- Introduced a new `LoadedCases` class to encapsulate benchmark cases and optional thresholds, improving data management.
- Updated `load_benchmark_cases` function to support loading cases from both bare arrays and object wrappers with a threshold.
- Modified CLI options to allow dynamic threshold configuration, defaulting to a value from `config.json` if not specified.
- Enhanced error handling for invalid benchmark case formats and added tests to validate new functionality.
These changes aim to improve the flexibility and usability of benchmark case management within the CrewAI framework.
- Added functionality to load environment variables from a `.env` file if it exists, improving configuration management.
- Updated the CLI to fallback to a `benchmarks` directory for test cases if the `tests` directory is not found, ensuring compatibility with previous project structures.
- Refactored benchmark case path handling to streamline testing processes.
These changes aim to improve the usability and flexibility of the CrewAI CLI in various project setups.
- Added a `_safe_render` function to escape Rich markup and convert markdown to Rich format.
- Implemented token-by-token streaming for agent responses in the TUI, improving user experience during interactions.
- Updated the CLI to allow selection of LLM providers and models, enhancing flexibility in agent creation.
- Refactored benchmark case paths to use a `tests` directory instead of `benchmarks`.
- Introduced a `last_stream_result` property in the `NewAgent` class to retrieve the latest streaming response.
These changes aim to provide a more interactive and user-friendly experience in managing agents within the CrewAI framework.
- Introduced a new `create_agent` command for interactive agent definition.
- Added `agent_tui.py` for a conversational TUI supporting multi-agent interactions.
- Updated CLI to support agent creation and training workflows.
- Enhanced `.gitignore` to exclude demo files and configuration artifacts.
- Implemented a benchmark runner for testing agent performance against defined cases.
This commit lays the groundwork for a more interactive and user-friendly experience in managing agents within the CrewAI framework.