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fix(ai): align chat assistant content (#41210)
Co-authored-by: Aiden Cline <63023139+rekram1-node@users.noreply.github.com>
This commit is contained in:
opencode-agent[bot]
GitHub
parent
e566c082f1
commit
7afe537c69
2 changed files with 64 additions and 38 deletions
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@ -371,12 +371,13 @@ const lowerAssistantMessage = Effect.fn("OpenAIChat.lowerAssistantMessage")(func
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return text
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})()
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const cached = message.content.findLast((part) => "cache" in part && part.cache !== undefined)
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const cacheControl = options.cacheControl?.(cached && "cache" in cached ? cached.cache : undefined)
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const result = {
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role: "assistant" as const,
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content: content.length === 0 ? null : ProviderShared.joinText(content),
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tool_calls: toolCalls.length === 0 ? undefined : toolCalls,
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reasoning_details: details,
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cache_control: options.cacheControl?.(cached && "cache" in cached ? cached.cache : undefined),
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content: content.length > 0 ? content.map((part) => part.text).join("") : toolCalls.length > 0 ? null : "",
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...(toolCalls.length > 0 ? { tool_calls: toolCalls } : {}),
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...(details !== undefined ? { reasoning_details: details } : {}),
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...(cacheControl !== undefined ? { cache_control: cacheControl } : {}),
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}
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if (field === undefined || reasoningText === undefined) return result
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return { ...result, [field]: reasoningText }
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@ -716,14 +717,13 @@ const step = (state: ParserState, event: OpenAIChatEvent) =>
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return [{ ...state, usage }, events] as const
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}
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const reasoningField = state.reasoningField ?? (!state.lifecycle.text.has("text-0") ? reasoning?.field : undefined)
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const reasoningField = state.reasoningField ?? reasoning?.field
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const detailDelta = Array.isArray(delta?.reasoning_details) ? delta.reasoning_details : undefined
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if (detailDelta !== undefined) appendReasoningDetails(state.reasoningDetails, detailDelta)
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const reasoningDetailsObserved = state.reasoningDetailsObserved || detailDelta !== undefined
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const deltaMetadata = reasoningMetadata(reasoningField)
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const text = detailDelta?.length ? (detailText(detailDelta) ?? reasoning?.text) : reasoning?.text
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if (!state.lifecycle.text.has("text-0") && text !== undefined)
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lifecycle = Lifecycle.reasoningDelta(lifecycle, events, "reasoning-0", text, deltaMetadata)
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if (text !== undefined) lifecycle = Lifecycle.reasoningDelta(lifecycle, events, "reasoning-0", text, deltaMetadata)
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else if (
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reasoningDetailsObserved &&
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!lifecycle.reasoning.has("reasoning-0") &&
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@ -812,14 +812,18 @@ const step = (state: ParserState, event: OpenAIChatEvent) =>
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const finishEvents = (state: ParserState): ReadonlyArray<LLMEvent> => {
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const events: LLMEvent[] = []
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const hasToolCalls = state.toolCallEvents.length > 0
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const toolCallEvents =
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state.finishReason === undefined && Object.keys(state.tools).length > 0
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? Effect.runSync(ToolStream.finishAll(ADAPTER, state.tools)).events
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: state.toolCallEvents
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const hasToolCalls = toolCallEvents.length > 0
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const reason = state.finishReason
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? {
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...state.finishReason,
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normalized:
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state.finishReason.normalized === "stop" && hasToolCalls ? "tool-calls" : state.finishReason.normalized,
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}
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: undefined
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: { normalized: hasToolCalls ? ("tool-calls" as const) : ("unknown" as const) }
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const metadata = reasoningMetadata(
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state.reasoningField,
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state.reasoningDetailsObserved ? state.reasoningDetails : undefined,
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@ -829,9 +833,9 @@ const finishEvents = (state: ParserState): ReadonlyArray<LLMEvent> => {
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? Lifecycle.reasoningStart(state.lifecycle, events, "reasoning-0", reasoningMetadata(state.reasoningField))
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: state.lifecycle
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const ended = Lifecycle.reasoningEnd(started, events, "reasoning-0", metadata)
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const lifecycle = state.toolCallEvents.length ? Lifecycle.stepStart(ended, events) : ended
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events.push(...state.toolCallEvents)
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if (reason) Lifecycle.finish(lifecycle, events, { reason, usage: state.usage })
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const lifecycle = toolCallEvents.length ? Lifecycle.stepStart(ended, events) : ended
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events.push(...toolCallEvents)
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Lifecycle.finish(lifecycle, events, { reason, usage: state.usage })
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return events
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}
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@ -102,6 +102,24 @@ describe("OpenAI Chat route", () => {
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}),
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)
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it.effect("concatenates assistant text parts without adding separators", () =>
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Effect.gen(function* () {
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const prepared = yield* compileRequest(
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LLM.request({
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model,
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messages: [
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Message.assistant([
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{ type: "text", text: "Hello" },
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{ type: "text", text: " world" },
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]),
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],
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}),
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)
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expect(prepared.body.messages).toEqual([{ role: "assistant", content: "Hello world" }])
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}),
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)
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it.effect("writes reasoning to a configured custom field on every assistant message", () =>
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Effect.gen(function* () {
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const prepared = yield* compileRequest(
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@ -578,7 +596,7 @@ describe("OpenAI Chat route", () => {
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}),
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)
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expect(prepared.body.messages).toEqual([{ role: "assistant", content: null, reasoning_content: "hidden" }])
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expect(prepared.body.messages).toEqual([{ role: "assistant", content: "", reasoning_content: "hidden" }])
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}),
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)
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@ -827,7 +845,7 @@ describe("OpenAI Chat route", () => {
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}),
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)
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it.effect("ignores scalar reasoning after content starts", () =>
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it.effect("preserves scalar reasoning after content starts", () =>
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Effect.gen(function* () {
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const details = [{ type: "reasoning.text", text: "detail", format: "unknown", index: 0 }]
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const response = yield* LLMClient.generate(request).pipe(
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@ -843,11 +861,11 @@ describe("OpenAI Chat route", () => {
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),
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)
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expect(response.reasoning).toBe("detail")
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expect(response.events.filter(LLMEvent.is.reasoningStart)).toHaveLength(1)
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expect(response.events.filter(LLMEvent.is.reasoningEnd)).toHaveLength(1)
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expect(response.reasoning).toBe("detailscalar")
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expect(response.events.filter(LLMEvent.is.reasoningStart)).toHaveLength(2)
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expect(response.events.filter(LLMEvent.is.reasoningEnd)).toHaveLength(2)
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expect(response.message.content.find((part) => part.type === "reasoning")?.providerMetadata).toEqual({
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openai: { reasoningDetails: details },
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openai: { reasoningField: "reasoning", reasoningDetails: details },
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})
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}),
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)
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@ -947,7 +965,7 @@ describe("OpenAI Chat route", () => {
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expect(response.events.filter(LLMEvent.is.reasoningEnd)).toHaveLength(1)
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const replay = yield* compileRequest(LLM.request({ model, messages: [response.message] }))
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expect(replay.body.messages).toEqual([{ role: "assistant", content: null, reasoning_details: details }])
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expect(replay.body.messages).toEqual([{ role: "assistant", content: "", reasoning_details: details }])
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}),
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)
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@ -997,7 +1015,7 @@ describe("OpenAI Chat route", () => {
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)
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expect(replay.body.messages).toEqual([
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{ role: "assistant", content: null, reasoning: "firstsecond", reasoning_details: [first, second] },
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{ role: "assistant", content: "", reasoning: "firstsecond", reasoning_details: [first, second] },
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])
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}),
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)
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@ -1022,7 +1040,7 @@ describe("OpenAI Chat route", () => {
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)
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expect(replay.body.messages).toEqual([
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{ role: "assistant", content: null, reasoning_content: "AB", reasoning_details: [detail] },
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{ role: "assistant", content: "", reasoning_content: "AB", reasoning_details: [detail] },
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])
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}),
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)
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@ -1044,7 +1062,7 @@ describe("OpenAI Chat route", () => {
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)
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expect(replay.body.messages).toEqual([
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{ role: "assistant", content: null, reasoning_content: "thinking", reasoning_details: details },
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{ role: "assistant", content: "", reasoning_content: "thinking", reasoning_details: details },
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])
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}),
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)
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@ -1152,7 +1170,7 @@ describe("OpenAI Chat route", () => {
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}),
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)
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it.effect("fails a streamed tool call when the provider ends without a finish reason", () =>
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it.effect("finalizes a streamed tool call when the provider ends without a finish reason", () =>
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Effect.gen(function* () {
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const body = sseEvents(
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deltaChunk({
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@ -1164,27 +1182,31 @@ describe("OpenAI Chat route", () => {
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const input = LLMRequest.update(request, {
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tools: [ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } })],
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})
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const events: LLMEvent[] = []
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const streamError = yield* LLMClient.stream(input).pipe(
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Stream.runForEach((event) => Effect.sync(() => events.push(event))),
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Effect.flip,
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Effect.provide(fixedResponse(body)),
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)
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const error = yield* LLMClient.generate(input).pipe(Effect.provide(fixedResponse(body)), Effect.flip)
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const response = yield* LLMClient.generate(input).pipe(Effect.provide(fixedResponse(body)))
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expect(events).toEqual([
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expect(response.events).toEqual([
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{ type: "step-start", index: 0 },
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{ type: "tool-input-start", id: "call_1", name: "lookup", providerMetadata: undefined },
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{ type: "tool-input-delta", id: "call_1", name: "lookup", text: '{"query"' },
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{ type: "tool-input-delta", id: "call_1", name: "lookup", text: ':"weather"}' },
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{ type: "tool-input-end", id: "call_1", name: "lookup", providerMetadata: undefined },
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{
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type: "tool-call",
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id: "call_1",
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name: "lookup",
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input: { query: "weather" },
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providerExecuted: undefined,
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providerMetadata: undefined,
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},
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{
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type: "step-finish",
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index: 0,
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reason: { normalized: "tool-calls" },
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usage: undefined,
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providerMetadata: undefined,
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},
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{ type: "finish", reason: { normalized: "tool-calls" }, usage: undefined },
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])
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expect(events.filter(LLMEvent.is.toolCall)).toEqual([])
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expect(streamError.reason).toMatchObject({
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_tag: "InvalidProviderOutput",
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classification: "incomplete-stream",
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})
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expect(streamError.message).toContain("The provider response ended unexpectedly.")
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expect(error.message).toContain("The provider response ended unexpectedly.")
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}),
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)
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