* fix(models): preserve Moonshot cache_write_tokens in usage metadata
langchain-openai 1.2.1's _create_usage_metadata reads
prompt_tokens_details.cached_tokens but not cache_write_tokens, so the
PatchedChatDeepSeek conversion dropped the cache-creation count that Kimi K3.1
reports, and DeerFlow's usage journal never saw it (#7426).
PatchedChatDeepSeek now overrides _create_chat_result to restore the raw SDK
cache_write_tokens as input_token_details["cache_creation"].
Offline regression: a real OpenAI ChatCompletion carrying
prompt_tokens_details {cached_tokens: 100, cache_write_tokens: 256} converts to
input_token_details {cache_read: 100, cache_creation: 256} (red before, green
after); the existing 14 patched_deepseek tests and the managed-provider suites
stay green.
* fix(models): restore cache_write_tokens on the streaming path too
Streamed runs (web UI messages-tuple) build usage metadata in
_convert_chunk_to_generation_chunk -> _create_usage_metadata, which ignores
cache_write_tokens, so the non-streaming-only override still lost the count on
the path streamed runs actually take (review follow-up on #7428).
_convert_chunk_to_generation_chunk now mirrors _create_chat_result's restore
for the final usage chunk. Note chunk["usage"] is JSON null on non-final
chunks, so the lookup uses `or {}` instead of a .get default (a None usage
would otherwise raise AttributeError inside every chunk and break
test_model's connection probe).
Update DeepSeek references from deprecated model names to the V4 lineup:
- deepseek-reasoner → deepseek-v4-pro
- deepseek-chat → deepseek-v4-flash
Keep docs and frontend mocks aligned with the wizard provider list.
