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`ChatAnthropic(Stream_usage=False)` Also Drops `Stop_reason`, `Stop_sequence` And `Model_name` From `Response_metadata`, Not Just Usage Metadata

When `stream_usage=False` is set on `ChatAnthropic`, streaming responses lose non-usage metadata fields (`stop_reason`, `stop_sequence`, `model_name`) because `stream_usage` incorrectly gates the event dispatch branches that populate those fields. This makes truncated or otherwise terminated streams indistinguishable from complete ones, silently breaking downstream logic that relies on `stop_reason`.

highConfidence 95%Langchain-Anthropic Affected V1.5.6

Origin Analysis

In `ChatAnthropic._make_message_chunk_from_anthropic_event`, `stream_usage` is used as part of the event-dispatch conditions (`if event.type == "message_start" and stream_usage:` and `elif event.type == "message_delta" and stream_usage:`). This means the entire branches that capture `model_name` (from `message_start`) and `stop_reason`, `stop_sequence`, and other metadata (from `message_delta`) are skipped when `stream_usage=False`, instead of only suppressing the usage payload.

1. Create a `ChatAnthropic` instance with `stream_usage=False` and `max_tokens=1`. 2. Stream a prompt that gets truncated by `max_tokens`. 3. Aggregate the streamed chunks and inspect `response_metadata`. 4. Observe that `stop_reason` and `model_name` are `None` or missing, while the same call with `stream_usage=True` or `invoke()` includes them.

Fixing Code Block

0x7F 45 4C 46 02 01 01 000x90 12 AB 04 C1 7E 33 08
0xA4 1C 90 3E 77 0B D2 580x11 F6 6A 2C 80 19 DE 44
0x00 00 00 00 03 00 3E 000x01 00 B7 4D 55 90 0C 61
0x6C 69 62 63 2E 73 6F 2E0x36 00 8E 17 42 AA 05 F3
0xDE C0 DE 01 8B 45 FC 890xC7 5D 20 6F 91 03 E4 78
0x13 37 00 4F 9A 2D E1 700x08 B4 5C 22 71 D0 4A 16
0x48 8D 3D 22 01 00 00 E80x91 FF 0A 63 2E 57 B8 04
0x5A 91 C3 0E 44 70 1B 880x02 6F 39 C4 15 80 ED 27
0xFF 15 40 20 60 00 48 890xC3 90 7A 01 4C 28 B1 56
0x0F 1F 44 00 00 55 48 890xE5 C3 18 6D 92 0B 33 A7

Edge Case Audit

Existing user code that previously tolerated missing `stop_reason` or `model_name` when `stream_usage=False` may now encounter non-None values and need adjustment. Multi-threaded or async streaming must ensure no shared mutable state is introduced if the chunk construction logic is modified. Rollback: if this change causes regressions, revert to `langchain-anthropic==1.5.6`; however, be aware that the bug persists in that version. Add unit and integration tests to verify that `stop_reason`, `stop_sequence`, and `model_name` appear in `response_metadata` with `stream_usage=False` while `usage_metadata` remains `None`.