feat(friendli): fetch model list dynamically from /v1/models

packages/types/src/__tests__/provider-identifiers.test.ts

@@ -106,6 +106,7 @@ describe("provider identifiers", () => {
 			providerIdentifiers.opencodeGo,
 			providerIdentifiers.kenari,
 			providerIdentifiers.kimiCode,
+			providerIdentifiers.friendli,
 		])
 		expect(localProviders).toEqual([providerIdentifiers.ollama, providerIdentifiers.lmstudio])
 		expect(internalProviders).toEqual([providerIdentifiers.vscodeLm])

packages/types/src/provider-settings.ts

@@ -56,6 +56,7 @@ export const dynamicProviders = [
 	providerIdentifiers.opencodeGo,
 	providerIdentifiers.kenari,
 	providerIdentifiers.kimiCode,
+	providerIdentifiers.friendli,
 ] as const
 
 export type DynamicProvider = (typeof dynamicProviders)[number]

packages/types/src/providers/friendli.ts

@@ -8,8 +8,12 @@ export type FriendliModelId =
 
 export const friendliDefaultModelId: FriendliModelId = "zai-org/GLM-5.2"
 
+// Static fallback for the Friendli provider. Used as a fallback when dynamic
+// models cannot be fetched (cold start, network errors, API lag), in tests,
+// and in the webview's MODELS_BY_PROVIDER fallback. The provider itself fetches
+// the live list from https://api.friendli.ai/serverless/v1/models at runtime.
 // Pricing sourced from https://friendli.ai/api/public/model-apis (per 1M tokens).
-export const friendliModels = {
+export const friendliModels: Record<string, ModelInfo> = {
 	"zai-org/GLM-5.2": {
 		maxTokens: 131_072,
 		contextWindow: 1_000_000,
@@ -64,4 +68,4 @@ export const friendliModels = {
 		description:
 			"MiniMax M2.5 is a high-performance language model with a 204.8K context window, optimized for long-context understanding and generation tasks, served via Friendli Model APIs.",
 	},
-} as const satisfies Record<string, ModelInfo>
+}

src/api/providers/fetchers/__tests__/friendli.spec.ts

@@ -0,0 +1,307 @@
+// npx vitest run api/providers/fetchers/__tests__/friendli.spec.ts
+
+import axios from "axios"
+
+import { getFriendliModels, parseFriendliModel } from "../friendli"
+import type { FriendliModel } from "../friendli"
+
+vi.mock("axios")
+const mockedAxios = vi.mocked(axios, { partial: true })
+
+describe("Friendli Fetchers", () => {
+	beforeEach(() => {
+		vitest.clearAllMocks()
+	})
+
+	describe("getFriendliModels", () => {
+		const mockResponse = {
+			data: {
+				data: [
+					{
+						id: "zai-org/GLM-5.2",
+						name: "zai-org/GLM-5.2",
+						created: 1776162486,
+						context_length: 1048576,
+						max_completion_tokens: 131072,
+						pricing: {
+							input: "0.0000014",
+							output: "0.0000044",
+							input_cache_read: "0.00000026",
+							cache_write: "0.0000015",
+						},
+						functionality: {
+							tool_call: true,
+							parallel_tool_call: true,
+							structured_output: true,
+							tool_choice: true,
+							system_messages: true,
+						},
+						description: "GLM-5.2 flagship model",
+						reasoning: true,
+						reasoning_options: [
+							{ type: "toggle" },
+							{ type: "effort", values: ["low", "medium", "high", "default"] },
+							{ type: "budget_tokens", min: -1, max: 202752 },
+						],
+						input_modalities: ["text"],
+						output_modalities: ["text"],
+						mode: "chat",
+					},
+					{
+						id: "deepseek-ai/DeepSeek-V3.2",
+						name: "deepseek-ai/DeepSeek-V3.2",
+						context_length: 163840,
+						max_completion_tokens: 163840,
+						pricing: {
+							input: "0.0000005",
+							output: "0.0000015",
+							input_cache_read: "0.00000025",
+						},
+						functionality: {
+							tool_call: true,
+							parallel_tool_call: true,
+							structured_output: true,
+						},
+						description: "DeepSeek V3.2",
+						reasoning: false,
+						input_modalities: ["text"],
+						output_modalities: ["text"],
+						mode: "chat",
+					},
+					{
+						id: "some/embedding-model",
+						context_length: 8192,
+						max_completion_tokens: 8192,
+						mode: "embedding",
+						pricing: { input: "0.0000001", output: "0" },
+					},
+				],
+			},
+		}
+
+		it("fetches and parses models correctly", async () => {
+			mockedAxios.get.mockResolvedValueOnce(mockResponse)
+
+			const models = await getFriendliModels()
+
+			expect(mockedAxios.get).toHaveBeenCalledWith("https://api.friendli.ai/serverless/v1/models")
+			// Two chat models, embedding model filtered out
+			expect(Object.keys(models)).toHaveLength(2)
+			expect(models["zai-org/GLM-5.2"]).toBeDefined()
+			expect(models["deepseek-ai/DeepSeek-V3.2"]).toBeDefined()
+		})
+
+		it("handles API errors gracefully", async () => {
+			const consoleErrorSpy = vitest.spyOn(console, "error").mockImplementation(function () {})
+			mockedAxios.get.mockRejectedValueOnce(new Error("Network error"))
+
+			const models = await getFriendliModels()
+
+			expect(models).toEqual({})
+			expect(consoleErrorSpy).toHaveBeenCalledWith(expect.stringContaining("Error fetching Friendli models"))
+			consoleErrorSpy.mockRestore()
+		})
+
+		it("handles invalid response schema gracefully", async () => {
+			const consoleErrorSpy = vitest.spyOn(console, "error").mockImplementation(function () {})
+			mockedAxios.get.mockResolvedValueOnce({
+				data: { invalid: "response" },
+			})
+
+			const models = await getFriendliModels()
+
+			expect(models).toEqual({})
+			expect(consoleErrorSpy).toHaveBeenCalled()
+			consoleErrorSpy.mockRestore()
+		})
+
+		it("filters out non-chat models", async () => {
+			mockedAxios.get.mockResolvedValueOnce({
+				data: {
+					data: [
+						{
+							id: "test/chat-model",
+							context_length: 4096,
+							max_completion_tokens: 2048,
+							mode: "chat",
+							pricing: { input: "0.0000001", output: "0.0000002" },
+						},
+						{
+							id: "test/embedding-model",
+							context_length: 4096,
+							max_completion_tokens: 2048,
+							mode: "embedding",
+							pricing: { input: "0.0000001", output: "0" },
+						},
+					],
+				},
+			})
+
+			const models = await getFriendliModels()
+
+			expect(Object.keys(models)).toHaveLength(1)
+			expect(models["test/chat-model"]).toBeDefined()
+			expect(models["test/embedding-model"]).toBeUndefined()
+		})
+	})
+
+	describe("parseFriendliModel", () => {
+		const baseModel: FriendliModel = {
+			id: "test/model",
+			name: "test/model",
+			context_length: 100000,
+			max_completion_tokens: 8000,
+			pricing: {
+				input: "0.0000025",
+				output: "0.00001",
+			},
+			description: "A test model",
+			input_modalities: ["text"],
+			output_modalities: ["text"],
+			mode: "chat",
+		}
+
+		it("parses basic model info correctly", () => {
+			const result = parseFriendliModel({ id: "test/model", model: baseModel })
+
+			expect(result.maxTokens).toBe(8000)
+			expect(result.contextWindow).toBe(100000)
+			expect(result.supportsImages).toBe(false)
+			expect(result.supportsPromptCache).toBe(false)
+			expect(result.inputPrice).toBe(2.5) // 0.0000025 * 1_000_000 = 2.5
+			expect(result.outputPrice).toBe(10) // 0.00001 * 1_000_000 = 10
+			expect(result.cacheWritesPrice).toBeUndefined()
+			expect(result.cacheReadsPrice).toBeUndefined()
+			expect(result.description).toBe("A test model")
+		})
+
+		it("parses cache pricing when available", () => {
+			const modelWithCache: FriendliModel = {
+				...baseModel,
+				pricing: {
+					input: "0.0000030",
+					output: "0.0000150",
+					input_cache_read: "0.00000030",
+					cache_write: "0.00000375",
+				},
+			}
+
+			const result = parseFriendliModel({ id: "test/model", model: modelWithCache })
+
+			expect(result.supportsPromptCache).toBe(true)
+			expect(result.cacheWritesPrice).toBe(3.75)
+			expect(result.cacheReadsPrice).toBe(0.3)
+		})
+
+		it("handles partial cache pricing (only read)", () => {
+			const modelPartialCache: FriendliModel = {
+				...baseModel,
+				pricing: {
+					input: "0.0000025",
+					output: "0.00001",
+					input_cache_read: "0.00000030",
+				},
+			}
+
+			const result = parseFriendliModel({ id: "test/model", model: modelPartialCache })
+
+			expect(result.supportsPromptCache).toBe(true)
+			expect(result.cacheWritesPrice).toBeUndefined()
+			expect(result.cacheReadsPrice).toBe(0.3)
+		})
+
+		it("detects image support from input_modalities", () => {
+			const visionModel: FriendliModel = {
+				...baseModel,
+				input_modalities: ["text", "image"],
+			}
+
+			const result = parseFriendliModel({ id: "test/model", model: visionModel })
+
+			expect(result.supportsImages).toBe(true)
+		})
+
+		it("sets supportsReasoningEffort as array for controllable reasoning models", () => {
+			const model: FriendliModel = {
+				...baseModel,
+				reasoning: true,
+				reasoning_options: [
+					{ type: "toggle" },
+					{ type: "effort", values: ["low", "medium", "high", "default"] },
+					{ type: "budget_tokens", min: -1, max: 8000 },
+				],
+			}
+
+			const result = parseFriendliModel({ id: "test/model", model })
+
+			expect(result.supportsReasoningEffort).toEqual(
+				expect.arrayContaining(["low", "medium", "high", "minimal", "xhigh", "max"]),
+			)
+			// "default" should be filtered out
+			expect(result.supportsReasoningEffort).not.toContain("default")
+			expect(result.reasoningEffort).toBe("high")
+			expect(result.supportsMaxTokens).toBe(true)
+		})
+
+		it("sets supportsReasoningEffort to true for reasoning models without effort options", () => {
+			const model: FriendliModel = {
+				...baseModel,
+				reasoning: true,
+			}
+
+			const result = parseFriendliModel({ id: "test/model", model })
+
+			expect(result.supportsReasoningEffort).toBe(true)
+			expect(result.reasoningEffort).toBeUndefined()
+			expect(result.supportsMaxTokens).toBeUndefined()
+		})
+
+		it("omits supportsReasoningEffort for non-reasoning models", () => {
+			const model: FriendliModel = {
+				...baseModel,
+				reasoning: false,
+			}
+
+			const result = parseFriendliModel({ id: "test/model", model })
+
+			expect(result.supportsReasoningEffort).toBeUndefined()
+		})
+
+		it("marks deprecated models", () => {
+			const model: FriendliModel = {
+				...baseModel,
+				deprecation_date: "2026-08-05T00:00:00Z",
+			}
+
+			const result = parseFriendliModel({ id: "test/model", model })
+
+			expect(result.deprecated).toBe(true)
+		})
+
+		it("handles empty description", () => {
+			const model: FriendliModel = {
+				...baseModel,
+				description: " ",
+			}
+
+			const result = parseFriendliModel({ id: "test/model", model })
+
+			expect(result.description).toBeUndefined()
+		})
+
+		it("falls back to prompt/completion pricing aliases", () => {
+			const model: FriendliModel = {
+				...baseModel,
+				pricing: {
+					prompt: "0.0000025",
+					completion: "0.00001",
+				},
+			}
+
+			const result = parseFriendliModel({ id: "test/model", model })
+
+			expect(result.inputPrice).toBe(2.5)
+			expect(result.outputPrice).toBe(10)
+		})
+	})
+})