Merge pull request #367 from RooVetGit/vscode-lm-provider

Add VSCode-LM as a provider

Author: mrubens

.changeset/eleven-papayas-fold.md

@@ -0,0 +1,5 @@
+---
+"roo-cline": patch
+---
+
+Experimental support for VS Code Language Models (thanks @RaySinner / @julesmons!)

README.md

@@ -60,6 +60,7 @@ Give it a try and let us know what you think in the reddit: https://www.reddit.c
 - Support for Glama
 - Support for listing models from OpenAI-compatible providers
 - Support for adding OpenAI-compatible models with or without streaming
+- Experimental support for VS Code Language Models (e.g. Copilot)
 - Per-tool MCP auto-approval
 - Enable/disable individual MCP servers
 - Enable/disable the MCP feature overall

package.json

@@ -42,7 +42,10 @@
     "ai",
     "llama"
   ],
-  "activationEvents": [],
+  "activationEvents": [
+    "onLanguage",
+    "onStartupFinished"
+  ],
   "main": "./dist/extension.js",
   "contributes": {
     "viewsContainers": {
@@ -151,6 +154,20 @@
             "git show"
           ],
           "description": "Commands that can be auto-executed when 'Always approve execute operations' is enabled"
+        },
+        "roo-cline.vsCodeLmModelSelector": {
+          "type": "object",
+          "properties": {
+            "vendor": {
+              "type": "string",
+              "description": "The vendor of the language model (e.g. copilot)"
+            },
+            "family": {
+              "type": "string", 
+              "description": "The family of the language model (e.g. gpt-4)"
+            }
+          },
+          "description": "Settings for VSCode Language Model API"
         }
       }
     }

src/api/index.ts

@@ -11,6 +11,7 @@ import { LmStudioHandler } from "./providers/lmstudio"
 import { GeminiHandler } from "./providers/gemini"
 import { OpenAiNativeHandler } from "./providers/openai-native"
 import { DeepSeekHandler } from "./providers/deepseek"
+import { VsCodeLmHandler } from "./providers/vscode-lm"
 import { ApiStream } from "./transform/stream"
 
 export interface SingleCompletionHandler {

src/api/providers/__tests__/vscode-lm.test.ts

@@ -0,0 +1,289 @@
+import * as vscode from 'vscode';
+import { VsCodeLmHandler } from '../vscode-lm';
+import { ApiHandlerOptions } from '../../../shared/api';
+import { Anthropic } from '@anthropic-ai/sdk';
+
+// Mock vscode namespace
+jest.mock('vscode', () => {
+	class MockLanguageModelTextPart {
+		type = 'text';
+		constructor(public value: string) {}
+	}
+
+	class MockLanguageModelToolCallPart {
+		type = 'tool_call';
+		constructor(
+			public callId: string,
+			public name: string,
+			public input: any
+		) {}
+	}
+
+	return {
+		workspace: {
+			onDidChangeConfiguration: jest.fn((callback) => ({
+				dispose: jest.fn()
+			}))
+		},
+		CancellationTokenSource: jest.fn(() => ({
+			token: {
+				isCancellationRequested: false,
+				onCancellationRequested: jest.fn()
+			},
+			cancel: jest.fn(),
+			dispose: jest.fn()
+		})),
+		CancellationError: class CancellationError extends Error {
+			constructor() {
+				super('Operation cancelled');
+				this.name = 'CancellationError';
+			}
+		},
+		LanguageModelChatMessage: {
+			Assistant: jest.fn((content) => ({
+				role: 'assistant',
+				content: Array.isArray(content) ? content : [new MockLanguageModelTextPart(content)]
+			})),
+			User: jest.fn((content) => ({
+				role: 'user',
+				content: Array.isArray(content) ? content : [new MockLanguageModelTextPart(content)]
+			}))
+		},
+		LanguageModelTextPart: MockLanguageModelTextPart,
+		LanguageModelToolCallPart: MockLanguageModelToolCallPart,
+		lm: {
+			selectChatModels: jest.fn()
+		}
+	};
+});
+
+const mockLanguageModelChat = {
+	id: 'test-model',
+	name: 'Test Model',
+	vendor: 'test-vendor',
+	family: 'test-family',
+	version: '1.0',
+	maxInputTokens: 4096,
+	sendRequest: jest.fn(),
+	countTokens: jest.fn()
+};
+
+describe('VsCodeLmHandler', () => {
+	let handler: VsCodeLmHandler;
+	const defaultOptions: ApiHandlerOptions = {
+		vsCodeLmModelSelector: {
+			vendor: 'test-vendor',
+			family: 'test-family'
+		}
+	};
+
+	beforeEach(() => {
+		jest.clearAllMocks();
+		handler = new VsCodeLmHandler(defaultOptions);
+	});
+
+	afterEach(() => {
+		handler.dispose();
+	});
+
+	describe('constructor', () => {
+		it('should initialize with provided options', () => {
+			expect(handler).toBeDefined();
+			expect(vscode.workspace.onDidChangeConfiguration).toHaveBeenCalled();
+		});
+
+		it('should handle configuration changes', () => {
+			const callback = (vscode.workspace.onDidChangeConfiguration as jest.Mock).mock.calls[0][0];
+			callback({ affectsConfiguration: () => true });
+			// Should reset client when config changes
+			expect(handler['client']).toBeNull();
+		});
+	});
+
+	describe('createClient', () => {
+		it('should create client with selector', async () => {
+			const mockModel = { ...mockLanguageModelChat };
+			(vscode.lm.selectChatModels as jest.Mock).mockResolvedValueOnce([mockModel]);
+
+			const client = await handler['createClient']({
+				vendor: 'test-vendor',
+				family: 'test-family'
+			});
+
+			expect(client).toBeDefined();
+			expect(client.id).toBe('test-model');
+			expect(vscode.lm.selectChatModels).toHaveBeenCalledWith({
+				vendor: 'test-vendor',
+				family: 'test-family'
+			});
+		});
+
+		it('should return default client when no models available', async () => {
+			(vscode.lm.selectChatModels as jest.Mock).mockResolvedValueOnce([]);
+
+			const client = await handler['createClient']({});
+			
+			expect(client).toBeDefined();
+			expect(client.id).toBe('default-lm');
+			expect(client.vendor).toBe('vscode');
+		});
+	});
+
+	describe('createMessage', () => {
+		beforeEach(() => {
+			const mockModel = { ...mockLanguageModelChat };
+			(vscode.lm.selectChatModels as jest.Mock).mockResolvedValueOnce([mockModel]);
+			mockLanguageModelChat.countTokens.mockResolvedValue(10);
+		});
+
+		it('should stream text responses', async () => {
+			const systemPrompt = 'You are a helpful assistant';
+			const messages: Anthropic.Messages.MessageParam[] = [{
+				role: 'user' as const,
+				content: 'Hello'
+			}];
+
+			const responseText = 'Hello! How can I help you?';
+			mockLanguageModelChat.sendRequest.mockResolvedValueOnce({
+				stream: (async function* () {
+					yield new vscode.LanguageModelTextPart(responseText);
+					return;
+				})(),
+				text: (async function* () {
+					yield responseText;
+					return;
+				})()
+			});
+
+			const stream = handler.createMessage(systemPrompt, messages);
+			const chunks = [];
+			for await (const chunk of stream) {
+				chunks.push(chunk);
+			}
+
+			expect(chunks).toHaveLength(2); // Text chunk + usage chunk
+			expect(chunks[0]).toEqual({
+				type: 'text',
+				text: responseText
+			});
+			expect(chunks[1]).toMatchObject({
+				type: 'usage',
+				inputTokens: expect.any(Number),
+				outputTokens: expect.any(Number)
+			});
+		});
+
+		it('should handle tool calls', async () => {
+			const systemPrompt = 'You are a helpful assistant';
+			const messages: Anthropic.Messages.MessageParam[] = [{
+				role: 'user' as const,
+				content: 'Calculate 2+2'
+			}];
+
+			const toolCallData = {
+				name: 'calculator',
+				arguments: { operation: 'add', numbers: [2, 2] },
+				callId: 'call-1'
+			};
+
+			mockLanguageModelChat.sendRequest.mockResolvedValueOnce({
+				stream: (async function* () {
+					yield new vscode.LanguageModelToolCallPart(
+						toolCallData.callId,
+						toolCallData.name,
+						toolCallData.arguments
+					);
+					return;
+				})(),
+				text: (async function* () {
+					yield JSON.stringify({ type: 'tool_call', ...toolCallData });
+					return;
+				})()
+			});
+
+			const stream = handler.createMessage(systemPrompt, messages);
+			const chunks = [];
+			for await (const chunk of stream) {
+				chunks.push(chunk);
+			}
+
+			expect(chunks).toHaveLength(2); // Tool call chunk + usage chunk
+			expect(chunks[0]).toEqual({
+				type: 'text',
+				text: JSON.stringify({ type: 'tool_call', ...toolCallData })
+			});
+		});
+
+		it('should handle errors', async () => {
+			const systemPrompt = 'You are a helpful assistant';
+			const messages: Anthropic.Messages.MessageParam[] = [{
+				role: 'user' as const,
+				content: 'Hello'
+			}];
+
+			mockLanguageModelChat.sendRequest.mockRejectedValueOnce(new Error('API Error'));
+
+			await expect(async () => {
+				const stream = handler.createMessage(systemPrompt, messages);
+				for await (const _ of stream) {
+					// consume stream
+				}
+			}).rejects.toThrow('API Error');
+		});
+	});
+
+	describe('getModel', () => {
+		it('should return model info when client exists', async () => {
+			const mockModel = { ...mockLanguageModelChat };
+			(vscode.lm.selectChatModels as jest.Mock).mockResolvedValueOnce([mockModel]);
+			
+			// Initialize client
+			await handler['getClient']();
+			
+			const model = handler.getModel();
+			expect(model.id).toBe('test-model');
+			expect(model.info).toBeDefined();
+			expect(model.info.contextWindow).toBe(4096);
+		});
+
+		it('should return fallback model info when no client exists', () => {
+			const model = handler.getModel();
+			expect(model.id).toBe('test-vendor/test-family');
+			expect(model.info).toBeDefined();
+		});
+	});
+
+	describe('completePrompt', () => {
+		it('should complete single prompt', async () => {
+			const mockModel = { ...mockLanguageModelChat };
+			(vscode.lm.selectChatModels as jest.Mock).mockResolvedValueOnce([mockModel]);
+
+			const responseText = 'Completed text';
+			mockLanguageModelChat.sendRequest.mockResolvedValueOnce({
+				stream: (async function* () {
+					yield new vscode.LanguageModelTextPart(responseText);
+					return;
+				})(),
+				text: (async function* () {
+					yield responseText;
+					return;
+				})()
+			});
+
+			const result = await handler.completePrompt('Test prompt');
+			expect(result).toBe(responseText);
+			expect(mockLanguageModelChat.sendRequest).toHaveBeenCalled();
+		});
+
+		it('should handle errors during completion', async () => {
+			const mockModel = { ...mockLanguageModelChat };
+			(vscode.lm.selectChatModels as jest.Mock).mockResolvedValueOnce([mockModel]);
+
+			mockLanguageModelChat.sendRequest.mockRejectedValueOnce(new Error('Completion failed'));
+
+			await expect(handler.completePrompt('Test prompt'))
+				.rejects
+				.toThrow('VSCode LM completion error: Completion failed');
+		});
+	});
+});