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Report cached tokens, reasoning, and cost in model usage - #3329
First step toward showing a run's model usage in tokens and cost, per step and per run. llm.Usage carried only prompt, completion and total counts, and providers filled those inconsistently. This PR makes every provider report the same, fuller picture. Nothing records or displays it yet; that comes in the next PRs.
llm.Usage gains:
CachedPromptTokens: the part of the prompt read from the prompt cache.
CacheWritePromptTokens: the part written to the cache (Anthropic).
ReasoningTokens: the part of the completion spent on reasoning.
Cost *float64: what the provider reported the call cost in US dollars. nil means not reported; zero is a reported free call. Today only OpenRouter reports one, and so do gateways that relay its answers and charge exactly that.
Every provider now reports PromptTokens with cached tokens included and CompletionTokens with reasoning tokens included, naming both parts.
Changes
providers/chatusage (new): one decoder for the usage object of OpenAI's chat completions API and of APIs compatible with it (prompt_tokens_details.cached_tokens, completion_tokens_details.reasoning_tokens, cost), plus the Responses API's (input_tokens_details, output_tokens_details).
openai, openrouter, zai and local share the chat completions decoder, replacing four copies of the same three-field struct.
The OpenAI computer-use session and Codex share the Responses API decoder.
Anthropic:
The prompt count now includes cache_read_input_tokens and cache_creation_input_tokens, which the API reports apart from input_tokens.
Fixes a streaming bug. message_delta's usage, which carries only output tokens, replaced message_start's, so every streamed message reported 0 prompt tokens. Each event's usage is now merged.
The computer-use session reads usage the same way as chat.
Gemini: chat usage now counts thinking tokens in the completion, as Gemini computer use already did, and names cached content.
Codex: stops subtracting cached tokens from the prompt, matching every other provider.
Behaviour change to note
The agent loop's observation aging compares the latest prompt size with max_context_tokens. For Anthropic with prompt caching, and for Codex, that size now includes cached tokens. They still occupy the context window, so aging starts when the context is actually that large rather than later.
Test plan
chatusage: details and cost decoded, cost unknown when absent, a reported zero kept, Responses API counts.
TestChatCountsCachedInput: Anthropic chat prompt includes cache reads and writes.
TestStreamResponse_MergesUsage: a streamed Anthropic message keeps message_start's input when message_delta reports only output. It fails without the fix.
TestStreamUsageCost: OpenRouter's streamed final chunk keeps its cost, cached and reasoning tokens.
TestStreamResponse_Usage: Gemini completion includes thinking tokens, and cached content is named.
The Codex stream test now expects the input with cached tokens included.
The existing computer-use and stream tests for Anthropic, Gemini, OpenAI, OpenRouter and Codex pass. golangci-lint v2.13.2 is clean for darwin, linux and windows.
Summary by CodeRabbit
Improvements
Token usage totals now include cached input and reasoning tokens where reported, with cached reads and cache writes shown separately.
Usage summaries from supported AI providers now include reported request costs, distinguishing free calls from costs that were not reported.
Streaming responses provide more complete usage details by combining token counts across events and including available usage in completed responses.
Token usage details are now reported consistently across supported providers, including cached input, reasoning, and request cost where available.
A run's model usage is to be shown in tokens and, where the provider
reports it, cost. llm.Usage carried only prompt, completion, and total
counts, so the OpenAI-compatible providers dropped the cached and
reasoning tokens they report and the cost OpenRouter reports, which is
also what a gateway relaying OpenRouter charges. Usage now carries
them, read by one decoder those providers share.
Anthropic reports input_tokens apart from the tokens read from and
written to its prompt cache, so a cached prompt looked a fraction of
its size. The prompt count now includes them, with the cache reads and
writes named. A streamed message also lost its input count, since
message_delta's usage, which carries only output, replaced
message_start's; each event's usage is now merged in.
Gemini's chat usage left its thinking tokens out of the completion,
which its computer use already counted, and Codex subtracted the cached
tokens from its input. Every provider now reports the prompt with its
cached tokens and the completion with its reasoning tokens, naming
both, so usage adds up the same whichever model answered.
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Walkthrough
The change adds cache, reasoning, and reported-cost fields to normalized LLM usage. It adds shared usage conversions and updates Anthropic, Gemini, and several chat providers to use expanded usage data in complete and streaming responses.
Changes: LLM usage accounting
Layer / File(s)
Summary
Usage fields and shared conversions internal/llm/types.go, internal/llm/providers/chatusage/*
llm.Usage adds cached-prompt, cache-write, reasoning, and optional cost fields. Shared types convert chat-completion and Responses API usage details into llm.Usage.
Anthropic includes cache creation and cache read counts in prompt and total tokens. Streaming usage merges cumulative counts and includes converted usage in completion events. Tests cover chat and streaming counts.
Gemini converts usage metadata for complete and streaming responses. The conversion includes cached prompt and reasoning tokens, with completion tokens combining candidate and thought counts.
Shared usage across chat providers internal/llm/providers/local/local.go, internal/llm/providers/openai/*, internal/llm/providers/openaicodex/*, internal/llm/providers/openrouter/*, internal/llm/providers/zai/zai.go
These providers use shared usage types and conversions in complete and streaming responses. Tests check cached tokens, reasoning tokens, and reported cost.
No actionable merge-blocking risk remains in the reviewed change.
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Write docstrings for the functions missing them to satisfy the coverage threshold.
Passed checks: 4 passed
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The title clearly and concisely describes the main change: reporting cached tokens, reasoning tokens, and cost in model usage.
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Actionable comments posted: 1
🪄 Fix comments: Fix CodeRabbit comments on this PR
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Inline comments:
Review comments at @internal/llm/providers/chatusage/chatusage.go:
- Around line 23-25: Add a cache-write token field to promptTokensDetails with
the matching JSON key, then update Usage.LLM() to assign it to
llm.Usage.CacheWritePromptTokens so OpenRouter cache-write usage is preserved.
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OpenRouter reports the prompt tokens written to a provider's cache as
prompt_tokens_details.cache_write_tokens, which the decoder dropped, so
a call that filled the cache showed no cache writes.
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Summary
First step toward showing a run's model usage in tokens and cost, per step and per run.
llm.Usagecarried only prompt, completion and total counts, and providers filled those inconsistently. This PR makes every provider report the same, fuller picture. Nothing records or displays it yet; that comes in the next PRs.llm.Usagegains:CachedPromptTokens: the part of the prompt read from the prompt cache.CacheWritePromptTokens: the part written to the cache (Anthropic).ReasoningTokens: the part of the completion spent on reasoning.Cost *float64: what the provider reported the call cost in US dollars.nilmeans not reported; zero is a reported free call. Today only OpenRouter reports one, and so do gateways that relay its answers and charge exactly that.Every provider now reports
PromptTokenswith cached tokens included andCompletionTokenswith reasoning tokens included, naming both parts.Changes
providers/chatusage(new): one decoder for the usage object of OpenAI's chat completions API and of APIs compatible with it (prompt_tokens_details.cached_tokens,completion_tokens_details.reasoning_tokens,cost), plus the Responses API's (input_tokens_details,output_tokens_details).cache_read_input_tokensandcache_creation_input_tokens, which the API reports apart frominput_tokens.message_delta's usage, which carries only output tokens, replacedmessage_start's, so every streamed message reported 0 prompt tokens. Each event's usage is now merged.Behaviour change to note
The agent loop's observation aging compares the latest prompt size with
max_context_tokens. For Anthropic with prompt caching, and for Codex, that size now includes cached tokens. They still occupy the context window, so aging starts when the context is actually that large rather than later.Test plan
chatusage: details and cost decoded, cost unknown when absent, a reported zero kept, Responses API counts.TestChatCountsCachedInput: Anthropic chat prompt includes cache reads and writes.TestStreamResponse_MergesUsage: a streamed Anthropic message keepsmessage_start's input whenmessage_deltareports only output. It fails without the fix.TestStreamUsageCost: OpenRouter's streamed final chunk keeps its cost, cached and reasoning tokens.TestStreamResponse_Usage: Gemini completion includes thinking tokens, and cached content is named.Summary by CodeRabbit