feat: expand secure assistant workflows
Harden runtime execution and add local knowledge, Smart Heartbeat, usage visibility, responsive product surfaces, and cross-platform packaging support. Co-authored-by: factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>
This commit is contained in:
lofyer
co-authored by
factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>
factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>
parent
6ef1795b81
commit
b3fdf96962
@@ -4,7 +4,18 @@ import { ModelAgentRuntime } from './model-runtime'
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function createEventStream(text: string): string {
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return [
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'event: message_start',
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'data: {"type":"message_start","message":{"id":"message-1"}}',
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`data: ${JSON.stringify({
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type: 'message_start',
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message: {
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id: 'message-1',
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model: 'claude-sonnet-provider',
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usage: {
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input_tokens: 23,
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cache_creation_input_tokens: 5,
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cache_read_input_tokens: 7
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}
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}
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})}`,
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'',
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'event: content_block_delta',
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`data: ${JSON.stringify({
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@@ -12,6 +23,12 @@ function createEventStream(text: string): string {
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delta: { type: 'text_delta', text }
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})}`,
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'',
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'event: message_delta',
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`data: ${JSON.stringify({
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type: 'message_delta',
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usage: { output_tokens: 11 }
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})}`,
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'',
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'event: message_stop',
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'data: {"type":"message_stop"}',
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'',
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@@ -30,6 +47,8 @@ describe('ModelAgentRuntime', () => {
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apiKey: 'test-key',
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baseUrl: 'https://bigtoken.ai',
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model: 'sonnet-5',
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protocol: 'anthropic-messages',
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authentication: 'api-key',
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fetcher
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})
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@@ -54,6 +73,8 @@ describe('ModelAgentRuntime', () => {
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apiKey: 'test-key',
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baseUrl: 'https://bigtoken.ai',
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model: 'sonnet-5',
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protocol: 'anthropic-messages',
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authentication: 'api-key',
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skillInstructions: '# 文档写作',
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fetcher
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})
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@@ -91,6 +112,21 @@ describe('ModelAgentRuntime', () => {
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delta: '真实模型回答'
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})
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)
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expect(events.filter((event) => event.type === 'model-usage')).toEqual([
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{
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requestId: 'a431666e-5ec8-45e6-beb4-654132eed125',
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type: 'model-usage',
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callId: 'message-1',
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runtime: 'model',
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provider: 'anthropic',
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model: 'claude-sonnet-provider',
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inputTokens: 23,
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outputTokens: 11,
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cacheReadTokens: 7,
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cacheWriteTokens: 5
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}
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])
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expect(events.at(-2)).toMatchObject({ type: 'model-usage' })
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expect(events.at(-1)).toMatchObject({ type: 'done' })
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})
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@@ -108,6 +144,8 @@ describe('ModelAgentRuntime', () => {
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apiKey: 'test-key',
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baseUrl: 'https://bigtoken.ai',
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model: 'sonnet-5',
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protocol: 'anthropic-messages',
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authentication: 'api-key',
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fetcher
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})
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@@ -126,4 +164,379 @@ describe('ModelAgentRuntime', () => {
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await expect(consume()).rejects.toThrow('意外中断')
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})
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it('redacts credentials from provider error messages', async () => {
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const runtime = new ModelAgentRuntime({
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apiKey: 'test-key',
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baseUrl: 'https://bigtoken.ai',
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model: 'claude-sonnet-5',
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protocol: 'anthropic-messages',
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authentication: 'api-key',
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fetcher: vi.fn<typeof fetch>(async () =>
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Response.json(
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{
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error: {
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message:
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'upstream failed Authorization: Bearer secret-token'
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}
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},
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{ status: 502 }
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)
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)
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})
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const consume = async (): Promise<void> => {
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for await (const _event of runtime.run(
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{
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requestId: crypto.randomUUID(),
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conversationId: crypto.randomUUID(),
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prompt: 'test'
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},
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new AbortController().signal
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)) {
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void _event
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}
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}
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await expect(consume()).rejects.toThrow(
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'upstream failed Authorization: [REDACTED]'
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)
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})
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it('uses OpenAI Chat Completions SSE and omits auth for Ollama', async () => {
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const stream = [
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`data: ${JSON.stringify({
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choices: [{ delta: { content: '本机回答' } }]
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})}`,
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'',
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`data: ${JSON.stringify({
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id: 'chatcmpl-provider-1',
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model: 'qwen3-provider',
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choices: [],
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usage: {
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prompt_tokens: 31,
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completion_tokens: 9,
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total_tokens: 40,
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prompt_tokens_details: { cached_tokens: 13 },
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cache_write_tokens: 4
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}
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})}`,
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'',
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'data: [DONE]',
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'',
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''
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].join('\n')
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const fetcher = vi.fn<typeof fetch>(async () =>
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new Response(stream, {
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status: 200,
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headers: { 'content-type': 'text/event-stream' }
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})
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)
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const runtime = new ModelAgentRuntime({
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baseUrl: 'http://127.0.0.1:11434/v1',
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model: 'qwen3',
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protocol: 'openai-chat-completions',
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authentication: 'none',
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fetcher
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})
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const events = []
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for await (const event of runtime.run(
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{
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requestId: 'a431666e-5ec8-45e6-beb4-654132eed127',
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conversationId: 'conversation-3',
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prompt: '你好'
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},
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new AbortController().signal
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)) {
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events.push(event)
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}
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const [input, init] = fetcher.mock.calls[0] ?? []
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expect(input?.toString()).toBe(
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'http://127.0.0.1:11434/v1/chat/completions'
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)
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expect(init?.headers).toEqual({
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'content-type': 'application/json'
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})
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expect(JSON.parse(init?.body as string)).toMatchObject({
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model: 'qwen3',
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stream: true,
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stream_options: {
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include_usage: true
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},
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messages: [
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expect.objectContaining({ role: 'system' }),
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expect.objectContaining({ role: 'user', content: '你好' })
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]
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})
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expect(events).toContainEqual(
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expect.objectContaining({
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type: 'text',
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delta: '本机回答'
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})
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)
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expect(events.filter((event) => event.type === 'model-usage')).toEqual([
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{
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requestId: 'a431666e-5ec8-45e6-beb4-654132eed127',
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type: 'model-usage',
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callId: 'chatcmpl-provider-1',
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runtime: 'model',
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provider: 'openai',
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model: 'qwen3-provider',
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inputTokens: 31,
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outputTokens: 9,
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cacheReadTokens: 13,
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cacheWriteTokens: 4,
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reportedTotalTokens: 40
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}
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])
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expect(events.at(-2)).toMatchObject({ type: 'model-usage' })
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expect(events.at(-1)).toMatchObject({ type: 'done' })
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})
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it('generates a bounded image through the BigToken-compatible endpoint', async () => {
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const png = Buffer.from([
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0x89, 0x50, 0x4e, 0x47, 0x0d, 0x0a, 0x1a, 0x0a,
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0x00
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]).toString('base64')
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const fetcher = vi.fn<typeof fetch>(async () =>
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Response.json({
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id: 'image-provider-1',
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model: 'gpt-image-provider',
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usage: {
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input_tokens: 17,
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output_tokens: 29,
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total_tokens: 46
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},
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data: [{ b64_json: png }]
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})
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)
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const runtime = new ModelAgentRuntime({
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apiKey: 'test-key',
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baseUrl: 'https://bigtoken.ai/v1',
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model: 'gpt-image-2',
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protocol: 'openai-images-generations',
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authentication: 'api-key',
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fetcher
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})
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const events = []
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for await (const event of runtime.run(
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{
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requestId: 'a431666e-5ec8-45e6-beb4-654132eed128',
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conversationId: 'conversation-image',
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prompt: '一只在窗边睡觉的猫'
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},
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new AbortController().signal
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)) {
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events.push(event)
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}
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const [input, init] = fetcher.mock.calls[0] ?? []
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expect(input?.toString()).toBe(
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'https://bigtoken.ai/v1/images/generations'
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)
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expect(init?.headers).toEqual({
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authorization: 'Bearer test-key',
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'content-type': 'application/json'
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})
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expect(JSON.parse(init?.body as string)).toEqual({
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model: 'gpt-image-2',
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prompt: '一只在窗边睡觉的猫',
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n: 1,
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response_format: 'b64_json'
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})
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expect(events).toContainEqual(
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expect.objectContaining({
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type: 'generated-image',
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mimeType: 'image/png',
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data: png
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})
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)
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expect(events.filter((event) => event.type === 'model-usage')).toEqual([
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{
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requestId: 'a431666e-5ec8-45e6-beb4-654132eed128',
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type: 'model-usage',
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callId: 'image-provider-1',
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runtime: 'model',
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provider: 'openai',
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model: 'gpt-image-provider',
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inputTokens: 17,
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outputTokens: 29,
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cacheReadTokens: 0,
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cacheWriteTokens: 0,
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reportedTotalTokens: 46
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}
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])
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expect(events.findIndex((event) => event.type === 'model-usage')).toBeLessThan(
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events.findIndex((event) => event.type === 'generated-image')
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)
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expect(events.at(-1)).toMatchObject({ type: 'done' })
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})
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it('rejects remote image URLs instead of fetching provider output', async () => {
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const runtime = new ModelAgentRuntime({
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apiKey: 'test-key',
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baseUrl: 'https://bigtoken.ai/v1',
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model: 'gpt-image-2',
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protocol: 'openai-images-generations',
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authentication: 'api-key',
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fetcher: vi.fn<typeof fetch>(async () =>
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Response.json({
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data: [{ url: 'https://untrusted.example/image.png' }]
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})
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)
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})
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const consume = async (): Promise<void> => {
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for await (const _event of runtime.run(
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{
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requestId: 'a431666e-5ec8-45e6-beb4-654132eed129',
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conversationId: 'conversation-image-url',
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prompt: '测试图片'
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},
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new AbortController().signal
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)) {
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void _event
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}
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}
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await expect(consume()).rejects.toThrow('未返回 base64 图片')
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})
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it('accepts a bounded inline image data URL from compatible gateways', async () => {
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const png = Buffer.from([
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0x89, 0x50, 0x4e, 0x47, 0x0d, 0x0a, 0x1a, 0x0a,
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0x00
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]).toString('base64')
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const runtime = new ModelAgentRuntime({
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apiKey: 'test-key',
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baseUrl: 'https://bigtoken.ai/v1',
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model: 'gpt-image-2',
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protocol: 'openai-images-generations',
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authentication: 'api-key',
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fetcher: vi.fn<typeof fetch>(async () =>
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Response.json({
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data: [{ url: `data:image/png;base64,${png}` }]
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})
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)
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})
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const events = []
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for await (const event of runtime.run(
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{
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requestId: crypto.randomUUID(),
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conversationId: crypto.randomUUID(),
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prompt: '测试内联图片'
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},
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new AbortController().signal
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)) {
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events.push(event)
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}
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expect(events).toContainEqual(
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expect.objectContaining({
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type: 'generated-image',
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mimeType: 'image/png',
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data: png
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})
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)
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})
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it.each([
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{
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body: JSON.stringify({
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error: {
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message:
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'upstream unavailable Authorization: Bearer secret-token'
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}
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}),
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headers: {
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'content-type': 'application/json',
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'x-request-id': 'image-request-502'
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},
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expected:
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'upstream unavailable Authorization: [REDACTED]（HTTP 502，请求 ID image-request-502）'
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},
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{
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body: '<html>Bad Gateway</html>',
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headers: { 'content-type': 'text/html' },
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expected: '图像生成请求失败（HTTP 502）'
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},
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{
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body: JSON.stringify({
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error: '模型接口请求失败（HTTP 502）'
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}),
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headers: { 'content-type': 'application/json' },
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expected:
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'上游图像服务暂时不可用，请稍后重试或联系服务商（HTTP 502）'
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}
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])(
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'retains HTTP status for image gateway failures',
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async ({ body, headers, expected }) => {
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const runtime = new ModelAgentRuntime({
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apiKey: 'test-key',
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baseUrl: 'https://bigtoken.ai/v1',
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model: 'gpt-image-2',
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protocol: 'openai-images-generations',
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authentication: 'api-key',
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fetcher: vi.fn<typeof fetch>(async () =>
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new Response(body, { status: 502, headers })
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)
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})
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const consume = async (): Promise<void> => {
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for await (const _event of runtime.run(
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{
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requestId: crypto.randomUUID(),
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conversationId: crypto.randomUUID(),
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prompt: '测试网关错误'
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},
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new AbortController().signal
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)) {
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void _event
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}
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}
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await expect(consume()).rejects.toThrow(expected)
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}
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)
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it.runIf(
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process.env.GOODBUDDY_BIGTOKEN_IMAGE_INTEGRATION === '1'
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)(
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'generates a real synthetic image with BigToken gpt-image-2',
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async () => {
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const apiKey = process.env.GOODBUDDY_BIGTOKEN_API_KEY
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if (!apiKey) {
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throw new Error('GOODBUDDY_BIGTOKEN_API_KEY is required')
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}
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const runtime = new ModelAgentRuntime({
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apiKey,
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baseUrl: 'https://bigtoken.ai/v1',
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model: 'gpt-image-2',
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protocol: 'openai-images-generations',
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authentication: 'api-key'
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})
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const events = []
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for await (const event of runtime.run(
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{
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requestId: crypto.randomUUID(),
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conversationId: crypto.randomUUID(),
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prompt:
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'A simple solid blue circle centered on a plain white background.'
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},
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new AbortController().signal
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)) {
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events.push(event)
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}
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expect(events).toContainEqual(
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expect.objectContaining({
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type: 'generated-image',
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mimeType: expect.stringMatching(/^image\//u)
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})
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)
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await runtime.dispose()
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},
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180_000
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)
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})
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Reference in New Issue
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