Introduced a new command "/compress" to the CLI, allowing users to manually trigger context compression on the current conversation. The method checks for sufficient conversation history and active agent status before performing compression, providing feedback on the number of messages and tokens before and after the operation. Updated command documentation accordingly.
- 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.
