fix(core): revert "fix: tool call streaming bug with inconsistent indices from Qwen3" (langchain-ai#32307)

Reverts langchain-ai#32160

Original issue stems from using `ChatOpenAI` to interact with a `qwen`
model. Recommended to use
[langchain-qwq](https://python.langchain.com/docs/integrations/chat/qwq/)
which is built for Qwen

Author: mdrxy

libs/core/langchain_core/utils/_merge.py

@@ -108,39 +108,6 @@ def merge_lists(left: Optional[list], *others: Optional[list]) -> Optional[list]
                             else e
                         )
                         merged[to_merge[0]] = merge_dicts(merged[to_merge[0]], new_e)
-                    # Special handling for tool call chunks: if this chunk appears to be
-                    # a continuation of a prior chunk (has None name/id) and no matching
-                    # index was found, try to merge with the most recent tool call chunk
-                    # that has a name/id.
-                    # Fixes issues with models that send inconsistent indices.
-                    # See #31511 for more.
-                    elif (
-                        e.get("type") == "tool_call_chunk"
-                        and e.get("name") is None
-                        and e.get("id") is None
-                        and merged
-                    ):
-                        # Find the most recent tool call chunk with a valid name or id
-                        for i in reversed(range(len(merged))):
-                            if (
-                                isinstance(merged[i], dict)
-                                and merged[i].get("type") == "tool_call_chunk"
-                                and (
-                                    merged[i].get("name") is not None
-                                    or merged[i].get("id") is not None
-                                )
-                            ):
-                                # Merge with this chunk
-                                new_e = (
-                                    {k: v for k, v in e.items() if k != "type"}
-                                    if "type" in e
-                                    else e
-                                )
-                                merged[i] = merge_dicts(merged[i], new_e)
-                                break
-                        else:
-                            # No suitable chunk found, append as new
-                            merged.append(e)
                     else:
                         merged.append(e)
                 else:

libs/core/tests/unit_tests/test_messages.py

@@ -1197,65 +1197,3 @@ def test_convert_to_openai_image_block() -> None:
     }
     result = convert_to_openai_image_block(input_block)
     assert result == expected
-
-
-def test_tool_call_streaming_different_indices() -> None:
-    """Test that tool call chunks with different indices but logically part of the same
-    tool call are merged correctly. This addresses issues with models like Qwen3 that
-    send inconsistent indices during streaming.
-
-    See #31511.
-
-    """  # noqa: D205
-    # Create chunks that simulate Qwen3 behavior:
-    # First chunk has index=1, subsequent chunks have index=0 with name=None, id=None
-    chunk1 = AIMessageChunk(
-        content="",
-        tool_call_chunks=[
-            create_tool_call_chunk(
-                name="search_function",
-                args='{"query": "langchain',
-                id="call_123",
-                index=1,  # Initial index
-            )
-        ],
-    )
-
-    chunk2 = AIMessageChunk(
-        content="",
-        tool_call_chunks=[
-            create_tool_call_chunk(
-                name=None,  # Continuation chunk
-                args=' tutorial"}',
-                id=None,  # Continuation chunk
-                index=0,  # Different index
-            )
-        ],
-    )
-
-    # Merge chunks as happens during streaming
-    merged_chunk: AIMessageChunk = chunk1 + chunk2  # type: ignore[assignment]
-
-    # Should result in a single merged tool call chunk
-    assert len(merged_chunk.tool_call_chunks) == 1
-    assert merged_chunk.tool_call_chunks[0]["name"] == "search_function"
-    assert merged_chunk.tool_call_chunks[0]["args"] == '{"query": "langchain tutorial"}'
-    assert merged_chunk.tool_call_chunks[0]["id"] == "call_123"
-
-    # Should result in a single valid tool call
-    assert len(merged_chunk.tool_calls) == 1
-    assert len(merged_chunk.invalid_tool_calls) == 0
-
-    # Verify the final tool call is correct
-    tool_call = merged_chunk.tool_calls[0]
-    assert tool_call["name"] == "search_function"
-    assert tool_call["args"] == {"query": "langchain tutorial"}
-    assert tool_call["id"] == "call_123"
-
-    # Test with message_chunk_to_message
-    message: AIMessage = message_chunk_to_message(merged_chunk)  # type: ignore[assignment]
-
-    assert len(message.tool_calls) == 1
-    assert len(message.invalid_tool_calls) == 0
-    assert message.tool_calls[0]["name"] == "search_function"
-    assert message.tool_calls[0]["args"] == {"query": "langchain tutorial"}