fix(api): release non-stream plugin chunk iterator

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

@@ -92,6 +92,10 @@ def _build_llm_result_from_first_chunk(
     Build a single `LLMResult` from the first returned chunk.
 
     This is used for `stream=False` because the plugin side may still implement the response via a chunked stream.
+
+    Note:
+        This function always drains the `chunks` iterator after reading the first chunk to ensure any underlying
+        streaming resources are released (e.g., HTTP connections owned by the plugin runtime).
     """
     content = ""
     content_list: list[PromptMessageContentUnionTypes] = []
@@ -99,18 +103,25 @@ def _build_llm_result_from_first_chunk(
     system_fingerprint: str | None = None
     tools_calls: list[AssistantPromptMessage.ToolCall] = []
 
-    first_chunk = next(chunks, None)
-    if first_chunk is not None:
-        if isinstance(first_chunk.delta.message.content, str):
-            content += first_chunk.delta.message.content
-        elif isinstance(first_chunk.delta.message.content, list):
-            content_list.extend(first_chunk.delta.message.content)
+    try:
+        first_chunk = next(chunks, None)
+        if first_chunk is not None:
+            if isinstance(first_chunk.delta.message.content, str):
+                content += first_chunk.delta.message.content
+            elif isinstance(first_chunk.delta.message.content, list):
+                content_list.extend(first_chunk.delta.message.content)
 
-        if first_chunk.delta.message.tool_calls:
-            _increase_tool_call(first_chunk.delta.message.tool_calls, tools_calls)
+            if first_chunk.delta.message.tool_calls:
+                _increase_tool_call(first_chunk.delta.message.tool_calls, tools_calls)
 
-        usage = first_chunk.delta.usage or LLMUsage.empty_usage()
-        system_fingerprint = first_chunk.system_fingerprint
+            usage = first_chunk.delta.usage or LLMUsage.empty_usage()
+            system_fingerprint = first_chunk.system_fingerprint
+    finally:
+        try:
+            for _ in chunks:
+                pass
+        except Exception:
+            logger.debug("Failed to drain non-stream plugin chunk iterator.", exc_info=True)
 
     return LLMResult(
         model=model,

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

@@ -101,3 +101,26 @@ def test__normalize_non_stream_plugin_result__empty_iterator_defaults():
     assert result.message.tool_calls == []
     assert result.usage == LLMUsage.empty_usage()
     assert result.system_fingerprint is None
+
+
+def test__normalize_non_stream_plugin_result__closes_chunk_iterator():
+    prompt_messages = [UserPromptMessage(content="hi")]
+
+    chunk = _make_chunk(content="hello", usage=LLMUsage.empty_usage())
+    closed: list[bool] = []
+
+    def _chunk_iter():
+        try:
+            yield chunk
+            yield _make_chunk(content="ignored", usage=LLMUsage.empty_usage())
+        finally:
+            closed.append(True)
+
+    result = _normalize_non_stream_plugin_result(
+        model="test-model",
+        prompt_messages=prompt_messages,
+        result=_chunk_iter(),
+    )
+
+    assert result.message.content == "hello"
+    assert closed == [True]