feat: migrate chat orchestration to deep langgraph workers

app/agents/task_agent.py

@@ -2,18 +2,14 @@
 
 from __future__ import annotations
 
-import json
 from datetime import datetime, timezone
 from typing import Any
 
-from langchain_core.messages import HumanMessage, SystemMessage
 from langchain_core.tools import tool
 
-from app.core.agent_registry import ChatAgent, registry
-from app.core.llm import get_llm
 from app.core.ws_context import execute_on_client
 
-_SYSTEM_PROMPT = (
+TASK_SYSTEM_PROMPT = (
     "You are a task management assistant for a project workspace.\n"
     "You create, update, list, and track tasks and their comments.\n\n"
     "Rules:\n"
@@ -223,32 +219,13 @@ async def delete_task_comment(comment_id: str) -> str:
 # ── Agent ─────────────────────────────────────────────────────────────
 
 
-@registry.register
-class TaskAgent(ChatAgent):
-    def get_name(self) -> str:
-        return "task_agent"
-
-    def get_description(self) -> str:
-        return "Manages tasks and comments: list, create, update, delete, due-today, comments"
-
-    def get_tools(self) -> list[Any]:
-        return [
-            list_tasks,
-            create_task,
-            update_task,
-            delete_task,
-            list_tasks_due_today,
-            list_task_comments,
-            add_task_comment,
-            delete_task_comment,
-        ]
-
-    async def handle(self, query: str, context: dict[str, Any]) -> str:
-        llm = get_llm()
-        messages = [
-            SystemMessage(content=_SYSTEM_PROMPT),
-            HumanMessage(
-                content=f"User query: {query}\nContext: {json.dumps(context)[:1000]}"
-            ),
-        ]
-        return await self._tool_loop(llm, messages, self.get_tools())
+TASK_TOOLS: list[Any] = [
+    list_tasks,
+    create_task,
+    update_task,
+    delete_task,
+    list_tasks_due_today,
+    list_task_comments,
+    add_task_comment,
+    delete_task_comment,
+]