fix: support full endpoint URLs in OpenAI Compatible provider (#5212) (#5214)

Co-authored-by: Matt Rubens <[email protected]>

Author: SannidhyaSah

src/services/code-index/embedders/__tests__/openai-compatible.spec.ts

@@ -6,6 +6,9 @@ import { MAX_ITEM_TOKENS, INITIAL_RETRY_DELAY_MS } from "../../constants"
 // Mock the OpenAI SDK
 vitest.mock("openai")
 
+// Mock global fetch
+global.fetch = vitest.fn()
+
 // Mock i18n
 vitest.mock("../../../../i18n", () => ({
 	t: (key: string, params?: Record<string, any>) => {
@@ -613,5 +616,270 @@ describe("OpenAICompatibleEmbedder", () => {
 				expect(returnedArray).toEqual([0.25, 0.5, 0.75, 1.0])
 			})
 		})
+
+		/**
+		 * Test Azure OpenAI compatibility with helper functions for conciseness
+		 */
+		describe("Azure OpenAI compatibility", () => {
+			const azureUrl =
+				"https://myresource.openai.azure.com/openai/deployments/mymodel/embeddings?api-version=2024-02-01"
+			const baseUrl = "https://api.openai.com/v1"
+
+			// Helper to create mock fetch response
+			const createMockResponse = (data: any, status = 200, ok = true) => ({
+				ok,
+				status,
+				json: vitest.fn().mockResolvedValue(data),
+				text: vitest.fn().mockResolvedValue(status === 200 ? "" : "Error message"),
+			})
+
+			// Helper to create base64 embedding
+			const createBase64Embedding = (values: number[]) => {
+				const embedding = new Float32Array(values)
+				return Buffer.from(embedding.buffer).toString("base64")
+			}
+
+			// Helper to verify embedding values with floating-point tolerance
+			const expectEmbeddingValues = (actual: number[], expected: number[]) => {
+				expect(actual).toHaveLength(expected.length)
+				expected.forEach((val, i) => expect(actual[i]).toBeCloseTo(val, 5))
+			}
+
+			beforeEach(() => {
+				vitest.clearAllMocks()
+				;(global.fetch as MockedFunction<typeof fetch>).mockReset()
+			})
+
+			describe("URL detection", () => {
+				it.each([
+					[
+						"https://myresource.openai.azure.com/openai/deployments/mymodel/embeddings?api-version=2024-02-01",
+						true,
+					],
+					["https://myresource.openai.azure.com/openai/deployments/text-embedding-ada-002/embeddings", true],
+					["https://api.openai.com/v1", false],
+					["https://api.example.com", false],
+					["http://localhost:8080", false],
+				])("should detect URL type correctly: %s -> %s", (url, expected) => {
+					const embedder = new OpenAICompatibleEmbedder(url, testApiKey, testModelId)
+					const isFullUrl = (embedder as any).isFullEndpointUrl(url)
+					expect(isFullUrl).toBe(expected)
+				})
+
+				// Edge cases where 'embeddings' or 'deployments' appear in non-endpoint contexts
+				it("should return false for URLs with 'embeddings' in non-endpoint contexts", () => {
+					const testUrls = [
+						"https://api.example.com/embeddings-service/v1",
+						"https://embeddings.example.com/api",
+						"https://api.example.com/v1/embeddings-api",
+						"https://my-embeddings-provider.com/v1",
+					]
+
+					testUrls.forEach((url) => {
+						const embedder = new OpenAICompatibleEmbedder(url, testApiKey, testModelId)
+						const isFullUrl = (embedder as any).isFullEndpointUrl(url)
+						expect(isFullUrl).toBe(false)
+					})
+				})
+
+				it("should return false for URLs with 'deployments' in non-endpoint contexts", () => {
+					const testUrls = [
+						"https://deployments.example.com/api",
+						"https://api.deployments.com/v1",
+						"https://my-deployments-service.com/api/v1",
+						"https://deployments-manager.example.com",
+					]
+
+					testUrls.forEach((url) => {
+						const embedder = new OpenAICompatibleEmbedder(url, testApiKey, testModelId)
+						const isFullUrl = (embedder as any).isFullEndpointUrl(url)
+						expect(isFullUrl).toBe(false)
+					})
+				})
+
+				it("should correctly identify actual endpoint URLs", () => {
+					const endpointUrls = [
+						"https://api.example.com/v1/embeddings",
+						"https://api.example.com/v1/embeddings?api-version=2024",
+						"https://myresource.openai.azure.com/openai/deployments/mymodel/embeddings",
+						"https://api.example.com/embed",
+						"https://api.example.com/embed?version=1",
+					]
+
+					endpointUrls.forEach((url) => {
+						const embedder = new OpenAICompatibleEmbedder(url, testApiKey, testModelId)
+						const isFullUrl = (embedder as any).isFullEndpointUrl(url)
+						expect(isFullUrl).toBe(true)
+					})
+				})
+			})
+
+			describe("direct HTTP requests", () => {
+				it("should use direct fetch for Azure URLs and SDK for base URLs", async () => {
+					const testTexts = ["Test text"]
+					const base64String = createBase64Embedding([0.1, 0.2, 0.3])
+
+					// Test Azure URL (direct fetch)
+					const azureEmbedder = new OpenAICompatibleEmbedder(azureUrl, testApiKey, testModelId)
+					const mockFetchResponse = createMockResponse({
+						data: [{ embedding: base64String }],
+						usage: { prompt_tokens: 10, total_tokens: 15 },
+					})
+					;(global.fetch as MockedFunction<typeof fetch>).mockResolvedValue(mockFetchResponse as any)
+
+					const azureResult = await azureEmbedder.createEmbeddings(testTexts)
+					expect(global.fetch).toHaveBeenCalledWith(
+						azureUrl,
+						expect.objectContaining({
+							method: "POST",
+							headers: expect.objectContaining({
+								"api-key": testApiKey,
+								Authorization: `Bearer ${testApiKey}`,
+							}),
+						}),
+					)
+					expect(mockEmbeddingsCreate).not.toHaveBeenCalled()
+					expectEmbeddingValues(azureResult.embeddings[0], [0.1, 0.2, 0.3])
+
+					// Reset and test base URL (SDK)
+					vitest.clearAllMocks()
+					const baseEmbedder = new OpenAICompatibleEmbedder(baseUrl, testApiKey, testModelId)
+					mockEmbeddingsCreate.mockResolvedValue({
+						data: [{ embedding: [0.4, 0.5, 0.6] }],
+						usage: { prompt_tokens: 10, total_tokens: 15 },
+					})
+
+					const baseResult = await baseEmbedder.createEmbeddings(testTexts)
+					expect(mockEmbeddingsCreate).toHaveBeenCalled()
+					expect(global.fetch).not.toHaveBeenCalled()
+					expect(baseResult.embeddings[0]).toEqual([0.4, 0.5, 0.6])
+				})
+
+				it.each([
+					[401, "Authentication failed. Please check your API key."],
+					[500, "Failed to create embeddings after 3 attempts"],
+				])("should handle HTTP errors: %d", async (status, expectedMessage) => {
+					const embedder = new OpenAICompatibleEmbedder(azureUrl, testApiKey, testModelId)
+					const mockResponse = createMockResponse({}, status, false)
+					;(global.fetch as MockedFunction<typeof fetch>).mockResolvedValue(mockResponse as any)
+
+					await expect(embedder.createEmbeddings(["test"])).rejects.toThrow(expectedMessage)
+				})
+
+				it("should handle rate limiting with retries", async () => {
+					vitest.useFakeTimers()
+					const embedder = new OpenAICompatibleEmbedder(azureUrl, testApiKey, testModelId)
+					const base64String = createBase64Embedding([0.1, 0.2, 0.3])
+
+					;(global.fetch as MockedFunction<typeof fetch>)
+						.mockResolvedValueOnce(createMockResponse({}, 429, false) as any)
+						.mockResolvedValueOnce(createMockResponse({}, 429, false) as any)
+						.mockResolvedValueOnce(
+							createMockResponse({
+								data: [{ embedding: base64String }],
+								usage: { prompt_tokens: 10, total_tokens: 15 },
+							}) as any,
+						)
+
+					const resultPromise = embedder.createEmbeddings(["test"])
+					await vitest.advanceTimersByTimeAsync(INITIAL_RETRY_DELAY_MS * 3)
+					const result = await resultPromise
+
+					expect(global.fetch).toHaveBeenCalledTimes(3)
+					expect(console.warn).toHaveBeenCalledWith(expect.stringContaining("Rate limit hit"))
+					expectEmbeddingValues(result.embeddings[0], [0.1, 0.2, 0.3])
+					vitest.useRealTimers()
+				})
+
+				it("should handle multiple embeddings and network errors", async () => {
+					const embedder = new OpenAICompatibleEmbedder(azureUrl, testApiKey, testModelId)
+
+					// Test multiple embeddings
+					const base64_1 = createBase64Embedding([0.25, 0.5])
+					const base64_2 = createBase64Embedding([0.75, 1.0])
+					const mockResponse = createMockResponse({
+						data: [{ embedding: base64_1 }, { embedding: base64_2 }],
+						usage: { prompt_tokens: 20, total_tokens: 30 },
+					})
+					;(global.fetch as MockedFunction<typeof fetch>).mockResolvedValue(mockResponse as any)
+
+					const result = await embedder.createEmbeddings(["test1", "test2"])
+					expect(result.embeddings).toHaveLength(2)
+					expectEmbeddingValues(result.embeddings[0], [0.25, 0.5])
+					expectEmbeddingValues(result.embeddings[1], [0.75, 1.0])
+
+					// Test network error
+					const networkError = new Error("Network failed")
+					;(global.fetch as MockedFunction<typeof fetch>).mockRejectedValue(networkError)
+					await expect(embedder.createEmbeddings(["test"])).rejects.toThrow(
+						"Failed to create embeddings after 3 attempts",
+					)
+				})
+			})
+		})
+	})
+
+	describe("URL detection", () => {
+		it("should detect Azure deployment URLs as full endpoints", async () => {
+			const embedder = new OpenAICompatibleEmbedder(
+				"https://myinstance.openai.azure.com/openai/deployments/my-deployment/embeddings?api-version=2023-05-15",
+				"test-key",
+			)
+
+			// The private method is tested indirectly through the createEmbeddings behavior
+			// If it's detected as a full URL, it will make a direct HTTP request
+			const mockFetch = vitest.fn().mockResolvedValue({
+				ok: true,
+				json: async () => ({
+					data: [{ embedding: [0.1, 0.2] }],
+					usage: { prompt_tokens: 10, total_tokens: 15 },
+				}),
+			})
+			global.fetch = mockFetch
+
+			await embedder.createEmbeddings(["test"])
+
+			// Should make direct HTTP request to the full URL
+			expect(mockFetch).toHaveBeenCalledWith(
+				"https://myinstance.openai.azure.com/openai/deployments/my-deployment/embeddings?api-version=2023-05-15",
+				expect.any(Object),
+			)
+		})
+
+		it("should detect /embed endpoints as full URLs", async () => {
+			const embedder = new OpenAICompatibleEmbedder("https://api.example.com/v1/embed", "test-key")
+
+			const mockFetch = vitest.fn().mockResolvedValue({
+				ok: true,
+				json: async () => ({
+					data: [{ embedding: [0.1, 0.2] }],
+					usage: { prompt_tokens: 10, total_tokens: 15 },
+				}),
+			})
+			global.fetch = mockFetch
+
+			await embedder.createEmbeddings(["test"])
+
+			// Should make direct HTTP request to the full URL
+			expect(mockFetch).toHaveBeenCalledWith("https://api.example.com/v1/embed", expect.any(Object))
+		})
+
+		it("should treat base URLs without endpoint patterns as SDK URLs", async () => {
+			const embedder = new OpenAICompatibleEmbedder("https://api.openai.com/v1", "test-key")
+
+			// Mock the OpenAI SDK's embeddings.create method
+			const mockCreate = vitest.fn().mockResolvedValue({
+				data: [{ embedding: [0.1, 0.2] }],
+				usage: { prompt_tokens: 10, total_tokens: 15 },
+			})
+			embedder["embeddingsClient"].embeddings = {
+				create: mockCreate,
+			} as any
+
+			await embedder.createEmbeddings(["test"])
+
+			// Should use SDK which will append /embeddings
+			expect(mockCreate).toHaveBeenCalled()
+		})
 	})
 })