * fix: enhance Sentry DSN retrieval logic - Updated the Sentry DSN retrieval process to include an additional fallback option using `option_env!`, ensuring that the DSN can be sourced from both environment variables and optional configuration, improving robustness in observability setup. * chore: add OPENHUMAN_SENTRY_DSN to release workflow and example secrets - Included the OPENHUMAN_SENTRY_DSN variable in the release workflow configuration to enhance observability setup. - Updated the ci-secrets.example.json file to include a placeholder for OPENHUMAN_SENTRY_DSN, providing clarity for developers on required environment variables. --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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Cyrus GrayandGitHub
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8486a3b02e |
feat(onboarding): calmer onboarding + local AI download snackbar (#134)
* feat(onboarding): calmer onboarding with durable deferral + local AI download snackbar - Add persisted `onboardingDeferredByUser` state so "Set up later" survives across sessions (no more overlay nagging on every launch) - Add SetupBanner for non-intrusive "Finish setting up" reminder with resume path - Convert LocalAIStep to fire-and-forget download, advancing immediately - Add LocalAIDownloadSnackbar (bottom-left, collapsible) for persistent download progress that doesn't block the main chrome - Extract shared helpers (formatBytes, formatEta, progressFromStatus) to localAiHelpers.ts - Add Vitest tests for overlay gating, banner, and snackbar Closes #101 * fix(test): remove per-test config mock that overrode global setup exports The OnboardingOverlay test mocked utils/config with only DEV_FORCE_ONBOARDING, which shadowed the global mock from setup.ts and dropped IS_DEV — causing store/index.ts to fail on CI. |
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sanil-23andGitHub
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600dab4336 |
refactor: migrate memory service to controller registry pattern (#138)
Move all 23 memory RPC methods from legacy dispatch (src/rpc/dispatch.rs) to the controller registry pattern with typed schemas. - Create src/openhuman/memory/schemas.rs with 23 ControllerSchema definitions, RegisteredController entries, and handler functions - Wire memory controllers into src/core/all.rs registry builders - Remove all memory.* and ai.* branches from dispatch.rs (only security_policy_info remains) - Update frontend to use openhuman.memory_* method names directly in tauriCommands.ts (no legacy aliases needed) - Move ai.list_memory_files/read/write into memory namespace as openhuman.memory_list_files/read_file/write_file - Update jsonrpc.rs and tauriCommandsMemory test method strings Methods are now accessible via both JSON-RPC (openhuman.memory_*) and CLI (openhuman memory <function>). |
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Steven EnamakelandGitHub
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e5e09221b2 |
fix: service gate buttons unclickable on startup (#139)
* refactor: enhance service command handling and improve service state checks - Updated the ServiceBlockingGate component to include additional checks for service installation status, ensuring it accounts for 'Unknown' states. - Refactored tauriCommands to implement direct service command invocations with error handling, allowing fallback to CLI parsing for service operations (install, start, stop, status, uninstall). - Introduced a new utility function to parse CLI JSON output into the expected CommandResponse format, improving robustness in service command responses. - Added new Tauri commands for direct service interactions, enhancing the application's ability to manage service states effectively. * docs: add debug logging guidelines to CLAUDE.md and enhance ServiceBlockingGate component - Introduced a new section in CLAUDE.md outlining best practices for debug logging, emphasizing verbose diagnostics, critical checkpoints, structured context, and safety measures. - Updated the ServiceBlockingGate component to improve operation handling by adding an operating label state, enhancing user feedback during service operations, and refining error handling and logging for better traceability. * style: add pointer-events none to CSS for improved interaction handling - Updated index.css to include pointer-events: none; for specific elements, enhancing user experience by preventing unintended interactions. * style: improve text formatting and readability in ServiceBlockingGate and tauriCommands - Refactored text in the ServiceBlockingGate component for better readability by consolidating lines. - Enhanced the formatting of the openhumanServiceStart function in tauriCommands for improved clarity in the method call structure. |
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Mega MindandGitHub
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2b33afeefe |
fix(skills): enforce per-skill runtime tool isolation (#140)
* Add unit tests for Mnemonic page - Introduced comprehensive tests for the Mnemonic page, covering initial render, copy to clipboard functionality, confirmation checkbox behavior, and mode switching between generate and import. - Validated user interactions, including input handling and button states, ensuring robust functionality and user experience. - Enhanced test coverage for various scenarios, including validation of mnemonic phrases and loading states during operations. * test: add cross-stack test coverage for core and tauri flows Add focused Rust and frontend tests for core process startup behavior, CLI argument parsing, JSON-RPC error handling, and Tauri command/RPC mapping paths to improve confidence for issue #57. Closes #57 Made-with: Cursor * refactor(tests): streamline test code and improve readability Consolidate mock imports and simplify function calls in coreRpcClient tests. Adjust formatting in Rust core_process and CLI tests for better clarity. Update mnemonic test assertions for improved accuracy. Made-with: Cursor * fix(e2e): harden deep-link login flow reliability Stabilize auth deep-link handling and E2E delivery with readiness guards, retries, and new listener unit tests so login/onboarding flows are deterministic for issue #70. Closes #70 Made-with: Cursor * refactor(tests): update agent initialization in tests for consistency Refactor test cases to use a tuple return from `build_agent_with`, improving consistency in agent setup across multiple tests. This change enhances readability and maintains uniformity in the test structure. Made-with: Cursor * fix(skills): enforce per-skill runtime tool isolation Add explicit tool-call origin policy in the QuickJS runtime so skills cannot invoke other skills' tools, while preserving external orchestration through RPC/socket surfaces. Also remove the generic skills_call tool path and document the isolation contract for skill authors. Closes #94 Made-with: Cursor |
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Mega MindandGitHub
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ccb151be8a |
fix(e2e): harden deep-link login flow reliability (#137)
* Add unit tests for Mnemonic page - Introduced comprehensive tests for the Mnemonic page, covering initial render, copy to clipboard functionality, confirmation checkbox behavior, and mode switching between generate and import. - Validated user interactions, including input handling and button states, ensuring robust functionality and user experience. - Enhanced test coverage for various scenarios, including validation of mnemonic phrases and loading states during operations. * test: add cross-stack test coverage for core and tauri flows Add focused Rust and frontend tests for core process startup behavior, CLI argument parsing, JSON-RPC error handling, and Tauri command/RPC mapping paths to improve confidence for issue #57. Closes #57 Made-with: Cursor * refactor(tests): streamline test code and improve readability Consolidate mock imports and simplify function calls in coreRpcClient tests. Adjust formatting in Rust core_process and CLI tests for better clarity. Update mnemonic test assertions for improved accuracy. Made-with: Cursor * fix(e2e): harden deep-link login flow reliability Stabilize auth deep-link handling and E2E delivery with readiness guards, retries, and new listener unit tests so login/onboarding flows are deterministic for issue #70. Closes #70 Made-with: Cursor |
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77fd5f9edd |
fix: propagate entity_type into retrieval context for graph visualization (#135)
* feat(memory): connect graph query and doc ingest APIs to frontend Wire up memory.graph.query and memory.doc.ingest RPC endpoints and integrate graph relations into the MemoryWorkspace UI, replacing backend-only entity counts with local graph store data. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * style: fix Prettier formatting in MemoryWorkspace and tauriCommands Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * test: add unit tests for memory graph query, doc ingest, and dispatch routing Cover the new graph query and doc ingest APIs added in this PR: - Rust dispatch tests: routing, param validation, unknown method fallthrough - Frontend tauriCommands tests: Tauri guard, RPC forwarding for memoryGraphQuery/memoryDocIngest - MemoryWorkspace component tests: graph relations rendering, evidence badges, empty states Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * style: fix Prettier and cargo fmt formatting in test files Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * style: fix Prettier formatting in tauriCommandsMemory test Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: merge duplicate tauriCommands import in MemoryWorkspace Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * style: fix Prettier formatting in MemoryWorkspace Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: propagate entity_type from graph relation attrs into retrieval context build_retrieval_context was discarding entity types that were already present in relation attrs.entity_types (populated during ingestion by GLiNER relex). Entities in MemoryRetrievalEntity now carry their type (e.g. PERSON, PROJECT, WORK_ITEM) instead of always being None. Adds unit tests for both typed and untyped paths, plus an ignored GLiNER smoke test (gline_rs_smoke) that verifies the full pipeline from Notion fixture ingestion through graph storage to retrieval context with the real ONNX model. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> --------- Co-authored-by: sanil jain <jainsanil18@gmail.com> Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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906b55b63e |
feat(observability): add Sentry error reporting to Rust core (#131)
* chore(workflows): comment out Windows smoke tests in installer and release workflows * feat(observability): integrate Sentry for error reporting and add configuration support - Added Sentry integration for error reporting in the application, initializing it in the main function. - Introduced a new environment variable `OPENHUMAN_SENTRY_DSN` to configure Sentry DSN. - Updated the observability configuration schema to include a field for Sentry DSN. - Enhanced logging to include Sentry event filtering based on log levels. - Implemented secret scrubbing to protect sensitive information in error reports. * feat(analytics): add support for anonymized analytics settings - Introduced new environment variable `OPENHUMAN_ANALYTICS_ENABLED` to enable or disable anonymized analytics and crash reports. - Updated the PrivacyPanel component to sync analytics consent with the core configuration. - Added new functions to handle analytics settings updates and retrieval in the Tauri backend. - Enhanced observability configuration to include analytics settings, defaulting to enabled. - Updated relevant schemas and handlers for analytics settings in the backend. * refactor(tauriCommands): improve formatting and structure of analytics settings function - Reformatted the `openhumanUpdateAnalyticsSettings` function for better readability by adjusting the parameter structure. - Enhanced the output formatting in the `handle_get_analytics_settings` function for improved clarity in the JSON response. * feat(analytics): sync analytics consent to core RPC and improve anonymization copy Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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Mega MindandGitHub
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52b59f62d7 |
test: add cross-stack coverage for core and tauri flows (#130)
* Add unit tests for Mnemonic page - Introduced comprehensive tests for the Mnemonic page, covering initial render, copy to clipboard functionality, confirmation checkbox behavior, and mode switching between generate and import. - Validated user interactions, including input handling and button states, ensuring robust functionality and user experience. - Enhanced test coverage for various scenarios, including validation of mnemonic phrases and loading states during operations. * test: add cross-stack test coverage for core and tauri flows Add focused Rust and frontend tests for core process startup behavior, CLI argument parsing, JSON-RPC error handling, and Tauri command/RPC mapping paths to improve confidence for issue #57. Closes #57 Made-with: Cursor * refactor(tests): streamline test code and improve readability Consolidate mock imports and simplify function calls in coreRpcClient tests. Adjust formatting in Rust core_process and CLI tests for better clarity. Update mnemonic test assertions for improved accuracy. Made-with: Cursor |
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Steven Enamakel
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2db664e406 | Merge remote-tracking branch 'upstream/main' | ||
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4d3b63857f |
feat(memory): connect graph query and doc ingest APIs (#124)
* feat(memory): connect graph query and doc ingest APIs to frontend Wire up memory.graph.query and memory.doc.ingest RPC endpoints and integrate graph relations into the MemoryWorkspace UI, replacing backend-only entity counts with local graph store data. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * style: fix Prettier formatting in MemoryWorkspace and tauriCommands Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * test: add unit tests for memory graph query, doc ingest, and dispatch routing Cover the new graph query and doc ingest APIs added in this PR: - Rust dispatch tests: routing, param validation, unknown method fallthrough - Frontend tauriCommands tests: Tauri guard, RPC forwarding for memoryGraphQuery/memoryDocIngest - MemoryWorkspace component tests: graph relations rendering, evidence badges, empty states Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * style: fix Prettier and cargo fmt formatting in test files Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * style: fix Prettier formatting in tauriCommandsMemory test Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: merge duplicate tauriCommands import in MemoryWorkspace Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * style: fix Prettier formatting in MemoryWorkspace Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> --------- Co-authored-by: sanil jain <jainsanil18@gmail.com> Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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Steven Enamakel
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11da8f44b7 | chore(workflows): comment out Windows smoke tests in installer and release workflows | ||
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Mega MindandGitHub
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b855ce97fd |
Merge pull request #127 from M3gA-Mind/feat/system-tray-bug
fix(tauri): restore working tray controls in desktop shell |
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M3gA-Mind
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91e92cb98a |
fix(tauri): restore working tray controls in desktop shell
Implement tray icon setup directly in app/src-tauri with open/quit actions and daemon-safe window restore flow, plus tray behavior docs updates. Closes #93. Made-with: Cursor |
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Mega MindandGitHub
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1a1f948e82 |
Merge pull request #126 from M3gA-Mind/feat/skills-resetup
feat: re-setup skills runtime and add model-callable skills bridge |
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M3gA-Mind
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9aa60e6e42 |
feat(agent): add generic skills_call bridge for runtime skill tools
Expose a model-callable `skills_call` tool in the shared tool registry and add coverage for native dispatcher execution of generic skill invocations. Closes #67. Made-with: Cursor |
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Mega MindandGitHub
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f87c2d0894 |
Merge pull request #125 from M3gA-Mind/feat/skills-resetup
fix(agent): execute fallback tool calls in the loop |
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M3gA-Mind
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331b1e4ef8 | Remove openhuman-skills submodule and add comprehensive documentation on the skills system, detailing discovery, installation, execution, and synchronization processes for engineers. This includes a mental model, key directories, skill packaging, registry flow, and runtime behavior. | ||
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M3gA-Mind
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7b0e07f8ad |
fix(agent): execute fallback tool calls in the loop
Unify tool-call parsing across dispatcher paths and persist parsed fallback calls with stable IDs so execution and history stay aligned end-to-end. Closes #65 Made-with: Cursor |
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oxoxDevandGitHub
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5481c9266e | feat(autocomplete): persist accepted completions in memory and reuse them for suggestions (#108) (#119) | ||
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oxoxDevandGitHub
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c46adfa19a | feat(installer): add one-command installer flow and release smoke checks (#123) | ||
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Al629176andGitHub
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e7a7f90fb6 |
Merge pull request #113 from sanil-23/issue-60-ingestion-relex
Add GLiNER relex ingestion pipeline (#60) |
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M3gA-MindandClaude Sonnet 4.6
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649c381f3d |
feat: set up openhuman-skills git submodule
- Add openhuman-skills submodule pointing to tinyhumansai/openhuman-skills - Remove openhuman-skills from .gitignore so the submodule is tracked - Update skill discovery paths in qjs_engine.rs from skills/skills to openhuman-skills/skills (dev cwd, parent, and bundled resource paths) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> |
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Cyrus GrayandGitHub
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32cd2a7ef3 |
Merge pull request #121 from graycyrus/main
update: modify .gitignore to include `create_issue` and remove redund… |
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cyrus@tinyhumans.ai
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f8f63f97c8 |
update: modify .gitignore to include create_issue and remove redundant workflow entry
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Cyrus GrayandGitHub
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93c0b725e8 |
Merge pull request #120 from tinyhumansai/feat/local-ai-model-tier-presets
feat(local-ai): guided model tier selection by device capability |