Rename variable, struct, and enum names from camelCase to snake_case throughout the llamacpp extension codebase to align with Rust naming conventions. This change improves readability and consistency without altering functionality.
Change the llama_server_process state from an Option<Child> to a HashMap<String, Child> to support managing multiple server instances by PID. This allows precise process tracking and termination, replacing the previous single-process limitation.
Previously, only one server process could be tracked at a time. Now, each process is stored with its PID as the key, enabling:
- Accurate session matching during unloading
- Proper termination of specific processes
- Better error handling for mismatched PIDs
The load_llama_model function now inserts processes into the map, and unload_llama_model removes them by PID.
The changes standardize identifier names across the codebase for clarity:
- Replaced `sessionId` with `pid` to reflect process ID usage
- Changed `modelName` to `modelId` for consistency with identifier naming
- Renamed `api_key` to `apiKey` for camelCase consistency
- Updated corresponding methods to use these new identifiers
- Improved type safety and readability by aligning variable names with their semantic meaning
This change allows the port to be specified via command line arguments, providing flexibility. The port is parsed from the arguments, defaulting to 8080 if not provided.
The changes improve the robustness of command-line argument parsing in the Llama model server by replacing direct index access with safe iteration methods. A new generate_api_key function was added to handle API key generation securely. The sessionId parameter was standardized to match the renamed property in the client code.
- Changed load method to accept modelId instead of loadOptions for better clarity and simplicity
- Renamed engineBasePath parameter to backendPath for consistency with the backend's directory structure
- Added getRandomPort method to ensure unique ports for each session to prevent conflicts
- Refactored configuration and model loading logic to improve maintainability and reduce redundancy
* wip
* update
* add download logic
* add decompress. support delete file
* download backend upon selecting setting
* add some logging and nootes
* add note on race condition
* remove then catch
* default to none backend. only download if it's not installed
* merge version and backend. fetch version from GH
* restrict scope of output_dir
* add note on unpack
This commit introduces API key generation for the Llama.cpp extension. The API key is now generated on the server side using HMAC-SHA256 and a secret key to ensure security and uniqueness. The frontend now passes the model ID and API secret to the server to generate the key. This addresses the requirement for secure model access and authorization.
* add pull and abortPull
* add model import (download only)
* write model.yaml. support local model import
* remove cortex-related command
* add TODO
* remove cortex-related command
* feat: implement retry mechanism for MCP server activation with exponential backoff
feat: enhance MCP server activation with configurable retry attempts
feat: implement MCP server restart monitoring and cleanup functionality
feat: enhance MCP server restart logic with improved monitoring and configuration handling
feat: add manual deactivation for MCP servers to prevent automatic restarts
* feat: enhance MCP server startup with initial attempt tracking and health monitoring
- Add filtering logic to proxy server for GET /models requests
- Keep only models with status "downloaded" in response
- Remove Content-Length header to prevent mismatch after filtering
- Support both ListModelsResponseDto and direct array formats
- Add comprehensive tests for filtering functionality
- Fix Content-Length header conflict causing empty responses
Fixes issue where all models were returned regardless of download status.
* chore: simple onboarding local model
* chore: update new model and improve flow e2e onboarding local model
* fix: default tool support models
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Co-authored-by: Louis <louis@jan.ai>
