2c6ec0119e
React 19 requires `supportsMicrotasks: true` in the reconciler host config so it can flush state updates from passive effects via queueMicrotask. Without this, state updates triggered inside useMcpConnectivityStatus were silently dropped, corrupting React's internal executionContext and causing all keyboard input to freeze after the "N MCP server(s) need auth" notification appeared. Root cause (three-part fix): 1. reconciler.ts: declare supportsMicrotasks + scheduleMicrotask so React 19 schedules passive-effect flushes correctly. 2. useMcpConnectivityStatus.tsx: wrap the MCP auth notification effect in try/catch so any unexpected throw does not propagate into flushPassiveEffects and permanently corrupt executionContext. 3. notifications.tsx: wrap addNotification, removeNotification, and processQueue in try/catch for the same reason — these are called from 12+ notification hooks across passive effects. Also fixes a pre-existing test isolation bug in context.test.ts where assigning `undefined` to process.env produced the string "undefined", polluting the env for subsequent test files. Resolves: #169, #205, #77
97 lines
3.1 KiB
TypeScript
97 lines
3.1 KiB
TypeScript
import { afterEach, expect, test } from 'bun:test'
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import { getMaxOutputTokensForModel } from '../services/api/claude.ts'
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import {
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getContextWindowForModel,
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getModelMaxOutputTokens,
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} from './context.ts'
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const originalEnv = {
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CLAUDE_CODE_USE_OPENAI: process.env.CLAUDE_CODE_USE_OPENAI,
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CLAUDE_CODE_MAX_OUTPUT_TOKENS: process.env.CLAUDE_CODE_MAX_OUTPUT_TOKENS,
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}
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afterEach(() => {
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if (originalEnv.CLAUDE_CODE_USE_OPENAI === undefined) {
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delete process.env.CLAUDE_CODE_USE_OPENAI
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} else {
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process.env.CLAUDE_CODE_USE_OPENAI = originalEnv.CLAUDE_CODE_USE_OPENAI
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}
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if (originalEnv.CLAUDE_CODE_MAX_OUTPUT_TOKENS === undefined) {
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delete process.env.CLAUDE_CODE_MAX_OUTPUT_TOKENS
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} else {
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process.env.CLAUDE_CODE_MAX_OUTPUT_TOKENS =
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originalEnv.CLAUDE_CODE_MAX_OUTPUT_TOKENS
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}
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})
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test('deepseek-chat uses provider-specific context and output caps', () => {
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process.env.CLAUDE_CODE_USE_OPENAI = '1'
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delete process.env.CLAUDE_CODE_MAX_OUTPUT_TOKENS
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expect(getContextWindowForModel('deepseek-chat')).toBe(128_000)
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expect(getModelMaxOutputTokens('deepseek-chat')).toEqual({
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default: 8_192,
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upperLimit: 8_192,
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})
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expect(getMaxOutputTokensForModel('deepseek-chat')).toBe(8_192)
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})
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test('deepseek-chat clamps oversized max output overrides to the provider limit', () => {
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process.env.CLAUDE_CODE_USE_OPENAI = '1'
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process.env.CLAUDE_CODE_MAX_OUTPUT_TOKENS = '32000'
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expect(getMaxOutputTokensForModel('deepseek-chat')).toBe(8_192)
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})
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test('gpt-4o uses provider-specific context and output caps', () => {
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process.env.CLAUDE_CODE_USE_OPENAI = '1'
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delete process.env.CLAUDE_CODE_MAX_OUTPUT_TOKENS
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expect(getContextWindowForModel('gpt-4o')).toBe(128_000)
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expect(getModelMaxOutputTokens('gpt-4o')).toEqual({
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default: 16_384,
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upperLimit: 16_384,
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})
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expect(getMaxOutputTokensForModel('gpt-4o')).toBe(16_384)
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})
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test('gpt-4o clamps oversized max output overrides to the provider limit', () => {
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process.env.CLAUDE_CODE_USE_OPENAI = '1'
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process.env.CLAUDE_CODE_MAX_OUTPUT_TOKENS = '32000'
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expect(getMaxOutputTokensForModel('gpt-4o')).toBe(16_384)
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})
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test('gpt-5.4 family uses provider-specific context and output caps', () => {
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process.env.CLAUDE_CODE_USE_OPENAI = '1'
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delete process.env.CLAUDE_CODE_MAX_OUTPUT_TOKENS
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expect(getContextWindowForModel('gpt-5.4')).toBe(1_050_000)
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expect(getModelMaxOutputTokens('gpt-5.4')).toEqual({
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default: 128_000,
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upperLimit: 128_000,
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})
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expect(getContextWindowForModel('gpt-5.4-mini')).toBe(400_000)
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expect(getModelMaxOutputTokens('gpt-5.4-mini')).toEqual({
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default: 128_000,
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upperLimit: 128_000,
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})
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expect(getContextWindowForModel('gpt-5.4-nano')).toBe(400_000)
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expect(getModelMaxOutputTokens('gpt-5.4-nano')).toEqual({
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default: 128_000,
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upperLimit: 128_000,
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})
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})
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test('gpt-5.4 family keeps large max output overrides within provider limits', () => {
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process.env.CLAUDE_CODE_USE_OPENAI = '1'
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process.env.CLAUDE_CODE_MAX_OUTPUT_TOKENS = '200000'
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expect(getMaxOutputTokensForModel('gpt-5.4')).toBe(128_000)
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expect(getMaxOutputTokensForModel('gpt-5.4-mini')).toBe(128_000)
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expect(getMaxOutputTokensForModel('gpt-5.4-nano')).toBe(128_000)
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})
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