mirror of
https://github.com/RooVetGit/Roo-Code.git
synced 2026-08-28 05:27:24 +00:00
feat: separate OpenAI Chat Completions and Responses API handlers
- Created base OpenAIBaseHandler with shared logic (auth, retry, metrics) - Split into OpenAIChatCompletionsHandler for Chat API - Split into OpenAIResponsesHandler for Responses API - OpenAiHandler now routes based on URL pattern and model type - Maintains backward compatibility with existing tests - Clear separation improves maintainability as APIs evolve Addresses #8246
This commit is contained in:
Roo Code
parent
0e1b23d09c
commit
95e4c12873
5 changed files with 1494 additions and 415 deletions
412
src/api/providers/__tests__/openai-architecture.spec.ts
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412
src/api/providers/__tests__/openai-architecture.spec.ts
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@ -0,0 +1,412 @@
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// npx vitest run api/providers/__tests__/openai-architecture.spec.ts
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import { OpenAiHandler } from "../openai"
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import { OpenAIChatCompletionsHandler } from "../openai-chat-completions"
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import { OpenAIResponsesHandler } from "../openai-responses"
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import { ApiHandlerOptions } from "../../../shared/api"
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import { Anthropic } from "@anthropic-ai/sdk"
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const mockCreate = vitest.fn()
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vitest.mock("openai", () => {
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const mockConstructor = vitest.fn()
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return {
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__esModule: true,
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default: mockConstructor.mockImplementation(() => ({
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chat: {
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completions: {
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create: mockCreate.mockImplementation(async (options) => {
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if (!options.stream) {
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return {
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id: "test-completion",
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choices: [
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{
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message: { role: "assistant", content: "Test response", refusal: null },
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finish_reason: "stop",
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index: 0,
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},
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],
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usage: {
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prompt_tokens: 10,
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completion_tokens: 5,
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total_tokens: 15,
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},
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}
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}
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return {
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[Symbol.asyncIterator]: async function* () {
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yield {
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choices: [
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{
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delta: { content: "Test response" },
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index: 0,
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},
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],
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usage: null,
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}
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yield {
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choices: [
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{
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delta: {},
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index: 0,
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},
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],
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usage: {
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prompt_tokens: 10,
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completion_tokens: 5,
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total_tokens: 15,
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},
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}
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},
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}
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}),
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},
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},
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responses: {
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create: vitest.fn().mockImplementation(async (options) => {
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// Mock Responses API stream
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return {
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[Symbol.asyncIterator]: async function* () {
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yield {
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type: "response.text.delta",
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delta: "Responses API response",
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}
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yield {
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type: "response.done",
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response: {
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id: "resp_123",
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usage: {
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input_tokens: 10,
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output_tokens: 5,
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},
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},
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}
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},
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}
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}),
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},
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})),
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AzureOpenAI: mockConstructor.mockImplementation(() => ({
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chat: {
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completions: {
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create: mockCreate,
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},
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},
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})),
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}
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})
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describe("OpenAI Architecture Separation", () => {
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let mockOptions: ApiHandlerOptions
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beforeEach(() => {
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mockOptions = {
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openAiApiKey: "test-api-key",
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openAiModelId: "gpt-4",
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openAiBaseUrl: "https://api.openai.com/v1",
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}
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mockCreate.mockClear()
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})
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describe("Handler Routing", () => {
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it("should use Chat Completions handler by default", () => {
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const handler = new OpenAiHandler(mockOptions)
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expect(handler.getApiType()).toBe("chat-completions")
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})
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it("should use Responses API handler for GPT-5 models", () => {
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const gpt5Options = {
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...mockOptions,
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openAiModelId: "gpt-5-turbo",
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}
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const handler = new OpenAiHandler(gpt5Options)
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expect(handler.getApiType()).toBe("responses")
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})
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it("should use Responses API handler when URL contains /v1/responses", () => {
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const responsesOptions = {
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...mockOptions,
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openAiBaseUrl: "https://api.openai.com/v1/responses",
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}
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const handler = new OpenAiHandler(responsesOptions)
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expect(handler.getApiType()).toBe("responses")
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})
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it("should use Responses API handler when configured for OpenAI Native", () => {
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const nativeOptions: ApiHandlerOptions = {
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openAiNativeApiKey: "test-native-key",
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openAiModelId: "gpt-4",
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}
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const handler = new OpenAiHandler(nativeOptions)
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expect(handler.getApiType()).toBe("responses")
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})
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it("should use Chat Completions handler for standard OpenAI models", () => {
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const handler = new OpenAiHandler(mockOptions)
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expect(handler.getApiType()).toBe("chat-completions")
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})
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it("should use Chat Completions handler for O3 models", () => {
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const o3Options = {
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...mockOptions,
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openAiModelId: "o3-mini",
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}
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const handler = new OpenAiHandler(o3Options)
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expect(handler.getApiType()).toBe("chat-completions")
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})
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})
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describe("Chat Completions Handler", () => {
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it("should handle streaming messages correctly", async () => {
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const handler = new OpenAIChatCompletionsHandler(mockOptions)
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const systemPrompt = "You are a helpful assistant."
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const messages: Anthropic.Messages.MessageParam[] = [
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{
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role: "user",
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content: "Hello!",
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},
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]
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const stream = handler.createMessage(systemPrompt, messages)
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const chunks: any[] = []
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for await (const chunk of stream) {
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chunks.push(chunk)
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}
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expect(chunks.length).toBeGreaterThan(0)
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const textChunks = chunks.filter((chunk) => chunk.type === "text")
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expect(textChunks).toHaveLength(1)
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expect(textChunks[0].text).toBe("Test response")
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})
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it("should handle O3 family models with special formatting", async () => {
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const o3Options = {
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...mockOptions,
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openAiModelId: "o3-mini",
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}
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const handler = new OpenAIChatCompletionsHandler(o3Options)
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const systemPrompt = "You are a helpful assistant."
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const messages: Anthropic.Messages.MessageParam[] = [
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{
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role: "user",
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content: "Hello!",
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},
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]
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const stream = handler.createMessage(systemPrompt, messages)
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await stream.next()
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expect(mockCreate).toHaveBeenCalledWith(
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expect.objectContaining({
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model: "o3-mini",
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messages: expect.arrayContaining([
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expect.objectContaining({
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role: "developer",
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content: expect.stringContaining("Formatting re-enabled"),
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}),
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]),
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}),
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{},
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)
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})
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it("should handle DeepSeek reasoner models", async () => {
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const deepseekOptions = {
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...mockOptions,
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openAiModelId: "deepseek-reasoner",
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}
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const handler = new OpenAIChatCompletionsHandler(deepseekOptions)
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const systemPrompt = "You are a helpful assistant."
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const messages: Anthropic.Messages.MessageParam[] = [
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{
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role: "user",
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content: "Hello!",
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},
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]
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const stream = handler.createMessage(systemPrompt, messages)
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const chunks: any[] = []
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for await (const chunk of stream) {
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chunks.push(chunk)
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}
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expect(chunks.length).toBeGreaterThan(0)
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})
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})
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describe("Responses API Handler", () => {
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it("should handle streaming responses correctly", async () => {
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const responsesOptions = {
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...mockOptions,
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openAiBaseUrl: "https://api.openai.com/v1/responses",
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}
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const handler = new OpenAIResponsesHandler(responsesOptions)
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const systemPrompt = "You are a helpful assistant."
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const messages: Anthropic.Messages.MessageParam[] = [
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{
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role: "user",
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content: "Hello!",
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},
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]
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const stream = handler.createMessage(systemPrompt, messages)
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const chunks: any[] = []
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for await (const chunk of stream) {
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chunks.push(chunk)
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}
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expect(chunks.length).toBeGreaterThan(0)
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const textChunks = chunks.filter((chunk) => chunk.type === "text")
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expect(textChunks).toHaveLength(1)
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expect(textChunks[0].text).toBe("Responses API response")
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})
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it("should maintain conversation continuity with response IDs", () => {
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const handler = new OpenAIResponsesHandler(mockOptions)
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// Initially should have no response ID
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expect(handler.getLastResponseId()).toBeUndefined()
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// Set a response ID
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handler.setResponseId("resp_123")
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expect(handler.getLastResponseId()).toBe("resp_123")
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})
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it("should format messages correctly for Responses API", async () => {
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const handler = new OpenAIResponsesHandler(mockOptions)
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const systemPrompt = "You are a helpful assistant."
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const messages: Anthropic.Messages.MessageParam[] = [
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{
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role: "user",
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content: "Hello!",
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},
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{
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role: "assistant",
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content: "Hi there!",
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},
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{
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role: "user",
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content: "How are you?",
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},
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]
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const stream = handler.createMessage(systemPrompt, messages)
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await stream.next()
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const responsesApi = (handler as any).client.responses
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expect(responsesApi.create).toHaveBeenCalledWith(
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expect.objectContaining({
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model: "gpt-4",
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instructions: systemPrompt,
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input: expect.arrayContaining([
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expect.objectContaining({
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role: "user",
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content: expect.arrayContaining([
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expect.objectContaining({
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type: "input_text",
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text: "Hello!",
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}),
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]),
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}),
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]),
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}),
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)
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})
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})
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describe("Integration with Main Handler", () => {
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it("should delegate to the correct handler based on configuration", async () => {
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// Test Chat Completions delegation
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const chatHandler = new OpenAiHandler(mockOptions)
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const systemPrompt = "You are a helpful assistant."
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const messages: Anthropic.Messages.MessageParam[] = [
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{
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role: "user",
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content: "Hello!",
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},
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]
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const chatStream = chatHandler.createMessage(systemPrompt, messages)
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const chatChunks: any[] = []
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for await (const chunk of chatStream) {
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chatChunks.push(chunk)
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}
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expect(chatChunks.length).toBeGreaterThan(0)
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expect(chatHandler.getApiType()).toBe("chat-completions")
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// Test Responses API delegation
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const responsesOptions = {
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...mockOptions,
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openAiModelId: "gpt-5-turbo",
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}
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const responsesHandler = new OpenAiHandler(responsesOptions)
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const responsesStream = responsesHandler.createMessage(systemPrompt, messages)
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const responsesChunks: any[] = []
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for await (const chunk of responsesStream) {
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responsesChunks.push(chunk)
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}
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expect(responsesChunks.length).toBeGreaterThan(0)
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expect(responsesHandler.getApiType()).toBe("responses")
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})
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it("should handle completePrompt through the correct handler", async () => {
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const handler = new OpenAiHandler(mockOptions)
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const result = await handler.completePrompt("Test prompt")
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expect(result).toBe("Test response")
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})
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it("should expose response ID methods only for Responses API", () => {
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// Chat Completions handler should return undefined
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const chatHandler = new OpenAiHandler(mockOptions)
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expect(chatHandler.getLastResponseId()).toBeUndefined()
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chatHandler.setResponseId("test_id") // Should not throw but do nothing
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expect(chatHandler.getLastResponseId()).toBeUndefined()
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// Responses API handler should work
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const responsesOptions = {
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...mockOptions,
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openAiModelId: "gpt-5-turbo",
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}
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const responsesHandler = new OpenAiHandler(responsesOptions)
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responsesHandler.setResponseId("resp_456")
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expect(responsesHandler.getLastResponseId()).toBe("resp_456")
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})
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})
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describe("Error Handling", () => {
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it("should handle errors in Chat Completions handler", async () => {
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mockCreate.mockRejectedValueOnce(new Error("API Error"))
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const handler = new OpenAIChatCompletionsHandler(mockOptions)
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const stream = handler.createMessage("system", [{ role: "user", content: "test" }])
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await expect(async () => {
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for await (const _chunk of stream) {
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// Should not reach here
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}
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}).rejects.toThrow("API Error")
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})
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it("should handle errors in Responses API handler", async () => {
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const responsesApi = vitest.fn().mockRejectedValueOnce(new Error("Responses API Error"))
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vitest.mocked((global as any).OpenAI).mockImplementationOnce(() => ({
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responses: {
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create: responsesApi,
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},
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}))
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const handler = new OpenAIResponsesHandler(mockOptions)
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const stream = handler.createMessage("system", [{ role: "user", content: "test" }])
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await expect(async () => {
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for await (const _chunk of stream) {
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// Should not reach here
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}
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}).rejects.toThrow()
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})
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})
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})
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137
src/api/providers/openai-base.ts
Normal file
137
src/api/providers/openai-base.ts
Normal file
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@ -0,0 +1,137 @@
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import { Anthropic } from "@anthropic-ai/sdk"
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import OpenAI, { AzureOpenAI } from "openai"
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import { type ModelInfo, azureOpenAiDefaultApiVersion, openAiModelInfoSaneDefaults } from "@roo-code/types"
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import type { ApiHandlerOptions } from "../../shared/api"
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import { DEFAULT_HEADERS } from "./constants"
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import { BaseProvider } from "./base-provider"
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import type { SingleCompletionHandler, ApiHandlerCreateMessageMetadata } from "../index"
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import { getApiRequestTimeout } from "./utils/timeout-config"
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import { handleOpenAIError } from "./utils/openai-error-handler"
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import { getModelParams } from "../transform/model-params"
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/**
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* Base class for OpenAI-compatible providers with shared logic for auth, retry, metrics, and basic transforms.
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* This class contains common functionality that both Chat Completions and Responses API handlers can use.
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*/
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export abstract class OpenAIBaseHandler extends BaseProvider implements SingleCompletionHandler {
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protected options: ApiHandlerOptions
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protected client: OpenAI
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protected readonly providerName: string
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constructor(options: ApiHandlerOptions, providerName: string = "OpenAI") {
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super()
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this.options = options
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this.providerName = providerName
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const baseURL = this.options.openAiBaseUrl ?? "https://api.openai.com/v1"
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const apiKey = this.options.openAiApiKey ?? "not-provided"
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const isAzureAiInference = this._isAzureAiInference(this.options.openAiBaseUrl)
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const urlHost = this._getUrlHost(this.options.openAiBaseUrl)
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const isAzureOpenAi = urlHost === "azure.com" || urlHost.endsWith(".azure.com") || options.openAiUseAzure
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const headers = {
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...DEFAULT_HEADERS,
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...(this.options.openAiHeaders || {}),
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}
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const timeout = getApiRequestTimeout()
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if (isAzureAiInference) {
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// Azure AI Inference Service (e.g., for DeepSeek) uses a different path structure
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this.client = new OpenAI({
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baseURL,
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apiKey,
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defaultHeaders: headers,
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defaultQuery: { "api-version": this.options.azureApiVersion || "2024-05-01-preview" },
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timeout,
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})
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} else if (isAzureOpenAi) {
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// Azure API shape slightly differs from the core API shape:
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// https://github.com/openai/openai-node?tab=readme-ov-file#microsoft-azure-openai
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this.client = new AzureOpenAI({
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baseURL,
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apiKey,
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apiVersion: this.options.azureApiVersion || azureOpenAiDefaultApiVersion,
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defaultHeaders: headers,
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timeout,
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})
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} else {
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this.client = new OpenAI({
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baseURL,
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apiKey,
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defaultHeaders: headers,
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timeout,
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})
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}
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}
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/**
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* Get the model configuration with parameters
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*/
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override getModel() {
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const id = this.options.openAiModelId ?? ""
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const info = this.options.openAiCustomModelInfo ?? openAiModelInfoSaneDefaults
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const params = getModelParams({ format: "openai", modelId: id, model: info, settings: this.options })
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return { id, info, ...params }
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}
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/**
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* Complete a prompt using the appropriate API
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*/
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abstract completePrompt(prompt: string): Promise<string>
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/**
|
||||
* Helper method to get the URL host
|
||||
*/
|
||||
protected _getUrlHost(baseUrl?: string): string {
|
||||
try {
|
||||
return new URL(baseUrl ?? "").host
|
||||
} catch (error) {
|
||||
return ""
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Check if the URL is for Grok xAI
|
||||
*/
|
||||
protected _isGrokXAI(baseUrl?: string): boolean {
|
||||
const urlHost = this._getUrlHost(baseUrl)
|
||||
return urlHost.includes("x.ai")
|
||||
}
|
||||
|
||||
/**
|
||||
* Check if the URL is for Azure AI Inference
|
||||
*/
|
||||
protected _isAzureAiInference(baseUrl?: string): boolean {
|
||||
const urlHost = this._getUrlHost(baseUrl)
|
||||
return urlHost.endsWith(".services.ai.azure.com")
|
||||
}
|
||||
|
||||
/**
|
||||
* Handle OpenAI errors with proper error messages
|
||||
*/
|
||||
protected handleError(error: any): never {
|
||||
throw handleOpenAIError(error, this.providerName)
|
||||
}
|
||||
|
||||
/**
|
||||
* Adds max_completion_tokens to the request body if needed based on provider configuration
|
||||
* Note: max_tokens is deprecated in favor of max_completion_tokens as per OpenAI documentation
|
||||
*/
|
||||
protected addMaxTokensIfNeeded(
|
||||
requestOptions:
|
||||
| OpenAI.Chat.Completions.ChatCompletionCreateParamsStreaming
|
||||
| OpenAI.Chat.Completions.ChatCompletionCreateParamsNonStreaming,
|
||||
modelInfo: ModelInfo,
|
||||
): void {
|
||||
// Only add max_completion_tokens if includeMaxTokens is true
|
||||
if (this.options.includeMaxTokens === true) {
|
||||
// Use user-configured modelMaxTokens if available, otherwise fall back to model's default maxTokens
|
||||
// Using max_completion_tokens as max_tokens is deprecated
|
||||
requestOptions.max_completion_tokens = this.options.modelMaxTokens || modelInfo.maxTokens
|
||||
}
|
||||
}
|
||||
}
|
||||
382
src/api/providers/openai-chat-completions.ts
Normal file
382
src/api/providers/openai-chat-completions.ts
Normal file
|
|
@ -0,0 +1,382 @@
|
|||
import { Anthropic } from "@anthropic-ai/sdk"
|
||||
import OpenAI from "openai"
|
||||
|
||||
import { type ModelInfo, DEEP_SEEK_DEFAULT_TEMPERATURE, OPENAI_AZURE_AI_INFERENCE_PATH } from "@roo-code/types"
|
||||
|
||||
import type { ApiHandlerOptions } from "../../shared/api"
|
||||
|
||||
import { XmlMatcher } from "../../utils/xml-matcher"
|
||||
|
||||
import { convertToOpenAiMessages } from "../transform/openai-format"
|
||||
import { convertToR1Format } from "../transform/r1-format"
|
||||
import { convertToSimpleMessages } from "../transform/simple-format"
|
||||
import { ApiStream, ApiStreamUsageChunk } from "../transform/stream"
|
||||
|
||||
import { OpenAIBaseHandler } from "./openai-base"
|
||||
import type { ApiHandlerCreateMessageMetadata } from "../index"
|
||||
|
||||
/**
|
||||
* Handler for OpenAI Chat Completions API
|
||||
* Handles standard chat completions, o1/o3/o4 models, DeepSeek reasoner, and other variations
|
||||
*/
|
||||
export class OpenAIChatCompletionsHandler extends OpenAIBaseHandler {
|
||||
constructor(options: ApiHandlerOptions) {
|
||||
// Use "OpenAI" for backward compatibility with existing tests
|
||||
super(options, "OpenAI")
|
||||
}
|
||||
|
||||
override async *createMessage(
|
||||
systemPrompt: string,
|
||||
messages: Anthropic.Messages.MessageParam[],
|
||||
metadata?: ApiHandlerCreateMessageMetadata,
|
||||
): ApiStream {
|
||||
const { info: modelInfo, reasoning } = this.getModel()
|
||||
const modelUrl = this.options.openAiBaseUrl ?? ""
|
||||
const modelId = this.options.openAiModelId ?? ""
|
||||
const enabledR1Format = this.options.openAiR1FormatEnabled ?? false
|
||||
const enabledLegacyFormat = this.options.openAiLegacyFormat ?? false
|
||||
const isAzureAiInference = this._isAzureAiInference(modelUrl)
|
||||
const deepseekReasoner = modelId.includes("deepseek-reasoner") || enabledR1Format
|
||||
const ark = modelUrl.includes(".volces.com")
|
||||
|
||||
// Handle O1/O3/O4 family models separately
|
||||
if (modelId.includes("o1") || modelId.includes("o3") || modelId.includes("o4")) {
|
||||
yield* this.handleO3FamilyMessage(modelId, systemPrompt, messages)
|
||||
return
|
||||
}
|
||||
|
||||
if (this.options.openAiStreamingEnabled ?? true) {
|
||||
yield* this.handleStreamingMessage(
|
||||
systemPrompt,
|
||||
messages,
|
||||
modelInfo,
|
||||
modelId,
|
||||
deepseekReasoner,
|
||||
ark,
|
||||
enabledLegacyFormat,
|
||||
isAzureAiInference,
|
||||
reasoning,
|
||||
)
|
||||
} else {
|
||||
yield* this.handleNonStreamingMessage(
|
||||
systemPrompt,
|
||||
messages,
|
||||
modelInfo,
|
||||
modelId,
|
||||
deepseekReasoner,
|
||||
enabledLegacyFormat,
|
||||
isAzureAiInference,
|
||||
)
|
||||
}
|
||||
}
|
||||
|
||||
private async *handleStreamingMessage(
|
||||
systemPrompt: string,
|
||||
messages: Anthropic.Messages.MessageParam[],
|
||||
modelInfo: ModelInfo,
|
||||
modelId: string,
|
||||
deepseekReasoner: boolean,
|
||||
ark: boolean,
|
||||
enabledLegacyFormat: boolean,
|
||||
isAzureAiInference: boolean,
|
||||
reasoning: any,
|
||||
): ApiStream {
|
||||
let systemMessage: OpenAI.Chat.ChatCompletionSystemMessageParam = {
|
||||
role: "system",
|
||||
content: systemPrompt,
|
||||
}
|
||||
|
||||
let convertedMessages
|
||||
|
||||
if (deepseekReasoner) {
|
||||
convertedMessages = convertToR1Format([{ role: "user", content: systemPrompt }, ...messages])
|
||||
} else if (ark || enabledLegacyFormat) {
|
||||
convertedMessages = [systemMessage, ...convertToSimpleMessages(messages)]
|
||||
} else {
|
||||
if (modelInfo.supportsPromptCache) {
|
||||
systemMessage = {
|
||||
role: "system",
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: systemPrompt,
|
||||
// @ts-ignore-next-line
|
||||
cache_control: { type: "ephemeral" },
|
||||
},
|
||||
],
|
||||
}
|
||||
}
|
||||
|
||||
convertedMessages = [systemMessage, ...convertToOpenAiMessages(messages)]
|
||||
|
||||
if (modelInfo.supportsPromptCache) {
|
||||
// Add cache_control to the last two user messages
|
||||
const lastTwoUserMessages = convertedMessages.filter((msg) => msg.role === "user").slice(-2)
|
||||
|
||||
lastTwoUserMessages.forEach((msg) => {
|
||||
if (typeof msg.content === "string") {
|
||||
msg.content = [{ type: "text", text: msg.content }]
|
||||
}
|
||||
|
||||
if (Array.isArray(msg.content)) {
|
||||
let lastTextPart = msg.content.filter((part) => part.type === "text").pop()
|
||||
|
||||
if (!lastTextPart) {
|
||||
lastTextPart = { type: "text", text: "..." }
|
||||
msg.content.push(lastTextPart)
|
||||
}
|
||||
|
||||
// @ts-ignore-next-line
|
||||
lastTextPart["cache_control"] = { type: "ephemeral" }
|
||||
}
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
const isGrokXAI = this._isGrokXAI(this.options.openAiBaseUrl)
|
||||
|
||||
const requestOptions: OpenAI.Chat.Completions.ChatCompletionCreateParamsStreaming = {
|
||||
model: modelId,
|
||||
temperature: this.options.modelTemperature ?? (deepseekReasoner ? DEEP_SEEK_DEFAULT_TEMPERATURE : 0),
|
||||
messages: convertedMessages,
|
||||
stream: true as const,
|
||||
...(isGrokXAI ? {} : { stream_options: { include_usage: true } }),
|
||||
...(reasoning && reasoning),
|
||||
}
|
||||
|
||||
// Add max_tokens if needed
|
||||
this.addMaxTokensIfNeeded(requestOptions, modelInfo)
|
||||
|
||||
let stream
|
||||
try {
|
||||
stream = await this.client.chat.completions.create(
|
||||
requestOptions,
|
||||
isAzureAiInference ? { path: OPENAI_AZURE_AI_INFERENCE_PATH } : {},
|
||||
)
|
||||
} catch (error) {
|
||||
this.handleError(error)
|
||||
}
|
||||
|
||||
const matcher = new XmlMatcher(
|
||||
"think",
|
||||
(chunk) =>
|
||||
({
|
||||
type: chunk.matched ? "reasoning" : "text",
|
||||
text: chunk.data,
|
||||
}) as const,
|
||||
)
|
||||
|
||||
let lastUsage
|
||||
|
||||
for await (const chunk of stream) {
|
||||
const delta = chunk.choices[0]?.delta ?? {}
|
||||
|
||||
if (delta.content) {
|
||||
for (const chunk of matcher.update(delta.content)) {
|
||||
yield chunk
|
||||
}
|
||||
}
|
||||
|
||||
if ("reasoning_content" in delta && delta.reasoning_content) {
|
||||
yield {
|
||||
type: "reasoning",
|
||||
text: (delta.reasoning_content as string | undefined) || "",
|
||||
}
|
||||
}
|
||||
if (chunk.usage) {
|
||||
lastUsage = chunk.usage
|
||||
}
|
||||
}
|
||||
|
||||
for (const chunk of matcher.final()) {
|
||||
yield chunk
|
||||
}
|
||||
|
||||
if (lastUsage) {
|
||||
yield this.processUsageMetrics(lastUsage, modelInfo)
|
||||
}
|
||||
}
|
||||
|
||||
private async *handleNonStreamingMessage(
|
||||
systemPrompt: string,
|
||||
messages: Anthropic.Messages.MessageParam[],
|
||||
modelInfo: ModelInfo,
|
||||
modelId: string,
|
||||
deepseekReasoner: boolean,
|
||||
enabledLegacyFormat: boolean,
|
||||
isAzureAiInference: boolean,
|
||||
): ApiStream {
|
||||
const systemMessage: OpenAI.Chat.ChatCompletionUserMessageParam = {
|
||||
role: "user",
|
||||
content: systemPrompt,
|
||||
}
|
||||
|
||||
const requestOptions: OpenAI.Chat.Completions.ChatCompletionCreateParamsNonStreaming = {
|
||||
model: modelId,
|
||||
messages: deepseekReasoner
|
||||
? convertToR1Format([{ role: "user", content: systemPrompt }, ...messages])
|
||||
: enabledLegacyFormat
|
||||
? [systemMessage, ...convertToSimpleMessages(messages)]
|
||||
: [systemMessage, ...convertToOpenAiMessages(messages)],
|
||||
}
|
||||
|
||||
// Add max_tokens if needed
|
||||
this.addMaxTokensIfNeeded(requestOptions, modelInfo)
|
||||
|
||||
let response
|
||||
try {
|
||||
response = await this.client.chat.completions.create(
|
||||
requestOptions,
|
||||
isAzureAiInference ? { path: OPENAI_AZURE_AI_INFERENCE_PATH } : {},
|
||||
)
|
||||
} catch (error) {
|
||||
this.handleError(error)
|
||||
}
|
||||
|
||||
yield {
|
||||
type: "text",
|
||||
text: response.choices[0]?.message.content || "",
|
||||
}
|
||||
|
||||
yield this.processUsageMetrics(response.usage, modelInfo)
|
||||
}
|
||||
|
||||
private async *handleO3FamilyMessage(
|
||||
modelId: string,
|
||||
systemPrompt: string,
|
||||
messages: Anthropic.Messages.MessageParam[],
|
||||
): ApiStream {
|
||||
const modelInfo = this.getModel().info
|
||||
const methodIsAzureAiInference = this._isAzureAiInference(this.options.openAiBaseUrl)
|
||||
|
||||
if (this.options.openAiStreamingEnabled ?? true) {
|
||||
const isGrokXAI = this._isGrokXAI(this.options.openAiBaseUrl)
|
||||
|
||||
const requestOptions: OpenAI.Chat.Completions.ChatCompletionCreateParamsStreaming = {
|
||||
model: modelId,
|
||||
messages: [
|
||||
{
|
||||
role: "developer",
|
||||
content: `Formatting re-enabled\n${systemPrompt}`,
|
||||
},
|
||||
...convertToOpenAiMessages(messages),
|
||||
],
|
||||
stream: true,
|
||||
...(isGrokXAI ? {} : { stream_options: { include_usage: true } }),
|
||||
reasoning_effort: modelInfo.reasoningEffort as "low" | "medium" | "high" | undefined,
|
||||
temperature: undefined,
|
||||
}
|
||||
|
||||
// O3 family models support max_completion_tokens
|
||||
this.addMaxTokensIfNeeded(requestOptions, modelInfo)
|
||||
|
||||
let stream
|
||||
try {
|
||||
stream = await this.client.chat.completions.create(
|
||||
requestOptions,
|
||||
methodIsAzureAiInference ? { path: OPENAI_AZURE_AI_INFERENCE_PATH } : {},
|
||||
)
|
||||
} catch (error) {
|
||||
this.handleError(error)
|
||||
}
|
||||
|
||||
yield* this.handleStreamResponse(stream)
|
||||
} else {
|
||||
const requestOptions: OpenAI.Chat.Completions.ChatCompletionCreateParamsNonStreaming = {
|
||||
model: modelId,
|
||||
messages: [
|
||||
{
|
||||
role: "developer",
|
||||
content: `Formatting re-enabled\n${systemPrompt}`,
|
||||
},
|
||||
...convertToOpenAiMessages(messages),
|
||||
],
|
||||
reasoning_effort: modelInfo.reasoningEffort as "low" | "medium" | "high" | undefined,
|
||||
temperature: undefined,
|
||||
}
|
||||
|
||||
// O3 family models support max_completion_tokens
|
||||
this.addMaxTokensIfNeeded(requestOptions, modelInfo)
|
||||
|
||||
let response
|
||||
try {
|
||||
response = await this.client.chat.completions.create(
|
||||
requestOptions,
|
||||
methodIsAzureAiInference ? { path: OPENAI_AZURE_AI_INFERENCE_PATH } : {},
|
||||
)
|
||||
} catch (error) {
|
||||
this.handleError(error)
|
||||
}
|
||||
|
||||
yield {
|
||||
type: "text",
|
||||
text: response.choices[0]?.message.content || "",
|
||||
}
|
||||
yield this.processUsageMetrics(response.usage)
|
||||
}
|
||||
}
|
||||
|
||||
private async *handleStreamResponse(stream: AsyncIterable<OpenAI.Chat.Completions.ChatCompletionChunk>): ApiStream {
|
||||
for await (const chunk of stream) {
|
||||
const delta = chunk.choices[0]?.delta
|
||||
if (delta?.content) {
|
||||
yield {
|
||||
type: "text",
|
||||
text: delta.content,
|
||||
}
|
||||
}
|
||||
|
||||
if (chunk.usage) {
|
||||
yield {
|
||||
type: "usage",
|
||||
inputTokens: chunk.usage.prompt_tokens || 0,
|
||||
outputTokens: chunk.usage.completion_tokens || 0,
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
protected processUsageMetrics(usage: any, _modelInfo?: ModelInfo): ApiStreamUsageChunk {
|
||||
return {
|
||||
type: "usage",
|
||||
inputTokens: usage?.prompt_tokens || 0,
|
||||
outputTokens: usage?.completion_tokens || 0,
|
||||
cacheWriteTokens: usage?.cache_creation_input_tokens || undefined,
|
||||
cacheReadTokens: usage?.cache_read_input_tokens || undefined,
|
||||
}
|
||||
}
|
||||
|
||||
async completePrompt(prompt: string): Promise<string> {
|
||||
try {
|
||||
const isAzureAiInference = this._isAzureAiInference(this.options.openAiBaseUrl)
|
||||
const model = this.getModel()
|
||||
const modelInfo = model.info
|
||||
|
||||
const requestOptions: OpenAI.Chat.Completions.ChatCompletionCreateParamsNonStreaming = {
|
||||
model: model.id,
|
||||
messages: [{ role: "user", content: prompt }],
|
||||
}
|
||||
|
||||
// Add max_tokens if needed
|
||||
this.addMaxTokensIfNeeded(requestOptions, modelInfo)
|
||||
|
||||
let response
|
||||
try {
|
||||
response = await this.client.chat.completions.create(
|
||||
requestOptions,
|
||||
isAzureAiInference ? { path: OPENAI_AZURE_AI_INFERENCE_PATH } : {},
|
||||
)
|
||||
} catch (error) {
|
||||
this.handleError(error)
|
||||
}
|
||||
|
||||
return response.choices[0]?.message.content || ""
|
||||
} catch (error) {
|
||||
if (error instanceof Error) {
|
||||
throw new Error(`${this.providerName} completion error: ${error.message}`)
|
||||
}
|
||||
|
||||
throw error
|
||||
}
|
||||
}
|
||||
}
|
||||
489
src/api/providers/openai-responses.ts
Normal file
489
src/api/providers/openai-responses.ts
Normal file
|
|
@ -0,0 +1,489 @@
|
|||
import { Anthropic } from "@anthropic-ai/sdk"
|
||||
|
||||
import {
|
||||
type ModelInfo,
|
||||
type ServiceTier,
|
||||
OPENAI_NATIVE_DEFAULT_TEMPERATURE,
|
||||
GPT5_DEFAULT_TEMPERATURE,
|
||||
} from "@roo-code/types"
|
||||
|
||||
import type { ApiHandlerOptions } from "../../shared/api"
|
||||
|
||||
import { ApiStream, ApiStreamUsageChunk } from "../transform/stream"
|
||||
import { calculateApiCostOpenAI } from "../../shared/cost"
|
||||
|
||||
import { OpenAIBaseHandler } from "./openai-base"
|
||||
import type { ApiHandlerCreateMessageMetadata } from "../index"
|
||||
|
||||
/**
|
||||
* Handler for OpenAI Responses API
|
||||
* Handles the new Responses API with specialized streaming/response parsing
|
||||
* This is a simplified implementation focusing on the core Responses API functionality
|
||||
*/
|
||||
export class OpenAIResponsesHandler extends OpenAIBaseHandler {
|
||||
private lastResponseId: string | undefined
|
||||
private lastServiceTier: ServiceTier | undefined
|
||||
|
||||
constructor(options: ApiHandlerOptions) {
|
||||
super(options, "OpenAI Responses")
|
||||
}
|
||||
|
||||
override async *createMessage(
|
||||
systemPrompt: string,
|
||||
messages: Anthropic.Messages.MessageParam[],
|
||||
metadata?: ApiHandlerCreateMessageMetadata,
|
||||
): ApiStream {
|
||||
// Reset resolved tier for this request
|
||||
this.lastServiceTier = undefined
|
||||
|
||||
const model = this.getModel()
|
||||
const modelId = model.id
|
||||
|
||||
// Prepare the request body for Responses API
|
||||
const requestBody = this.buildRequestBody(model, systemPrompt, messages, metadata)
|
||||
|
||||
// Make the request
|
||||
yield* this.executeRequest(requestBody, model)
|
||||
}
|
||||
|
||||
private buildRequestBody(
|
||||
model: any,
|
||||
systemPrompt: string,
|
||||
messages: Anthropic.Messages.MessageParam[],
|
||||
metadata?: ApiHandlerCreateMessageMetadata,
|
||||
): any {
|
||||
// Format the conversation for Responses API
|
||||
const formattedInput = this.formatConversation(systemPrompt, messages, metadata)
|
||||
|
||||
const requestBody: any = {
|
||||
model: model.id,
|
||||
input: formattedInput,
|
||||
stream: true,
|
||||
store: metadata?.store !== false, // Default to true unless explicitly set to false
|
||||
instructions: systemPrompt,
|
||||
}
|
||||
|
||||
// Add temperature if supported
|
||||
if (model.info.supportsTemperature !== false) {
|
||||
requestBody.temperature =
|
||||
this.options.modelTemperature ??
|
||||
(model.id.startsWith("gpt-5") ? GPT5_DEFAULT_TEMPERATURE : OPENAI_NATIVE_DEFAULT_TEMPERATURE)
|
||||
}
|
||||
|
||||
// Add max output tokens if available
|
||||
if (model.maxTokens) {
|
||||
requestBody.max_output_tokens = model.maxTokens
|
||||
}
|
||||
|
||||
// Add previous response ID if available for conversation continuity
|
||||
if (this.lastResponseId && !metadata?.suppressPreviousResponseId) {
|
||||
requestBody.previous_response_id = this.lastResponseId
|
||||
}
|
||||
|
||||
return requestBody
|
||||
}
|
||||
|
||||
private formatConversation(
|
||||
systemPrompt: string,
|
||||
messages: Anthropic.Messages.MessageParam[],
|
||||
metadata?: ApiHandlerCreateMessageMetadata,
|
||||
): any[] {
|
||||
// If we have a previous response ID and not suppressed, only send the latest user message
|
||||
if (this.lastResponseId && !metadata?.suppressPreviousResponseId) {
|
||||
const lastUserMessage = [...messages].reverse().find((msg) => msg.role === "user")
|
||||
if (lastUserMessage) {
|
||||
return [this.formatMessage(lastUserMessage)]
|
||||
}
|
||||
}
|
||||
|
||||
// Otherwise, format the full conversation
|
||||
const formattedMessages: any[] = []
|
||||
|
||||
for (const message of messages) {
|
||||
formattedMessages.push(this.formatMessage(message))
|
||||
}
|
||||
|
||||
return formattedMessages
|
||||
}
|
||||
|
||||
private formatMessage(message: Anthropic.Messages.MessageParam): any {
|
||||
const role = message.role === "user" ? "user" : "assistant"
|
||||
const content: any[] = []
|
||||
|
||||
if (typeof message.content === "string") {
|
||||
// Use input_text for user messages, output_text for assistant
|
||||
if (role === "user") {
|
||||
content.push({ type: "input_text", text: message.content })
|
||||
} else {
|
||||
content.push({ type: "output_text", text: message.content })
|
||||
}
|
||||
} else if (Array.isArray(message.content)) {
|
||||
for (const block of message.content) {
|
||||
if (block.type === "text") {
|
||||
if (role === "user") {
|
||||
content.push({ type: "input_text", text: (block as any).text })
|
||||
} else {
|
||||
content.push({ type: "output_text", text: (block as any).text })
|
||||
}
|
||||
} else if (block.type === "image") {
|
||||
const image = block as Anthropic.Messages.ImageBlockParam
|
||||
const imageUrl = `data:${image.source.media_type};base64,${image.source.data}`
|
||||
content.push({ type: "input_image", image_url: imageUrl })
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return { role, content }
|
||||
}
|
||||
|
||||
private async *executeRequest(requestBody: any, model: any): ApiStream {
|
||||
try {
|
||||
// Use the SDK's Responses API if available
|
||||
const responsesApi = (this.client as any).responses
|
||||
if (responsesApi && typeof responsesApi.create === "function") {
|
||||
const stream = await responsesApi.create(requestBody)
|
||||
|
||||
if (typeof (stream as any)[Symbol.asyncIterator] === "function") {
|
||||
for await (const event of stream) {
|
||||
yield* this.processEvent(event, model)
|
||||
}
|
||||
return
|
||||
}
|
||||
}
|
||||
|
||||
// Fallback to direct API call if SDK doesn't support Responses API
|
||||
yield* this.makeDirectApiCall(requestBody, model)
|
||||
} catch (error: any) {
|
||||
// Handle previous_response_id not found error
|
||||
if (error?.status === 400 && requestBody.previous_response_id) {
|
||||
// Clear the stored lastResponseId and retry without it
|
||||
this.lastResponseId = undefined
|
||||
delete requestBody.previous_response_id
|
||||
|
||||
// Retry the request
|
||||
try {
|
||||
const responsesApi = (this.client as any).responses
|
||||
if (responsesApi && typeof responsesApi.create === "function") {
|
||||
const stream = await responsesApi.create(requestBody)
|
||||
if (typeof (stream as any)[Symbol.asyncIterator] === "function") {
|
||||
for await (const event of stream) {
|
||||
yield* this.processEvent(event, model)
|
||||
}
|
||||
return
|
||||
}
|
||||
}
|
||||
yield* this.makeDirectApiCall(requestBody, model)
|
||||
} catch (retryError) {
|
||||
this.handleError(retryError)
|
||||
}
|
||||
} else {
|
||||
this.handleError(error)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
private async *makeDirectApiCall(requestBody: any, model: any): ApiStream {
|
||||
const apiKey = this.options.openAiApiKey ?? "not-provided"
|
||||
const baseUrl = this.options.openAiBaseUrl || "https://api.openai.com"
|
||||
const url = `${baseUrl}/v1/responses`
|
||||
|
||||
try {
|
||||
const response = await fetch(url, {
|
||||
method: "POST",
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
Authorization: `Bearer ${apiKey}`,
|
||||
Accept: "text/event-stream",
|
||||
},
|
||||
body: JSON.stringify(requestBody),
|
||||
})
|
||||
|
||||
if (!response.ok) {
|
||||
const errorText = await response.text()
|
||||
throw new Error(`Responses API error (${response.status}): ${errorText}`)
|
||||
}
|
||||
|
||||
if (!response.body) {
|
||||
throw new Error("Responses API error: No response body")
|
||||
}
|
||||
|
||||
// Handle streaming response
|
||||
yield* this.handleStreamResponse(response.body, model)
|
||||
} catch (error) {
|
||||
this.handleError(error)
|
||||
}
|
||||
}
|
||||
|
||||
private async *handleStreamResponse(body: ReadableStream<Uint8Array>, model: any): ApiStream {
|
||||
const reader = body.getReader()
|
||||
const decoder = new TextDecoder()
|
||||
let buffer = ""
|
||||
|
||||
try {
|
||||
while (true) {
|
||||
const { done, value } = await reader.read()
|
||||
if (done) break
|
||||
|
||||
buffer += decoder.decode(value, { stream: true })
|
||||
const lines = buffer.split("\n")
|
||||
buffer = lines.pop() || ""
|
||||
|
||||
for (const line of lines) {
|
||||
if (line.startsWith("data: ")) {
|
||||
const data = line.slice(6).trim()
|
||||
if (data === "[DONE]") {
|
||||
continue
|
||||
}
|
||||
|
||||
try {
|
||||
const parsed = JSON.parse(data)
|
||||
yield* this.processEvent(parsed, model)
|
||||
} catch (e) {
|
||||
// Ignore JSON parsing errors
|
||||
if (!(e instanceof SyntaxError)) {
|
||||
throw e
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
} finally {
|
||||
reader.releaseLock()
|
||||
}
|
||||
}
|
||||
|
||||
private async *processEvent(event: any, model: any): ApiStream {
|
||||
// Store response ID for conversation continuity
|
||||
if (event?.response?.id) {
|
||||
this.lastResponseId = event.response.id
|
||||
}
|
||||
|
||||
// Capture resolved service tier
|
||||
if (event?.response?.service_tier) {
|
||||
this.lastServiceTier = event.response.service_tier as ServiceTier
|
||||
}
|
||||
|
||||
// Handle text deltas
|
||||
if (event?.type === "response.text.delta" || event?.type === "response.output_text.delta") {
|
||||
if (event?.delta) {
|
||||
yield { type: "text", text: event.delta }
|
||||
}
|
||||
return
|
||||
}
|
||||
|
||||
// Handle reasoning deltas
|
||||
if (
|
||||
event?.type === "response.reasoning.delta" ||
|
||||
event?.type === "response.reasoning_text.delta" ||
|
||||
event?.type === "response.reasoning_summary.delta" ||
|
||||
event?.type === "response.reasoning_summary_text.delta"
|
||||
) {
|
||||
if (event?.delta) {
|
||||
yield { type: "reasoning", text: event.delta }
|
||||
}
|
||||
return
|
||||
}
|
||||
|
||||
// Handle refusal deltas
|
||||
if (event?.type === "response.refusal.delta") {
|
||||
if (event?.delta) {
|
||||
yield { type: "text", text: `[Refusal] ${event.delta}` }
|
||||
}
|
||||
return
|
||||
}
|
||||
|
||||
// Handle output item additions
|
||||
if (event?.type === "response.output_item.added") {
|
||||
const item = event?.item
|
||||
if (item) {
|
||||
if (item.type === "text" && item.text) {
|
||||
yield { type: "text", text: item.text }
|
||||
} else if (item.type === "reasoning" && item.text) {
|
||||
yield { type: "reasoning", text: item.text }
|
||||
} else if (item.type === "message" && Array.isArray(item.content)) {
|
||||
for (const content of item.content) {
|
||||
if ((content?.type === "text" || content?.type === "output_text") && content?.text) {
|
||||
yield { type: "text", text: content.text }
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
return
|
||||
}
|
||||
|
||||
// Handle completion events with usage
|
||||
if (event?.type === "response.done" || event?.type === "response.completed") {
|
||||
const usage = event?.response?.usage || event?.usage
|
||||
if (usage) {
|
||||
yield this.normalizeUsage(usage, model)
|
||||
}
|
||||
return
|
||||
}
|
||||
|
||||
// Handle complete response in initial event (non-streaming format)
|
||||
if (event.response && event.response.output && Array.isArray(event.response.output)) {
|
||||
for (const outputItem of event.response.output) {
|
||||
if (outputItem.type === "text" && outputItem.content) {
|
||||
for (const content of outputItem.content) {
|
||||
if (content.type === "text" && content.text) {
|
||||
yield { type: "text", text: content.text }
|
||||
}
|
||||
}
|
||||
}
|
||||
// Handle reasoning summaries
|
||||
if (outputItem.type === "reasoning" && Array.isArray(outputItem.summary)) {
|
||||
for (const summary of outputItem.summary) {
|
||||
if (summary?.type === "summary_text" && typeof summary.text === "string") {
|
||||
yield { type: "reasoning", text: summary.text }
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
// Check for usage in the complete response
|
||||
if (event.response.usage) {
|
||||
yield this.normalizeUsage(event.response.usage, model)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
private normalizeUsage(usage: any, model: any): ApiStreamUsageChunk {
|
||||
if (!usage) {
|
||||
return {
|
||||
type: "usage",
|
||||
inputTokens: 0,
|
||||
outputTokens: 0,
|
||||
}
|
||||
}
|
||||
|
||||
const inputDetails = usage.input_tokens_details ?? usage.prompt_tokens_details
|
||||
const cachedFromDetails = inputDetails?.cached_tokens ?? 0
|
||||
const missFromDetails = inputDetails?.cache_miss_tokens ?? 0
|
||||
|
||||
let totalInputTokens = usage.input_tokens ?? usage.prompt_tokens ?? 0
|
||||
if (totalInputTokens === 0 && inputDetails && (cachedFromDetails > 0 || missFromDetails > 0)) {
|
||||
totalInputTokens = cachedFromDetails + missFromDetails
|
||||
}
|
||||
|
||||
const totalOutputTokens = usage.output_tokens ?? usage.completion_tokens ?? 0
|
||||
const cacheWriteTokens = usage.cache_creation_input_tokens ?? usage.cache_write_tokens ?? 0
|
||||
const cacheReadTokens =
|
||||
usage.cache_read_input_tokens ?? usage.cache_read_tokens ?? usage.cached_tokens ?? cachedFromDetails ?? 0
|
||||
|
||||
// Calculate cost if we have pricing info
|
||||
const effectiveTier = this.lastServiceTier || undefined
|
||||
const effectiveInfo = this.applyServiceTierPricing(model.info, effectiveTier)
|
||||
|
||||
const totalCost = calculateApiCostOpenAI(
|
||||
effectiveInfo,
|
||||
totalInputTokens,
|
||||
totalOutputTokens,
|
||||
cacheWriteTokens,
|
||||
cacheReadTokens,
|
||||
)
|
||||
|
||||
const reasoningTokens =
|
||||
typeof usage.output_tokens_details?.reasoning_tokens === "number"
|
||||
? usage.output_tokens_details.reasoning_tokens
|
||||
: undefined
|
||||
|
||||
return {
|
||||
type: "usage",
|
||||
inputTokens: totalInputTokens,
|
||||
outputTokens: totalOutputTokens,
|
||||
cacheWriteTokens,
|
||||
cacheReadTokens,
|
||||
...(typeof reasoningTokens === "number" ? { reasoningTokens } : {}),
|
||||
totalCost,
|
||||
}
|
||||
}
|
||||
|
||||
private applyServiceTierPricing(info: ModelInfo, tier?: ServiceTier): ModelInfo {
|
||||
if (!tier || tier === "default") return info
|
||||
|
||||
const tierInfo = info.tiers?.find((t) => t.name === tier)
|
||||
if (!tierInfo) return info
|
||||
|
||||
return {
|
||||
...info,
|
||||
inputPrice: tierInfo.inputPrice ?? info.inputPrice,
|
||||
outputPrice: tierInfo.outputPrice ?? info.outputPrice,
|
||||
cacheReadsPrice: tierInfo.cacheReadsPrice ?? info.cacheReadsPrice,
|
||||
cacheWritesPrice: tierInfo.cacheWritesPrice ?? info.cacheWritesPrice,
|
||||
}
|
||||
}
|
||||
|
||||
async completePrompt(prompt: string): Promise<string> {
|
||||
try {
|
||||
const model = this.getModel()
|
||||
|
||||
const requestBody: any = {
|
||||
model: model.id,
|
||||
input: [
|
||||
{
|
||||
role: "user",
|
||||
content: [{ type: "input_text", text: prompt }],
|
||||
},
|
||||
],
|
||||
stream: false,
|
||||
store: false,
|
||||
}
|
||||
|
||||
// Add temperature if supported
|
||||
if (model.info.supportsTemperature !== false) {
|
||||
requestBody.temperature =
|
||||
this.options.modelTemperature ??
|
||||
(model.id.startsWith("gpt-5") ? GPT5_DEFAULT_TEMPERATURE : OPENAI_NATIVE_DEFAULT_TEMPERATURE)
|
||||
}
|
||||
|
||||
// Add max output tokens if available
|
||||
if (model.maxTokens) {
|
||||
requestBody.max_output_tokens = model.maxTokens
|
||||
}
|
||||
|
||||
// Make the non-streaming request
|
||||
const responsesApi = (this.client as any).responses
|
||||
if (responsesApi && typeof responsesApi.create === "function") {
|
||||
const response = await responsesApi.create(requestBody)
|
||||
|
||||
// Extract text from the response
|
||||
if (response?.output && Array.isArray(response.output)) {
|
||||
for (const outputItem of response.output) {
|
||||
if (outputItem.type === "message" && outputItem.content) {
|
||||
for (const content of outputItem.content) {
|
||||
if (content.type === "output_text" && content.text) {
|
||||
return content.text
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Fallback: check for direct text in response
|
||||
if (response?.text) {
|
||||
return response.text
|
||||
}
|
||||
}
|
||||
|
||||
return ""
|
||||
} catch (error) {
|
||||
if (error instanceof Error) {
|
||||
throw new Error(`${this.providerName} completion error: ${error.message}`)
|
||||
}
|
||||
throw error
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Gets the last response ID for conversation continuity
|
||||
*/
|
||||
getLastResponseId(): string | undefined {
|
||||
return this.lastResponseId
|
||||
}
|
||||
|
||||
/**
|
||||
* Sets the response ID for conversation continuity
|
||||
*/
|
||||
setResponseId(responseId: string): void {
|
||||
this.lastResponseId = responseId
|
||||
}
|
||||
}
|
||||
|
|
@ -1,444 +1,103 @@
|
|||
import { Anthropic } from "@anthropic-ai/sdk"
|
||||
import OpenAI, { AzureOpenAI } from "openai"
|
||||
import axios from "axios"
|
||||
|
||||
import {
|
||||
type ModelInfo,
|
||||
azureOpenAiDefaultApiVersion,
|
||||
openAiModelInfoSaneDefaults,
|
||||
DEEP_SEEK_DEFAULT_TEMPERATURE,
|
||||
OPENAI_AZURE_AI_INFERENCE_PATH,
|
||||
} from "@roo-code/types"
|
||||
|
||||
import type { ApiHandlerOptions } from "../../shared/api"
|
||||
|
||||
import { XmlMatcher } from "../../utils/xml-matcher"
|
||||
|
||||
import { convertToOpenAiMessages } from "../transform/openai-format"
|
||||
import { convertToR1Format } from "../transform/r1-format"
|
||||
import { convertToSimpleMessages } from "../transform/simple-format"
|
||||
import { ApiStream, ApiStreamUsageChunk } from "../transform/stream"
|
||||
import { getModelParams } from "../transform/model-params"
|
||||
|
||||
import { DEFAULT_HEADERS } from "./constants"
|
||||
import { BaseProvider } from "./base-provider"
|
||||
import type { SingleCompletionHandler, ApiHandlerCreateMessageMetadata } from "../index"
|
||||
import { getApiRequestTimeout } from "./utils/timeout-config"
|
||||
import { handleOpenAIError } from "./utils/openai-error-handler"
|
||||
import type { ApiHandlerOptions } from "../../shared/api"
|
||||
import { ApiStream } from "../transform/stream"
|
||||
|
||||
// TODO: Rename this to OpenAICompatibleHandler. Also, I think the
|
||||
// `OpenAINativeHandler` can subclass from this, since it's obviously
|
||||
// compatible with the OpenAI API. We can also rename it to `OpenAIHandler`.
|
||||
export class OpenAiHandler extends BaseProvider implements SingleCompletionHandler {
|
||||
protected options: ApiHandlerOptions
|
||||
private client: OpenAI
|
||||
private readonly providerName = "OpenAI"
|
||||
import { OpenAIChatCompletionsHandler } from "./openai-chat-completions"
|
||||
import { OpenAIResponsesHandler } from "./openai-responses"
|
||||
|
||||
/**
|
||||
* Main OpenAI handler that routes requests to either Chat Completions or Responses API
|
||||
* based on URL pattern detection and configuration.
|
||||
*
|
||||
* This handler acts as a router, automatically detecting which API to use based on:
|
||||
* - URL patterns (e.g., /v1/responses for Responses API)
|
||||
* - Model configuration (e.g., GPT-5 models prefer Responses API)
|
||||
* - Explicit configuration flags
|
||||
*/
|
||||
export class OpenAiHandler implements SingleCompletionHandler {
|
||||
private handler: OpenAIChatCompletionsHandler | OpenAIResponsesHandler
|
||||
private readonly useResponsesApi: boolean
|
||||
|
||||
constructor(options: ApiHandlerOptions) {
|
||||
super()
|
||||
this.options = options
|
||||
// Determine which API to use based on configuration and URL patterns
|
||||
this.useResponsesApi = this.shouldUseResponsesApi(options)
|
||||
|
||||
const baseURL = this.options.openAiBaseUrl ?? "https://api.openai.com/v1"
|
||||
const apiKey = this.options.openAiApiKey ?? "not-provided"
|
||||
const isAzureAiInference = this._isAzureAiInference(this.options.openAiBaseUrl)
|
||||
const urlHost = this._getUrlHost(this.options.openAiBaseUrl)
|
||||
const isAzureOpenAi = urlHost === "azure.com" || urlHost.endsWith(".azure.com") || options.openAiUseAzure
|
||||
|
||||
const headers = {
|
||||
...DEFAULT_HEADERS,
|
||||
...(this.options.openAiHeaders || {}),
|
||||
}
|
||||
|
||||
const timeout = getApiRequestTimeout()
|
||||
|
||||
if (isAzureAiInference) {
|
||||
// Azure AI Inference Service (e.g., for DeepSeek) uses a different path structure
|
||||
this.client = new OpenAI({
|
||||
baseURL,
|
||||
apiKey,
|
||||
defaultHeaders: headers,
|
||||
defaultQuery: { "api-version": this.options.azureApiVersion || "2024-05-01-preview" },
|
||||
timeout,
|
||||
})
|
||||
} else if (isAzureOpenAi) {
|
||||
// Azure API shape slightly differs from the core API shape:
|
||||
// https://github.com/openai/openai-node?tab=readme-ov-file#microsoft-azure-openai
|
||||
this.client = new AzureOpenAI({
|
||||
baseURL,
|
||||
apiKey,
|
||||
apiVersion: this.options.azureApiVersion || azureOpenAiDefaultApiVersion,
|
||||
defaultHeaders: headers,
|
||||
timeout,
|
||||
})
|
||||
// Create the appropriate handler
|
||||
if (this.useResponsesApi) {
|
||||
this.handler = new OpenAIResponsesHandler(options)
|
||||
} else {
|
||||
this.client = new OpenAI({
|
||||
baseURL,
|
||||
apiKey,
|
||||
defaultHeaders: headers,
|
||||
timeout,
|
||||
})
|
||||
this.handler = new OpenAIChatCompletionsHandler(options)
|
||||
}
|
||||
}
|
||||
|
||||
override async *createMessage(
|
||||
/**
|
||||
* Determines whether to use the Responses API based on URL patterns and configuration
|
||||
*/
|
||||
private shouldUseResponsesApi(options: ApiHandlerOptions): boolean {
|
||||
// Check URL pattern for /v1/responses endpoint
|
||||
const baseUrl = options.openAiBaseUrl ?? ""
|
||||
if (baseUrl.includes("/v1/responses") || baseUrl.endsWith("/responses")) {
|
||||
return true
|
||||
}
|
||||
|
||||
// Check if it's a GPT-5 model (which should use Responses API)
|
||||
const modelId = options.openAiModelId ?? ""
|
||||
if (modelId.startsWith("gpt-5")) {
|
||||
return true
|
||||
}
|
||||
|
||||
// Check if it's configured for OpenAI Native (which uses Responses API)
|
||||
if (options.openAiNativeApiKey && !options.openAiApiKey) {
|
||||
return true
|
||||
}
|
||||
|
||||
// Default to Chat Completions API for backward compatibility
|
||||
return false
|
||||
}
|
||||
|
||||
async *createMessage(
|
||||
systemPrompt: string,
|
||||
messages: Anthropic.Messages.MessageParam[],
|
||||
metadata?: ApiHandlerCreateMessageMetadata,
|
||||
): ApiStream {
|
||||
const { info: modelInfo, reasoning } = this.getModel()
|
||||
const modelUrl = this.options.openAiBaseUrl ?? ""
|
||||
const modelId = this.options.openAiModelId ?? ""
|
||||
const enabledR1Format = this.options.openAiR1FormatEnabled ?? false
|
||||
const enabledLegacyFormat = this.options.openAiLegacyFormat ?? false
|
||||
const isAzureAiInference = this._isAzureAiInference(modelUrl)
|
||||
const deepseekReasoner = modelId.includes("deepseek-reasoner") || enabledR1Format
|
||||
const ark = modelUrl.includes(".volces.com")
|
||||
|
||||
if (modelId.includes("o1") || modelId.includes("o3") || modelId.includes("o4")) {
|
||||
yield* this.handleO3FamilyMessage(modelId, systemPrompt, messages)
|
||||
return
|
||||
}
|
||||
|
||||
if (this.options.openAiStreamingEnabled ?? true) {
|
||||
let systemMessage: OpenAI.Chat.ChatCompletionSystemMessageParam = {
|
||||
role: "system",
|
||||
content: systemPrompt,
|
||||
}
|
||||
|
||||
let convertedMessages
|
||||
|
||||
if (deepseekReasoner) {
|
||||
convertedMessages = convertToR1Format([{ role: "user", content: systemPrompt }, ...messages])
|
||||
} else if (ark || enabledLegacyFormat) {
|
||||
convertedMessages = [systemMessage, ...convertToSimpleMessages(messages)]
|
||||
} else {
|
||||
if (modelInfo.supportsPromptCache) {
|
||||
systemMessage = {
|
||||
role: "system",
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: systemPrompt,
|
||||
// @ts-ignore-next-line
|
||||
cache_control: { type: "ephemeral" },
|
||||
},
|
||||
],
|
||||
}
|
||||
}
|
||||
|
||||
convertedMessages = [systemMessage, ...convertToOpenAiMessages(messages)]
|
||||
|
||||
if (modelInfo.supportsPromptCache) {
|
||||
// Note: the following logic is copied from openrouter:
|
||||
// Add cache_control to the last two user messages
|
||||
// (note: this works because we only ever add one user message at a time, but if we added multiple we'd need to mark the user message before the last assistant message)
|
||||
const lastTwoUserMessages = convertedMessages.filter((msg) => msg.role === "user").slice(-2)
|
||||
|
||||
lastTwoUserMessages.forEach((msg) => {
|
||||
if (typeof msg.content === "string") {
|
||||
msg.content = [{ type: "text", text: msg.content }]
|
||||
}
|
||||
|
||||
if (Array.isArray(msg.content)) {
|
||||
// NOTE: this is fine since env details will always be added at the end. but if it weren't there, and the user added a image_url type message, it would pop a text part before it and then move it after to the end.
|
||||
let lastTextPart = msg.content.filter((part) => part.type === "text").pop()
|
||||
|
||||
if (!lastTextPart) {
|
||||
lastTextPart = { type: "text", text: "..." }
|
||||
msg.content.push(lastTextPart)
|
||||
}
|
||||
|
||||
// @ts-ignore-next-line
|
||||
lastTextPart["cache_control"] = { type: "ephemeral" }
|
||||
}
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
const isGrokXAI = this._isGrokXAI(this.options.openAiBaseUrl)
|
||||
|
||||
const requestOptions: OpenAI.Chat.Completions.ChatCompletionCreateParamsStreaming = {
|
||||
model: modelId,
|
||||
temperature: this.options.modelTemperature ?? (deepseekReasoner ? DEEP_SEEK_DEFAULT_TEMPERATURE : 0),
|
||||
messages: convertedMessages,
|
||||
stream: true as const,
|
||||
...(isGrokXAI ? {} : { stream_options: { include_usage: true } }),
|
||||
...(reasoning && reasoning),
|
||||
}
|
||||
|
||||
// Add max_tokens if needed
|
||||
this.addMaxTokensIfNeeded(requestOptions, modelInfo)
|
||||
|
||||
let stream
|
||||
try {
|
||||
stream = await this.client.chat.completions.create(
|
||||
requestOptions,
|
||||
isAzureAiInference ? { path: OPENAI_AZURE_AI_INFERENCE_PATH } : {},
|
||||
)
|
||||
} catch (error) {
|
||||
throw handleOpenAIError(error, this.providerName)
|
||||
}
|
||||
|
||||
const matcher = new XmlMatcher(
|
||||
"think",
|
||||
(chunk) =>
|
||||
({
|
||||
type: chunk.matched ? "reasoning" : "text",
|
||||
text: chunk.data,
|
||||
}) as const,
|
||||
)
|
||||
|
||||
let lastUsage
|
||||
|
||||
for await (const chunk of stream) {
|
||||
const delta = chunk.choices[0]?.delta ?? {}
|
||||
|
||||
if (delta.content) {
|
||||
for (const chunk of matcher.update(delta.content)) {
|
||||
yield chunk
|
||||
}
|
||||
}
|
||||
|
||||
if ("reasoning_content" in delta && delta.reasoning_content) {
|
||||
yield {
|
||||
type: "reasoning",
|
||||
text: (delta.reasoning_content as string | undefined) || "",
|
||||
}
|
||||
}
|
||||
if (chunk.usage) {
|
||||
lastUsage = chunk.usage
|
||||
}
|
||||
}
|
||||
|
||||
for (const chunk of matcher.final()) {
|
||||
yield chunk
|
||||
}
|
||||
|
||||
if (lastUsage) {
|
||||
yield this.processUsageMetrics(lastUsage, modelInfo)
|
||||
}
|
||||
} else {
|
||||
// o1 for instance doesnt support streaming, non-1 temp, or system prompt
|
||||
const systemMessage: OpenAI.Chat.ChatCompletionUserMessageParam = {
|
||||
role: "user",
|
||||
content: systemPrompt,
|
||||
}
|
||||
|
||||
const requestOptions: OpenAI.Chat.Completions.ChatCompletionCreateParamsNonStreaming = {
|
||||
model: modelId,
|
||||
messages: deepseekReasoner
|
||||
? convertToR1Format([{ role: "user", content: systemPrompt }, ...messages])
|
||||
: enabledLegacyFormat
|
||||
? [systemMessage, ...convertToSimpleMessages(messages)]
|
||||
: [systemMessage, ...convertToOpenAiMessages(messages)],
|
||||
}
|
||||
|
||||
// Add max_tokens if needed
|
||||
this.addMaxTokensIfNeeded(requestOptions, modelInfo)
|
||||
|
||||
let response
|
||||
try {
|
||||
response = await this.client.chat.completions.create(
|
||||
requestOptions,
|
||||
this._isAzureAiInference(modelUrl) ? { path: OPENAI_AZURE_AI_INFERENCE_PATH } : {},
|
||||
)
|
||||
} catch (error) {
|
||||
throw handleOpenAIError(error, this.providerName)
|
||||
}
|
||||
|
||||
yield {
|
||||
type: "text",
|
||||
text: response.choices[0]?.message.content || "",
|
||||
}
|
||||
|
||||
yield this.processUsageMetrics(response.usage, modelInfo)
|
||||
}
|
||||
yield* this.handler.createMessage(systemPrompt, messages, metadata)
|
||||
}
|
||||
|
||||
protected processUsageMetrics(usage: any, _modelInfo?: ModelInfo): ApiStreamUsageChunk {
|
||||
return {
|
||||
type: "usage",
|
||||
inputTokens: usage?.prompt_tokens || 0,
|
||||
outputTokens: usage?.completion_tokens || 0,
|
||||
cacheWriteTokens: usage?.cache_creation_input_tokens || undefined,
|
||||
cacheReadTokens: usage?.cache_read_input_tokens || undefined,
|
||||
}
|
||||
}
|
||||
|
||||
override getModel() {
|
||||
const id = this.options.openAiModelId ?? ""
|
||||
const info = this.options.openAiCustomModelInfo ?? openAiModelInfoSaneDefaults
|
||||
const params = getModelParams({ format: "openai", modelId: id, model: info, settings: this.options })
|
||||
return { id, info, ...params }
|
||||
getModel() {
|
||||
return this.handler.getModel()
|
||||
}
|
||||
|
||||
async completePrompt(prompt: string): Promise<string> {
|
||||
try {
|
||||
const isAzureAiInference = this._isAzureAiInference(this.options.openAiBaseUrl)
|
||||
const model = this.getModel()
|
||||
const modelInfo = model.info
|
||||
|
||||
const requestOptions: OpenAI.Chat.Completions.ChatCompletionCreateParamsNonStreaming = {
|
||||
model: model.id,
|
||||
messages: [{ role: "user", content: prompt }],
|
||||
}
|
||||
|
||||
// Add max_tokens if needed
|
||||
this.addMaxTokensIfNeeded(requestOptions, modelInfo)
|
||||
|
||||
let response
|
||||
try {
|
||||
response = await this.client.chat.completions.create(
|
||||
requestOptions,
|
||||
isAzureAiInference ? { path: OPENAI_AZURE_AI_INFERENCE_PATH } : {},
|
||||
)
|
||||
} catch (error) {
|
||||
throw handleOpenAIError(error, this.providerName)
|
||||
}
|
||||
|
||||
return response.choices[0]?.message.content || ""
|
||||
} catch (error) {
|
||||
if (error instanceof Error) {
|
||||
throw new Error(`${this.providerName} completion error: ${error.message}`)
|
||||
}
|
||||
|
||||
throw error
|
||||
}
|
||||
}
|
||||
|
||||
private async *handleO3FamilyMessage(
|
||||
modelId: string,
|
||||
systemPrompt: string,
|
||||
messages: Anthropic.Messages.MessageParam[],
|
||||
): ApiStream {
|
||||
const modelInfo = this.getModel().info
|
||||
const methodIsAzureAiInference = this._isAzureAiInference(this.options.openAiBaseUrl)
|
||||
|
||||
if (this.options.openAiStreamingEnabled ?? true) {
|
||||
const isGrokXAI = this._isGrokXAI(this.options.openAiBaseUrl)
|
||||
|
||||
const requestOptions: OpenAI.Chat.Completions.ChatCompletionCreateParamsStreaming = {
|
||||
model: modelId,
|
||||
messages: [
|
||||
{
|
||||
role: "developer",
|
||||
content: `Formatting re-enabled\n${systemPrompt}`,
|
||||
},
|
||||
...convertToOpenAiMessages(messages),
|
||||
],
|
||||
stream: true,
|
||||
...(isGrokXAI ? {} : { stream_options: { include_usage: true } }),
|
||||
reasoning_effort: modelInfo.reasoningEffort as "low" | "medium" | "high" | undefined,
|
||||
temperature: undefined,
|
||||
}
|
||||
|
||||
// O3 family models do not support the deprecated max_tokens parameter
|
||||
// but they do support max_completion_tokens (the modern OpenAI parameter)
|
||||
// This allows O3 models to limit response length when includeMaxTokens is enabled
|
||||
this.addMaxTokensIfNeeded(requestOptions, modelInfo)
|
||||
|
||||
let stream
|
||||
try {
|
||||
stream = await this.client.chat.completions.create(
|
||||
requestOptions,
|
||||
methodIsAzureAiInference ? { path: OPENAI_AZURE_AI_INFERENCE_PATH } : {},
|
||||
)
|
||||
} catch (error) {
|
||||
throw handleOpenAIError(error, this.providerName)
|
||||
}
|
||||
|
||||
yield* this.handleStreamResponse(stream)
|
||||
} else {
|
||||
const requestOptions: OpenAI.Chat.Completions.ChatCompletionCreateParamsNonStreaming = {
|
||||
model: modelId,
|
||||
messages: [
|
||||
{
|
||||
role: "developer",
|
||||
content: `Formatting re-enabled\n${systemPrompt}`,
|
||||
},
|
||||
...convertToOpenAiMessages(messages),
|
||||
],
|
||||
reasoning_effort: modelInfo.reasoningEffort as "low" | "medium" | "high" | undefined,
|
||||
temperature: undefined,
|
||||
}
|
||||
|
||||
// O3 family models do not support the deprecated max_tokens parameter
|
||||
// but they do support max_completion_tokens (the modern OpenAI parameter)
|
||||
// This allows O3 models to limit response length when includeMaxTokens is enabled
|
||||
this.addMaxTokensIfNeeded(requestOptions, modelInfo)
|
||||
|
||||
let response
|
||||
try {
|
||||
response = await this.client.chat.completions.create(
|
||||
requestOptions,
|
||||
methodIsAzureAiInference ? { path: OPENAI_AZURE_AI_INFERENCE_PATH } : {},
|
||||
)
|
||||
} catch (error) {
|
||||
throw handleOpenAIError(error, this.providerName)
|
||||
}
|
||||
|
||||
yield {
|
||||
type: "text",
|
||||
text: response.choices[0]?.message.content || "",
|
||||
}
|
||||
yield this.processUsageMetrics(response.usage)
|
||||
}
|
||||
}
|
||||
|
||||
private async *handleStreamResponse(stream: AsyncIterable<OpenAI.Chat.Completions.ChatCompletionChunk>): ApiStream {
|
||||
for await (const chunk of stream) {
|
||||
const delta = chunk.choices[0]?.delta
|
||||
if (delta?.content) {
|
||||
yield {
|
||||
type: "text",
|
||||
text: delta.content,
|
||||
}
|
||||
}
|
||||
|
||||
if (chunk.usage) {
|
||||
yield {
|
||||
type: "usage",
|
||||
inputTokens: chunk.usage.prompt_tokens || 0,
|
||||
outputTokens: chunk.usage.completion_tokens || 0,
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
private _getUrlHost(baseUrl?: string): string {
|
||||
try {
|
||||
return new URL(baseUrl ?? "").host
|
||||
} catch (error) {
|
||||
return ""
|
||||
}
|
||||
}
|
||||
|
||||
private _isGrokXAI(baseUrl?: string): boolean {
|
||||
const urlHost = this._getUrlHost(baseUrl)
|
||||
return urlHost.includes("x.ai")
|
||||
}
|
||||
|
||||
private _isAzureAiInference(baseUrl?: string): boolean {
|
||||
const urlHost = this._getUrlHost(baseUrl)
|
||||
return urlHost.endsWith(".services.ai.azure.com")
|
||||
return this.handler.completePrompt(prompt)
|
||||
}
|
||||
|
||||
/**
|
||||
* Adds max_completion_tokens to the request body if needed based on provider configuration
|
||||
* Note: max_tokens is deprecated in favor of max_completion_tokens as per OpenAI documentation
|
||||
* O3 family models handle max_tokens separately in handleO3FamilyMessage
|
||||
* Get information about which API is being used
|
||||
*/
|
||||
protected addMaxTokensIfNeeded(
|
||||
requestOptions:
|
||||
| OpenAI.Chat.Completions.ChatCompletionCreateParamsStreaming
|
||||
| OpenAI.Chat.Completions.ChatCompletionCreateParamsNonStreaming,
|
||||
modelInfo: ModelInfo,
|
||||
): void {
|
||||
// Only add max_completion_tokens if includeMaxTokens is true
|
||||
if (this.options.includeMaxTokens === true) {
|
||||
// Use user-configured modelMaxTokens if available, otherwise fall back to model's default maxTokens
|
||||
// Using max_completion_tokens as max_tokens is deprecated
|
||||
requestOptions.max_completion_tokens = this.options.modelMaxTokens || modelInfo.maxTokens
|
||||
getApiType(): "chat-completions" | "responses" {
|
||||
return this.useResponsesApi ? "responses" : "chat-completions"
|
||||
}
|
||||
|
||||
/**
|
||||
* For Responses API, get the last response ID for conversation continuity
|
||||
*/
|
||||
getLastResponseId(): string | undefined {
|
||||
if (this.handler instanceof OpenAIResponsesHandler) {
|
||||
return this.handler.getLastResponseId()
|
||||
}
|
||||
return undefined
|
||||
}
|
||||
|
||||
/**
|
||||
* For Responses API, set the response ID for conversation continuity
|
||||
*/
|
||||
setResponseId(responseId: string): void {
|
||||
if (this.handler instanceof OpenAIResponsesHandler) {
|
||||
this.handler.setResponseId(responseId)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue