Fixes #710 This PR implements comprehensive Azure OpenAI integration for Dyad, enabling users to leverage Azure OpenAI models through proper environment variable configuration. The implementation adds Azure as a supported provider with full integration into the existing language model architecture, including support for GPT-5 models. Key features include environment-based configuration using `AZURE_API_KEY` and `AZURE_RESOURCE_NAME`, specialized UI components that provide clear setup instructions and status indicators, and seamless integration with Dyad's existing provider system. The Azure provider leverages the @ai-sdk/azure package (v1.3.25) for compatibility with the current TypeScript language model interfaces. The implementation includes robust error handling for missing configuration, comprehensive test coverage with 9 new unit tests covering critical functionality like model client creation and error scenarios, and an E2E test for the Azure-specific settings UI. <img width="1510" height="908" alt="Screenshot 2025-08-18 at 9 14 32 PM" src="https://github.com/user-attachments/assets/04aa99e1-1590-4bb0-86c9-a67b97bc7500" /> --------- Co-authored-by: graphite-app[bot] <96075541+graphite-app[bot]@users.noreply.github.com> Co-authored-by: Will Chen <willchen90@gmail.com>
194 lines
5.1 KiB
TypeScript
194 lines
5.1 KiB
TypeScript
import express from "express";
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import { createServer } from "http";
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import cors from "cors";
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import { createChatCompletionHandler } from "./chatCompletionHandler";
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import {
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handleDeviceCode,
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handleAccessToken,
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handleUser,
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handleUserEmails,
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handleUserRepos,
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handleRepo,
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handleRepoBranches,
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handleOrgRepos,
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handleGitPush,
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handleGetPushEvents,
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handleClearPushEvents,
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} from "./githubHandler";
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// Create Express app
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const app = express();
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app.use(cors());
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app.use(express.json({ limit: "50mb" }));
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app.use(express.urlencoded({ extended: true, limit: "50mb" }));
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const PORT = 3500;
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// Helper function to create OpenAI-like streaming response chunks
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export function createStreamChunk(
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content: string,
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role: string = "assistant",
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isLast: boolean = false,
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) {
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const chunk = {
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id: `chatcmpl-${Date.now()}`,
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object: "chat.completion.chunk",
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created: Math.floor(Date.now() / 1000),
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model: "fake-model",
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choices: [
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{
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index: 0,
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delta: isLast ? {} : { content, role },
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finish_reason: isLast ? "stop" : null,
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},
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],
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};
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return `data: ${JSON.stringify(chunk)}\n\n${isLast ? "data: [DONE]\n\n" : ""}`;
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}
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export const CANNED_MESSAGE = `
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<dyad-write path="file1.txt">
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A file (2)
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</dyad-write>
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More
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EOM`;
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app.get("/health", (req, res) => {
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res.send("OK");
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});
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// Ollama-specific endpoints
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app.get("/ollama/api/tags", (req, res) => {
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const ollamaModels = {
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models: [
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{
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name: "testollama",
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modified_at: "2024-05-01T10:00:00.000Z",
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size: 4700000000,
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digest: "abcdef123456",
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details: {
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format: "gguf",
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family: "llama",
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families: ["llama"],
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parameter_size: "8B",
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quantization_level: "Q4_0",
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},
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},
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{
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name: "codellama:7b",
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modified_at: "2024-04-25T12:30:00.000Z",
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size: 3800000000,
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digest: "fedcba654321",
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details: {
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format: "gguf",
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family: "llama",
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families: ["llama", "codellama"],
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parameter_size: "7B",
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quantization_level: "Q5_K_M",
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},
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},
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],
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};
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console.log("* Sending fake Ollama models");
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res.json(ollamaModels);
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});
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// LM Studio specific endpoints
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app.get("/lmstudio/api/v0/models", (req, res) => {
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const lmStudioModels = {
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data: [
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{
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type: "llm",
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id: "lmstudio-model-1",
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object: "model",
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publisher: "lmstudio",
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state: "loaded",
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max_context_length: 4096,
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quantization: "Q4_0",
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compatibility_type: "gguf",
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arch: "llama",
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},
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{
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type: "llm",
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id: "lmstudio-model-2-chat",
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object: "model",
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publisher: "lmstudio",
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state: "not-loaded",
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max_context_length: 8192,
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quantization: "Q5_K_M",
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compatibility_type: "gguf",
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arch: "mixtral",
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},
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{
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type: "embedding", // Should be filtered out by client
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id: "lmstudio-embedding-model",
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object: "model",
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publisher: "lmstudio",
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state: "loaded",
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max_context_length: 2048,
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quantization: "F16",
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compatibility_type: "gguf",
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arch: "bert",
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},
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],
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};
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console.log("* Sending fake LM Studio models");
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res.json(lmStudioModels);
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});
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["lmstudio", "gateway", "engine", "ollama", "azure"].forEach((provider) => {
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app.post(
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`/${provider}/v1/chat/completions`,
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createChatCompletionHandler(provider),
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);
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});
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// Azure-specific endpoints (Azure client uses different URL patterns)
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app.post("/azure/chat/completions", createChatCompletionHandler("azure"));
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app.post(
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"/azure/openai/deployments/:deploymentId/chat/completions",
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createChatCompletionHandler("azure"),
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);
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// Default test provider handler:
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app.post("/v1/chat/completions", createChatCompletionHandler("."));
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// GitHub API Mock Endpoints
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console.log("Setting up GitHub mock endpoints");
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// GitHub OAuth Device Flow
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app.post("/github/login/device/code", handleDeviceCode);
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app.post("/github/login/oauth/access_token", handleAccessToken);
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// GitHub API endpoints
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app.get("/github/api/user", handleUser);
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app.get("/github/api/user/emails", handleUserEmails);
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app.get("/github/api/user/repos", handleUserRepos);
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app.post("/github/api/user/repos", handleUserRepos);
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app.get("/github/api/repos/:owner/:repo", handleRepo);
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app.get("/github/api/repos/:owner/:repo/branches", handleRepoBranches);
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app.post("/github/api/orgs/:org/repos", handleOrgRepos);
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// GitHub test endpoints for verifying push operations
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app.get("/github/api/test/push-events", handleGetPushEvents);
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app.post("/github/api/test/clear-push-events", handleClearPushEvents);
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// GitHub Git endpoints - intercept all paths with /github/git prefix
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app.all("/github/git/*", handleGitPush);
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// Start the server
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const server = createServer(app);
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server.listen(PORT, () => {
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console.log(`Fake LLM server running on http://localhost:${PORT}`);
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});
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// Handle SIGINT (Ctrl+C)
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process.on("SIGINT", () => {
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console.log("Shutting down fake LLM server");
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server.close(() => {
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console.log("Server closed");
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process.exit(0);
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});
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});
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