Struct AgentLoop 

pub struct AgentLoop { /* private fields */ }

Agent loop executor

Implementations

impl AgentLoop

pub fn new( llm_client: Arc<dyn LlmClient>, tool_executor: Arc<ToolExecutor>, tool_context: ToolContext, config: AgentConfig, ) -> Self

pub fn with_tool_metrics(self, metrics: Arc<RwLock<ToolMetrics>>) -> Self

Set the tool metrics collector for this agent loop

pub fn with_queue(self, queue: Arc<SessionLaneQueue>) -> Self

Set the lane queue for priority-based tool execution.

When set, tools are routed through the lane queue which supports External task handling for multi-machine parallel processing.

pub async fn execute( &self, history: &[Message], prompt: &str, event_tx: Option<Sender<AgentEvent>>, ) -> Result<AgentResult>

Execute the agent loop for a prompt

Takes the conversation history and a new user prompt. Returns the agent result and updated message history. When event_tx is provided, uses streaming LLM API for real-time text output.

pub async fn execute_from_messages( &self, messages: Vec<Message>, session_id: Option<&str>, event_tx: Option<Sender<AgentEvent>>, ) -> Result<AgentResult>

Execute the agent loop with pre-built messages (user message already included).

Used by send_with_attachments / stream_with_attachments where the user message contains multi-modal content and is already appended to the messages vec.

pub async fn execute_with_session( &self, history: &[Message], prompt: &str, session_id: Option<&str>, event_tx: Option<Sender<AgentEvent>>, ) -> Result<AgentResult>

Execute the agent loop for a prompt with session context

Takes the conversation history, user prompt, and optional session ID. When session_id is provided, context providers can use it for session-specific context.

pub async fn execute_streaming( &self, history: &[Message], prompt: &str, ) -> Result<(Receiver<AgentEvent>, JoinHandle<Result<AgentResult>>)>

Execute with streaming events

pub async fn plan( &self, prompt: &str, _context: Option<&str>, ) -> Result<ExecutionPlan>

Create an execution plan for a prompt

Delegates to [LlmPlanner] for structured JSON plan generation, falling back to heuristic planning if the LLM call fails.

pub async fn execute_with_planning( &self, history: &[Message], prompt: &str, event_tx: Option<Sender<AgentEvent>>, ) -> Result<AgentResult>

Execute with planning phase

pub async fn extract_goal(&self, prompt: &str) -> Result<AgentGoal>

Extract goal from prompt

Delegates to [LlmPlanner] for structured JSON goal extraction, falling back to heuristic logic if the LLM call fails.

pub async fn check_goal_achievement( &self, goal: &AgentGoal, current_state: &str, ) -> Result<bool>

Check if goal is achieved

Delegates to [LlmPlanner] for structured JSON achievement check, falling back to heuristic logic if the LLM call fails.

Trait Implementations

impl Clone for AgentLoop

fn clone(&self) -> AgentLoop

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.