- Added imports for resource cleanup during safe shutdown, including terminal and browser session cleanup.
- Refactored command handling to preserve original case for model names and prompt text, improving user experience.
- Introduced a dedicated interrupt queue to manage user input while the agent is running, preventing race conditions.
- Updated comments and documentation for clarity on command processing and input handling.
- Changed the default LLM model in the setup wizard and example environment file to 'anthropic/claude-opus-4.6'.
- Updated terminal working directory settings in CLI and related files to use the current directory ('.') instead of '/tmp'.
- Enhanced documentation comments for clarity on terminal configuration and working directory behavior.
- Updated `ALL_POSSIBLE_TOOLS` to auto-derive from `TOOL_TO_TOOLSET_MAP` for consistent schema.
- Introduced `_extract_reasoning_stats` function to track reasoning coverage in assistant turns.
- Enhanced `_process_batch_worker` to discard prompts with no reasoning and aggregate reasoning statistics.
- Updated documentation and comments for clarity on new features and changes.
- Added `max_tokens`, `reasoning_config`, and `prefill_messages` parameters to `BatchRunner` and `AIAgent` for improved model response control.
- Updated CLI to support new options for reasoning effort and prefill messages from a JSON file.
- Modified example configuration files to reflect changes in default model and summary model.
- Improved error handling for loading prefill messages and reasoning configurations in the CLI.
- Updated documentation to include new parameters and usage examples.
- Updated `.gitignore` to exclude `testlogs` directory.
- Refactored `handle_web_function_call` in `model_tools.py` to support running async functions in existing event loops, improving compatibility with Atropos.
- Introduced a thread pool executor in `agent_loop.py` for running synchronous tool calls that internally use `asyncio.run()`, preventing deadlocks.
- Added `ToolError` class to track tool execution errors, enhancing error reporting during agent loops.
- Updated `wandb_log` method in `hermes_base_env.py` to log tool error statistics for better monitoring.
- Implemented patches in `patches.py` to ensure async-safe operation of tools within Atropos's event loop.
- Enhanced `ToolContext` and `terminal_tool.py` to utilize the new async handling, improving overall tool execution reliability.
- 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.
- Reorganized the 'all' dependencies to include specific optional groups for better modularity.
- Added support for 'hermes-agent' with distinct categories: modal, messaging, cron, cli, and dev.
- Added new environments for reinforcement learning, including `HermesSweEnv` for software engineering tasks and `TerminalTestEnv` for inline testing.
- Introduced `ToolContext` for unrestricted access to tools during reward computation.
- Updated `.gitignore` to exclude `wandb/` directory.
- Enhanced `README.md` with detailed architecture and usage instructions for Atropos environments.
- Added configuration files for SWE and terminal test environments to streamline setup.
- Removed unnecessary compiled Python files from `__pycache__`.
- 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.
- Added unique run ID generation for WandB tracking during test inference.
- Enabled WandB usage for test tracking and updated command-line arguments accordingly.
- Implemented real-time output streaming for process execution, improving log visibility and debugging.
- Enhanced error handling to display last few lines of stderr for better troubleshooting.
- Modified `model_tools.py` to update default model IDs and add new RL function `rl_test_inference`.
- Enhanced `README.md` with installation instructions for submodules and updated API key usage.
- Improved `rl_cli.py` to load configuration from `~/.hermes/config.yaml` and set terminal working directory for RL tools.
- Updated `run_agent.py` to handle empty string arguments as empty objects for better JSON validation.
- Refined installation scripts to ensure submodules are cloned and installed correctly, enhancing setup experience.
- Added the tinker-atropos submodule for enhanced RL training capabilities.
- Updated model_tools.py to reorder RL function definitions and improve descriptions.
- Modified rl_cli.py to include checks for the tinker-atropos setup and provide user guidance.
- Adjusted toolsets.py and __init__.py to reflect changes in RL function availability.
- Enhanced rl_training_tool.py to manage training processes directly without a separate API server.
- Updated `.env.example` to include Tinker and WandB API keys for reinforcement learning training.
- Enhanced `model_tools.py` to clarify configuration options and streamline the RL training process.
- Expanded `README.md` with detailed instructions for setting up RL training using Tinker and WandB.
- Modified `hermes_cli` files to integrate RL training tools and ensure proper configuration checks.
- Improved `rl_training_tool.py` to reflect changes in training parameters and configuration management.
- Introduced a monitoring mechanism in GatewayRunner to detect incoming messages while an agent is active, allowing for graceful interruption and processing of new messages.
- Enhanced BasePlatformAdapter to manage active sessions and pending messages, ensuring that new messages can interrupt ongoing tasks effectively.
- Improved the handling of pending messages by checking for interrupts and processing them in the correct order, enhancing user experience during message interactions.
- Updated the cleanup process for active tasks to ensure proper resource management after interruptions.
- Enhanced the AIAgent class to support interrupt requests, allowing for graceful interruption of ongoing tasks and processing of new messages.
- Updated the HermesCLI to manage user input in a persistent manner, enabling real-time interruption of the agent's conversation.
- Introduced a mechanism in the GatewayRunner to handle incoming messages while an agent is running, allowing for immediate response to user commands.
- Improved overall user experience by providing feedback during interruptions and ensuring that pending messages are processed correctly.
- Updated the AIAgent class to extract the first user message for trajectory formatting, improving the accuracy of user queries in the trajectory format.
- Enhanced the GatewayRunner to convert transcript history into the agent format, ensuring proper handling of message roles and content.
- Adjusted the typing indicator refresh rate to every 2 seconds for better responsiveness.
- Improved error handling in the message sending process for the Telegram adapter, implementing a fallback mechanism for Markdown parsing failures, and logging send failures for better debugging.
- Updated the `skills_categories` function to include a `verbose` parameter, allowing users to request skill counts per category.
- Modified the `handle_skills_function_call` method to pass the `verbose` argument to `skills_categories`.
- Improved error handling in the `AIAgent` class by injecting a recovery message when invalid JSON arguments are detected, guiding users on how to correct their tool calls.
- Enhanced the `GatewayRunner` to return a user-friendly error message if the agent fails to generate a final response, improving overall user experience.
- Adjusted the `_keep_typing` method to refresh the typing indicator every 2 seconds instead of 4, improving responsiveness after progress messages.
- Updated the `GatewayRunner` to restore the typing indicator after sending progress messages, enhancing user experience during message processing.
- Updated the AIAgent class to include new parameters for maximum iterations and tool progress callback, improving agent behavior and user feedback.
- Added detailed documentation on working directory behavior for CLI and messaging platforms, clarifying the use of `MESSAGING_CWD`.
- Introduced tool progress notifications in messaging, allowing users to receive real-time updates during tool execution.
- Updated relevant sections in AGENTS.md, README.md, and messaging.md to reflect these enhancements and provide clearer setup instructions.
- Introduced a new callback mechanism in the AIAgent class to send tool progress messages during execution, enhancing user feedback in messaging platforms.
- Updated the GatewayRunner to support tool progress notifications, allowing users to enable or disable this feature via environment variables.
- Enhanced the CLI setup wizard to prompt users for enabling tool progress messages and selecting the notification mode (all or new), improving configuration options.
- Updated relevant documentation to reflect the new features and configuration settings for tool progress notifications.
- Added a new private method `_keep_typing` to send a typing indicator continuously while processing messages, refreshing every 4 seconds to comply with Telegram/Discord limitations.
- Updated the `handle_message` method to initiate the typing indicator at the start of message processing and ensure it stops once processing is complete, improving user experience during message handling.
- Increased the default maximum tool-calling iterations from 20 to 60 in the CLI configuration and related files, allowing for more complex tasks.
- Updated documentation and comments to reflect the new recommended range for iterations, enhancing user guidance.
- Implemented backward compatibility for loading max iterations from the root-level configuration, ensuring a smooth transition for existing users.
- Adjusted the setup wizard to prompt for the maximum iterations setting, improving user experience during configuration.
