- Updated CLI documentation to reflect the new handling of `CIVITAI_API_TOKEN`, which is now automatically passed to SwarmUI user settings during startup.
- Improved the `render_access_panel` function to include additional warnings for idle-killer failures and stack errors, enhancing user feedback.
- Introduced a new function `seed_swarmui_api_keys` to manage API key injection into SwarmUI, ensuring seamless integration with the Model Downloader.
- Enhanced GPU environment verification logic to include fail-fast checks for critical components like CUDA, improving error handling and user notifications.
- Updated tests to validate the new API key handling and access panel behavior, ensuring robustness in the integration process.
- Marked critical bugs as resolved in the review documentation, including changes to the `arm_idle_killer` function to raise errors on credential creation failures and ensure proper file permissions for JSON credentials.
- Introduced a new `_try_arm_idle_killer` function in `provision.py` to manage idle-killer state more effectively, ensuring it arms correctly during provisioning.
- Updated the `swarm_busy` function in `remote/idle_killer.py` to allow idle state after a specified duration of Swarm unavailability, preventing unnecessary billing.
- Enhanced performance tuning logic in `tune_swarm_perf.py` to ensure proper handling of pip installation success before applying extra arguments.
- Added tests to validate the new idle-killer behavior and swarm management logic, ensuring robustness in handling idle states and error conditions.
- Updated `env.example` and `gpu-rent.vars.example` to include new variables for LLM runtime and SwarmUI options.
- Refactored CLI commands to support interactive selection of LLM runtime and workload type (SwarmUI, LLM, or both).
- Improved access link generation to handle cases where SwarmUI is disabled, providing clearer user feedback.
- Enhanced provisioning logic to conditionally bootstrap SwarmUI based on user configuration, allowing for LLM-only setups.
- Updated documentation across multiple files to reflect changes in LLM integration, CLI usage, and configuration management.
- Added support for `llamacpp-models.yaml` in `.gitignore` and implemented logic to copy it in `gpu-rent.ps1` and `gpu-rent.sh`.
- Enhanced CLI to prompt for llama.cpp model presets during setup and execution, improving user experience.
- Updated configuration handling to include `llamacpp_models_manifest` and related functions for managing llama.cpp models.
- Improved documentation in `cli.md` and `llm.md` to reflect changes in llama.cpp integration and model management.
- Refactored provisioning logic to handle llama.cpp model downloads and configurations effectively.
- Introduced GPU probing functionality to gather and store GPU specifications in `/mnt/swarm_data/.gpu-rent-gpu.json`, aiding in performance tuning.
- Updated `install_ollama.sh` and `install_llamacpp.sh` to utilize GPU information for configuring optimal runtime parameters.
- Enhanced `provision.py` to include GPU probing and performance tuning logic, ensuring better resource allocation for LLM operations.
- Improved documentation in `decisions.md`, `llm.md`, and `swarmui.md` to reflect changes in GPU handling and performance tuning processes.
- Added new tests to validate the GPU probing and model resolution logic, ensuring robustness in handling various GPU configurations.
- Added support for a new extension, `swarm-assistent`, in `extensions.example.yaml` with a requirement for `ollama`.
- Enhanced the README.md to clarify the setup process and provide a quick start guide for using extensions.
- Updated documentation in `llm.md` to reflect the opt-in nature of LLM support and provide clearer instructions for enabling it.
- Improved the `autocomplete.md` to detail the automatic setup of word lists during the initial launch.
- Revised `cli.md` to include new commands and options related to LLM runtime handling and extension management.
- Enhanced the `spike-notes.md` to guide users through the first live run with a focus on LLM integration.
- Updated `resolve_llm_runtime` to prioritize live configuration over legacy notes, ensuring accurate runtime resolution.
- Enhanced `tunnel_forwards` to prefer current configuration for LLM runtime, improving tunnel setup logic.
- Improved idle-killer logic to handle stale markers and provide clearer warnings in the status output.
- Updated CLI documentation in `cli.md` to reflect changes in command behavior and runtime handling.
- Enhanced tests to validate new runtime resolution logic and ensure proper handling of configuration states.
- Added `ollama-models.yaml` to .gitignore and implemented logic to copy it in gpu-rent.ps1 and gpu-rent.sh.
- Enhanced env.example to include new variables for LLM runtime options and local watchdog configuration.
- Updated CLI commands to support LLM options during setup and execution, including new flags for Ollama and llama.cpp.
- Improved documentation in cli.md and README.md to reflect changes in LLM integration and local watchdog functionality.
- Adjusted architecture and decisions documentation to clarify the role of LLMs and local watchdog in the system.
- Updated .gitignore to include gpu-rent.vars.
- Modified env.example to introduce the UPDATE_GIT variable for controlling git updates during execution.
- Implemented Import-GpuRentVars function in gpu-rent.ps1 to load environment variables from gpu-rent.vars.
- Enhanced gpu-rent.sh to support loading variables from gpu-rent.vars and added logic for handling default and extra arguments.
- Updated CLI documentation to reflect the new gpu-rent.vars file and its usage in configuration.
- Improved bootstrap and provisioning logic to conditionally perform git updates based on the new configuration.
- Updated version number in pyproject.toml and __init__.py to 0.2.0.
- Revised README.md to reflect the current state of the project, including usage instructions and setup steps.
- Improved CLI documentation in cli.md, adding details about new commands and their functionalities.
- Enhanced the quick start section in README.md for better clarity on initial setup.
- Updated local folder documentation to clarify file handling and commands.
- Added a new command for listing GPU flavors and improved error handling in the CLI.
- Implemented a watchdog feature in the tunnel to manage server states effectively.
- Added package data configuration for the 'gpu_rent' package in pyproject.toml.
- Updated README.md to include usage instructions for Windows and Unix launchers.
- Enhanced CLI documentation in cli.md to reflect new commands and their functionalities.
- Revised setup.md to clarify installation steps and environment setup.
- Improved error handling and command descriptions in the CLI implementation.
- Added new functions for model version handling and flavor resolution in the codebase.
- Updated state management to include additional properties for better tracking.
Leonid Pershin