import { describe, expect, it } from 'vitest'; import { ModelsService } from '$lib/services/models.service'; const { parseModelId } = ModelsService; describe('parseModelId', () => { it('handles unknown patterns correctly', () => { expect(parseModelId('model-name-1')).toStrictEqual({ activatedParams: null, modelName: 'model-name-1', orgName: null, params: null, quantization: null, raw: 'model-name-1', tags: [] }); expect(parseModelId('org/model-name-2')).toStrictEqual({ activatedParams: null, modelName: 'model-name-2', orgName: 'org', params: null, quantization: null, raw: 'org/model-name-2', tags: [] }); }); it('extracts model parameters correctly', () => { expect(parseModelId('model-100B-BF16')).toMatchObject({ params: '100B' }); expect(parseModelId('model-100B:Q4_K_M')).toMatchObject({ params: '100B' }); }); it('extracts model parameters correctly in lowercase', () => { expect(parseModelId('model-100b-bf16')).toMatchObject({ params: '100B' }); expect(parseModelId('model-100b:q4_k_m')).toMatchObject({ params: '100B' }); }); it('extracts activated parameters correctly', () => { expect(parseModelId('model-100B-A10B-BF16')).toMatchObject({ activatedParams: 'A10B' }); expect(parseModelId('model-100B-A10B:Q4_K_M')).toMatchObject({ activatedParams: 'A10B' }); }); it('extracts activated parameters correctly in lowercase', () => { expect(parseModelId('model-100b-a10b-bf16')).toMatchObject({ activatedParams: 'A10B' }); expect(parseModelId('model-100b-a10b:q4_k_m')).toMatchObject({ activatedParams: 'A10B' }); }); it('extracts quantization correctly', () => { // Dash-separated quantization expect(parseModelId('model-100B-UD-IQ1_S')).toMatchObject({ quantization: 'UD-IQ1_S' }); expect(parseModelId('model-100B-IQ4_XS')).toMatchObject({ quantization: 'IQ4_XS' }); expect(parseModelId('model-100B-Q4_K_M')).toMatchObject({ quantization: 'Q4_K_M' }); expect(parseModelId('model-100B-Q8_0')).toMatchObject({ quantization: 'Q8_0' }); expect(parseModelId('model-100B-UD-Q8_K_XL')).toMatchObject({ quantization: 'UD-Q8_K_XL' }); expect(parseModelId('model-100B-F16')).toMatchObject({ quantization: 'F16' }); expect(parseModelId('model-100B-BF16')).toMatchObject({ quantization: 'BF16' }); expect(parseModelId('model-100B-MXFP4')).toMatchObject({ quantization: 'MXFP4' }); // Colon-separated quantization expect(parseModelId('model-100B:UD-IQ1_S')).toMatchObject({ quantization: 'UD-IQ1_S' }); expect(parseModelId('model-100B:IQ4_XS')).toMatchObject({ quantization: 'IQ4_XS' }); expect(parseModelId('model-100B:Q4_K_M')).toMatchObject({ quantization: 'Q4_K_M' }); expect(parseModelId('model-100B:Q8_0')).toMatchObject({ quantization: 'Q8_0' }); expect(parseModelId('model-100B:UD-Q8_K_XL')).toMatchObject({ quantization: 'UD-Q8_K_XL' }); expect(parseModelId('model-100B:F16')).toMatchObject({ quantization: 'F16' }); expect(parseModelId('model-100B:BF16')).toMatchObject({ quantization: 'BF16' }); expect(parseModelId('model-100B:MXFP4')).toMatchObject({ quantization: 'MXFP4' }); // Dot-separated quantization expect(parseModelId('nomic-embed-text-v2-moe.Q4_K_M')).toMatchObject({ quantization: 'Q4_K_M' }); }); it('extracts additional tags correctly', () => { expect(parseModelId('model-100B-foobar-Q4_K_M')).toMatchObject({ tags: ['foobar'] }); expect(parseModelId('model-100B-A10B-foobar-1M-BF16')).toMatchObject({ tags: ['foobar', '1M'] }); expect(parseModelId('model-100B-1M-foobar:UD-Q8_K_XL')).toMatchObject({ tags: ['1M', 'foobar'] }); }); it('filters out container format segments from tags', () => { expect(parseModelId('model-100B-GGUF-Instruct-BF16')).toMatchObject({ tags: ['Instruct'] }); expect(parseModelId('model-100B-GGML-Instruct:Q4_K_M')).toMatchObject({ tags: ['Instruct'] }); }); it('handles real-world examples correctly', () => { expect(parseModelId('meta-llama/Llama-3.1-8B')).toStrictEqual({ activatedParams: null, modelName: 'Llama-3.1', orgName: 'meta-llama', params: '8B', quantization: null, raw: 'meta-llama/Llama-3.1-8B', tags: [] }); expect(parseModelId('openai/gpt-oss-120b-MXFP4')).toStrictEqual({ activatedParams: null, modelName: 'gpt-oss', orgName: 'openai', params: '120B', quantization: 'MXFP4', raw: 'openai/gpt-oss-120b-MXFP4', tags: [] }); expect(parseModelId('openai/gpt-oss-20b:Q4_K_M')).toStrictEqual({ activatedParams: null, modelName: 'gpt-oss', orgName: 'openai', params: '20B', quantization: 'Q4_K_M', raw: 'openai/gpt-oss-20b:Q4_K_M', tags: [] }); expect(parseModelId('Qwen/Qwen3-Coder-30B-A3B-Instruct-1M-BF16')).toStrictEqual({ activatedParams: 'A3B', modelName: 'Qwen3-Coder', orgName: 'Qwen', params: '30B', quantization: 'BF16', raw: 'Qwen/Qwen3-Coder-30B-A3B-Instruct-1M-BF16', tags: ['Instruct', '1M'] }); }); it('handles real-world examples with quantization in segments', () => { expect(parseModelId('meta-llama/Llama-4-Scout-17B-16E-Instruct-Q4_K_M')).toStrictEqual({ activatedParams: null, modelName: 'Llama-4-Scout', orgName: 'meta-llama', params: '17B', quantization: 'Q4_K_M', raw: 'meta-llama/Llama-4-Scout-17B-16E-Instruct-Q4_K_M', tags: ['16E', 'Instruct'] }); expect(parseModelId('MiniMaxAI/MiniMax-M2-IQ4_XS')).toStrictEqual({ activatedParams: null, modelName: 'MiniMax-M2', orgName: 'MiniMaxAI', params: null, quantization: 'IQ4_XS', raw: 'MiniMaxAI/MiniMax-M2-IQ4_XS', tags: [] }); expect(parseModelId('MiniMaxAI/MiniMax-M2-UD-Q3_K_XL')).toStrictEqual({ activatedParams: null, modelName: 'MiniMax-M2', orgName: 'MiniMaxAI', params: null, quantization: 'UD-Q3_K_XL', raw: 'MiniMaxAI/MiniMax-M2-UD-Q3_K_XL', tags: [] }); expect(parseModelId('mistralai/Devstral-2-123B-Instruct-2512-Q4_K_M')).toStrictEqual({ activatedParams: null, modelName: 'Devstral-2', orgName: 'mistralai', params: '123B', quantization: 'Q4_K_M', raw: 'mistralai/Devstral-2-123B-Instruct-2512-Q4_K_M', tags: ['Instruct', '2512'] }); expect(parseModelId('mistralai/Devstral-Small-2-24B-Instruct-2512-Q8_0')).toStrictEqual({ activatedParams: null, modelName: 'Devstral-Small-2', orgName: 'mistralai', params: '24B', quantization: 'Q8_0', raw: 'mistralai/Devstral-Small-2-24B-Instruct-2512-Q8_0', tags: ['Instruct', '2512'] }); expect(parseModelId('noctrex/GLM-4.7-Flash-MXFP4_MOE')).toStrictEqual({ activatedParams: null, modelName: 'GLM-4.7-Flash', orgName: 'noctrex', params: null, quantization: 'MXFP4_MOE', raw: 'noctrex/GLM-4.7-Flash-MXFP4_MOE', tags: [] }); expect(parseModelId('Qwen/Qwen3-Coder-Next-Q4_K_M')).toStrictEqual({ activatedParams: null, modelName: 'Qwen3-Coder-Next', orgName: 'Qwen', params: null, quantization: 'Q4_K_M', raw: 'Qwen/Qwen3-Coder-Next-Q4_K_M', tags: [] }); expect(parseModelId('openai/gpt-oss-120b-Q4_K_M')).toStrictEqual({ activatedParams: null, modelName: 'gpt-oss', orgName: 'openai', params: '120B', quantization: 'Q4_K_M', raw: 'openai/gpt-oss-120b-Q4_K_M', tags: [] }); expect(parseModelId('openai/gpt-oss-20b-F16')).toStrictEqual({ activatedParams: null, modelName: 'gpt-oss', orgName: 'openai', params: '20B', quantization: 'F16', raw: 'openai/gpt-oss-20b-F16', tags: [] }); expect(parseModelId('nomic-embed-text-v2-moe.Q4_K_M')).toStrictEqual({ activatedParams: null, modelName: 'nomic-embed-text-v2-moe', orgName: null, params: null, quantization: 'Q4_K_M', raw: 'nomic-embed-text-v2-moe.Q4_K_M', tags: [] }); }); it('handles ambiguous model names', () => { // Qwen3.5 Instruct vs Thinking — tags should distinguish them expect(parseModelId('Qwen/Qwen3.5-30B-A3B-Instruct')).toMatchObject({ modelName: 'Qwen3.5', params: '30B', activatedParams: 'A3B', tags: ['Instruct'] }); expect(parseModelId('Qwen/Qwen3.5-30B-A3B-Thinking')).toMatchObject({ modelName: 'Qwen3.5', params: '30B', activatedParams: 'A3B', tags: ['Thinking'] }); // Dot-separated quantization with variant suffixes expect(parseModelId('gemma-3-27b-it-heretic-v2.Q8_0')).toMatchObject({ modelName: 'gemma-3', params: '27B', quantization: 'Q8_0', tags: ['it', 'heretic', 'v2'] }); expect(parseModelId('gemma-3-27b-it.Q8_0')).toMatchObject({ modelName: 'gemma-3', params: '27B', quantization: 'Q8_0', tags: ['it'] }); }); });