feat: add SambaNova provider integration

.github/ISSUE_TEMPLATE/bug_report.yml

@@ -38,6 +38,7 @@ body:
         - OpenAI Compatible
         - OpenRouter
         - Requesty
+        - SambaNova
         - Unbound
         - VS Code Language Model API
         - xAI (Grok)

packages/types/src/global-settings.ts

@@ -185,6 +185,7 @@ export const SECRET_STATE_KEYS = [
 	"codebaseIndexGeminiApiKey",
 	"codebaseIndexMistralApiKey",
 	"huggingFaceApiKey",
+	"sambaNovaApiKey",
 ] as const satisfies readonly (keyof ProviderSettings)[]
 export type SecretState = Pick<ProviderSettings, (typeof SECRET_STATE_KEYS)[number]>
 

packages/types/src/provider-settings.ts

@@ -33,6 +33,7 @@ export const providerNames = [
 	"chutes",
 	"litellm",
 	"huggingface",
+	"sambanova",
 ] as const
 
 export const providerNamesSchema = z.enum(providerNames)
@@ -240,6 +241,10 @@ const litellmSchema = baseProviderSettingsSchema.extend({
 	litellmModelId: z.string().optional(),
 })
 
+const sambaNovaSchema = apiModelIdProviderModelSchema.extend({
+	sambaNovaApiKey: z.string().optional(),
+})
+
 const defaultSchema = z.object({
 	apiProvider: z.undefined(),
 })
@@ -270,6 +275,7 @@ export const providerSettingsSchemaDiscriminated = z.discriminatedUnion("apiProv
 	huggingFaceSchema.merge(z.object({ apiProvider: z.literal("huggingface") })),
 	chutesSchema.merge(z.object({ apiProvider: z.literal("chutes") })),
 	litellmSchema.merge(z.object({ apiProvider: z.literal("litellm") })),
+	sambaNovaSchema.merge(z.object({ apiProvider: z.literal("sambanova") })),
 	defaultSchema,
 ])
 
@@ -300,6 +306,7 @@ export const providerSettingsSchema = z.object({
 	...huggingFaceSchema.shape,
 	...chutesSchema.shape,
 	...litellmSchema.shape,
+	...sambaNovaSchema.shape,
 	...codebaseIndexProviderSchema.shape,
 })
 

packages/types/src/providers/index.ts

@@ -15,6 +15,7 @@ export * from "./ollama.js"
 export * from "./openai.js"
 export * from "./openrouter.js"
 export * from "./requesty.js"
+export * from "./sambanova.js"
 export * from "./unbound.js"
 export * from "./vertex.js"
 export * from "./vscode-llm.js"

packages/types/src/providers/sambanova.ts

@@ -0,0 +1,90 @@
+import type { ModelInfo } from "../model.js"
+
+// https://docs.sambanova.ai/cloud/docs/get-started/supported-models
+export type SambaNovaModelId =
+	| "Meta-Llama-3.1-8B-Instruct"
+	| "Meta-Llama-3.3-70B-Instruct"
+	| "DeepSeek-R1"
+	| "DeepSeek-V3-0324"
+	| "DeepSeek-R1-Distill-Llama-70B"
+	| "Llama-4-Maverick-17B-128E-Instruct"
+	| "Llama-3.3-Swallow-70B-Instruct-v0.4"
+	| "Qwen3-32B"
+
+export const sambaNovaDefaultModelId: SambaNovaModelId = "Meta-Llama-3.3-70B-Instruct"
+
+export const sambaNovaModels = {
+	"Meta-Llama-3.1-8B-Instruct": {
+		maxTokens: 8192,
+		contextWindow: 16384,
+		supportsImages: false,
+		supportsPromptCache: false,
+		inputPrice: 0.1,
+		outputPrice: 0.2,
+		description: "Meta Llama 3.1 8B Instruct model with 16K context window.",
+	},
+	"Meta-Llama-3.3-70B-Instruct": {
+		maxTokens: 8192,
+		contextWindow: 131072,
+		supportsImages: false,
+		supportsPromptCache: false,
+		inputPrice: 0.6,
+		outputPrice: 1.2,
+		description: "Meta Llama 3.3 70B Instruct model with 128K context window.",
+	},
+	"DeepSeek-R1": {
+		maxTokens: 8192,
+		contextWindow: 32768,
+		supportsImages: false,
+		supportsPromptCache: false,
+		supportsReasoningBudget: true,
+		inputPrice: 5.0,
+		outputPrice: 7.0,
+		description: "DeepSeek R1 reasoning model with 32K context window.",
+	},
+	"DeepSeek-V3-0324": {
+		maxTokens: 8192,
+		contextWindow: 32768,
+		supportsImages: false,
+		supportsPromptCache: false,
+		inputPrice: 3.0,
+		outputPrice: 4.5,
+		description: "DeepSeek V3 model with 32K context window.",
+	},
+	"DeepSeek-R1-Distill-Llama-70B": {
+		maxTokens: 8192,
+		contextWindow: 131072,
+		supportsImages: false,
+		supportsPromptCache: false,
+		inputPrice: 0.7,
+		outputPrice: 1.4,
+		description: "DeepSeek R1 distilled Llama 70B model with 128K context window.",
+	},
+	"Llama-4-Maverick-17B-128E-Instruct": {
+		maxTokens: 8192,
+		contextWindow: 131072,
+		supportsImages: true,
+		supportsPromptCache: false,
+		inputPrice: 0.63,
+		outputPrice: 1.8,
+		description: "Meta Llama 4 Maverick 17B 128E Instruct model with 128K context window.",
+	},
+	"Llama-3.3-Swallow-70B-Instruct-v0.4": {
+		maxTokens: 8192,
+		contextWindow: 16384,
+		supportsImages: false,
+		supportsPromptCache: false,
+		inputPrice: 0.6,
+		outputPrice: 1.2,
+		description: "Tokyotech Llama 3.3 Swallow 70B Instruct v0.4 model with 16K context window.",
+	},
+	"Qwen3-32B": {
+		maxTokens: 8192,
+		contextWindow: 8192,
+		supportsImages: false,
+		supportsPromptCache: false,
+		inputPrice: 0.4,
+		outputPrice: 0.8,
+		description: "Alibaba Qwen 3 32B model with 8K context window.",
+	},
+} as const satisfies Record<string, ModelInfo>

src/api/index.ts

@@ -30,6 +30,7 @@ import {
 	ChutesHandler,
 	LiteLLMHandler,
 	ClaudeCodeHandler,
+	SambaNovaHandler,
 } from "./providers"
 
 export interface SingleCompletionHandler {
@@ -115,6 +116,8 @@ export function buildApiHandler(configuration: ProviderSettings): ApiHandler {
 			return new ChutesHandler(options)
 		case "litellm":
 			return new LiteLLMHandler(options)
+		case "sambanova":
+			return new SambaNovaHandler(options)
 		default:
 			apiProvider satisfies "gemini-cli" | undefined
 			return new AnthropicHandler(options)

src/api/providers/__tests__/sambanova.spec.ts

@@ -0,0 +1,154 @@
+// npx vitest run src/api/providers/__tests__/sambanova.spec.ts
+
+// Mock vscode first to avoid import errors
+vitest.mock("vscode", () => ({}))
+
+import OpenAI from "openai"
+import { Anthropic } from "@anthropic-ai/sdk"
+
+import { type SambaNovaModelId, sambaNovaDefaultModelId, sambaNovaModels } from "@roo-code/types"
+
+import { SambaNovaHandler } from "../sambanova"
+
+vitest.mock("openai", () => {
+	const createMock = vitest.fn()
+	return {
+		default: vitest.fn(() => ({ chat: { completions: { create: createMock } } })),
+	}
+})
+
+describe("SambaNovaHandler", () => {
+	let handler: SambaNovaHandler
+	let mockCreate: any
+
+	beforeEach(() => {
+		vitest.clearAllMocks()
+		mockCreate = (OpenAI as unknown as any)().chat.completions.create
+		handler = new SambaNovaHandler({ sambaNovaApiKey: "test-sambanova-api-key" })
+	})
+
+	it("should use the correct SambaNova base URL", () => {
+		new SambaNovaHandler({ sambaNovaApiKey: "test-sambanova-api-key" })
+		expect(OpenAI).toHaveBeenCalledWith(expect.objectContaining({ baseURL: "https://api.sambanova.ai/v1" }))
+	})
+
+	it("should use the provided API key", () => {
+		const sambaNovaApiKey = "test-sambanova-api-key"
+		new SambaNovaHandler({ sambaNovaApiKey })
+		expect(OpenAI).toHaveBeenCalledWith(expect.objectContaining({ apiKey: sambaNovaApiKey }))
+	})
+
+	it("should return default model when no model is specified", () => {
+		const model = handler.getModel()
+		expect(model.id).toBe(sambaNovaDefaultModelId)
+		expect(model.info).toEqual(sambaNovaModels[sambaNovaDefaultModelId])
+	})
+
+	it("should return specified model when valid model is provided", () => {
+		const testModelId: SambaNovaModelId = "Meta-Llama-3.3-70B-Instruct"
+		const handlerWithModel = new SambaNovaHandler({
+			apiModelId: testModelId,
+			sambaNovaApiKey: "test-sambanova-api-key",
+		})
+		const model = handlerWithModel.getModel()
+		expect(model.id).toBe(testModelId)
+		expect(model.info).toEqual(sambaNovaModels[testModelId])
+	})
+
+	it("completePrompt method should return text from SambaNova API", async () => {
+		const expectedResponse = "This is a test response from SambaNova"
+		mockCreate.mockResolvedValueOnce({ choices: [{ message: { content: expectedResponse } }] })
+		const result = await handler.completePrompt("test prompt")
+		expect(result).toBe(expectedResponse)
+	})
+
+	it("should handle errors in completePrompt", async () => {
+		const errorMessage = "SambaNova API error"
+		mockCreate.mockRejectedValueOnce(new Error(errorMessage))
+		await expect(handler.completePrompt("test prompt")).rejects.toThrow(
+			`SambaNova completion error: ${errorMessage}`,
+		)
+	})
+
+	it("createMessage should yield text content from stream", async () => {
+		const testContent = "This is test content from SambaNova stream"
+
+		mockCreate.mockImplementationOnce(() => {
+			return {
+				[Symbol.asyncIterator]: () => ({
+					next: vitest
+						.fn()
+						.mockResolvedValueOnce({
+							done: false,
+							value: { choices: [{ delta: { content: testContent } }] },
+						})
+						.mockResolvedValueOnce({ done: true }),
+				}),
+			}
+		})
+
+		const stream = handler.createMessage("system prompt", [])
+		const firstChunk = await stream.next()
+
+		expect(firstChunk.done).toBe(false)
+		expect(firstChunk.value).toEqual({ type: "text", text: testContent })
+	})
+
+	it("createMessage should yield usage data from stream", async () => {
+		mockCreate.mockImplementationOnce(() => {
+			return {
+				[Symbol.asyncIterator]: () => ({
+					next: vitest
+						.fn()
+						.mockResolvedValueOnce({
+							done: false,
+							value: { choices: [{ delta: {} }], usage: { prompt_tokens: 10, completion_tokens: 20 } },
+						})
+						.mockResolvedValueOnce({ done: true }),
+				}),
+			}
+		})
+
+		const stream = handler.createMessage("system prompt", [])
+		const firstChunk = await stream.next()
+
+		expect(firstChunk.done).toBe(false)
+		expect(firstChunk.value).toEqual({ type: "usage", inputTokens: 10, outputTokens: 20 })
+	})
+
+	it("createMessage should pass correct parameters to SambaNova client", async () => {
+		const modelId: SambaNovaModelId = "Meta-Llama-3.3-70B-Instruct"
+		const modelInfo = sambaNovaModels[modelId]
+		const handlerWithModel = new SambaNovaHandler({
+			apiModelId: modelId,
+			sambaNovaApiKey: "test-sambanova-api-key",
+		})
+
+		mockCreate.mockImplementationOnce(() => {
+			return {
+				[Symbol.asyncIterator]: () => ({
+					async next() {
+						return { done: true }
+					},
+				}),
+			}
+		})
+
+		const systemPrompt = "Test system prompt for SambaNova"
+		const messages: Anthropic.Messages.MessageParam[] = [{ role: "user", content: "Test message for SambaNova" }]
+
+		const messageGenerator = handlerWithModel.createMessage(systemPrompt, messages)
+		await messageGenerator.next()
+
+		expect(mockCreate).toHaveBeenCalledWith(
+			expect.objectContaining({
+				model: modelId,
+				max_tokens: modelInfo.maxTokens,
+				temperature: 0.7,
+				messages: expect.arrayContaining([{ role: "system", content: systemPrompt }]),
+				stream: true,
+				stream_options: { include_usage: true },
+			}),
+		)
+	})
+})

src/api/providers/index.ts

@@ -19,6 +19,7 @@ export { OpenAiNativeHandler } from "./openai-native"
 export { OpenAiHandler } from "./openai"
 export { OpenRouterHandler } from "./openrouter"
 export { RequestyHandler } from "./requesty"
+export { SambaNovaHandler } from "./sambanova"
 export { UnboundHandler } from "./unbound"
 export { VertexHandler } from "./vertex"
 export { VsCodeLmHandler } from "./vscode-lm"

src/api/providers/sambanova.ts

@@ -0,0 +1,19 @@
+import { type SambaNovaModelId, sambaNovaDefaultModelId, sambaNovaModels } from "@roo-code/types"
+
+import type { ApiHandlerOptions } from "../../shared/api"
+
+import { BaseOpenAiCompatibleProvider } from "./base-openai-compatible-provider"
+
+export class SambaNovaHandler extends BaseOpenAiCompatibleProvider<SambaNovaModelId> {
+	constructor(options: ApiHandlerOptions) {
+		super({
+			...options,
+			providerName: "SambaNova",
+			baseURL: "https://api.sambanova.ai/v1",
+			apiKey: options.sambaNovaApiKey,
+			defaultProviderModelId: sambaNovaDefaultModelId,
+			providerModels: sambaNovaModels,
+			defaultTemperature: 0.7,
+		})
+	}
+}

src/shared/ProfileValidator.ts

@@ -65,6 +65,7 @@ export class ProfileValidator {
 			case "deepseek":
 			case "xai":
 			case "groq":
+			case "sambanova":
 			case "chutes":
 				return profile.apiModelId
 			case "litellm":

src/shared/__tests__/ProfileValidator.spec.ts

@@ -192,6 +192,7 @@ describe("ProfileValidator", () => {
 			"xai",
 			"groq",
 			"chutes",
+			"sambanova",
 		]
 
 		apiModelProviders.forEach((provider) => {