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| 1 | +import { describe, it, expect } from "vitest" |
| 2 | +import { |
| 3 | + getModelDimension, |
| 4 | + getModelScoreThreshold, |
| 5 | + getModelQueryPrefix, |
| 6 | + getDefaultModelId, |
| 7 | + EMBEDDING_MODEL_PROFILES, |
| 8 | +} from "../embeddingModels" |
| 9 | + |
| 10 | +describe("embeddingModels", () => { |
| 11 | + describe("getModelDimension", () => { |
| 12 | + it("should return the correct dimension for a valid model", () => { |
| 13 | + expect(getModelDimension("openai", "text-embedding-3-small")).toBe(1536) |
| 14 | + expect(getModelDimension("openai", "text-embedding-3-large")).toBe(3072) |
| 15 | + expect(getModelDimension("openrouter", "qwen/qwen3-embedding-8b")).toBe(4096) |
| 16 | + }) |
| 17 | + |
| 18 | + it("should be case-insensitive for model IDs", () => { |
| 19 | + // Test with different case variations |
| 20 | + expect(getModelDimension("openai", "TEXT-EMBEDDING-3-SMALL")).toBe(1536) |
| 21 | + expect(getModelDimension("openai", "Text-Embedding-3-Large")).toBe(3072) |
| 22 | + expect(getModelDimension("openrouter", "Qwen/Qwen3-Embedding-8B")).toBe(4096) |
| 23 | + expect(getModelDimension("openrouter", "QWEN/QWEN3-EMBEDDING-8B")).toBe(4096) |
| 24 | + |
| 25 | + // Test with mixed case for other providers |
| 26 | + expect(getModelDimension("gemini", "TEXT-EMBEDDING-004")).toBe(768) |
| 27 | + expect(getModelDimension("mistral", "CODESTRAL-EMBED-2505")).toBe(1536) |
| 28 | + }) |
| 29 | + |
| 30 | + it("should return undefined for non-existent model", () => { |
| 31 | + expect(getModelDimension("openai", "non-existent-model")).toBeUndefined() |
| 32 | + }) |
| 33 | + |
| 34 | + it("should return undefined for non-existent provider", () => { |
| 35 | + // @ts-expect-error Testing with invalid provider |
| 36 | + expect(getModelDimension("non-existent-provider", "text-embedding-3-small")).toBeUndefined() |
| 37 | + }) |
| 38 | + |
| 39 | + it("should handle lowercase model IDs that exist in profiles", () => { |
| 40 | + expect(getModelDimension("openai", "text-embedding-ada-002")).toBe(1536) |
| 41 | + expect(getModelDimension("ollama", "nomic-embed-text")).toBe(768) |
| 42 | + }) |
| 43 | + }) |
| 44 | + |
| 45 | + describe("getModelScoreThreshold", () => { |
| 46 | + it("should return the correct score threshold for a valid model", () => { |
| 47 | + expect(getModelScoreThreshold("openai", "text-embedding-3-small")).toBe(0.4) |
| 48 | + expect(getModelScoreThreshold("ollama", "nomic-embed-code")).toBe(0.15) |
| 49 | + expect(getModelScoreThreshold("openrouter", "qwen/qwen3-embedding-8b")).toBe(0.4) |
| 50 | + }) |
| 51 | + |
| 52 | + it("should be case-insensitive for model IDs", () => { |
| 53 | + // Test with different case variations |
| 54 | + expect(getModelScoreThreshold("openai", "TEXT-EMBEDDING-3-SMALL")).toBe(0.4) |
| 55 | + expect(getModelScoreThreshold("ollama", "NOMIC-EMBED-CODE")).toBe(0.15) |
| 56 | + expect(getModelScoreThreshold("openrouter", "Qwen/Qwen3-Embedding-8B")).toBe(0.4) |
| 57 | + |
| 58 | + // Test models without score thresholds |
| 59 | + expect(getModelScoreThreshold("gemini", "TEXT-EMBEDDING-004")).toBeUndefined() |
| 60 | + }) |
| 61 | + |
| 62 | + it("should return undefined for model without score threshold", () => { |
| 63 | + expect(getModelScoreThreshold("gemini", "text-embedding-004")).toBeUndefined() |
| 64 | + }) |
| 65 | + |
| 66 | + it("should return undefined for non-existent model", () => { |
| 67 | + expect(getModelScoreThreshold("openai", "non-existent-model")).toBeUndefined() |
| 68 | + }) |
| 69 | + |
| 70 | + it("should return undefined for non-existent provider", () => { |
| 71 | + // @ts-expect-error Testing with invalid provider |
| 72 | + expect(getModelScoreThreshold("non-existent-provider", "text-embedding-3-small")).toBeUndefined() |
| 73 | + }) |
| 74 | + }) |
| 75 | + |
| 76 | + describe("getModelQueryPrefix", () => { |
| 77 | + it("should return the correct query prefix for a model that has one", () => { |
| 78 | + expect(getModelQueryPrefix("ollama", "nomic-embed-code")).toBe( |
| 79 | + "Represent this query for searching relevant code: ", |
| 80 | + ) |
| 81 | + }) |
| 82 | + |
| 83 | + it("should be case-insensitive for model IDs", () => { |
| 84 | + // Test with different case variations |
| 85 | + expect(getModelQueryPrefix("ollama", "NOMIC-EMBED-CODE")).toBe( |
| 86 | + "Represent this query for searching relevant code: ", |
| 87 | + ) |
| 88 | + expect(getModelQueryPrefix("ollama", "Nomic-Embed-Code")).toBe( |
| 89 | + "Represent this query for searching relevant code: ", |
| 90 | + ) |
| 91 | + expect(getModelQueryPrefix("openai-compatible", "NOMIC-EMBED-CODE")).toBe( |
| 92 | + "Represent this query for searching relevant code: ", |
| 93 | + ) |
| 94 | + }) |
| 95 | + |
| 96 | + it("should return undefined for model without query prefix", () => { |
| 97 | + expect(getModelQueryPrefix("openai", "text-embedding-3-small")).toBeUndefined() |
| 98 | + expect(getModelQueryPrefix("gemini", "text-embedding-004")).toBeUndefined() |
| 99 | + }) |
| 100 | + |
| 101 | + it("should return undefined for non-existent model", () => { |
| 102 | + expect(getModelQueryPrefix("ollama", "non-existent-model")).toBeUndefined() |
| 103 | + }) |
| 104 | + |
| 105 | + it("should return undefined for non-existent provider", () => { |
| 106 | + // @ts-expect-error Testing with invalid provider |
| 107 | + expect(getModelQueryPrefix("non-existent-provider", "nomic-embed-code")).toBeUndefined() |
| 108 | + }) |
| 109 | + }) |
| 110 | + |
| 111 | + describe("getDefaultModelId", () => { |
| 112 | + it("should return the correct default model for each provider", () => { |
| 113 | + expect(getDefaultModelId("openai")).toBe("text-embedding-3-small") |
| 114 | + expect(getDefaultModelId("openai-compatible")).toBe("text-embedding-3-small") |
| 115 | + expect(getDefaultModelId("gemini")).toBe("gemini-embedding-001") |
| 116 | + expect(getDefaultModelId("mistral")).toBe("codestral-embed-2505") |
| 117 | + expect(getDefaultModelId("vercel-ai-gateway")).toBe("openai/text-embedding-3-large") |
| 118 | + expect(getDefaultModelId("openrouter")).toBe("openai/text-embedding-3-large") |
| 119 | + }) |
| 120 | + |
| 121 | + it("should return a default for Ollama", () => { |
| 122 | + const defaultModel = getDefaultModelId("ollama") |
| 123 | + expect(defaultModel).toBeDefined() |
| 124 | + expect(EMBEDDING_MODEL_PROFILES.ollama?.[defaultModel]).toBeDefined() |
| 125 | + }) |
| 126 | + |
| 127 | + it("should return fallback for unknown provider", () => { |
| 128 | + // @ts-expect-error Testing with invalid provider |
| 129 | + expect(getDefaultModelId("unknown-provider")).toBe("text-embedding-3-small") |
| 130 | + }) |
| 131 | + }) |
| 132 | + |
| 133 | + describe("Qwen model specific tests", () => { |
| 134 | + it("should handle Qwen model with original casing", () => { |
| 135 | + expect(getModelDimension("openrouter", "qwen/qwen3-embedding-8b")).toBe(4096) |
| 136 | + expect(getModelScoreThreshold("openrouter", "qwen/qwen3-embedding-8b")).toBe(0.4) |
| 137 | + }) |
| 138 | + |
| 139 | + it("should handle Qwen model with user's casing from issue", () => { |
| 140 | + // This is the exact casing from the user's issue |
| 141 | + expect(getModelDimension("openrouter", "Qwen/Qwen3-Embedding-8B")).toBe(4096) |
| 142 | + expect(getModelScoreThreshold("openrouter", "Qwen/Qwen3-Embedding-8B")).toBe(0.4) |
| 143 | + }) |
| 144 | + |
| 145 | + it("should handle Qwen model with all uppercase", () => { |
| 146 | + expect(getModelDimension("openrouter", "QWEN/QWEN3-EMBEDDING-8B")).toBe(4096) |
| 147 | + expect(getModelScoreThreshold("openrouter", "QWEN/QWEN3-EMBEDDING-8B")).toBe(0.4) |
| 148 | + }) |
| 149 | + |
| 150 | + it("should handle Qwen model with random casing", () => { |
| 151 | + expect(getModelDimension("openrouter", "qWeN/QwEn3-EmBeDdInG-8b")).toBe(4096) |
| 152 | + expect(getModelScoreThreshold("openrouter", "qWeN/QwEn3-EmBeDdInG-8b")).toBe(0.4) |
| 153 | + }) |
| 154 | + }) |
| 155 | +}) |
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