fix(ai): handle additional usage locations and tool history for OpenAI Chat (#44502)

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Aiden Cline 2026-08-23 13:48:30 -05:00 committed by GitHub
parent 6020f36862
commit 049f0b0c3b
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2 changed files with 41 additions and 8 deletions

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@ -156,6 +156,9 @@ const OpenAIChatUsage = Schema.StructWithRest(
prompt_tokens: optionalNull(Schema.Number),
completion_tokens: optionalNull(Schema.Number),
total_tokens: optionalNull(Schema.Number),
// Zai reports cache hits as top-level `cached_tokens`; DeepSeek uses `prompt_cache_hit_tokens`.
cached_tokens: optionalNull(Schema.Number),
prompt_cache_hit_tokens: optionalNull(Schema.Number),
prompt_tokens_details: optionalNull(
Schema.StructWithRest(
Schema.Struct({
@ -204,11 +207,16 @@ const OpenAIChatDelta = Schema.StructWithRest(
[Schema.Record(Schema.String, Schema.Unknown)],
)
const OpenAIChatChoice = Schema.Struct({
delta: optionalNull(OpenAIChatDelta),
finish_reason: optionalNull(Schema.String),
native_finish_reason: optionalNull(Schema.String),
})
const OpenAIChatChoice = Schema.StructWithRest(
Schema.Struct({
delta: optionalNull(OpenAIChatDelta),
finish_reason: optionalNull(Schema.String),
native_finish_reason: optionalNull(Schema.String),
// Moonshot streams usage on `choice.usage` instead of top-level `usage`.
usage: optionalNull(OpenAIChatUsage),
}),
[Schema.Record(Schema.String, Schema.Unknown)],
)
const OpenAIChatError = Schema.Struct({
code: optionalNull(Schema.Union([Schema.String, Schema.Number])),
@ -509,6 +517,17 @@ const lowerMessages = Effect.fn("OpenAIChat.lowerMessages")(function* (request:
return messages
})
// Anthropic via LiteLLM and Amazon Bedrock require `tools` to be present
// whenever the conversation history contains tool calls/results. Send an
// explicit empty array when we have history but no active tools.
const hasToolHistory = (messages: ReadonlyArray<LLMRequest["messages"][number]>) => {
for (const message of messages) {
if (message.role === "tool") return true
if (message.role === "assistant" && message.content.some((part) => part.type === "tool-call")) return true
}
return false
}
const lowerOptions = (request: LLMRequest) => {
const options = OpenAIOptions.resolve(request)
return {
@ -532,12 +551,15 @@ export const fromRequest = Effect.fn("OpenAIChat.fromRequest")(function* (
const generation = request.generation
const toolSchemaCompatibility = request.model.compatibility?.toolSchema
const maxTokensField = request.model.compatibility?.maxTokensField ?? "max_tokens"
const hasHistory = hasToolHistory(request.messages)
return {
model: request.model.id,
messages: yield* lowerMessages(request, options),
tools:
request.tools.length === 0
? undefined
? hasHistory
? []
: undefined
: request.tools.map((tool) =>
lowerTool(
tool,
@ -581,11 +603,18 @@ const mapFinishReason = (reason: string | null | undefined): FinishReason => {
// total) with a `reasoning_tokens` subset. We pass the inclusive totals
// through and derive the non-cached breakdown so the `AI.Usage` contract is
// satisfied on both sides.
// Providers differ on cache-hit location: OpenAI uses
// `prompt_tokens_details.cached_tokens`, DeepSeek uses
// `prompt_cache_hit_tokens`, and Zai uses top-level `cached_tokens`.
const mapUsage = (usage: OpenAIChatEvent["usage"]): Usage | undefined => {
if (!usage) return undefined
const input = usage.prompt_tokens ?? undefined
const output = usage.completion_tokens ?? undefined
const cached = usage.prompt_tokens_details?.cached_tokens ?? undefined
const cached =
(usage.prompt_tokens_details?.cached_tokens ??
(usage as { prompt_cache_hit_tokens?: number | null }).prompt_cache_hit_tokens ??
(usage as { cached_tokens?: number | null }).cached_tokens ??
undefined) as number | undefined
const cacheWrite = usage.prompt_tokens_details?.cache_write_tokens ?? undefined
const reasoning = usage.completion_tokens_details?.reasoning_tokens ?? undefined
const nonCached = ProviderShared.subtractTokens(input, ProviderShared.sumTokens(cached, cacheWrite))
@ -691,8 +720,11 @@ const step = (state: ParserState, event: OpenAIChatEvent) =>
}),
})
const events: LLMEvent[] = []
const usage = mapUsage(event.usage) ?? state.usage
const choice = event.choices?.[0]
// Moonshot (and a few other OpenAI-compatible providers) attach usage to
// `choice.usage` instead of the top-level `usage` field.
const choiceUsage = (choice as unknown as { usage?: OpenAIChatEvent["usage"] })?.usage
const usage = mapUsage(event.usage) ?? (choiceUsage ? mapUsage(choiceUsage) : undefined) ?? state.usage
const rawFinishReason = choice?.finish_reason
const finishReason =
rawFinishReason !== undefined && rawFinishReason !== null

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@ -342,6 +342,7 @@ describe("OpenAI Chat route", () => {
},
{ role: "tool", tool_call_id: "call_1", content: encodeJson({ forecast: "sunny" }) },
],
tools: [],
stream: true,
stream_options: { include_usage: true },
})