- Removed references to llamacpp from configuration files, scripts, and documentation, streamlining the LLM setup process to focus solely on Ollama.
- Updated environment variables and paths to eliminate llamacpp-related entries, ensuring clarity in the configuration.
- Adjusted CLI commands and help messages to reflect the removal of llamacpp, enhancing user experience and reducing confusion.
- Revised documentation to provide clear guidance on using Ollama exclusively, including updates to setup instructions and runtime options.
- Added support for balance tracking using `SELECTEL_API_TOKEN` in the configuration.
- Introduced new balance notification logic in the local watchdog, alerting users on balance changes based on defined thresholds.
- Updated documentation to include instructions for setting up balance notifications and the required environment variables.
- Enhanced the `ready` and `session` modules to initialize balance state and handle notifications during GPU operations.
- Refactored the CLI and related components to support the new balance monitoring features, ensuring a seamless user experience.
- 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.
- 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.
- Introduced new `capture` commands in the CLI to allow users to merge VM inventory into local manifests without downloading weights.
- Updated `README.md` and `cli.md` to include detailed instructions for the new capture functionality, including options for models and extensions.
- Enhanced `decisions.md` to clarify the role of captured links in the manifest files.
- Improved `extensions.md` to document the process of capturing installed extensions back to the local configuration.
- Added new functions in `civitai.py` to support fetching model versions by hash and generating canonical URLs for models.
- 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.
- 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.
- Enhanced README.md to clarify the `gpu-rent up` command, including default tunnel behavior and options for cloud-only operation.
- Updated cli.md to reflect changes in the `gpu-rent up` command, detailing the new `--no-tunnel` option and its implications.
- Revised decisions.md to explain the separation of `up` and `tunnel` commands, emphasizing the default tunnel opening after `up`.
- Improved doctor.py to provide clearer instructions regarding tunnel creation and cloud-only usage.
- Adjusted notify.py to reflect the updated command usage for accessing the SwarmUI.
- Introduced SCAN_POOLS configuration to specify pools for GPU flavor scanning.
- Updated the `flavors` command to scan specified pools and list available GPU flavors based on `FLAVOR_PREFERENCE`.
- Revised CLI documentation to reflect changes in the `flavors` command behavior.
- Enhanced decision documentation to include details about GPU pool scanning.
- Updated setup instructions to guide users on selecting appropriate GPU pools.
- Updated the project structure to store configuration files (.env, models.yaml, extensions.yaml) in the project root instead of the user's home directory.
- Enhanced the setup process to automatically copy example files to the project root on first run.
- Implemented a migration function to transfer legacy configuration files from the user's home directory to the new project structure.
- Revised documentation to reflect changes in file locations and setup instructions.
- Improved code readability and maintainability by refactoring path management functions.