- Regenerate uv.lock with sha256 hashes for all 2965 package artifacts
- Add python_version marker to yc-bench (requires >=3.12)
- Update setup-hermes.sh to prefer 'uv sync --locked' for hash-verified
installs, with fallback to 'uv pip install' when lockfile is stale
This completes the supply chain hardening: pyproject.toml bounds the
version ranges, and uv.lock pins exact versions with cryptographic
hashes so tampered packages are rejected at install time.
Drop the mini-swe-agent git submodule. All terminal backends now use
hermes-agent's own environment implementations directly.
Docker backend:
- Inline the `docker run -d` container startup (was 15 lines in
minisweagent's DockerEnvironment). Our wrapper already handled
execute(), cleanup(), security hardening, volumes, and resource limits.
Modal backend:
- Import swe-rex's ModalDeployment directly instead of going through
minisweagent's 90-line passthrough wrapper.
- Bake the _AsyncWorker pattern (from environments/patches.py) directly
into ModalEnvironment for Atropos compatibility without monkey-patching.
Cleanup:
- Remove minisweagent_path.py (submodule path resolution helper)
- Remove submodule init/install from install.sh and setup-hermes.sh
- Remove mini-swe-agent from .gitmodules
- environments/patches.py is now a no-op (kept for backward compat)
- terminal_tool.py no longer does sys.path hacking for minisweagent
- mini_swe_runner.py guards imports (optional, for RL training only)
- Update all affected tests to mock the new direct subprocess calls
- Update README.md, CONTRIBUTING.md
No functionality change — all Docker, Modal, local, SSH, Singularity,
and Daytona backends behave identically. 6093 tests pass.
litellm 1.82.7/1.82.8 contained a credential stealer (.pth auto-exec
payload). PyPI quarantined the entire package, blocking all fresh
hermes-agent installs since litellm was listed as a hard dependency.
These three deps (litellm, typer, platformdirs) are only used by the
mini-swe-agent submodule, which has its own pyproject.toml and manages
its own dependencies. They were redundantly duplicated in hermes-agent's
pyproject.toml.
Also fixes install.sh to not print 'mini-swe-agent installed' on
failure, and updates warning messages in both install scripts to clarify
that only Docker/Modal backends are affected — local terminal is
unaffected.
Ref: https://github.com/BerriAI/litellm/issues/24512
- Removed legacy cron daemon functionality, integrating cron job execution directly into the gateway process for improved efficiency.
- Updated CLI commands to reflect changes, replacing `hermes cron daemon` with `hermes cron status` and enhancing documentation for cron job management.
- Clarified messaging in the README and other documentation regarding the gateway's role in managing cron jobs.
- Removed obsolete terminal_hecate tool and related configurations to simplify the codebase.
- Updated the README to include a new banner image and changed the title emoji from 🦋 to ⚕.
- Modified various CLI outputs and scripts to reflect the new branding, ensuring consistency in the use of the ⚕ emoji.
- Added a new banner image asset for enhanced visual appeal during installation and setup processes.
- Added a new `skill_manager_tool` to enable agents to create, update, and delete their own skills, enhancing procedural memory capabilities.
- Updated the skills directory structure to support user-created skills in `~/.hermes/skills/`, allowing for better organization and management.
- Enhanced the CLI and documentation to reflect the new skill management functionalities, including detailed instructions on creating and modifying skills.
- Implemented a manifest-based syncing mechanism for bundled skills to ensure user modifications are preserved during updates.
- Integrated `uv` as a fast Python package manager for automatic Python provisioning and dependency management.
- Updated installation scripts (`setup-hermes.sh`, `install.sh`, `install.ps1`) to utilize `uv` for installing Python and packages, streamlining the setup process.
- Revised `README.md` to reflect changes in installation steps, including symlinking `hermes` for global access and clarifying Python version requirements.
- Adjusted commands in `doctor.py` and other scripts to recommend `uv` for package installations, ensuring consistency across the project.
- Added `prompt_toolkit` as a direct dependency for interactive CLI support.
- Updated `modal` optional dependency to require `swe-rex[modal]>=1.4.0` for improved cloud execution capabilities.
- Enhanced `messaging` optional dependencies to include `aiohttp>=3.9.0` for WhatsApp bridge communication.
- Refined installation scripts to check for Python version requirements, emphasizing the need for Python 3.11+ for RL training tools.
- Improved setup scripts to ensure proper installation of submodules and dependencies, enhancing user experience during setup.
- Introduced file manipulation capabilities in `model_tools.py`, including functions for reading, writing, patching, and searching files.
- Added a new `file` toolset in `toolsets.py` and updated distributions to include file tools.
- Enhanced `setup-hermes.sh` and `install.sh` scripts to check for and optionally install `ripgrep` for faster file searching.
- Implemented a new `file_operations.py` module to encapsulate file operations using shell commands.
- Updated `doctor.py` and `install.ps1` to check for `ripgrep` and provide installation guidance if not found.
- Added fuzzy matching and patch parsing capabilities to improve file manipulation accuracy and flexibility.
- Updated CLI to load configuration from user-specific and project-specific YAML files, prioritizing user settings.
- Introduced a new command `/platforms` to display the status of connected messaging platforms (Telegram, Discord, WhatsApp).
- Implemented a gateway system for handling messaging interactions, including session management and delivery routing for cron job outputs.
- Added support for environment variable configuration and a dedicated gateway configuration file for advanced settings.
- Enhanced documentation in README.md and added a new messaging.md file to guide users on platform integrations and setup.
- Updated toolsets to include platform-specific capabilities for Telegram, Discord, and WhatsApp, ensuring secure and tailored interactions.
- Updated `.env.example` to include `BROWSER_INACTIVITY_TIMEOUT` for auto-cleanup of inactive sessions.
- Enhanced `cli.py` to load the new inactivity timeout configuration into environment variables.
- Added background thread functionality in `browser_tool.py` to periodically clean up inactive browser sessions based on the configured timeout.
- Improved session management by tracking last activity timestamps and ensuring cleanup occurs when sessions exceed inactivity limits.
