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greatmengqi
1f11ba10a9
Post-review cleanup for the token-level streaming fix. No behavior change for correct inputs; one efficiency regression fixed. Fix: chat() O(n²) accumulator ----------------------------- `chat()` accumulated per-id text via `buffers[id] = buffers.get(id,"") + delta`, which is O(n) per concat → O(n²) total over a streamed response. At ~2 KB cumulative text this becomes user-visible; at 50 KB / 5000 chunks it costs roughly 100-300 ms of pure copying. Switched to `dict[str, list[str]]` + `"".join()` once at return. Cleanup ------- - Extract `_serialize_tool_calls`, `_ai_text_event`, `_ai_tool_calls_event`, and `_tool_message_event` static helpers. The messages-mode and values-mode branches previously repeated four inline dict literals each; they now call the same builders. - `StreamEvent.type` is now typed as `Literal["values", "messages-tuple", "custom", "end"]` via a `StreamEventType` alias. Makes the closed set explicit and catches typos at type-check time. - Direct attribute access on `AIMessage`/`AIMessageChunk`: `.usage_metadata`, `.tool_calls`, `.id` all have default values on the base class, so the `getattr(..., None)` fallbacks were dead code. Removed from the hot path. - `_account_usage` parameter type loosened to `Any` so that LangChain's `UsageMetadata` TypedDict is accepted under strict type checking. - Trimmed narrating comments on `seen_ids` / `streamed_ids` / the values-synthesis skip block; kept the non-obvious ones that document the cross-mode dedup invariant. Net diff: -15 lines. All 132 unit tests + harness boundary test still pass; ruff check and ruff format pass.