feat(orchestration): LLM-based task planner (Phase 2, #1237)#1251
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feat(orchestration): LLM-based task planner (Phase 2, #1237)#1251
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…hase 2, #1237) Add Planner trait and LlmPlanner implementation that decomposes user goals into validated TaskGraphs via structured LLM output (chat_typed). - Planner trait with async plan() method accepting goal and agent catalog - LlmPlanner<P: LlmProvider> using chat_typed for JSON schema injection, retry-on-malformed, and code fence stripping - PlannerResponse/PlannedTask with schemars::JsonSchema derives - String task_id to TaskId(u32) mapping via HashMap with duplicate detection - Kebab-case task_id validation (max 64 chars, [a-z0-9-]) - Agent hint validation against SubAgentDef catalog (warn on mismatch) - Failure strategy parsing with warn on invalid values - DAG validation via dag::validate after conversion - OrchestrationConfig: add planner_model and planner_max_tokens fields - 24 tests covering conversion, prompt building, and integration
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Summary
Plannertrait andLlmPlanner<P: LlmProvider>for LLM-based goal decomposition into validatedTaskGraphchat_typedfor structured JSON output with automatic schema injection, retry-on-malformed, and code fence strippingTaskId(u32)mapping via HashMap, kebab-case validation (max 64 chars)SubAgentDefcatalog (warn on unknown, proceed with None)OrchestrationConfigwithplanner_modelandplanner_max_tokensfieldsParent: #1235
Blocked by: #1236 (merged)
Parallel with: #1238
Test plan
cargo +nightly fmt --checkpassescargo clippy --workspace --features full -- -D warningspassescargo nextest run --workspace --features full --lib --bins— 4198 passed, 11 skipped