fix: add fallback to OpenAI-compatible API for LM Studio model detection

- Modified getLMStudioModels to fall back to /v1/models endpoint when SDK methods fail
- This fixes the issue where models like openai/gpt-oss-20b were not being detected
- Added comprehensive test coverage for the fallback behavior
- Fixes #6766

src/api/providers/fetchers/__tests__/lmstudio.test.ts

@@ -212,11 +212,12 @@ describe("LMStudio Fetcher", () => {
 			consoleInfoSpy.mockRestore()
 		})
 
-		it("should return an empty object and log error if listDownloadedModels fails", async () => {
-			const consoleErrorSpy = vi.spyOn(console, "error").mockImplementation(() => {})
+		it("should return an empty object and log warning if listLoaded fails", async () => {
+			const consoleWarnSpy = vi.spyOn(console, "warn").mockImplementation(() => {})
 			const listError = new Error("LMStudio SDK internal error")
 
 			mockedAxios.get.mockResolvedValueOnce({ data: {} })
+			mockListDownloadedModels.mockRejectedValueOnce(new Error("Failed to list downloaded"))
 			mockListLoaded.mockRejectedValueOnce(listError)
 
 			const result = await getLMStudioModels(baseUrl)
@@ -225,11 +226,86 @@ describe("LMStudio Fetcher", () => {
 			expect(MockedLMStudioClientConstructor).toHaveBeenCalledTimes(1)
 			expect(MockedLMStudioClientConstructor).toHaveBeenCalledWith({ baseUrl: lmsUrl })
 			expect(mockListLoaded).toHaveBeenCalledTimes(1)
-			expect(consoleErrorSpy).toHaveBeenCalledWith(
-				`Error fetching LMStudio models: ${JSON.stringify(listError, Object.getOwnPropertyNames(listError), 2)}`,
+			// Now it should log a warning for failed SDK methods, not an error
+			expect(consoleWarnSpy).toHaveBeenCalledWith(
+				"Failed to list downloaded models, falling back to loaded models only",
 			)
+			expect(consoleWarnSpy).toHaveBeenCalledWith("Failed to list loaded models via SDK")
 			expect(result).toEqual({})
-			consoleErrorSpy.mockRestore()
+			consoleWarnSpy.mockRestore()
+		})
+
+		it("should fall back to OpenAI API models when SDK methods fail", async () => {
+			const consoleLogSpy = vi.spyOn(console, "log").mockImplementation(() => {})
+			const consoleWarnSpy = vi.spyOn(console, "warn").mockImplementation(() => {})
+
+			// Mock OpenAI API response with models
+			const openAiModels = {
+				data: [
+					{ id: "openai/gpt-oss-20b", object: "model", owned_by: "organization_owner" },
+					{ id: "unsloth/gpt-oss-20b", object: "model", owned_by: "organization_owner" },
+					{ id: "qwen/qwen3-coder-30b", object: "model", owned_by: "organization_owner" },
+				],
+				object: "list",
+			}
+
+			mockedAxios.get.mockResolvedValueOnce({ data: openAiModels })
+
+			// Make SDK methods fail
+			mockListDownloadedModels.mockRejectedValueOnce(new Error("SDK not available"))
+			mockListLoaded.mockRejectedValueOnce(new Error("SDK not available"))
+
+			const result = await getLMStudioModels(baseUrl)
+
+			// Should have called the OpenAI endpoint
+			expect(mockedAxios.get).toHaveBeenCalledWith(`${baseUrl}/v1/models`)
+
+			// Should have tried SDK methods
+			expect(MockedLMStudioClientConstructor).toHaveBeenCalledWith({ baseUrl: lmsUrl })
+			expect(mockListDownloadedModels).toHaveBeenCalled()
+			expect(mockListLoaded).toHaveBeenCalled()
+
+			// Should have logged the fallback
+			expect(consoleLogSpy).toHaveBeenCalledWith("Falling back to OpenAI-compatible API models")
+
+			// Should return models from OpenAI API
+			expect(Object.keys(result)).toHaveLength(3)
+			expect(result["openai/gpt-oss-20b"]).toBeDefined()
+			expect(result["openai/gpt-oss-20b"].description).toBe("openai/gpt-oss-20b")
+			expect(result["unsloth/gpt-oss-20b"]).toBeDefined()
+			expect(result["qwen/qwen3-coder-30b"]).toBeDefined()
+
+			consoleLogSpy.mockRestore()
+			consoleWarnSpy.mockRestore()
+		})
+
+		it("should not use OpenAI API fallback if SDK returns models", async () => {
+			const consoleLogSpy = vi.spyOn(console, "log").mockImplementation(() => {})
+
+			// Mock OpenAI API response with models
+			const openAiModels = {
+				data: [{ id: "openai/gpt-oss-20b", object: "model", owned_by: "organization_owner" }],
+				object: "list",
+			}
+
+			mockedAxios.get.mockResolvedValueOnce({ data: openAiModels })
+
+			// SDK returns models successfully
+			mockListDownloadedModels.mockResolvedValueOnce([])
+			mockListLoaded.mockResolvedValueOnce([{ getModelInfo: mockGetModelInfo }])
+			mockGetModelInfo.mockResolvedValueOnce(mockRawModel)
+
+			const result = await getLMStudioModels(baseUrl)
+
+			// Should NOT log the fallback message
+			expect(consoleLogSpy).not.toHaveBeenCalledWith("Falling back to OpenAI-compatible API models")
+
+			// Should return SDK models, not OpenAI API models
+			expect(Object.keys(result)).toHaveLength(1)
+			expect(result[mockRawModel.modelKey]).toBeDefined()
+			expect(result["openai/gpt-oss-20b"]).toBeUndefined()
+
+			consoleLogSpy.mockRestore()
 		})
 	})
 })

src/api/providers/fetchers/lmstudio.ts

@@ -65,9 +65,9 @@ export async function getLMStudioModels(baseUrl = "http://localhost:1234"): Prom
 			return models
 		}
 
-		// test the connection to LM Studio first
+		// test the connection to LM Studio first and get models from OpenAI-compatible endpoint
 		// errors will be caught further down
-		await axios.get(`${baseUrl}/v1/models`)
+		const openAiModelsResponse = await axios.get(`${baseUrl}/v1/models`)
 
 		const client = new LMStudioClient({ baseUrl: lmsUrl })
 
@@ -82,13 +82,37 @@ export async function getLMStudioModels(baseUrl = "http://localhost:1234"): Prom
 			console.warn("Failed to list downloaded models, falling back to loaded models only")
 		}
 		// We want to list loaded models *anyway* since they provide valuable extra info (context size)
-		const loadedModels = (await client.llm.listLoaded().then((models: LLM[]) => {
-			return Promise.all(models.map((m) => m.getModelInfo()))
-		})) as Array<LLMInstanceInfo>
+		try {
+			const loadedModels = (await client.llm.listLoaded().then((models: LLM[]) => {
+				return Promise.all(models.map((m) => m.getModelInfo()))
+			})) as Array<LLMInstanceInfo>
 
-		for (const lmstudioModel of loadedModels) {
-			models[lmstudioModel.modelKey] = parseLMStudioModel(lmstudioModel)
-			modelsWithLoadedDetails.add(lmstudioModel.modelKey)
+			for (const lmstudioModel of loadedModels) {
+				models[lmstudioModel.modelKey] = parseLMStudioModel(lmstudioModel)
+				modelsWithLoadedDetails.add(lmstudioModel.modelKey)
+			}
+		} catch (error) {
+			console.warn("Failed to list loaded models via SDK")
+		}
+
+		// If we didn't get any models from the SDK, fall back to OpenAI-compatible API
+		if (Object.keys(models).length === 0 && openAiModelsResponse.data?.data) {
+			console.log("Falling back to OpenAI-compatible API models")
+			const openAiModels = openAiModelsResponse.data.data
+
+			for (const model of openAiModels) {
+				// Use the model ID as the key
+				models[model.id] = {
+					...lMStudioDefaultModelInfo,
+					description: model.id,
+					// We don't have detailed info from the OpenAI API, so use defaults
+					contextWindow: lMStudioDefaultModelInfo.contextWindow,
+					maxTokens: lMStudioDefaultModelInfo.maxTokens,
+					supportsPromptCache: true,
+					supportsImages: false, // Conservative default
+					supportsComputerUse: false,
+				}
+			}
 		}
 	} catch (error) {
 		if (error.code === "ECONNREFUSED") {