fix: #2171 dedupe nested handoff inputs

src/agents/_run_impl.py

@@ -245,7 +245,8 @@ class SingleStepResult:
     """Items generated before the current step."""
 
     new_step_items: list[RunItem]
-    """Items generated during this current step."""
+    """Items generated during this current step. May be filtered during handoffs to avoid
+    duplication in model input."""
 
     next_step: NextStepHandoff | NextStepFinalOutput | NextStepRunAgain
     """The next step to take."""
@@ -256,11 +257,18 @@ class SingleStepResult:
     tool_output_guardrail_results: list[ToolOutputGuardrailResult]
     """Tool output guardrail results from this step."""
 
+    session_step_items: list[RunItem] | None = None
+    """Full unfiltered items for session history. When set, these are used instead of
+    new_step_items for session saving and generated_items property."""
+
     @property
     def generated_items(self) -> list[RunItem]:
         """Items generated during the agent run (i.e. everything generated after
-        `original_input`)."""
-        return self.pre_step_items + self.new_step_items
+        `original_input`). Uses session_step_items when available for full observability."""
+        items = (
+            self.session_step_items if self.session_step_items is not None else self.new_step_items
+        )
+        return self.pre_step_items + items
 
 
 def get_model_tracing_impl(
@@ -1290,6 +1298,12 @@ async def execute_handoffs(
                 )
                 pre_step_items = list(filtered.pre_handoff_items)
                 new_step_items = list(filtered.new_items)
+                # For custom input filters, use input_items if available, otherwise new_items
+                if filtered.input_items is not None:
+                    session_step_items = list(filtered.new_items)
+                    new_step_items = list(filtered.input_items)
+                else:
+                    session_step_items = None
             elif should_nest_history and handoff_input_data is not None:
                 nested = nest_handoff_history(
                     handoff_input_data,
@@ -1301,7 +1315,16 @@ async def execute_handoffs(
                     else list(nested.input_history)
                 )
                 pre_step_items = list(nested.pre_handoff_items)
-                new_step_items = list(nested.new_items)
+                # Keep full new_items for session history.
+                session_step_items = list(nested.new_items)
+                # Use input_items (filtered) for model input if available.
+                if nested.input_items is not None:
+                    new_step_items = list(nested.input_items)
+                else:
+                    new_step_items = session_step_items
+            else:
+                # No filtering or nesting - session_step_items not needed
+                session_step_items = None
 
         return SingleStepResult(
             original_input=original_input,
@@ -1311,6 +1334,7 @@ async def execute_handoffs(
             next_step=NextStepHandoff(new_agent),
             tool_input_guardrail_results=[],
             tool_output_guardrail_results=[],
+            session_step_items=session_step_items,
         )
 
     @classmethod

src/agents/handoffs/__init__.py

@@ -62,6 +62,13 @@ class HandoffInputData:
     later on, it is optional for backwards compatibility.
     """
 
+    input_items: tuple[RunItem, ...] | None = None
+    """
+    Items to include in the next agent's input. When set, these items are used instead of
+    new_items for building the input to the next agent. This allows filtering duplicates
+    from agent input while preserving all items in new_items for session history.
+    """
+
     def clone(self, **kwargs: Any) -> HandoffInputData:
         """
         Make a copy of the handoff input data, with the given arguments changed. For example, you
@@ -117,10 +124,11 @@ class Handoff(Generic[TContext, TAgent]):
     filter inputs (for example, to remove older inputs or remove tools from existing inputs). The
     function receives the entire conversation history so far, including the input item that
     triggered the handoff and a tool call output item representing the handoff tool's output. You
-    are free to modify the input history or new items as you see fit. The next agent that runs will
-    receive ``handoff_input_data.all_items``. IMPORTANT: in streaming mode, we will not stream
-    anything as a result of this function. The items generated before will already have been
-    streamed.
+    are free to modify the input history or new items as you see fit. The next agent receives the
+    input history plus ``input_items`` when provided, otherwise it receives ``new_items``. Use
+    ``input_items`` to filter model input while keeping ``new_items`` intact for session history.
+    IMPORTANT: in streaming mode, we will not stream anything as a result of this function. The
+    items generated before will already have been streamed.
     """
 
     nest_handoff_history: bool | None = None

src/agents/handoffs/history.py

@@ -26,6 +26,13 @@
 _conversation_history_start = _DEFAULT_CONVERSATION_HISTORY_START
 _conversation_history_end = _DEFAULT_CONVERSATION_HISTORY_END
 
+# Item types that are summarized in the conversation history.
+# They should not be forwarded verbatim to the next agent to avoid duplication.
+_SUMMARY_ONLY_INPUT_TYPES = {
+    "function_call",
+    "function_call_output",
+}
+
 
 def set_conversation_history_wrappers(
     *,
@@ -67,23 +74,34 @@ def nest_handoff_history(
 
     normalized_history = _normalize_input_history(handoff_input_data.input_history)
     flattened_history = _flatten_nested_history_messages(normalized_history)
-    pre_items_as_inputs = [
-        _run_item_to_plain_input(item) for item in handoff_input_data.pre_handoff_items
-    ]
-    new_items_as_inputs = [_run_item_to_plain_input(item) for item in handoff_input_data.new_items]
+
+    # Convert items to plain inputs for the transcript summary.
+    pre_items_as_inputs: list[TResponseInputItem] = []
+    filtered_pre_items: list[RunItem] = []
+    for run_item in handoff_input_data.pre_handoff_items:
+        plain_input = _run_item_to_plain_input(run_item)
+        pre_items_as_inputs.append(plain_input)
+        if _should_forward_pre_item(plain_input):
+            filtered_pre_items.append(run_item)
+
+    new_items_as_inputs: list[TResponseInputItem] = []
+    filtered_input_items: list[RunItem] = []
+    for run_item in handoff_input_data.new_items:
+        plain_input = _run_item_to_plain_input(run_item)
+        new_items_as_inputs.append(plain_input)
+        if _should_forward_new_item(plain_input):
+            filtered_input_items.append(run_item)
+
     transcript = flattened_history + pre_items_as_inputs + new_items_as_inputs
 
     mapper = history_mapper or default_handoff_history_mapper
     history_items = mapper(transcript)
-    filtered_pre_items = tuple(
-        item
-        for item in handoff_input_data.pre_handoff_items
-        if _get_run_item_role(item) != "assistant"
-    )
 
     return handoff_input_data.clone(
         input_history=tuple(deepcopy(item) for item in history_items),
-        pre_handoff_items=filtered_pre_items,
+        pre_handoff_items=tuple(filtered_pre_items),
+        # new_items stays unchanged for session history.
+        input_items=tuple(filtered_input_items),
     )
 
 
@@ -231,6 +249,20 @@ def _split_role_and_name(role_text: str) -> tuple[str, str | None]:
     return (role_text or "developer", None)
 
 
-def _get_run_item_role(run_item: RunItem) -> str | None:
-    role_candidate = run_item.to_input_item().get("role")
-    return role_candidate if isinstance(role_candidate, str) else None
+def _should_forward_pre_item(input_item: TResponseInputItem) -> bool:
+    """Return False when the previous transcript item is represented in the summary."""
+    role_candidate = input_item.get("role")
+    if isinstance(role_candidate, str) and role_candidate == "assistant":
+        return False
+    type_candidate = input_item.get("type")
+    return not (isinstance(type_candidate, str) and type_candidate in _SUMMARY_ONLY_INPUT_TYPES)
+
+
+def _should_forward_new_item(input_item: TResponseInputItem) -> bool:
+    """Return False for tool or side-effect items that the summary already covers."""
+    # Items with a role should always be forwarded.
+    role_candidate = input_item.get("role")
+    if isinstance(role_candidate, str) and role_candidate:
+        return True
+    type_candidate = input_item.get("type")
+    return not (isinstance(type_candidate, str) and type_candidate in _SUMMARY_ONLY_INPUT_TYPES)

src/agents/result.py

@@ -209,6 +209,9 @@ class RunResultStreaming(RunResultBase):
         default=None,
     )
 
+    _model_input_items: list[RunItem] = field(default_factory=list, repr=False)
+    """Filtered items used to build model input between streaming turns."""
+
     # Queues that the background run_loop writes to
     _event_queue: asyncio.Queue[StreamEvent | QueueCompleteSentinel] = field(
         default_factory=asyncio.Queue, repr=False