step-2: add agent streaming and tool result capture (agent_registry.py)

- ChatAgent.__init__: adds tool_results: list[dict] = []
- _tool_loop: wraps execution in a result collector; populates
  self.tool_results with raw execute_on_client dicts after each run
- _tool_loop_stream: streaming variant — uses ainvoke for tool-call
  iterations, llm.astream() for the final answer; same result capture
- ws_context.py: adds _tool_result_collector ContextVar +
  set/clear helpers; execute_on_client appends to collector when set

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

app/core/ws_context.py

@@ -17,6 +17,22 @@ _client_executor: ContextVar[Callable[[dict], Coroutine[Any, Any, dict]]] = Cont
     "_client_executor"
 )
 
+# Optional collector that captures raw execute_on_client results.
+# Set by _tool_loop / _tool_loop_stream to populate ChatAgent.tool_results.
+_tool_result_collector: ContextVar[list[dict] | None] = ContextVar(
+    "_tool_result_collector", default=None
+)
+
+
+def set_tool_result_collector(lst: list[dict]) -> None:
+    """Register *lst* as the collector for this async context."""
+    _tool_result_collector.set(lst)
+
+
+def clear_tool_result_collector() -> None:
+    """Clear the collector (best-effort)."""
+    _tool_result_collector.set(None)
+
 
 def set_client_executor(fn: Callable[[dict], Coroutine[Any, Any, dict]]) -> None:
     """Bind *fn* as the executor for the current async context (task/coroutine)."""
@@ -65,4 +81,8 @@ async def execute_on_client(
     if limit is not None:
         payload["limit"] = limit
 
-    return await callback(payload)
+    result = await callback(payload)
+    collector = _tool_result_collector.get(None)
+    if collector is not None:
+        collector.append(result)
+    return result