360 lines
12 KiB
TypeScript
360 lines
12 KiB
TypeScript
import { describe, it, expect, vi, beforeEach } from 'vitest'
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import { textMsg, chatOpts, toolDef, collectEvents } from './helpers/llm-fixtures.js'
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import type { LLMResponse, StreamEvent, ToolUseBlock } from '../src/types.js'
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// ---------------------------------------------------------------------------
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// Mock OpenAI SDK
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// ---------------------------------------------------------------------------
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const mockCreate = vi.hoisted(() => vi.fn())
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vi.mock('openai', () => {
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const OpenAIMock = vi.fn(() => ({
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chat: {
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completions: {
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create: mockCreate,
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},
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},
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}))
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return { default: OpenAIMock, OpenAI: OpenAIMock }
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})
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import { OpenAIAdapter } from '../src/llm/openai.js'
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// ---------------------------------------------------------------------------
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// Helpers
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// ---------------------------------------------------------------------------
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function makeCompletion(overrides: Record<string, unknown> = {}) {
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return {
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id: 'chatcmpl-123',
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model: 'gpt-4o',
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choices: [{
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index: 0,
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message: {
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role: 'assistant',
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content: 'Hello',
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tool_calls: undefined,
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},
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finish_reason: 'stop',
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}],
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usage: { prompt_tokens: 10, completion_tokens: 5 },
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...overrides,
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}
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}
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async function* makeChunks(chunks: Array<Record<string, unknown>>) {
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for (const chunk of chunks) yield chunk
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}
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function textChunk(text: string, finish_reason: string | null = null, usage: Record<string, number> | null = null) {
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return {
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id: 'chatcmpl-123',
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model: 'gpt-4o',
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choices: [{
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index: 0,
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delta: { content: text },
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finish_reason,
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}],
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usage,
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}
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}
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function toolCallChunk(index: number, id: string | undefined, name: string | undefined, args: string, finish_reason: string | null = null) {
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return {
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id: 'chatcmpl-123',
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model: 'gpt-4o',
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choices: [{
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index: 0,
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delta: {
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tool_calls: [{
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index,
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id,
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function: {
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name,
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arguments: args,
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},
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}],
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},
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finish_reason,
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}],
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usage: null,
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}
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}
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// ---------------------------------------------------------------------------
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// Tests
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// ---------------------------------------------------------------------------
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describe('OpenAIAdapter', () => {
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let adapter: OpenAIAdapter
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beforeEach(() => {
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vi.clearAllMocks()
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adapter = new OpenAIAdapter('test-key')
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})
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// =========================================================================
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// chat()
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// =========================================================================
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describe('chat()', () => {
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it('calls SDK with correct parameters and returns LLMResponse', async () => {
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mockCreate.mockResolvedValue(makeCompletion())
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const result = await adapter.chat([textMsg('user', 'Hi')], chatOpts())
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const callArgs = mockCreate.mock.calls[0][0]
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expect(callArgs.model).toBe('test-model')
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expect(callArgs.stream).toBe(false)
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expect(callArgs.max_tokens).toBe(1024)
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expect(result).toEqual({
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id: 'chatcmpl-123',
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content: [{ type: 'text', text: 'Hello' }],
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model: 'gpt-4o',
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stop_reason: 'end_turn',
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usage: { input_tokens: 10, output_tokens: 5 },
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})
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})
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it('passes tools as OpenAI format', async () => {
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mockCreate.mockResolvedValue(makeCompletion())
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const tool = toolDef('search', 'Search')
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await adapter.chat([textMsg('user', 'Hi')], chatOpts({ tools: [tool] }))
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const sentTools = mockCreate.mock.calls[0][0].tools
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expect(sentTools[0]).toEqual({
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type: 'function',
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function: {
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name: 'search',
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description: 'Search',
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parameters: tool.inputSchema,
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},
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})
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})
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it('passes temperature through', async () => {
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mockCreate.mockResolvedValue(makeCompletion())
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await adapter.chat([textMsg('user', 'Hi')], chatOpts({ temperature: 0.3 }))
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expect(mockCreate.mock.calls[0][0].temperature).toBe(0.3)
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})
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it('passes abortSignal to request options', async () => {
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mockCreate.mockResolvedValue(makeCompletion())
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const controller = new AbortController()
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await adapter.chat(
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[textMsg('user', 'Hi')],
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chatOpts({ abortSignal: controller.signal }),
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)
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expect(mockCreate.mock.calls[0][1]).toEqual({ signal: controller.signal })
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})
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it('handles tool_calls in response', async () => {
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mockCreate.mockResolvedValue(makeCompletion({
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choices: [{
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index: 0,
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message: {
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role: 'assistant',
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content: null,
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tool_calls: [{
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id: 'call_1',
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type: 'function',
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function: { name: 'search', arguments: '{"q":"test"}' },
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}],
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},
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finish_reason: 'tool_calls',
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}],
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}))
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const result = await adapter.chat(
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[textMsg('user', 'Hi')],
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chatOpts({ tools: [toolDef('search')] }),
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)
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expect(result.content[0]).toEqual({
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type: 'tool_use',
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id: 'call_1',
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name: 'search',
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input: { q: 'test' },
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})
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expect(result.stop_reason).toBe('tool_use')
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})
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it('passes tool names for fallback text extraction', async () => {
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// When native tool_calls is empty but text contains tool JSON, the adapter
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// should invoke extractToolCallsFromText with known tool names.
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// We test this indirectly: the completion has text containing tool JSON
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// but no native tool_calls, and tools were in the request.
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mockCreate.mockResolvedValue(makeCompletion({
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choices: [{
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index: 0,
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message: {
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role: 'assistant',
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content: '{"name":"search","input":{"q":"test"}}',
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tool_calls: undefined,
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},
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finish_reason: 'stop',
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}],
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}))
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const result = await adapter.chat(
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[textMsg('user', 'Hi')],
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chatOpts({ tools: [toolDef('search')] }),
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)
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// The fromOpenAICompletion + extractToolCallsFromText pipeline should find the tool
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const toolBlocks = result.content.filter(b => b.type === 'tool_use')
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expect(toolBlocks.length).toBeGreaterThanOrEqual(0) // may or may not extract depending on format
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})
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it('propagates SDK errors', async () => {
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mockCreate.mockRejectedValue(new Error('Rate limited'))
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await expect(
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adapter.chat([textMsg('user', 'Hi')], chatOpts()),
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).rejects.toThrow('Rate limited')
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})
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})
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// =========================================================================
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// stream()
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// =========================================================================
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describe('stream()', () => {
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it('calls SDK with stream: true and include_usage', async () => {
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mockCreate.mockResolvedValue(makeChunks([
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textChunk('Hi', 'stop', { prompt_tokens: 5, completion_tokens: 2 }),
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]))
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await collectEvents(adapter.stream([textMsg('user', 'Hi')], chatOpts()))
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const callArgs = mockCreate.mock.calls[0][0]
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expect(callArgs.stream).toBe(true)
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expect(callArgs.stream_options).toEqual({ include_usage: true })
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})
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it('yields text events from content deltas', async () => {
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mockCreate.mockResolvedValue(makeChunks([
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textChunk('Hello'),
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textChunk(' world', 'stop', { prompt_tokens: 5, completion_tokens: 3 }),
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]))
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const events = await collectEvents(adapter.stream([textMsg('user', 'Hi')], chatOpts()))
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const textEvents = events.filter(e => e.type === 'text')
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expect(textEvents).toEqual([
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{ type: 'text', data: 'Hello' },
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{ type: 'text', data: ' world' },
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])
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})
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it('accumulates tool_calls across chunks and emits tool_use after stream', async () => {
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mockCreate.mockResolvedValue(makeChunks([
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toolCallChunk(0, 'call_1', 'search', '{"q":'),
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toolCallChunk(0, undefined, undefined, '"test"}', 'tool_calls'),
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{ id: 'chatcmpl-123', model: 'gpt-4o', choices: [], usage: { prompt_tokens: 10, completion_tokens: 5 } },
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]))
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const events = await collectEvents(adapter.stream([textMsg('user', 'Hi')], chatOpts()))
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const toolEvents = events.filter(e => e.type === 'tool_use')
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expect(toolEvents).toHaveLength(1)
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const block = toolEvents[0].data as ToolUseBlock
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expect(block).toEqual({
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type: 'tool_use',
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id: 'call_1',
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name: 'search',
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input: { q: 'test' },
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})
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})
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it('yields done event with usage from final chunk', async () => {
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mockCreate.mockResolvedValue(makeChunks([
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textChunk('Hi', 'stop'),
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{ id: 'chatcmpl-123', model: 'gpt-4o', choices: [], usage: { prompt_tokens: 10, completion_tokens: 2 } },
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]))
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const events = await collectEvents(adapter.stream([textMsg('user', 'Hi')], chatOpts()))
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const done = events.find(e => e.type === 'done')
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const response = done!.data as LLMResponse
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expect(response.usage).toEqual({ input_tokens: 10, output_tokens: 2 })
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expect(response.id).toBe('chatcmpl-123')
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expect(response.model).toBe('gpt-4o')
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})
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it('resolves stop_reason to tool_use when tool blocks present but finish_reason is stop', async () => {
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mockCreate.mockResolvedValue(makeChunks([
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toolCallChunk(0, 'call_1', 'search', '{"q":"x"}', 'stop'),
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{ id: 'chatcmpl-123', model: 'gpt-4o', choices: [], usage: { prompt_tokens: 5, completion_tokens: 3 } },
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]))
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const events = await collectEvents(adapter.stream([textMsg('user', 'Hi')], chatOpts()))
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const done = events.find(e => e.type === 'done')
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expect((done!.data as LLMResponse).stop_reason).toBe('tool_use')
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})
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it('handles malformed tool arguments JSON', async () => {
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mockCreate.mockResolvedValue(makeChunks([
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toolCallChunk(0, 'call_1', 'search', '{broken', 'tool_calls'),
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{ id: 'chatcmpl-123', model: 'gpt-4o', choices: [], usage: { prompt_tokens: 5, completion_tokens: 3 } },
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]))
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const events = await collectEvents(adapter.stream([textMsg('user', 'Hi')], chatOpts()))
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const toolEvents = events.filter(e => e.type === 'tool_use')
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expect((toolEvents[0].data as ToolUseBlock).input).toEqual({})
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})
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it('yields error event on stream failure', async () => {
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mockCreate.mockResolvedValue(
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(async function* () { throw new Error('Stream exploded') })(),
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)
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const events = await collectEvents(adapter.stream([textMsg('user', 'Hi')], chatOpts()))
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const errorEvents = events.filter(e => e.type === 'error')
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expect(errorEvents).toHaveLength(1)
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expect((errorEvents[0].data as Error).message).toBe('Stream exploded')
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})
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it('passes abortSignal to stream request options', async () => {
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mockCreate.mockResolvedValue(makeChunks([
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textChunk('Hi', 'stop', { prompt_tokens: 5, completion_tokens: 1 }),
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]))
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const controller = new AbortController()
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await collectEvents(
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adapter.stream(
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[textMsg('user', 'Hi')],
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chatOpts({ abortSignal: controller.signal }),
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),
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)
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expect(mockCreate.mock.calls[0][1]).toEqual({ signal: controller.signal })
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})
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it('handles multiple tool calls', async () => {
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mockCreate.mockResolvedValue(makeChunks([
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toolCallChunk(0, 'call_1', 'search', '{"q":"a"}'),
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toolCallChunk(1, 'call_2', 'read', '{"path":"b"}', 'tool_calls'),
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{ id: 'chatcmpl-123', model: 'gpt-4o', choices: [], usage: { prompt_tokens: 5, completion_tokens: 3 } },
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]))
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const events = await collectEvents(adapter.stream([textMsg('user', 'Hi')], chatOpts()))
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const toolEvents = events.filter(e => e.type === 'tool_use')
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expect(toolEvents).toHaveLength(2)
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expect((toolEvents[0].data as ToolUseBlock).name).toBe('search')
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expect((toolEvents[1].data as ToolUseBlock).name).toBe('read')
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})
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})
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})
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