feat(01-02): Celery orchestrator — handle_message task, system prompt builder, LLM pool runner

- Create orchestrator/main.py: Celery app with Redis broker/backend, task_acks_late=True, 10-min timeout
- Create orchestrator/tasks.py: SYNC def handle_message (critical pattern: asyncio.run for async work)
  - Deserializes KonstructMessage, sets RLS context, loads agent from DB, calls run_agent
  - Retries up to 3x on deserialization failure
- Create orchestrator/agents/builder.py: build_system_prompt assembles system_prompt + identity + persona + AI transparency clause
- Create orchestrator/agents/runner.py: run_agent posts to llm-pool /complete via httpx, returns polite fallback on error
- Add Celery[redis] dependency to orchestrator pyproject.toml
- Create tests/integration/test_llm_fallback.py: 7 tests for fallback routing and 503 on total failure (LLM-01)
- Create tests/integration/test_llm_providers.py: 12 tests verifying all three providers configured correctly (LLM-02)
- All 19 integration tests pass

packages/orchestrator/pyproject.toml

@@ -10,6 +10,7 @@ requires-python = ">=3.12"
 dependencies = [
     "konstruct-shared",
     "fastapi[standard]>=0.115.0",
+    "celery[redis]>=5.4.0",
     "httpx>=0.28.0",
 ]