fix: properly handle multi-turn conversations for codex-mini-latest

- Updated convertMessagesToInput to include both user and assistant messages
- Added role prefixes (User:/Assistant:) to maintain conversation context
- Added comprehensive test for multi-turn conversation handling
- Fixes the issue raised by daniel-lxs about missing assistant messages

Author: daniel-lxs

src/api/providers/__tests__/openai-native.spec.ts

@@ -482,7 +482,7 @@ describe("OpenAiNativeHandler", () => {
 			expect(mockResponsesCreate).toHaveBeenCalledWith({
 				model: "codex-mini-latest",
 				instructions: systemPrompt,
-				input: "Hello!",
+				input: "User: Hello!",
 				stream: true,
 			})
 
@@ -519,6 +519,57 @@ describe("OpenAiNativeHandler", () => {
 				}
 			}).rejects.toThrow("OpenAI Responses API error: This model is only supported in v1/responses")
 		})
+
+		it("should handle multi-turn conversations with both user and assistant messages", async () => {
+			const multiTurnMessages: Anthropic.Messages.MessageParam[] = [
+				{
+					role: "user",
+					content: "What is TypeScript?",
+				},
+				{
+					role: "assistant",
+					content: "TypeScript is a typed superset of JavaScript.",
+				},
+				{
+					role: "user",
+					content: "Can you give me an example?",
+				},
+			]
+
+			mockResponsesCreate.mockImplementation(async (options) => {
+				// Verify that the input includes both user and assistant messages
+				expect(options.input).toContain("User: What is TypeScript?")
+				expect(options.input).toContain("Assistant: TypeScript is a typed superset of JavaScript.")
+				expect(options.input).toContain("User: Can you give me an example?")
+				expect(options.stream).toBe(true)
+
+				return {
+					[Symbol.asyncIterator]: async function* () {
+						yield { type: "response.output_text.delta", delta: "Here's an example:" }
+						yield { type: "response.output_text.delta", delta: " const x: number = 5;" }
+						yield { type: "response.completed" }
+					},
+				}
+			})
+
+			const responseStream = handler.createMessage(systemPrompt, multiTurnMessages)
+			const chunks: any[] = []
+			for await (const chunk of responseStream) {
+				chunks.push(chunk)
+			}
+
+			expect(mockResponsesCreate).toHaveBeenCalledWith({
+				model: "codex-mini-latest",
+				instructions: systemPrompt,
+				input: "User: What is TypeScript?\n\nAssistant: TypeScript is a typed superset of JavaScript.\n\nUser: Can you give me an example?",
+				stream: true,
+			})
+
+			const textChunks = chunks.filter((chunk) => chunk.type === "text")
+			expect(textChunks).toHaveLength(2)
+			expect(textChunks[0].text).toBe("Here's an example:")
+			expect(textChunks[1].text).toBe(" const x: number = 5;")
+		})
 	})
 
 	describe("getModel", () => {

src/api/providers/openai-native.ts

@@ -159,19 +159,25 @@ export class OpenAiNativeHandler extends BaseProvider implements SingleCompletio
 	}
 
 	private convertMessagesToInput(messages: Anthropic.Messages.MessageParam[]): string {
-		// Extract only user messages and convert to plain text
-		// This is specific to the codex-mini-latest model's requirements
+		// Convert both user and assistant messages to maintain conversation context
+		// The v1/responses endpoint expects a formatted conversation string
 		return messages
 			.map((msg) => {
-				if (msg.role === "user") {
-					if (typeof msg.content === "string") {
-						return msg.content
-					} else if (Array.isArray(msg.content)) {
-						return msg.content
-							.filter((part) => part.type === "text")
-							.map((part) => part.text)
-							.join("\n")
-					}
+				let content = ""
+
+				// Extract text content from the message
+				if (typeof msg.content === "string") {
+					content = msg.content
+				} else if (Array.isArray(msg.content)) {
+					content = msg.content
+						.filter((part) => part.type === "text")
+						.map((part) => part.text)
+						.join("\n")
+				}
+
+				// Add role prefix to maintain conversation structure
+				if (content) {
+					return msg.role === "user" ? `User: ${content}` : `Assistant: ${content}`
 				}
 				return ""
 			})