fix: flatten message content to string for SambaNova DeepSeek models

DeepSeek models on SambaNova expect string content in messages, not
array content. This fix adds:
1. flattenAiSdkMessagesToStringContent utility that converts text-only
   messages to string format
2. transform option to convertToAiSdkMessages for flexible message
   transformation

The SambaNova handler passes the flattening function to convertToAiSdkMessages
for models that don't support images.

Fixes: 400 'Invalid content type' error for DeepSeek-R1-0528 model

Author: daniel-lxs

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

@@ -259,7 +259,7 @@ describe("SambaNovaHandler", () => {
 			expect(usageChunks[0].cacheWriteTokens).toBeUndefined()
 		})
 
-		it("should pass correct temperature (0.5 default) to streamText", async () => {
+		it("should pass correct temperature (0.7 default) to streamText", async () => {
 			async function* mockFullStream() {
 				yield { type: "text-delta", text: "Test" }
 			}
@@ -282,7 +282,7 @@ describe("SambaNovaHandler", () => {
 
 			expect(mockStreamText).toHaveBeenCalledWith(
 				expect.objectContaining({
-					temperature: 0.5,
+					temperature: 0.7,
 				}),
 			)
 		})
@@ -369,7 +369,7 @@ describe("SambaNovaHandler", () => {
 
 			expect(mockGenerateText).toHaveBeenCalledWith(
 				expect.objectContaining({
-					temperature: 0.5,
+					temperature: 0.7,
 				}),
 			)
 		})

src/api/providers/sambanova.ts

@@ -12,6 +12,7 @@ import {
 	processAiSdkStreamPart,
 	mapToolChoice,
 	handleAiSdkError,
+	flattenAiSdkMessagesToStringContent,
 } from "../transform/ai-sdk"
 import { ApiStream, ApiStreamUsageChunk } from "../transform/stream"
 import { getModelParams } from "../transform/model-params"
@@ -20,7 +21,7 @@ import { DEFAULT_HEADERS } from "./constants"
 import { BaseProvider } from "./base-provider"
 import type { SingleCompletionHandler, ApiHandlerCreateMessageMetadata } from "../index"
 
-const SAMBANOVA_DEFAULT_TEMPERATURE = 0.5
+const SAMBANOVA_DEFAULT_TEMPERATURE = 0.7
 
 /**
  * SambaNova provider using the dedicated sambanova-ai-provider package.
@@ -112,11 +113,15 @@ export class SambaNovaHandler extends BaseProvider implements SingleCompletionHa
 		messages: Anthropic.Messages.MessageParam[],
 		metadata?: ApiHandlerCreateMessageMetadata,
 	): ApiStream {
-		const { temperature } = this.getModel()
+		const { temperature, info } = this.getModel()
 		const languageModel = this.getLanguageModel()
 
 		// Convert messages to AI SDK format
-		const aiSdkMessages = convertToAiSdkMessages(messages)
+		// For models that don't support multi-part content (like DeepSeek), flatten messages to string content
+		// SambaNova's DeepSeek models expect string content, not array content
+		const aiSdkMessages = convertToAiSdkMessages(messages, {
+			transform: info.supportsImages ? undefined : flattenAiSdkMessagesToStringContent,
+		})
 
 		// Convert tools to OpenAI format first, then to AI SDK format
 		const openAiTools = this.convertToolsForOpenAI(metadata?.tools)

src/api/transform/__tests__/ai-sdk.spec.ts

@@ -7,6 +7,7 @@ import {
 	mapToolChoice,
 	extractAiSdkErrorMessage,
 	handleAiSdkError,
+	flattenAiSdkMessagesToStringContent,
 } from "../ai-sdk"
 
 vitest.mock("ai", () => ({
@@ -644,4 +645,177 @@ describe("AI SDK conversion utilities", () => {
 			expect((result as any).cause).toBe(originalError)
 		})
 	})
+
+	describe("flattenAiSdkMessagesToStringContent", () => {
+		it("should return messages unchanged if content is already a string", () => {
+			const messages = [
+				{ role: "user" as const, content: "Hello" },
+				{ role: "assistant" as const, content: "Hi there" },
+			]
+
+			const result = flattenAiSdkMessagesToStringContent(messages)
+
+			expect(result).toEqual(messages)
+		})
+
+		it("should flatten user messages with only text parts to string", () => {
+			const messages = [
+				{
+					role: "user" as const,
+					content: [
+						{ type: "text" as const, text: "Hello" },
+						{ type: "text" as const, text: "World" },
+					],
+				},
+			]
+
+			const result = flattenAiSdkMessagesToStringContent(messages)
+
+			expect(result).toHaveLength(1)
+			expect(result[0].role).toBe("user")
+			expect(result[0].content).toBe("Hello\nWorld")
+		})
+
+		it("should flatten assistant messages with only text parts to string", () => {
+			const messages = [
+				{
+					role: "assistant" as const,
+					content: [{ type: "text" as const, text: "I am an assistant" }],
+				},
+			]
+
+			const result = flattenAiSdkMessagesToStringContent(messages)
+
+			expect(result).toHaveLength(1)
+			expect(result[0].role).toBe("assistant")
+			expect(result[0].content).toBe("I am an assistant")
+		})
+
+		it("should not flatten user messages with image parts", () => {
+			const messages = [
+				{
+					role: "user" as const,
+					content: [
+						{ type: "text" as const, text: "Look at this" },
+						{ type: "image" as const, image: "data:image/png;base64,abc123" },
+					],
+				},
+			]
+
+			const result = flattenAiSdkMessagesToStringContent(messages)
+
+			expect(result).toEqual(messages)
+		})
+
+		it("should not flatten assistant messages with tool calls", () => {
+			const messages = [
+				{
+					role: "assistant" as const,
+					content: [
+						{ type: "text" as const, text: "Let me use a tool" },
+						{
+							type: "tool-call" as const,
+							toolCallId: "123",
+							toolName: "read_file",
+							input: { path: "test.txt" },
+						},
+					],
+				},
+			]
+
+			const result = flattenAiSdkMessagesToStringContent(messages)
+
+			expect(result).toEqual(messages)
+		})
+
+		it("should not flatten tool role messages", () => {
+			const messages = [
+				{
+					role: "tool" as const,
+					content: [
+						{
+							type: "tool-result" as const,
+							toolCallId: "123",
+							toolName: "test",
+							output: { type: "text" as const, value: "result" },
+						},
+					],
+				},
+			] as any
+
+			const result = flattenAiSdkMessagesToStringContent(messages)
+
+			expect(result).toEqual(messages)
+		})
+
+		it("should respect flattenUserMessages option", () => {
+			const messages = [
+				{
+					role: "user" as const,
+					content: [{ type: "text" as const, text: "Hello" }],
+				},
+			]
+
+			const result = flattenAiSdkMessagesToStringContent(messages, { flattenUserMessages: false })
+
+			expect(result).toEqual(messages)
+		})
+
+		it("should respect flattenAssistantMessages option", () => {
+			const messages = [
+				{
+					role: "assistant" as const,
+					content: [{ type: "text" as const, text: "Hi" }],
+				},
+			]
+
+			const result = flattenAiSdkMessagesToStringContent(messages, { flattenAssistantMessages: false })
+
+			expect(result).toEqual(messages)
+		})
+
+		it("should handle mixed message types correctly", () => {
+			const messages = [
+				{ role: "user" as const, content: "Simple string" },
+				{
+					role: "user" as const,
+					content: [{ type: "text" as const, text: "Text parts" }],
+				},
+				{
+					role: "assistant" as const,
+					content: [{ type: "text" as const, text: "Assistant text" }],
+				},
+				{
+					role: "assistant" as const,
+					content: [
+						{ type: "text" as const, text: "With tool" },
+						{ type: "tool-call" as const, toolCallId: "456", toolName: "test", input: {} },
+					],
+				},
+			]
+
+			const result = flattenAiSdkMessagesToStringContent(messages)
+
+			expect(result[0].content).toBe("Simple string") // unchanged
+			expect(result[1].content).toBe("Text parts") // flattened
+			expect(result[2].content).toBe("Assistant text") // flattened
+			expect(result[3]).toEqual(messages[3]) // unchanged (has tool call)
+		})
+
+		it("should handle empty text parts", () => {
+			const messages = [
+				{
+					role: "user" as const,
+					content: [
+						{ type: "text" as const, text: "" },
+						{ type: "text" as const, text: "Hello" },
+					],
+				},
+			]
+
+			const result = flattenAiSdkMessagesToStringContent(messages)
+
+			expect(result[0].content).toBe("\nHello")
+		})
+	})
 })

src/api/transform/ai-sdk.ts

@@ -8,14 +8,29 @@ import OpenAI from "openai"
 import { tool as createTool, jsonSchema, type ModelMessage, type TextStreamPart } from "ai"
 import type { ApiStreamChunk } from "./stream"
 
+/**
+ * Options for converting Anthropic messages to AI SDK format.
+ */
+export interface ConvertToAiSdkMessagesOptions {
+	/**
+	 * Optional function to transform the converted messages.
+	 * Useful for transformations like flattening message content for models that require string content.
+	 */
+	transform?: (messages: ModelMessage[]) => ModelMessage[]
+}
+
 /**
  * Convert Anthropic messages to AI SDK ModelMessage format.
  * Handles text, images, tool uses, and tool results.
  *
  * @param messages - Array of Anthropic message parameters
+ * @param options - Optional conversion options including post-processing function
  * @returns Array of AI SDK ModelMessage objects
  */
-export function convertToAiSdkMessages(messages: Anthropic.Messages.MessageParam[]): ModelMessage[] {
+export function convertToAiSdkMessages(
+	messages: Anthropic.Messages.MessageParam[],
+	options?: ConvertToAiSdkMessagesOptions,
+): ModelMessage[] {
 	const modelMessages: ModelMessage[] = []
 
 	// First pass: build a map of tool call IDs to tool names from assistant messages
@@ -149,9 +164,84 @@ export function convertToAiSdkMessages(messages: Anthropic.Messages.MessageParam
 		}
 	}
 
+	// Apply transform if provided
+	if (options?.transform) {
+		return options.transform(modelMessages)
+	}
+
 	return modelMessages
 }
 
+/**
+ * Options for flattening AI SDK messages.
+ */
+export interface FlattenMessagesOptions {
+	/**
+	 * If true, flattens user messages with only text parts to string content.
+	 * Default: true
+	 */
+	flattenUserMessages?: boolean
+	/**
+	 * If true, flattens assistant messages with only text (no tool calls) to string content.
+	 * Default: true
+	 */
+	flattenAssistantMessages?: boolean
+}
+
+/**
+ * Flatten AI SDK messages to use string content where possible.
+ * Some models (like DeepSeek on SambaNova) require string content instead of array content.
+ * This function converts messages that contain only text parts to use simple string content.
+ *
+ * @param messages - Array of AI SDK ModelMessage objects
+ * @param options - Options for controlling which message types to flatten
+ * @returns Array of AI SDK ModelMessage objects with flattened content where applicable
+ */
+export function flattenAiSdkMessagesToStringContent(
+	messages: ModelMessage[],
+	options: FlattenMessagesOptions = {},
+): ModelMessage[] {
+	const { flattenUserMessages = true, flattenAssistantMessages = true } = options
+
+	return messages.map((message) => {
+		// Skip if content is already a string
+		if (typeof message.content === "string") {
+			return message
+		}
+
+		// Handle user messages
+		if (message.role === "user" && flattenUserMessages && Array.isArray(message.content)) {
+			const parts = message.content as Array<{ type: string; text?: string }>
+			// Only flatten if all parts are text
+			const allText = parts.every((part) => part.type === "text")
+			if (allText && parts.length > 0) {
+				const textContent = parts.map((part) => part.text || "").join("\n")
+				return {
+					...message,
+					content: textContent,
+				}
+			}
+		}
+
+		// Handle assistant messages
+		if (message.role === "assistant" && flattenAssistantMessages && Array.isArray(message.content)) {
+			const parts = message.content as Array<{ type: string; text?: string }>
+			// Only flatten if all parts are text (no tool calls)
+			const allText = parts.every((part) => part.type === "text")
+			if (allText && parts.length > 0) {
+				const textContent = parts.map((part) => part.text || "").join("\n")
+				return {
+					...message,
+					content: textContent,
+				}
+			}
+		}
+
+		// Return unchanged for tool role and messages with non-text content
+		return message
+	})
+}
+
 /**
  * Convert OpenAI-style function tool definitions to AI SDK tool format.
  *