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fix: correct Gemini embedding model dimensions #7349

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fix: correct Gemini embedding model dimensions #7349

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44302b0
fix: correct Gemini embedding model dimensions
roomote Aug 23, 2025
32fc3d6
fix: correct gemini-embedding-001 dimension from 768 to 3072
roomote Aug 23, 2025
5d27110
fix: correct buffer handling for base64 embedding decoding
roomote Aug 23, 2025
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8 changes: 4 additions & 4 deletions src/services/code-index/__tests__/service-factory.spec.ts
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Original file line number Diff line number Diff line change
Expand Up @@ -566,7 +566,7 @@ describe("CodeIndexServiceFactory", () => {
qdrantApiKey: "test-key",
}
mockConfigManager.getConfig.mockReturnValue(testConfig as any)
mockGetModelDimension.mockReturnValue(3072)
mockGetModelDimension.mockReturnValue(768)
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@roomote roomote bot Aug 23, 2025

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These test changes assume 768 dimensions for gemini-embedding-001, but this appears to be incorrect based on the issue reporter's feedback. The tests were correctly expecting 3072 dimensions before.

Changing tests to match incorrect assumptions could mask the real issue and make it harder to detect problems in the future.


// Act
factory.createVectorStore()
Expand All @@ -576,7 +576,7 @@ describe("CodeIndexServiceFactory", () => {
expect(MockedQdrantVectorStore).toHaveBeenCalledWith(
"/test/workspace",
"http://localhost:6333",
3072,
768,
"test-key",
)
})
Expand All @@ -590,7 +590,7 @@ describe("CodeIndexServiceFactory", () => {
}
mockConfigManager.getConfig.mockReturnValue(testConfig as any)
mockGetDefaultModelId.mockReturnValue("gemini-embedding-001")
mockGetModelDimension.mockReturnValue(3072)
mockGetModelDimension.mockReturnValue(768)

// Act
factory.createVectorStore()
Expand All @@ -601,7 +601,7 @@ describe("CodeIndexServiceFactory", () => {
expect(MockedQdrantVectorStore).toHaveBeenCalledWith(
"/test/workspace",
"http://localhost:6333",
3072,
768,
"test-key",
)
})
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2 changes: 1 addition & 1 deletion src/services/code-index/embedders/gemini.ts
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Original file line number Diff line number Diff line change
Expand Up @@ -11,7 +11,7 @@ import { TelemetryService } from "@roo-code/telemetry"
*
* Supported models:
* - text-embedding-004 (dimension: 768)
* - gemini-embedding-001 (dimension: 2048)
* - gemini-embedding-001 (dimension: 3072)
*/
export class GeminiEmbedder implements IEmbedder {
private readonly openAICompatibleEmbedder: OpenAICompatibleEmbedder
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11 changes: 9 additions & 2 deletions src/services/code-index/embedders/openai-compatible.ts
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Original file line number Diff line number Diff line change
Expand Up @@ -278,8 +278,15 @@ export class OpenAICompatibleEmbedder implements IEmbedder {
if (typeof item.embedding === "string") {
const buffer = Buffer.from(item.embedding, "base64")

// Create Float32Array view over the buffer
const float32Array = new Float32Array(buffer.buffer, buffer.byteOffset, buffer.byteLength / 4)
// Safe approach: Create Float32Array from a properly aligned copy
// This avoids issues with Node.js Buffers that may be views into larger ArrayBuffers
const float32Array = new Float32Array(buffer.length / 4)
const dataView = new DataView(buffer.buffer, buffer.byteOffset, buffer.byteLength)

// Read floats with proper byte order handling (little-endian)
for (let i = 0; i < float32Array.length; i++) {
float32Array[i] = dataView.getFloat32(i * 4, true)
}

return {
...item,
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