- Updated the structure of the TODO list, renaming and expanding the "Context Management" section to "Subagent Architecture" with detailed problem and solution descriptions.
- Added a new section for "Interactive Clarifying Questions Tool," outlining the problem of agent assumptions and proposing a multiple-choice prompt tool for user interaction.
- Included implementation details and benefits for both features, enhancing clarity and direction for future development.
- Added 'images/' to the ignore list to prevent tracking of image files.
- Retained existing entries for private keys and CLI config to maintain security and privacy.
- Added detailed descriptions for new skills categories: Machine Learning Operations and Note Taking.
- Introduced a new Obsidian skill with commands for reading, listing, searching, creating, and appending notes.
- Enhanced the skills tool to load and display category descriptions from DESCRIPTION.md files, improving user guidance and discovery of available skills.
- 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.
- 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.
- Updated `.cursorrules` to provide a comprehensive overview of the interactive CLI, including its architecture, key components, and command handling.
- Expanded `README.md` to introduce the CLI features, quick start instructions, and detailed command descriptions for user guidance.
- Added `docs/cli.md` to document CLI usage, configuration, and animated feedback, ensuring clarity for users and developers.
- Revised `docs/tools.md` to include support for SSH backend in terminal tools, enhancing the documentation for terminal execution options.
- 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.
- Added patterns to ignore private key files (*.ppk, *.pem) and any files starting with 'privvy'.
- Included cli-config.yaml in the ignore list to prevent sensitive SSH paths from being tracked.
- Expanded `.cursorrules` to include detailed sections on the skills system, outlining the directory structure, progressive disclosure pattern, and YAML frontmatter usage for skill files.
- Updated `README.md` to introduce skills tools, providing examples of usage and creation, along with a comprehensive overview of available skills functionalities.
- Enhanced `architecture/tools.md` to document the skills tools and their integration within the Hermes-Agent framework, ensuring clarity for developers and users.
- Introduced new skills tools: `skills_categories`, `skills_list`, and `skill_view` in `model_tools.py`, allowing for better organization and access to skill-related functionalities.
- Updated `toolsets.py` to include a new `skills` toolset, providing a dedicated space for skill tools.
- Enhanced `batch_runner.py` to recognize and validate skills tools during batch processing.
- Added comprehensive tool definitions for skills tools, ensuring compatibility with OpenAI's expected format.
- Created new shell script `test_skills_kimi.sh` for testing skills tool functionality with Kimi K2.5.
- Added example skill files demonstrating the structure and usage of skills within the Hermes-Agent framework, including `SKILL.md` for example and audiocraft skills.
- Improved documentation for skills tools and their integration into the existing tool framework, ensuring clarity for future development and usage.
- 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.
- Expanded the `.cursorrules` file to include detailed sections on project structure, file dependency chain, and guidelines for adding new tools.
- Provided a comprehensive tool implementation pattern and outlined requirements for stateful tools and environment variables.
- Enhanced clarity on the agent loop and reasoning model support, ensuring better understanding for future development and contributions.
- Modified `.env.example` to set the default terminal environment to 'singularity' and updated Docker and Singularity image references for better compatibility.
- Enhanced `run_mixed_tasks.sh` and `run_terminal_tasks.sh` scripts to utilize the new Singularity setup, including improved logging and cache directory management.
- Introduced functionality in `terminal_tool.py` to automatically build and cache SIF images from Docker URLs, streamlining the execution environment setup.
- Updated logging messages for clarity on image usage and cache directory paths.
- Modified `.env.example` to set default terminal environment to 'local' and updated Docker, Singularity, and Modal image references to use 'python:3.11-slim'.
- Updated `package.json` to include Node.js engine requirements and modified post-install script for better user guidance.
- Enhanced `pyproject.toml` to reflect new dependencies and optional dependencies for modal and development environments.
- Improved `README.md` with additional setup instructions for Singularity and Node.js dependencies, along with clearer toolset documentation.
- Refactored `model_tools.py` to include new tool definitions and ensure consistency across toolsets.
- Updated architecture documentation to clarify tool structure and registration processes.
- Created package.json to define project metadata, dependencies, and scripts for the Hermes-Agent.
- Added package-lock.json to lock dependency versions, ensuring consistent installations across environments.
- Included agent-browser as a dependency for enhanced tool-calling capabilities.
- 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 `run_browser_tasks.sh` for executing browser-focused data generation tasks with specific guidelines for automation.
- Added `run_eval_glm4.7_newterm.sh` for evaluating terminal tasks using the GLM 4.7 model, including logging and configuration for terminal environments.
- Created `run_eval_terminal.sh` for terminal-only evaluations with Modal sandboxes, ensuring proper logging and environment setup.
- Developed `run_mixed_tasks.sh` for running mixed browser and terminal tasks, integrating capabilities for both environments.
- Implemented `run_terminal_tasks.sh` for terminal-focused data generation, with detailed instructions for task execution and logging.
- All scripts include timestamped logging for better tracking of task execution and outputs.
- 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.
- Added entries for `node_modules/`, `browser-use/`, and `agent-browser/` to prevent unnecessary files from being tracked.
- Updated `data/*` entry to `data/*` for consistency in ignoring data files.
- Ensured no newline at the end of the file for proper formatting.
- Updated the main function to accept both single JSONL files and directories for compression.
- Added support for sampling a percentage of trajectories before compression.
- Improved usage documentation with detailed examples for various compression scenarios.
- Enhanced error handling for input validation and dry run mode.
- Streamlined output handling to manage temporary files during processing.
- 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.
- Introduced mini_swe_runner.py for executing tasks using mini-swe-agent environments (local, Docker, Modal) and outputting trajectories in Hermes format.
- Implemented trajectory_compressor.py to post-process agent trajectories, compressing them within a target token budget while preserving essential content.
- Added trajectory_compression.yaml configuration file for customizable compression settings.
- Created sample_and_compress.py script to download, sample, and compress trajectories from HuggingFace datasets.
- Enhanced logging and error handling across new modules for improved usability and debugging.
- Updated batch processing to include robust resume functionality by scanning completed prompts based on content rather than indices, improving recovery from failures.
- Implemented retry logic for image downloads with exponential backoff to handle transient failures effectively.
- Refined image generation tool to utilize the FLUX 2 Pro model, updating descriptions and parameters for clarity and consistency.
- Added new configuration scripts for GLM 4.7 and Imagen tasks, enhancing usability and logging capabilities.
- Removed outdated scripts and test files to streamline the codebase.
- 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.
