feat(kernel): add multi-skill orchestration bridge + true parallel execution
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- Kernel orchestration bridge: execute_orchestration, auto_compose_skills, validate_orchestration methods on Kernel struct - True parallel execution: replace sequential for-loop with tokio::JoinSet for concurrent node execution within parallel groups - Tauri commands: orchestration_execute (auto-compose or pre-defined graph), orchestration_validate (dry-run validation) - Full type conversions: OrchestrationRequest/Response with camelCase serde Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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@@ -13,6 +13,7 @@ pub mod chat;
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pub mod hand;
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pub mod lifecycle;
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pub mod mcp;
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pub mod orchestration;
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pub mod scheduled_task;
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pub mod skill;
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pub mod trigger;
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273
desktop/src-tauri/src/kernel_commands/orchestration.rs
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273
desktop/src-tauri/src/kernel_commands/orchestration.rs
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@@ -0,0 +1,273 @@
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//! Skill orchestration Tauri commands
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//!
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//! Exposes the multi-skill orchestration engine to the frontend,
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//! enabling parallel/serial/conditional execution of skill graphs.
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use std::collections::HashMap;
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use serde::{Deserialize, Serialize};
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use serde_json::Value;
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use tauri::State;
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use super::KernelState;
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// ============================================================================
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// Request/Response Types
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// ============================================================================
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/// Orchestration execution request
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#[derive(Debug, Clone, Serialize, Deserialize)]
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#[serde(rename_all = "camelCase")]
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pub struct OrchestrationRequest {
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/// Skill IDs to orchestrate (for auto-compose)
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pub skill_ids: Vec<String>,
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/// Optional pre-defined graph (overrides auto-compose)
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pub graph: Option<OrchestrationGraphInput>,
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/// Input data for the orchestration
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pub inputs: HashMap<String, Value>,
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/// Agent context
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pub agent_id: String,
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pub session_id: String,
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}
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/// Graph input for pre-defined orchestration
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#[derive(Debug, Clone, Serialize, Deserialize)]
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#[serde(rename_all = "camelCase")]
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pub struct OrchestrationGraphInput {
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pub id: String,
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pub name: String,
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#[serde(default)]
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pub description: String,
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pub nodes: Vec<NodeInput>,
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#[serde(default)]
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pub edges: Vec<EdgeInput>,
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#[serde(default)]
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pub on_error: Option<String>,
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#[serde(default)]
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pub timeout_secs: Option<u64>,
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}
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/// Node input for orchestration graph
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#[derive(Debug, Clone, Serialize, Deserialize)]
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#[serde(rename_all = "camelCase")]
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pub struct NodeInput {
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pub id: String,
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pub skill_id: String,
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#[serde(default)]
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pub description: String,
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#[serde(default)]
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pub input_mappings: HashMap<String, String>,
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#[serde(default)]
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pub when: Option<String>,
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#[serde(default)]
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pub skip_on_error: Option<bool>,
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#[serde(default)]
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pub timeout_secs: Option<u64>,
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}
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/// Edge input for orchestration graph
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#[derive(Debug, Clone, Serialize, Deserialize)]
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#[serde(rename_all = "camelCase")]
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pub struct EdgeInput {
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pub from_node: String,
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pub to_node: String,
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#[serde(default)]
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pub field_mapping: HashMap<String, String>,
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#[serde(default)]
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pub condition: Option<String>,
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}
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/// Orchestration execution result for frontend
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#[derive(Debug, Clone, Serialize, Deserialize)]
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#[serde(rename_all = "camelCase")]
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pub struct OrchestrationResponse {
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pub success: bool,
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pub output: Value,
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pub node_count: usize,
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pub completed_nodes: usize,
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pub failed_nodes: usize,
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pub duration_ms: u64,
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pub error: Option<String>,
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pub node_results: HashMap<String, NodeResultResponse>,
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}
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/// Node execution result for frontend
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#[derive(Debug, Clone, Serialize, Deserialize)]
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#[serde(rename_all = "camelCase")]
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pub struct NodeResultResponse {
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pub success: bool,
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pub output: Value,
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pub error: Option<String>,
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pub duration_ms: u64,
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pub retries: u32,
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pub skipped: bool,
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}
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/// Validation response for frontend
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#[derive(Debug, Clone, Serialize, Deserialize)]
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#[serde(rename_all = "camelCase")]
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pub struct ValidationResponse {
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pub valid: bool,
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pub errors: Vec<ValidationErrorInfo>,
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}
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/// Validation error info
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#[derive(Debug, Clone, Serialize, Deserialize)]
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#[serde(rename_all = "camelCase")]
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pub struct ValidationErrorInfo {
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pub code: String,
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pub message: String,
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pub location: Option<String>,
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}
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// ============================================================================
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// Type Conversions
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// ============================================================================
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impl TryFrom<OrchestrationGraphInput> for zclaw_skills::orchestration::SkillGraph {
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type Error = String;
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fn try_from(input: OrchestrationGraphInput) -> Result<Self, Self::Error> {
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let nodes: Vec<zclaw_skills::orchestration::SkillNode> = input.nodes.into_iter().map(|n| {
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zclaw_skills::orchestration::SkillNode {
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id: n.id,
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skill_id: zclaw_types::SkillId::new(&n.skill_id),
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description: n.description,
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input_mappings: n.input_mappings,
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retry: None,
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timeout_secs: n.timeout_secs,
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when: n.when,
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skip_on_error: n.skip_on_error.unwrap_or(false),
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}
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}).collect();
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let edges: Vec<zclaw_skills::orchestration::SkillEdge> = input.edges.into_iter().map(|e| {
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zclaw_skills::orchestration::SkillEdge {
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from_node: e.from_node,
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to_node: e.to_node,
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field_mapping: e.field_mapping,
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condition: e.condition,
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}
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}).collect();
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let on_error = match input.on_error.as_deref() {
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Some("continue") => zclaw_skills::orchestration::ErrorStrategy::Continue,
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Some("retry") => zclaw_skills::orchestration::ErrorStrategy::Retry,
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_ => zclaw_skills::orchestration::ErrorStrategy::Stop,
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};
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Ok(zclaw_skills::orchestration::SkillGraph {
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id: input.id,
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name: input.name,
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description: input.description,
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nodes,
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edges,
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input_schema: None,
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output_mapping: HashMap::new(),
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on_error,
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timeout_secs: input.timeout_secs.unwrap_or(300),
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})
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}
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}
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impl From<zclaw_skills::orchestration::OrchestrationResult> for OrchestrationResponse {
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fn from(result: zclaw_skills::orchestration::OrchestrationResult) -> Self {
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let completed = result.node_results.values().filter(|r| r.success).count();
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let failed = result.node_results.values().filter(|r| !r.success).count();
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let node_results = result.node_results.into_iter().map(|(id, nr)| {
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(id, NodeResultResponse {
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success: nr.success,
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output: nr.output,
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error: nr.error,
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duration_ms: nr.duration_ms,
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retries: nr.retries,
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skipped: nr.skipped,
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})
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}).collect();
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Self {
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success: result.success,
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output: result.output,
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node_count: completed + failed,
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completed_nodes: completed,
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failed_nodes: failed,
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duration_ms: result.duration_ms,
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error: result.error,
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node_results,
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}
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}
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}
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// ============================================================================
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// Tauri Commands
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// ============================================================================
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/// Execute a skill orchestration
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///
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/// Either auto-composes a graph from skill_ids, or uses a pre-defined graph.
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/// Executes with true parallel execution within each dependency level.
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#[tauri::command]
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pub async fn orchestration_execute(
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state: State<'_, KernelState>,
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request: OrchestrationRequest,
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) -> Result<OrchestrationResponse, String> {
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let kernel_lock = state.lock().await;
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let kernel = kernel_lock.as_ref()
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.ok_or_else(|| "Kernel not initialized".to_string())?;
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// Build or auto-compose graph
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let graph = if let Some(graph_input) = request.graph {
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graph_input.try_into()?
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} else if request.skill_ids.is_empty() {
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return Err("Must provide either skill_ids or graph".to_string());
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} else {
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let skill_ids: Vec<zclaw_types::SkillId> = request.skill_ids.iter()
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.map(|s| zclaw_types::SkillId::new(s))
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.collect();
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kernel.auto_compose_skills(&skill_ids).await
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.map_err(|e| format!("Auto-compose failed: {}", e))?
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};
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// Build skill context
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let context = zclaw_skills::SkillContext {
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agent_id: request.agent_id,
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session_id: request.session_id,
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working_dir: None,
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env: HashMap::new(),
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timeout_secs: graph.timeout_secs,
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network_allowed: true,
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file_access_allowed: true,
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llm: None,
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};
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// Execute orchestration
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let result = kernel.execute_orchestration(&graph, request.inputs, &context).await
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.map_err(|e| format!("Orchestration failed: {}", e))?;
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Ok(OrchestrationResponse::from(result))
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}
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/// Validate an orchestration graph without executing it
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#[tauri::command]
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pub async fn orchestration_validate(
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state: State<'_, KernelState>,
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graph: OrchestrationGraphInput,
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) -> Result<ValidationResponse, String> {
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let kernel_lock = state.lock().await;
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let kernel = kernel_lock.as_ref()
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.ok_or_else(|| "Kernel not initialized".to_string())?;
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let skill_graph: zclaw_skills::orchestration::SkillGraph = graph.try_into()?;
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let errors = kernel.validate_orchestration(&skill_graph).await;
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let valid = errors.is_empty();
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let error_infos = errors.into_iter().map(|e| ValidationErrorInfo {
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code: e.code,
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message: e.message,
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location: e.location,
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}).collect();
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Ok(ValidationResponse { valid, errors: error_infos })
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}
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@@ -146,6 +146,9 @@ pub fn run() {
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kernel_commands::skill::skill_create,
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kernel_commands::skill::skill_update,
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kernel_commands::skill::skill_delete,
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// Orchestration commands (multi-skill graphs)
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kernel_commands::orchestration::orchestration_execute,
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kernel_commands::orchestration::orchestration_validate,
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// Hands commands (autonomous capabilities)
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kernel_commands::hand::hand_list,
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kernel_commands::hand::hand_execute,
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