- Enhanced Codex model discovery by fetching available models from the API, with fallback to local cache and defaults.
- Updated the context compressor's summary target tokens to 2500 for improved performance.
- Added external credential detection for Codex CLI to streamline authentication.
- Refactored various components to ensure consistent handling of authentication and model selection across the application.
Closes#77. Users can now type /verbose in the CLI to toggle verbose
mode on or off without restarting. When enabled, full tool call
parameters, results, and debug logs are shown. The agent's
verbose_logging and quiet_mode flags are updated live, and Python
logging levels are reconfigured accordingly.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Opt-in persistent cross-session user modeling via Honcho. Reads
~/.honcho/config.json as single source of truth (shared with
Claude Code, Cursor, and other Honcho-enabled tools). Zero impact
when disabled or unconfigured.
- honcho_integration/ package (client, session manager, peer resolution)
- Host-based config resolution matching claude-honcho/cursor-honcho pattern
- Prefetch user context into system prompt per conversation turn
- Sync user/assistant messages to Honcho after each exchange
- query_user_context tool for mid-conversation dialectic reasoning
- Gated activation: requires ~/.honcho/config.json with enabled=true
show_config() always checked cli-config.yaml in the project directory,
but load_cli_config() first looks at ~/.hermes/config.yaml. When the
user config existed, /config would display "cli-config.yaml (not found)"
even though configuration was loaded successfully from ~/.hermes/.
Use the same lookup order as load_cli_config and display the actual
resolved path.
max_turns used 60 as both the default and the sentinel to detect
whether the user passed the flag. This meant `--max-turns 60` was
indistinguishable from "not passed", so the env var
HERMES_MAX_ITERATIONS would silently override the explicit CLI value.
Change the default to None so any user-supplied value takes priority.
The _on_text_changed handler collapsed buffer contents into a file
reference whenever the buffer had 5+ newlines, regardless of how
those lines were entered. This meant manually typing with Alt+Enter
would trigger the paste heuristic and silently replace the user's
carefully typed input.
Track the previous buffer length and only treat a change as a paste
when more than one character is added at once (real pastes insert many
characters in a single event, while typing adds one at a time).
load_cli_config() supports both string and dict formats for the model
key (e.g. `model: "anthropic/claude-opus-4"`), but save_config_value()
assumed all intermediate keys are dicts. When the config file used the
string format, running `/model <name>` would crash with TypeError:
'str' object does not support item assignment.
Add an isinstance check so non-dict values are replaced with a fresh
dict before descending.
- Updated the description extraction logic to split on ". " (period+space) to avoid breaking on abbreviations like "e.g." or version numbers.
- Changed the method to prioritize the first line of the description, ensuring more relevant information is captured for display.
Load ~/.hermes/.env first with project root as dev fallback, and remove
redundant second load_dotenv call inside load_cli_config(). Also sets
MSWEA_GLOBAL_CONFIG_DIR so mini-swe-agent shares the same config.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Introduced a new configuration option for reasoning effort in the CLI, allowing users to specify the level of reasoning the agent should perform before responding.
- Updated the CLI and agent initialization to incorporate the reasoning configuration, enhancing the agent's responsiveness and adaptability.
- Implemented logic to load reasoning effort from environment variables and configuration files, providing flexibility in agent behavior.
- Enhanced the documentation in the example configuration file to clarify the new reasoning effort options available.
- Implemented functionality to load ephemeral prefill messages from a JSON file, enhancing few-shot priming capabilities for the agent.
- Introduced a mechanism to load an ephemeral system prompt from environment variables or configuration files, ensuring dynamic prompt adjustments at API-call time.
- Updated the CLI and agent initialization to utilize the new prefill messages and system prompt, improving the overall interaction experience.
- Enhanced configuration options with new environment variables for prefill messages and system prompts, allowing for greater customization without persistence.
- Updated the toolset ID retrieval logic in the build_welcome_banner function to use a fallback to the toolset name if the ID is not present, ensuring robustness in displaying unavailable toolsets.
- Updated the mapping of unavailable toolsets in the welcome banner from using the internal toolset ID to the toolset name for improved clarity and accuracy in display.
- Introduced a shared interrupt signaling mechanism to allow tools to check for user interrupts during long-running operations.
- Updated the AIAgent to handle interrupts more effectively, ensuring in-progress tool calls are canceled and multiple interrupt messages are combined into one prompt.
- Enhanced the CLI configuration to include container resource limits (CPU, memory, disk) and persistence options for Docker, Singularity, and Modal environments.
- Improved documentation to clarify interrupt behaviors and container resource settings, providing users with better guidance on configuration and usage.
- Added configuration options for memory nudge interval and flush minimum turns in cli-config.yaml.example.
- Implemented memory flushing before conversation reset, clearing, and exit in the CLI to ensure memories are saved.
- Introduced a flush_memories method in AIAgent to handle memory persistence before context loss.
- Added periodic nudges to remind the agent to consider saving memories based on user interactions.
- Extracted agent internals into a dedicated `agent/` directory, including model metadata, context compression, and prompt handling.
- Enhanced CLI structure by separating banner, commands, and callbacks into distinct modules within `hermes_cli/`.
- Updated README to reflect the new directory organization and clarify the purpose of each component.
- Improved tool registration and terminal execution backends for better maintainability and usability.
- 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 placeholder text logic to append new fragments after existing ones, preserving the prompt appearance.
- Adjusted the hint height to maintain a 1-line spacer while the agent is running, preventing output from crowding the input area.
- Added input processors for password masking during sudo prompts and inline placeholder text for various states in the CLI.
- Implemented a custom placeholder processor to display context-sensitive instructions based on the current state (e.g., sudo, approval, clarify).
- Updated hint text logic to improve user guidance during interactive prompts, enhancing overall user experience.
- Added methods for handling sudo password and dangerous command approval prompts using a callback mechanism in cli.py.
- Integrated these prompts with the prompt_toolkit UI for improved user experience.
- Updated terminal_tool.py to support callback registration for interactive prompts, enhancing the CLI's interactivity.
- Introduced a background thread for API calls in run_agent.py to allow for interrupt handling during long-running operations.
- Enhanced error handling for interrupted API calls, ensuring graceful degradation of user experience.
- Updated various modules including cli.py, run_agent.py, gateway, and tools to replace silent exception handling with structured logging.
- Improved error messages to provide more context, aiding in debugging and monitoring.
- Ensured consistent logging practices throughout the codebase, enhancing traceability and maintainability.
- Introduced logging functionality in cli.py, run_agent.py, scheduler.py, and various tool modules to replace print statements with structured logging.
- Enhanced error handling and informational messages to improve debugging and monitoring capabilities.
- Ensured consistent logging practices across the codebase, facilitating better traceability and maintenance.
- Added a new function to deactivate the active provider without deleting credentials, facilitating smoother transitions between different provider types.
- Updated the model flow logic to ensure the active provider is correctly set in the configuration, including handling custom endpoints and OAuth providers.
- Improved error handling in the CLI to consistently format authentication error messages.
- Enhanced the model selection process to reflect the effective provider based on configuration and environment variables.
- Implemented a multi-provider authentication system for the Hermes Agent, supporting OAuth for Nous Portal and traditional API key methods for OpenRouter and custom endpoints.
- Enhanced CLI with commands for logging in and out of providers, allowing users to authenticate and manage their credentials easily.
- Updated configuration options to select inference providers, with detailed documentation on usage and setup.
- Improved status reporting to include authentication status and provider details, enhancing user awareness of their current configuration.
- Added new files for authentication handling and updated existing components to integrate the new provider system.
- Introduced the `delegate_task` tool, allowing the main agent to spawn child AIAgent instances with isolated context for complex tasks.
- Supported both single-task and batch processing (up to 3 concurrent tasks) to enhance task management capabilities.
- Updated configuration options for delegation, including maximum iterations and default toolsets for subagents.
- Enhanced documentation to provide clear guidance on using the delegation feature and its configuration.
- Added comprehensive tests to ensure the functionality and reliability of the delegation logic.
- Updated the default timeout for sandbox script execution from 120 seconds to 300 seconds (5 minutes) to allow longer-running scripts.
- Enhanced comments in the code execution tool to clarify the timeout duration.
- Suppressed stdout and stderr output from internal tool handlers during execution to prevent clutter in the CLI interface.
- Introduced a new `execute_code` tool that allows the agent to run Python scripts that call Hermes tools via RPC, reducing the number of round trips required for tool interactions.
- Added configuration options for timeout and maximum tool calls in the sandbox environment.
- Updated the toolset definitions to include the new code execution capabilities, ensuring integration across platforms.
- Implemented comprehensive tests for the code execution sandbox, covering various scenarios including tool call limits and error handling.
- Enhanced the CLI and documentation to reflect the new functionality, providing users with clear guidance on using the code execution tool.
- Added a new configuration option for the clarify tool to set a custom timeout for user responses.
- Updated the clarify callback to implement a countdown display during user interaction, improving user experience.
- Refactored timeout handling to ensure the UI remains responsive and provides feedback on remaining time.
- Enhanced hint text to include countdown information when clarify questions are active.
- Added a new `clarify_tool` to enable the agent to ask structured multiple-choice or open-ended questions to users.
- Implemented callback functionality for user interaction, allowing the platform to handle UI presentation.
- Updated the CLI and agent to support clarify questions, including timeout handling and response management.
- Enhanced toolset definitions and requirements to include the clarify tool, ensuring availability across platforms.
- 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.
