* fix: generate a response button should appear when an incomplete tool call message is present
* fix: wording
* fix: do not send duplicate messages on regenerating
* fix: tests
* fix: remove CREATE_NEW_PROCESS_GROUP flag for proper Ctrl-C handling
CREATE_NEW_PROCESS_GROUP prevented GenerateConsoleCtrlEvent from working,
causing graceful shutdown failures. Removed to enable proper signal handling.
* Revert "fix: remove CREATE_NEW_PROCESS_GROUP flag for proper Ctrl-C handling"
This reverts commit 82ace3e72e4bf7338f422d5c79bdd6a0f8a2440e.
* fix: use direct process termination instead of console events
Simplified Windows process cleanup by removing console attachment logic
and using direct child.kill() method. More reliable for headless processes.
* Fix missing imports
* switch to tokio::time
* Don't wait while forcefully terminate process using kill API on Windows
Disabled use of windows-sys crate as graceful shutdown on Windows is unreliable in this context.
Updated cleanup.rs and server.rs to directly call child.kill().await for terminating processes on Windows.
Improved logging for process termination and error handling during kill and wait.
Removed timeout-based graceful shutdown attempt on Windows since TerminateProcess is inherently forceful and immediate.
This ensures more predictable process cleanup behavior on Windows platforms.
* final cleanups
This change improves the robustness of the llama.cpp extension's server port selection.
Previously, the `getRandomPort()` method only checked for ports already in use by active sessions, which could lead to model load failures if the chosen port was occupied by another external process.
This change introduces a new Tauri command, `is_port_available`, which performs a system-level check to ensure the randomly selected port is truly free before attempting to start the llama-server. It also adds a retry mechanism with a maximum number of attempts (20,000) to find an available port, throwing an error if no suitable port is found within the specified range after all attempts.
This enhancement prevents port conflicts and improves the reliability and user experience of the llama.cpp extension within Jan.
Closes#5965
* fix: assistant with last used and fix metadata
* chore: revert instruction and desc
* chore: fix current assistant state
* chore: updae metadata message assistant
* chore: update test case
Previously, the `autoUnload` flag was not being updated when set via config,
causing models to be auto-unloaded regardless of the intended behavior.
This patch ensures the setting is respected at runtime.
This commit addresses a race condition where, with "Auto-Unload Old Models" enabled, rapidly attempting to load multiple models could result in more than one model being loaded simultaneously.
Previously, the unloading logic did not account for models that were still in the process of loading when a new load operation was initiated. This allowed new models to start loading before the previous ones had fully completed their unload cycle.
To resolve this:
- A `loadingModels` map has been introduced to track promises for models currently in the loading state.
- The `load` method now checks if a model is already being loaded and, if so, returns the existing promise, preventing duplicate load operations for the same model.
- The `performLoad` method (which encapsulates the actual loading logic) now ensures that when `autoUnload` is active, it waits for any *other* models that are concurrently loading to finish before proceeding to unload all currently loaded models. This guarantees that the auto-unload mechanism properly unloads all models, including those initiated in quick succession, thereby preventing the race condition.
This fixes the issue where clicking the start button very fast on multiple models would bypass the auto-unload functionality.
* fix: migrate app settings to the new version
* fix: edge cases
* fix: migrate HF import model on Windows
* fix hardware page broken after downgraded
* test: correct test
* fix: backward compatible hardware info
This commit addresses a potential race condition that could lead to "connection errors" when unloading a llamacpp model.
The issue arose because the `activeSessions` map still has the session info of the model during unload. This could lead to "connection errors" when the backend is taking time to unload while there is an ongoing request to the model.
The fix involves:
1. **Deleting the `pid` from `activeSessions` before calling backend's unload:** This ensures that the model is cleared from the map before we start unloading.
2. **Failure handling**: If somehow the backend fails to unload, the session info for that model is added back to prevent any race conditions.
This commit improves the robustness and reliability of the unloading process by preventing potential conflicts.
* fix: Allow N-GPU Layers (NGL) to be set to 0 in llama.cpp
The `n_gpu_layers` (NGL) setting in the llama.cpp extension was incorrectly preventing users from disabling GPU layers by automatically defaulting to 100 when set to 0.
This was caused by a condition that only pushed `cfg.n_gpu_layers` if it was greater than 0 (`cfg.n_gpu_layers > 0`).
This commit updates the condition to `cfg.n_gpu_layers >= 0`, allowing 0 to be a valid and accepted value for NGL. This ensures that users can effectively disable GPU offloading when desired.
* fix: default ngl
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Co-authored-by: Louis <louis@jan.ai>
The 'Auto-Unload Old Models' setting in the llama.cpp extension failed to persist due to a typo in its key name within `settings.json`. The key was incorrectly `auto_unload_models` instead of `auto_unload`.
This commit corrects the key name to `auto_unload`, ensuring that user-configured changes to this setting are properly saved, retrieved, and persist across application restarts.
This resolves the issue where the setting would change and remain to its previous value after being changed.
* feat: Enhance Llama.cpp backend management with persistence
This commit introduces significant improvements to how the Llama.cpp extension manages and updates its backend installations, focusing on user preference persistence and smarter auto-updates.
Key changes include:
* **Persistent Backend Type Preference:** The extension now stores the user's preferred backend type (e.g., `cuda`, `cpu`, `metal`) in `localStorage`. This ensures that even after updates or restarts, the system attempts to use the user's previously selected backend type, if available.
* **Intelligent Auto-Update:** The auto-update mechanism has been refined to prioritize updating to the **latest version of the *currently selected backend type*** rather than always defaulting to the "best available" backend (which might change). This respects user choice while keeping the chosen backend type up-to-date.
* **Improved Initial Installation/Configuration:** For fresh installations or cases where the `version_backend` setting is invalid, the system now intelligently determines and installs the best available backend, then persists its type.
* **Refined Old Backend Cleanup:** The `removeOldBackends` function has been renamed to `removeOldBackend` and modified to specifically clean up *older versions of the currently selected backend type*, preventing the accumulation of unnecessary files while preserving other backend types the user might switch to.
* **Robust Local Storage Handling:** New private methods (`getStoredBackendType`, `setStoredBackendType`, `clearStoredBackendType`) are introduced to safely interact with `localStorage`, including error handling for potential `localStorage` access issues.
* **Version Filtering Utility:** A new utility `findLatestVersionForBackend` helps in identifying the latest available version for a specific backend type from a list of supported backends.
These changes provide a more stable, user-friendly, and maintainable backend management experience for the Llama.cpp extension.
Fixes: #5883
* fix: cortex models migration should be done once
* feat: Optimize Llama.cpp backend preference storage and UI updates
This commit refines the Llama.cpp extension's backend management by:
* **Optimizing `localStorage` Writes:** The system now only writes the backend type preference to `localStorage` if the new value is different from the currently stored one. This reduces unnecessary `localStorage` operations.
* **Ensuring UI Consistency on Initial Setup:** When a fresh installation or an invalid backend configuration is detected, the UI settings are now explicitly updated to reflect the newly determined `effectiveBackendString`, ensuring the displayed setting matches the active configuration.
These changes improve performance by reducing redundant storage operations and enhance user experience by maintaining UI synchronization with the backend state.
* Revert "fix: provider settings should be refreshed on page load (#5887)"
This reverts commit ce6af62c7df4a7e7ea8c0896f307309d6bf38771.
* fix: add loader version backend llamacpp
* fix: wrong key name
* fix: model setting issues
* fix: virtual dom hub
* chore: cleanup
* chore: hide device ofload setting
---------
Co-authored-by: Louis <louis@jan.ai>
Co-authored-by: Faisal Amir <urmauur@gmail.com>
* feat: add support for querying available backend devices
This change introduces a new `get_devices` method to the `llamacpp_extension` engine that allows the frontend to query and display a list of available devices (e.g., Vulkan, CUDA, SYCL) from the compiled `llama-server` binary.
* Added `DeviceList` interface to represent GPU/device metadata.
* Implemented `getDevices(): Promise<DeviceList[]>` method.
* Splits `version/backend`, ensures backend is ready.
* Invokes the new Tauri command `get_devices`.
* Introduced a new `get_devices` Tauri command.
* Parses `llama-server --list-devices` output to extract available devices with memory info.
* Introduced `DeviceInfo` struct (`id`, `name`, `mem`, `free`) and exposed it via serialization.
* Robust parsing logic using string processing (non-regex) to locate memory stats.
* Registered the new command in the `tauri::Builder` in `lib.rs`.
* Fixed logic to correctly parse multiple devices from the llama-server output.
* Handles common failure modes: binary not found, malformed memory info, etc.
This sets the foundation for device selection, memory-aware model loading, and improved diagnostics in Jan AI engine setup flows.
* Update extensions/llamacpp-extension/src/index.ts
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
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Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
