How to Test Responses from OpenAI in n8n Without Re-Running the Whole Workflow

1// Code node: LLM response test fixtures
2// Use this node to simulate different OpenAI response scenarios
3// without making real API calls
4
5// Set the test case to simulate:
6// 'normal', 'empty', 'truncated', 'malformed_json', 'error', 'long'
7const testCase = 'normal';
8
9const fixtures = {
10  normal: {
11    message: {
12      role: 'assistant',
13      content: 'Based on the data provided, the top three recommendations are: 1) Increase the batch size to 50, 2) Enable caching on the API gateway, 3) Add retry logic for transient failures.'
14    },
15    finish_reason: 'stop',
16    usage: { prompt_tokens: 200, completion_tokens: 45, total_tokens: 245 }
17  },
18  empty: {
19    message: { role: 'assistant', content: '' },
20    finish_reason: 'stop',
21    usage: { prompt_tokens: 200, completion_tokens: 0, total_tokens: 200 }
22  },
23  truncated: {
24    message: {
25      role: 'assistant',
26      content: 'The analysis shows that performance degrades significantly when the input exceeds'
27    },
28    finish_reason: 'length',
29    usage: { prompt_tokens: 200, completion_tokens: 4096, total_tokens: 4296 }
30  },
31  malformed_json: {
32    message: {
33      role: 'assistant',
34      content: '{"result": "success", "items": [{"id": 1, "name":'
35    },
36    finish_reason: 'stop',
37    usage: { prompt_tokens: 200, completion_tokens: 30, total_tokens: 230 }
38  },
39  error: {
40    error: { message: 'Rate limit exceeded', type: 'rate_limit_error', code: 429 }
41  },
42  long: {
43    message: {
44      role: 'assistant',
45      content: 'A'.repeat(10000)
46    },
47    finish_reason: 'stop',
48    usage: { prompt_tokens: 200, completion_tokens: 3000, total_tokens: 3200 }
49  }
50};
51
52const output = fixtures[testCase];
53if (!output) throw new Error(`Unknown test case: ${testCase}`);
54
55return [{ json: output }];