Raise on invalid tool-call deltas

agent-notes/api/core/model_runtime/model_providers/__base/large_language_model.py.md

@@ -13,6 +13,8 @@ bridge plugin daemon streaming semantics back into API-layer entities (`LLMResul
   `_normalize_non_stream_plugin_result(...)` / `_build_llm_result_from_first_chunk(...)`.
 - Tool call deltas are merged incrementally via `_increase_tool_call(...)` to support multiple provider chunking
   patterns (IDs anchored to first chunk, every chunk, or missing entirely).
+- A tool-call delta with an empty `id` requires at least one existing tool call; otherwise we raise `ValueError` to
+  surface invalid delta sequences explicitly.
 - Callback invocation is centralized in `_run_callbacks(...)` to ensure consistent error handling/logging.
 - For compatibility with dify issue `#17799`, `prompt_messages` may be removed by the plugin daemon in chunks and must
   be re-attached in this layer before callbacks/consumers use them.

api/core/model_runtime/model_providers/__base/large_language_model.py

@@ -53,23 +53,12 @@ def _get_or_create_tool_call(
     If `tool_call_id` is empty, returns the most recently created tool call.
     """
     if not tool_call_id:
-        if existing_tools_calls:
-            return existing_tools_calls[-1]
-
-        tool_call = AssistantPromptMessage.ToolCall(
-            id="",
-            type="function",
-            function=AssistantPromptMessage.ToolCall.ToolCallFunction(name="", arguments=""),
-        )
-        existing_tools_calls.append(tool_call)
-        return tool_call
+        if not existing_tools_calls:
+            raise ValueError("tool_call_id is empty but no existing tool call is available to apply the delta")
+        return existing_tools_calls[-1]
 
     tool_call = next((tool_call for tool_call in existing_tools_calls if tool_call.id == tool_call_id), None)
     if tool_call is None:
-        if existing_tools_calls and not existing_tools_calls[-1].id:
-            existing_tools_calls[-1].id = tool_call_id
-            return existing_tools_calls[-1]
-
         tool_call = AssistantPromptMessage.ToolCall(
             id=tool_call_id,
             type="function",

api/tests/unit_tests/core/model_runtime/__base/test_increase_tool_call.py

@@ -1,5 +1,7 @@
 from unittest.mock import MagicMock, patch
 
+import pytest
+
 from core.model_runtime.entities.message_entities import AssistantPromptMessage
 from core.model_runtime.model_providers.__base.large_language_model import _increase_tool_call
 
@@ -99,21 +101,12 @@ def test__increase_tool_call():
         _run_case(INPUTS_CASE_4, EXPECTED_CASE_4)
 
 
-def test__increase_tool_call__no_id_no_name_first_delta():
+def test__increase_tool_call__no_id_no_name_first_delta_should_raise():
     inputs = [
         ToolCall(id="", type="function", function=ToolCall.ToolCallFunction(name="", arguments='{"arg1": ')),
         ToolCall(id="", type="function", function=ToolCall.ToolCallFunction(name="func_foo", arguments='"value"}')),
     ]
-
-    expected = [
-        ToolCall(
-            id="RANDOM_ID_1",
-            type="function",
-            function=ToolCall.ToolCallFunction(name="func_foo", arguments='{"arg1": "value"}'),
-        ),
-    ]
-
-    mock_id_generator = MagicMock()
-    mock_id_generator.side_effect = ["RANDOM_ID_1"]
-    with patch("core.model_runtime.model_providers.__base.large_language_model._gen_tool_call_id", mock_id_generator):
-        _run_case(inputs, expected)
+    actual: list[ToolCall] = []
+    with patch("core.model_runtime.model_providers.__base.large_language_model._gen_tool_call_id", MagicMock()):
+        with pytest.raises(ValueError):
+            _increase_tool_call(inputs, actual)