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* test/unit-openai-chat-input.mjs
*
* 单元测试：/v1/chat/completions 输入内容块兼容性
* 运行方式：node test/unit-openai-chat-input.mjs
*/
let passed = 0;
let failed = 0;
function test(name, fn) {
try {
fn();
console.log(` ✅ ${name}`);
passed++;
} catch (e) {
console.error(` ❌ ${name}`);
console.error(` ${e.message}`);
failed++;
}
}
function assert(condition, msg) {
if (!condition) throw new Error(msg || 'Assertion failed');
}
function assertEqual(a, b, msg) {
const as = JSON.stringify(a), bs = JSON.stringify(b);
if (as !== bs) throw new Error(msg || `Expected ${bs}, got ${as}`);
}
function extractOpenAIContentBlocks(msg) {
if (msg.content === null || msg.content === undefined) return '';
if (typeof msg.content === 'string') return msg.content;
if (Array.isArray(msg.content)) {
const blocks = [];
for (const p of msg.content) {
if ((p.type === 'text' || p.type === 'input_text') && p.text) {
blocks.push({ type: 'text', text: p.text });
} else if (p.type === 'image_url' && p.image_url?.url) {
blocks.push({
type: 'image',
source: { type: 'url', media_type: 'image/jpeg', data: p.image_url.url },
});
} else if (p.type === 'input_image' && p.image_url?.url) {
blocks.push({
type: 'image',
source: { type: 'url', media_type: 'image/jpeg', data: p.image_url.url },
});
}
}
return blocks.length > 0 ? blocks : '';
}
return String(msg.content);
}
function extractOpenAIContent(msg) {
const blocks = extractOpenAIContentBlocks(msg);
if (typeof blocks === 'string') return blocks;
return blocks.filter(b => b.type === 'text').map(b => b.text).join('\n');
}
function convertToAnthropicRequest(body) {
const rawMessages = [];
let systemPrompt;
for (const msg of body.messages) {
switch (msg.role) {
case 'system':
systemPrompt = (systemPrompt ? systemPrompt + '\n\n' : '') + extractOpenAIContent(msg);
break;
case 'user': {
const contentBlocks = extractOpenAIContentBlocks(msg);
rawMessages.push({
role: 'user',
content: Array.isArray(contentBlocks) ? contentBlocks : (contentBlocks || ''),
});
break;
}
}
}
return {
system: systemPrompt,
messages: rawMessages,
};
}
console.log('\n📦 [1] chat.completions input_text 兼容\n');
test('user input_text 不应丢失', () => {
const req = convertToAnthropicRequest({
model: 'gpt-4.1',
messages: [{
role: 'user',
content: [
{ type: 'input_text', text: '请描述这张图' },
{ type: 'input_image', image_url: { url: 'https://example.com/a.jpg' } },
],
}],
});
assertEqual(req.messages.length, 1);
assert(Array.isArray(req.messages[0].content), 'content should be block array');
assertEqual(req.messages[0].content[0], { type: 'text', text: '请描述这张图' });
assertEqual(req.messages[0].content[1].type, 'image');
});
test('system input_text 应拼接进 system prompt', () => {
const req = convertToAnthropicRequest({
model: 'gpt-4.1',
messages: [{
role: 'system',
content: [
{ type: 'input_text', text: '你是一个严谨的助手。' },
{ type: 'input_text', text: '请直接回答。' },
],
}, {
role: 'user',
content: 'hi',
}],
});
assertEqual(req.system, '你是一个严谨的助手。\n请直接回答。');
});
test('传统 text 块仍然兼容', () => {
const req = convertToAnthropicRequest({
model: 'gpt-4.1',
messages: [{
role: 'user',
content: [{ type: 'text', text: 'hello' }],
}],
});
assertEqual(req.messages[0].content[0], { type: 'text', text: 'hello' });
});
console.log('\n' + '═'.repeat(55));
console.log(` 结果: ${passed} 通过 / ${failed} 失败 / ${passed + failed} 总计`);
console.log('═'.repeat(55) + '\n');
if (failed > 0) process.exit(1);
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