agentic_fabric.runners.local_cli_runner

Universal local CLI runner for single-agent coding tools.

This runner provides a universal interface for any CLI-based coding agent, eliminating the need to write custom runners for each tool. Just define the CLI flags in local_cli_profiles.yaml and it works.

Supported tools (via profiles):

• Aider: AI pair programming

• Claude Code: Anthropic’s coding agent

• OpenAI Codex: OpenAI’s local agent

• Ollama: Free local LLMs (codellama, deepseek-coder, etc.)

• Custom: Define your own tool’s CLI flags

Benefits:

• Zero code to add new agents

• Consistent interface across all tools

• Automatic auth env var handling

• Configurable modes (auto-approve, structured output)

Module Contents

Classes

LocalCLIConfig	Configuration for a CLI-based coding agent.
LocalCLIRunner	Universal runner for CLI-based coding agents.

API

class agentic_fabric.runners.local_cli_runner.LocalCLIConfig

Configuration for a CLI-based coding agent.

This defines how to invoke any CLI tool that can execute coding tasks. All fields map to the tool’s command-line interface.

command: str = None

task_flag: str = None

subcommand: str | None = None

auth_env: list[str] = 'field(...)'

auto_approve: str | None = None

structured_output: str | None = None

model_flag: str | None = None

default_model: str | None = None

working_dir_flag: str | None = None

additional_flags: list[str] = 'field(...)'

timeout: int = 300

name: str = <Multiline-String>

description: str = <Multiline-String>

install_cmd: str = <Multiline-String>

docs_url: str = <Multiline-String>

notes: str = <Multiline-String>

class agentic_fabric.runners.local_cli_runner.LocalCLIRunner(profile: str | agentic_fabric.runners.local_cli_runner.LocalCLIConfig | dict[str, Any], model: str | None = None)

Bases: agentic_fabric.runners.single_agent_runner.SingleAgentRunner

Universal runner for CLI-based coding agents.

This runner can invoke any CLI tool that accepts a task/prompt and executes it. Configuration is done via profiles (built-in or custom).

Examples: # Use built-in profile runner = LocalCLIRunner(“aider”) result = runner.run(“Add error handling to auth.py”)

# Use custom config
config = LocalCLIConfig(
    command="my-tool",
    task_flag="--task",
    auto_approve="--yes",
)
runner = LocalCLIRunner(config)
result = runner.run("Fix the bug")

Initialization

Initialize the runner with a profile or custom config.

Args: profile: Profile name (e.g., “aider”), LocalCLIConfig object, or dict of config parameters. model: Optional model override (if tool supports model selection).

classmethod get_available_profiles() → list[str]

Get list of available profile names.

Returns: List of profile names that can be used.

is_available() → bool

Check if the CLI tool is available (installed and accessible).

Returns: True if the command exists in PATH.

get_required_env_vars() → list[str]

Get list of required environment variables.

Returns: List of environment variable names from config.auth_env.

run(task: str, working_dir: str | None = None, auto_approve: bool = True, structured_output: bool = False, model: str | None = None, **kwargs: Any) → str

Execute a task using the configured CLI tool.

Args: task: The task to execute (e.g., “Add error handling”). working_dir: Optional working directory for execution. auto_approve: Whether to auto-approve changes (if supported). structured_output: Whether to request JSON output (if supported). model: Optional model override. **kwargs: Additional tool-specific arguments.

Returns: Tool output as a string.

Raises: RuntimeError: If tool execution fails or required env vars missing. subprocess.TimeoutExpired: If execution exceeds timeout.

runner_name: str = 'single_agent'

agent_capabilities: ClassVar[collections.abc.Mapping[str, agentic_fabric.capabilities.AgentCapabilitySpec]] = None

agent_capability_methods: ClassVar[collections.abc.Mapping[str, str]] = None

classmethod list_capabilities(*, kind: str | None = None) → tuple[agentic_fabric.capabilities.AgentCapabilitySpec, ...]

call_capability(name: str, *args: Any, **kwargs: Any) → Any

capability_map() → collections.abc.Mapping[str, agentic_fabric.capabilities.AgentCapabilitySpec]