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DeepSeek's own API (api.deepseek.com) reports context-cache hits as top-level usage.prompt_cache_hit_tokens / prompt_cache_miss_tokens (prompt_tokens = hit + miss), not the OpenAI nested prompt_tokens_details.cached_tokens shape. Neither normalize_usage() nor the chat_completions transport's extract_cache_stats() read those fields, so direct DeepSeek sessions always showed 0 cache-hit tokens: invisible in accounting, mis-billed at the full input rate, and 0% cache display. Both layers now fall back to prompt_cache_hit_tokens when the nested shape is absent; the nested value wins when both are present (proxies). Fixes #61871. |
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| .. | ||
| __init__.py | ||
| anthropic.py | ||
| base.py | ||
| bedrock.py | ||
| chat_completions.py | ||
| codex.py | ||
| codex_app_server.py | ||
| codex_app_server_session.py | ||
| codex_event_projector.py | ||
| hermes_tools_mcp_server.py | ||
| types.py | ||