diff --git a/src/google/adk/agents/llm_agent.py b/src/google/adk/agents/llm_agent.py
index ed83d00413..301081cfb8 100644
--- a/src/google/adk/agents/llm_agent.py
+++ b/src/google/adk/agents/llm_agent.py
@@ -484,9 +484,13 @@ async def _run_async_impl(
       return
 
     should_pause = False
+    output_accumulator = ''
     async with Aclosing(self._llm_flow.run_async(ctx)) as agen:
       async for event in agen:
         self.__maybe_save_output_to_state(event)
+        output_accumulator = self.__maybe_accumulate_streaming_output(
+            event, output_accumulator
+        )
         yield event
         if ctx.should_pause_invocation(event):
           # Do not pause immediately, wait until the long-running tool call is
@@ -508,9 +512,13 @@ async def _run_async_impl(
   async def _run_live_impl(
       self, ctx: InvocationContext
   ) -> AsyncGenerator[Event, None]:
+    output_accumulator = ''
     async with Aclosing(self._llm_flow.run_live(ctx)) as agen:
       async for event in agen:
         self.__maybe_save_output_to_state(event)
+        output_accumulator = self.__maybe_accumulate_streaming_output(
+            event, output_accumulator
+        )
         yield event
       if ctx.end_invocation:
         return
@@ -865,6 +873,47 @@ def __maybe_save_output_to_state(self, event: Event):
         return
       event.actions.state_delta[self.output_key] = result
 
+  def __maybe_accumulate_streaming_output(
+      self, event: Event, accumulator: str
+  ) -> str:
+    """Accumulates output_key text across a streaming model turn.
+
+    Streaming with tool calls produces non-partial events that carry text
+    alongside a function_call. is_final_response() rejects those, so
+    __maybe_save_output_to_state skips them and the text on those events
+    is dropped from output_key. Accumulate every non-partial text-bearing
+    event from this agent across the model turn so the segments survive
+    in session state. See issue #5590.
+
+    No-op when accumulation doesn't apply (different author, no
+    output_key, output_schema set, partial event, no content, no text).
+    For applicable events, appends the event's text to ``accumulator``
+    and writes the running value to state_delta[output_key], overwriting
+    any value __maybe_save_output_to_state set on the same event.
+    Returns the new accumulator value.
+    """
+    if (
+        not self.output_key
+        or self.output_schema
+        or event.author != self.name
+        or event.partial
+        or not event.content
+        or not event.content.parts
+    ):
+      return accumulator
+
+    text = ''.join(
+        part.text
+        for part in event.content.parts
+        if part.text and not part.thought
+    )
+    if not text:
+      return accumulator
+
+    accumulator += text
+    event.actions.state_delta[self.output_key] = accumulator
+    return accumulator
+
   @model_validator(mode='after')
   def __model_validator_after(self) -> LlmAgent:
     return self
diff --git a/tests/unittests/agents/test_llm_agent_streaming_output.py b/tests/unittests/agents/test_llm_agent_streaming_output.py
new file mode 100644
index 0000000000..3426fd9a6c
--- /dev/null
+++ b/tests/unittests/agents/test_llm_agent_streaming_output.py
@@ -0,0 +1,120 @@
+# Copyright 2026 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Integration tests for LlmAgent output_key under streaming with tool calls."""
+
+from __future__ import annotations
+
+from typing import AsyncGenerator
+from unittest import mock
+
+from google.adk.agents.invocation_context import InvocationContext
+from google.adk.agents.llm_agent import LlmAgent
+from google.adk.agents.run_config import RunConfig
+from google.adk.events.event import Event
+from google.adk.events.event_actions import EventActions
+from google.adk.sessions.in_memory_session_service import InMemorySessionService
+from google.genai import types
+import pytest
+
+
+def _text(text: str) -> types.Part:
+  return types.Part.from_text(text=text)
+
+
+def _call(name: str) -> types.Part:
+  return types.Part(function_call=types.FunctionCall(name=name, args={}))
+
+
+def _response(name: str) -> types.Part:
+  return types.Part(
+      function_response=types.FunctionResponse(name=name, response={"ok": True})
+  )
+
+
+def _event(
+    parts: list[types.Part], *, role: str = "model", partial: bool = False
+) -> Event:
+  return Event(
+      invocation_id="inv",
+      author="agent",
+      content=types.Content(role=role, parts=parts),
+      actions=EventActions(),
+      partial=partial,
+  )
+
+
+@pytest.mark.asyncio
+async def test_run_async_accumulates_text_around_tool_calls():
+  """Regression test for issue #5590.
+
+  Under StreamingMode.SSE with tools, an LlmAgent emits text in several
+  non-partial events: some carry text only, others carry text alongside a
+  function_call. Event.is_final_response() returns False for any event
+  with a function_call or function_response part, so the text on those
+  events was historically dropped from output_key — only the final
+  tool-free event's text was saved. Reporters measured ~60-70% loss.
+
+  Drive _run_async_impl with a stubbed _llm_flow that yields the canned
+  event sequence the streaming flow produces, merge each event's
+  state_delta into session state via session_service.append_event, and
+  assert that the user-visible session.state[output_key] contains every
+  non-partial text segment the agent emitted, in order.
+  """
+  canned = [
+      _event([_text("Intro one. ")], partial=True),
+      _event([_text("Intro two.")], partial=True),
+      _event([_text("Intro one. Intro two."), _call("t")]),
+      _event([_response("t")], role="user"),
+      _event([_text("Progress.")], partial=True),
+      _event([_text("Progress."), _call("t")]),
+      _event([_response("t")], role="user"),
+      _event([_text("Conclusion one. ")], partial=True),
+      _event([_text("Conclusion two.")], partial=True),
+      _event([_text("Conclusion one. Conclusion two.")]),
+  ]
+
+  class _FakeFlow:
+
+    async def run_async(
+        self, _ctx: InvocationContext
+    ) -> AsyncGenerator[Event, None]:
+      for event in canned:
+        yield event
+
+  agent = LlmAgent(name="agent", output_key="final_output")
+  session_service = InMemorySessionService()
+  session = await session_service.create_session(
+      app_name="t", user_id="u", session_id="s"
+  )
+  ctx = InvocationContext(
+      invocation_id="inv",
+      agent=agent,
+      session=session,
+      session_service=session_service,
+      run_config=RunConfig(),
+  )
+
+  with mock.patch.object(
+      type(agent),
+      "_llm_flow",
+      new_callable=mock.PropertyMock,
+      return_value=_FakeFlow(),
+  ):
+    async for event in agent._run_async_impl(ctx):
+      await session_service.append_event(session, event)
+
+  assert session.state["final_output"] == (
+      "Intro one. Intro two.Progress.Conclusion one. Conclusion two."
+  )