from pathlib import Path def run_chat( db_path: Path | None = None, read_only: bool = False, model: str | None = None, capabilities: list[str] | None = None, ) -> None: """Run the chat TUI. Args: db_path: Path to the LanceDB database. If None, uses default from config. read_only: Whether to open the database in read-only mode. model: Model to use for the chat. capabilities: Capabilities to enable ("rag", "analysis"). Defaults to ["rag"]. """ try: from haiku.rag.chat.app import ChatApp except ImportError as e: raise ImportError( "textual is not installed. Please install it with `pip install 'haiku.rag-slim[tui]'` or use the full haiku.rag package." ) from e from haiku.rag.config import get_config from haiku.rag.utils import get_model, parse_model_option config = get_config() if db_path is None and not config.lancedb.databases: db_path = config.storage.data_dir / "haiku.rag.lancedb" if model: model_config = parse_model_option(model) config.qa.model = model_config config.analysis.model = model_config enabled = capabilities or ["rag"] capability_list = [] defer_loading = len(enabled) > 1 # One agent drives every attached capability, so a capability's # image-attachment gate must track that single model: analysis.model only # when analysis runs alone, otherwise qa.model. Passing it to every # capability keeps their vision flag aligned with the model actually running. if "rag" not in enabled and "analysis" in enabled: driving_model = config.analysis.model or config.qa.model else: driving_model = config.qa.model if "rag" in enabled: from haiku.rag.capabilities.rag import create_capability capability_list.append( create_capability( db_path=db_path, config=config, defer_loading=defer_loading, vision=driving_model.vision, ) ) if "analysis" in enabled: from haiku.rag.capabilities.analysis import create_capability capability_list.append( create_capability( db_path=db_path, config=config, defer_loading=defer_loading, vision=driving_model.vision, ) ) app = ChatApp( db_path, capabilities=capability_list, read_only=read_only, model=model or get_model(driving_model, config), ) app.run()