- Introduced `assistent-personas.yaml` to the project and updated the `.gitignore` accordingly.
- Implemented functions to seed and merge assistent personas from local files to the VM.
- Enhanced the model capture process to include merging of wanted models from the VM into `models.yaml`.
- Updated documentation to reflect changes in the assistent personas and model management processes.
Co-authored-by: Cursor <cursoragent@cursor.com>
A 1-token /api/chat after tags (and again if /api/ps is empty) loads VL weights before the first message. Mid KEEP_ALIVE is 15m so a short image-gen burst does not unload the model.
Co-authored-by: Cursor <cursoragent@cursor.com>
- Updated the `provision_llm` function to utilize the `/api/tags` endpoint for verifying available models, improving accuracy in model management.
- Introduced a new `already_have_ollama_tag` function to ensure exact tag matching, preventing mismatches during model checks.
- Enhanced the `pull_stream` function to require a successful status from the API before proceeding, ensuring reliable model downloads.
- Added logic to handle unwritten blob files, improving the robustness of the model pulling process.
- Updated documentation and tests to reflect these changes, ensuring clarity and reliability in Ollama model operations.
- Clarified the behavior of `Ctrl+C` and `Ctrl+D` in the README and other documentation, specifying that `Ctrl+C` only stops the tunnel while keeping the GPU active, and `Ctrl+D` stops the GPU while preserving disk data.
- Enhanced the CLI documentation to reflect these changes, ensuring users understand the implications of these commands during GPU operations.
- Improved the handling of data bindings and remounting logic in the codebase to prevent issues with empty model tabs in the UI.
- Added tests to validate the new command behaviors and ensure proper documentation alignment.
- Updated the `gpu-rent` logic to ensure the `IsInstalled` flag is accurately set based on the presence of ComfyUI, preventing conflicts during installation.
- Improved the handling of the `/mnt/swarm_data` directory to skip creation if it does not exist, enhancing robustness in provisioning.
- Added tests to validate the new installation state checks and ensure proper diagnostics during the installation process, including scenarios for clearing and setting the `IsInstalled` flag.
- Added a loop to check for the presence of ComfyUI in specified candidate paths, enhancing the logic for determining if ComfyUI is installed on disk.
- This change improves the accuracy of installation state reporting by expanding the search for ComfyUI binaries.
- Introduced `comfy_on_disk` and `sync_is_installed` functions to manage the `IsInstalled` flag based on the presence of ComfyUI, ensuring accurate installation state reporting.
- Updated `install_swarm_comfy.py` to clear the `IsInstalled` flag when necessary, allowing the installation process to proceed without conflicts.
- Improved logic to prevent setting `IsInstalled` to true on first boot or empty data volumes, addressing issues with the InstallConfirmWS process.
- Enhanced diagnostics and logging for installation state changes, providing clearer feedback during the installation process.
- Introduced functions to ensure the `IsInstalled` flag is set in `Settings.fds`, preventing the UI from displaying the /Install wizard.
- Added logic to create or patch `Settings.fds` with installation details, including the installation date and version.
- Updated the `install_swarm_comfy.py` script to call the new function, ensuring the installation state is correctly managed during backend operations.
- Added tests to verify the presence of the `IsInstalled` flag in the relevant scripts and ensure proper functionality during installation checks.
- Added a `--update` option to the `up` command in the CLI for forced updates during warm ACTIVE states.
- Improved the idle-killer logic with new functions to check for reusable credentials and refresh settings on existing remote credentials.
- Enhanced the `seed_civitai` function to implement caching for model jobs, optimizing the provisioning process.
- Updated the installation script for Ollama to prevent unnecessary restarts when the service configuration has not changed.
- Added diagnostics for model job caching and improved error handling in various functions.
- Introduced the `file_size_bytes` function to convert Civitai model sizes from kilobytes to bytes, improving data handling.
- Updated the `seed_civitai` function to include file size in job definitions, enhancing model processing efficiency.
- Enhanced the `should_skip` function to utilize expected size for faster decision-making during job processing.
- Added tests for new functionality, ensuring robustness in file size handling and job processing logic.
- Introduced the `pick_preview_image` function to extract the first usable preview image URL and its suffix from model version data.
- Updated the `seed_civitai` function to include preview image URLs and destinations in job definitions, improving model handling.
- Implemented the `ensure_preview` function to download missing preview images during job processing, enhancing user experience.
- Added tests for `pick_preview_image` to ensure correct functionality across various scenarios, ensuring robustness in image handling.
- Introduced a new CLI command `diag` to collect diagnostics from SwarmUI/Comfy, including API, journal, and paths.
- Enhanced the `ensure_swarm_comfy_installed` function to include diagnostic script handling for errored backends.
- Updated `wait_backend_idle` to trigger diagnostics when backends are in an errored state, improving error recovery.
- Implemented fallback mechanisms for diagnostics in the `run_diagnostics` function, ensuring better visibility into backend issues.
- Added tests to validate the new diagnostic functionality and error handling, ensuring robustness in backend management.
- Updated the idle-killer logic to treat SwarmUI `empty` and `disabled` states as busy, preventing unnecessary idle time during provisioning.
- Enhanced the `wait_backend_idle` function to recognize suspended backends as ready, improving resource utilization and user feedback.
- Refined the `install_swarm_comfy` script to skip installation when backends are already present, streamlining the setup process.
- Improved the `resolve_llm_runtime` function to prioritize live configuration over stale state notes, ensuring accurate runtime detection.
- Added tests to validate the new backend status handling and idle management logic, ensuring robustness and reliability.
- Enhanced documentation to clarify the transition from 'Idle' to 'ready (running)' for backend states, improving user understanding of system readiness.
- Updated logging messages in the notification system to reflect the new backend status terminology, ensuring accurate feedback during operations.
- Refined access link collection logic to better handle tunneled and non-tunneled scenarios, enhancing user experience.
- Improved tests to validate the new backend status handling and ensure accurate reporting of access links and notifications.
- Updated the `collect_access_links` function to provide clearer user-facing endpoint labels and notes, particularly for non-tunneled scenarios.
- Improved logging messages in the provisioning process to reflect the status of the SwarmUI and Ollama API, enhancing user feedback during setup.
- Added human-readable status messages for backend loading and running states, improving clarity during the waiting process.
- Updated tests to verify the new behavior and ensure accurate reporting of access links and backend statuses.
- Added a new function to ensure headless installation of ComfyUI when backends are empty, enhancing the setup process for SwarmUI.
- Updated documentation to clarify the installation flow and backend readiness checks, ensuring users understand the requirements for a successful setup.
- Enhanced backend status checks to differentiate between 'empty' and 'idle' states, improving error handling and user feedback during provisioning.
- Adjusted logging messages to provide clearer insights into the installation and backend status processes.
- 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 a new configuration option `UP_STOP_ON_FAIL` to control whether the GPU should be stopped automatically if the `up` command fails, enhancing user control over resource management.
- Updated the CLI to include a `--keep-on-fail` flag, allowing users to prevent GPU shutdown during installation errors.
- Enhanced the installation scripts and documentation to reflect these changes, providing clearer guidance on the new behavior and configuration options.
- Improved error handling in the CLI to ensure proper cleanup of resources in case of failure, preventing unexpected billing for unused GPU resources.
- Added new environment variables in `env.example` and `gpu-rent.vars.example` for fine-tuning LLM settings, including CUDA build options and model version pinning.
- Updated `llm.md` documentation to include detailed descriptions of new configuration options and usage cases for LLM setups.
- Enhanced the `provision.py` script to forward new environment variables during remote installations, improving the installation process for LLM components.
- Modified the `install_llamacpp.sh` script to support conditional CUDA builds and asset URL overrides, ensuring better compatibility with various environments.
- Improved logging in the installation scripts to provide clearer feedback during the setup process.
- Revised model URLs and descriptions in `llamacpp-models.example.yaml` and `ollama-models.example.yaml` to reflect new recommendations and vision capabilities.
- Updated the LLM runtime logic to support vision projectors and improved model resolution handling.
- Enhanced the installation script to conditionally include vision projectors when available.
- Added tests to validate the inclusion of vision projectors in model presets and ensure proper URL remapping for deprecated models.
- Improved documentation to clarify model usage and configuration options.
- Introduced support for Hugging Face API integration, allowing fallback model resolution when Civitai fails.
- Updated configuration to include `HF_TOKEN` and `HF_TOKEN_PATH` for authentication.
- Enhanced model capture logic to differentiate between Civitai and Hugging Face sources.
- Improved error handling for model downloads, providing clearer messages for authentication issues.
- Updated documentation to reflect new environment variables and usage instructions for Hugging Face integration.
- Added tests to validate the new fallback mechanism and ensure robust model resolution.
- 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 PershinandCursor