- Introduced a default skills guidance prompt to assist the model in checking relevant skills before technical tasks.
- Updated the logic in AIAgent to auto-include skills guidance when skills tools are available, enhancing the model's contextual understanding during API calls.
- Introduced `cli-config.yaml.example` to provide a template for configuring the CLI behavior, including model settings, terminal tool configurations, agent behavior, and toolsets.
- Created `cli.py` for an interactive terminal interface, allowing users to start the Hermes Agent with various options and toolsets.
- Added `hermes` launcher script for convenient CLI access.
- Updated `model_tools.py` to support quiet mode for suppressing output during tool initialization and execution.
- Enhanced logging in various tools to respect quiet mode, improving user experience by reducing unnecessary output.
- Added `prompt_toolkit` to `requirements.txt` for improved CLI interaction capabilities.
- Created `TODO.md` for future improvements and enhancements to the Hermes Agent framework.
- Updated `trajectory_compression.yaml` to include a new `per_trajectory_timeout` setting, allowing for a timeout of 300 seconds per trajectory. This enhancement helps prevent hanging on problematic entries during processing, improving overall reliability and efficiency in trajectory handling.
- Updated logging configuration in `run_agent.py` to suppress debug messages from additional third-party libraries, reducing noise in logs.
- Enhanced shell scripts for terminal tasks to utilize Singularity for containerized execution, including pre-build SIF image logic and improved logging.
- Refactored tool initialization in `mixture_of_agents_tool.py`, `vision_tools.py`, and `web_tools.py` to implement lazy loading of API clients, optimizing resource usage and error handling.
- Updated ephemeral system prompts in shell scripts to provide clearer guidance on task execution and resource usage.
- Introduced new browser automation tools in `browser_tool.py` for navigating, interacting with, and extracting content from web pages using the agent-browser CLI and Browserbase cloud execution.
- Updated `.env.example` to include new configuration options for Browserbase API keys and session settings.
- Enhanced `model_tools.py` and `toolsets.py` to integrate browser tools into the existing tool framework, ensuring consistent access across toolsets.
- Updated `README.md` with setup instructions for browser tools and their usage examples.
- Added new test script `test_modal_terminal.py` to validate Modal terminal backend functionality.
- Improved `run_agent.py` to support browser tool integration and logging enhancements for better tracking of API responses.
- Updated `.env.example` to include new API keys and configuration options for the mini-swe-agent backend, including support for local, Docker, and Modal environments.
- Added `.gitmodules` to include mini-swe-agent as a submodule for easier integration.
- Refactored `mini_swe_runner.py` to use the updated model format and default to OpenRouter for API calls.
- Enhanced `model_tools.py` to support the new terminal tool definitions and ensure compatibility with the mini-swe-agent backend.
- Updated `README.md` to reflect changes in setup instructions and environment variable configurations.
- Improved `terminal_tool.py` to manage execution environments and lifecycle, ensuring proper cleanup and error handling.
- Introduced `terminal_hecate.py` for executing commands on MorphCloud VMs, providing an alternative backend for terminal operations.
- Replaced tqdm with rich for enhanced visual progress tracking in batch processing.
- Adjusted logging levels in AIAgent to suppress asyncio debug messages.
- Modified datagen script to reduce number of workers for improved performance.
- Integrated tqdm for progress tracking in batch processing, replacing map with imap_unordered for improved performance.
- Added base_url attribute in AIAgent to facilitate OpenRouter detection.
- Introduced normalization functions for tool statistics and error counts to ensure consistent schema across all trajectory entries, facilitating compatibility with HuggingFace datasets.
- Updated batch processing to utilize normalized tool stats and error counts, improving data integrity.
- Refactored vision tools and mixture of agents tool to integrate with OpenRouter API, replacing Nous Research API references and updating model configurations.
- Enabled reasoning capabilities in API calls for enhanced response quality across various tools.
- Improved error handling and API key validation for OpenRouter integration.
- Added methods to check for meaningful content after <think> blocks and to retrieve messages up to the last complete assistant turn.
- Introduced retry logic for handling truncated responses and invalid JSON arguments in tool calls, with a maximum retry limit.
- Improved logging for invalid JSON and empty responses, ensuring better error tracking and handling.
- Updated the batch data generation script to adjust dataset file, batch size, and ephemeral system prompt for improved context management.
- Added support for tracking partial results and tool error counts in batch processing.
- Implemented filtering of corrupted entries during batch file combination based on valid tool names.
- Updated terminal tool to improve command execution and error handling, including retry logic for transient failures.
- Refactored model tools to use a simple terminal tool with no session persistence.
- Improved logging and error messages for invalid API responses and tool calls.
- Introduced chunked processing for large content in web tools to manage size limitations effectively.
