* fix: allow users to download the same model from different authors
* fix: importing models should have author name in the ID
* fix: incorrect model id show
* fix: tests
* fix: default to mmproj f16 instead of bf16
* fix: type
* fix: build error
* feat: add getTokensCount method to compute token usage
Implemented a new async `getTokensCount` function in the LLaMA.cpp extension.
The method validates the model session, checks process health, applies the request template, and tokenizes the resulting prompt to return the token count. Includes detailed error handling for crashed models and API failures, enabling callers to assess token usage before sending completions.
* Fix: typos
* chore: update ui token usage
* chore: remove unused code
* feat: add image token handling for multimodal LlamaCPP models
Implemented support for counting image tokens when using vision-enabled models:
- Extended `SessionInfo` with optional `mmprojPath` to store the multimodal project file.
- Propagated `mmproj_path` from the Tauri plugin into the session info.
- Added import of `chatCompletionRequestMessage` and enhanced token calculation logic in the LlamaCPP extension:
- Detects image content in messages.
- Reads GGUF metadata from `mmprojPath` to compute accurate image token counts.
- Provides a fallback estimation if metadata reading fails.
- Returns the sum of text and image tokens.
- Introduced helper methods `calculateImageTokens` and `estimateImageTokensFallback`.
- Minor clean‑ups such as comment capitalization and debug logging.
* chore: update FE send params message include content type image_url
* fix mmproj path from session info and num tokens calculation
* fix: Correct image token estimation calculation in llamacpp extension
This commit addresses an inaccurate token count for images in the llama.cpp extension.
The previous logic incorrectly calculated the token count based on image patch size and dimensions. This has been replaced with a more precise method that uses the clip.vision.projection_dim value from the model metadata.
Additionally, unnecessary debug logging was removed, and a new log was added to show the mmproj metadata for improved visibility.
* fix per image calc
* fix: crash due to force unwrap
---------
Co-authored-by: Faisal Amir <urmauur@gmail.com>
Co-authored-by: Louis <louis@jan.ai>
Expose the new `mmproj_offload` option in the model settings UI and include it in the `ModelPlan` type. The component now collects the offload flag (`result.offloadMmproj`) and queues it with other setting updates to ensure a single atomic change, preventing race conditions when toggling this feature. This enables users to control MMProj offloading directly from the app.
* feat: Smart model management
* **New UI option** – `memory_util` added to `settings.json` with a dropdown (high / medium / low) to let users control how aggressively the engine uses system memory.
* **Configuration updates** – `LlamacppConfig` now includes `memory_util`; the extension class stores it in a new `memoryMode` property and handles updates through `updateConfig`.
* **System memory handling**
* Introduced `SystemMemory` interface and `getTotalSystemMemory()` to report combined VRAM + RAM.
* Added helper methods `getKVCachePerToken`, `getLayerSize`, and a new `ModelPlan` type.
* **Smart model‑load planner** – `planModelLoad()` computes:
* Number of GPU layers that can fit in usable VRAM.
* Maximum context length based on KV‑cache size and the selected memory utilization mode (high/medium/low).
* Whether KV‑cache must be off‑loaded to CPU and the overall loading mode (GPU, Hybrid, CPU, Unsupported).
* Detailed logging of the planning decision.
* **Improved support check** – `isModelSupported()` now:
* Uses the combined VRAM/RAM totals from `getTotalSystemMemory()`.
* Applies an 80% usable‑memory heuristic.
* Returns **GREEN** only when both weights and KV‑cache fit in VRAM, **YELLOW** when they fit only in total memory or require CPU off‑load, and **RED** when the model cannot fit at all.
* **Cleanup** – Removed unused `GgufMetadata` import; updated imports and type definitions accordingly.
* **Documentation/comments** – Added explanatory JSDoc comments for the new methods and clarified the return semantics of `isModelSupported`.
* chore: migrate no_kv_offload from llamacpp setting to model setting
* chore: add UI auto optimize model setting
* feat: improve model loading planner with mmproj support and smarter memory budgeting
* Extend `ModelPlan` with optional `noOffloadMmproj` flag to indicate when a multimodal projector can stay in VRAM.
* Add `mmprojPath` parameter to `planModelLoad` and calculate its size, attempting to keep it on GPU when possible.
* Refactor system memory detection:
* Use `used_memory` (actual free RAM) instead of total RAM for budgeting.
* Introduced `usableRAM` placeholder for future use.
* Rewrite KV‑cache size calculation:
* Properly handle GQA models via `attention.head_count_kv`.
* Compute bytes per token as `nHeadKV * headDim * 2 * 2 * nLayer`.
* Replace the old 70 % VRAM heuristic with a more flexible budget:
* Reserve a fixed VRAM amount and apply an overhead factor.
* Derive usable system RAM from total memory minus VRAM.
* Implement a robust allocation algorithm:
* Prioritize placing the mmproj in VRAM.
* Search for the best balance of GPU layers and context length.
* Fallback strategies for hybrid and pure‑CPU modes with detailed safety checks.
* Add extensive validation of model size, KV‑cache size, layer size, and memory mode.
* Improve logging throughout the planning process for easier debugging.
* Adjust final plan return shape to include the new `noOffloadMmproj` field.
* remove unused variable
---------
Co-authored-by: Faisal Amir <urmauur@gmail.com>
* call jan api
* fix lint
* ci: add jan server web
* chore: add Dockerfile
* clean up ui ux and support for reasoning fields, make app spa
* add logo
* chore: update tag for preview image
* chore: update k8s service name
* chore: update image tag and image name
* fixed test
---------
Co-authored-by: Minh141120 <minh.itptit@gmail.com>
Co-authored-by: Nguyen Ngoc Minh <91668012+Minh141120@users.noreply.github.com>
* feat: Add model compatibility check and memory estimation
This commit introduces a new feature to check if a given model is supported based on available device memory.
The change includes:
- A new `estimateKVCache` method that calculates the required memory for the model's KV cache. It uses GGUF metadata such as `block_count`, `head_count`, `key_length`, and `value_length` to perform the calculation.
- An `isModelSupported` method that combines the model file size and the estimated KV cache size to determine the total memory required. It then checks if any available device has sufficient free memory to load the model.
- An updated error message for the `version_backend` check to be more user-friendly, suggesting a stable internet connection as a potential solution for backend setup failures.
This functionality helps prevent the application from attempting to load models that would exceed the device's memory capacity, leading to more stable and predictable behavior.
fixes: #5505
* Update extensions/llamacpp-extension/src/index.ts
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
* Update extensions/llamacpp-extension/src/index.ts
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
* Extend this to available system RAM if GGML device is not available
* fix: Improve model metadata and memory checks
This commit refactors the logic for checking if a model is supported by a system's available memory.
**Key changes:**
- **Remote model support**: The `read_gguf_metadata` function can now fetch metadata from a remote URL by reading the file in chunks.
- **Improved KV cache size calculation**: The KV cache size is now estimated more accurately by using `attention.key_length` and `attention.value_length` from the GGUF metadata, with a fallback to `embedding_length`.
- **Granular memory check statuses**: The `isModelSupported` function now returns a more specific status (`'RED'`, `'YELLOW'`, `'GREEN'`) to indicate whether the model weights or the KV cache are too large for the available memory.
- **Consolidated logic**: The logic for checking local and remote models has been consolidated into a single `isModelSupported` function, improving code clarity and maintainability.
These changes provide more robust and informative model compatibility checks, especially for models hosted on remote servers.
* Update extensions/llamacpp-extension/src/index.ts
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
* Make ctx_size optional and use sum free memory across ggml devices
* feat: hub and dropdown model selection handle model compatibility
* feat: update bage model info color
* chore: enable detail page to get compatibility model
* chore: update copy
* chore: update shrink indicator UI
---------
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
Co-authored-by: Faisal Amir <urmauur@gmail.com>
