Merge remote-tracking branch 'origin/main' into vscode-lm-provider

src/api/providers/__tests__/anthropic.test.ts

@@ -0,0 +1,239 @@
+import { AnthropicHandler } from '../anthropic';
+import { ApiHandlerOptions } from '../../../shared/api';
+import { ApiStream } from '../../transform/stream';
+import { Anthropic } from '@anthropic-ai/sdk';
+
+// Mock Anthropic client
+const mockBetaCreate = jest.fn();
+const mockCreate = jest.fn();
+jest.mock('@anthropic-ai/sdk', () => {
+    return {
+        Anthropic: jest.fn().mockImplementation(() => ({
+            beta: {
+                promptCaching: {
+                    messages: {
+                        create: mockBetaCreate.mockImplementation(async () => ({
+                            async *[Symbol.asyncIterator]() {
+                                yield {
+                                    type: 'message_start',
+                                    message: {
+                                        usage: {
+                                            input_tokens: 100,
+                                            output_tokens: 50,
+                                            cache_creation_input_tokens: 20,
+                                            cache_read_input_tokens: 10
+                                        }
+                                    }
+                                };
+                                yield {
+                                    type: 'content_block_start',
+                                    index: 0,
+                                    content_block: {
+                                        type: 'text',
+                                        text: 'Hello'
+                                    }
+                                };
+                                yield {
+                                    type: 'content_block_delta',
+                                    delta: {
+                                        type: 'text_delta',
+                                        text: ' world'
+                                    }
+                                };
+                            }
+                        }))
+                    }
+                }
+            },
+            messages: {
+                create: mockCreate.mockImplementation(async (options) => {
+                    if (!options.stream) {
+                        return {
+                            id: 'test-completion',
+                            content: [
+                                { type: 'text', text: 'Test response' }
+                            ],
+                            role: 'assistant',
+                            model: options.model,
+                            usage: {
+                                input_tokens: 10,
+                                output_tokens: 5
+                            }
+                        }
+                    }
+                    return {
+                        async *[Symbol.asyncIterator]() {
+                            yield {
+                                type: 'message_start',
+                                message: {
+                                    usage: {
+                                        input_tokens: 10,
+                                        output_tokens: 5
+                                    }
+                                }
+                            }
+                            yield {
+                                type: 'content_block_start',
+                                content_block: {
+                                    type: 'text',
+                                    text: 'Test response'
+                                }
+                            }
+                        }
+                    }
+                })
+            }
+        }))
+    };
+});
+
+describe('AnthropicHandler', () => {
+    let handler: AnthropicHandler;
+    let mockOptions: ApiHandlerOptions;
+
+    beforeEach(() => {
+        mockOptions = {
+            apiKey: 'test-api-key',
+            apiModelId: 'claude-3-5-sonnet-20241022'
+        };
+        handler = new AnthropicHandler(mockOptions);
+        mockBetaCreate.mockClear();
+        mockCreate.mockClear();
+    });
+
+    describe('constructor', () => {
+        it('should initialize with provided options', () => {
+            expect(handler).toBeInstanceOf(AnthropicHandler);
+            expect(handler.getModel().id).toBe(mockOptions.apiModelId);
+        });
+
+        it('should initialize with undefined API key', () => {
+            // The SDK will handle API key validation, so we just verify it initializes
+            const handlerWithoutKey = new AnthropicHandler({
+                ...mockOptions,
+                apiKey: undefined
+            });
+            expect(handlerWithoutKey).toBeInstanceOf(AnthropicHandler);
+        });
+
+        it('should use custom base URL if provided', () => {
+            const customBaseUrl = 'https://custom.anthropic.com';
+            const handlerWithCustomUrl = new AnthropicHandler({
+                ...mockOptions,
+                anthropicBaseUrl: customBaseUrl
+            });
+            expect(handlerWithCustomUrl).toBeInstanceOf(AnthropicHandler);
+        });
+    });
+
+    describe('createMessage', () => {
+        const systemPrompt = 'You are a helpful assistant.';
+        const messages: Anthropic.Messages.MessageParam[] = [
+            {
+                role: 'user',
+                content: [{ 
+                    type: 'text' as const,
+                    text: 'Hello!'
+                }]
+            }
+        ];
+
+        it('should handle prompt caching for supported models', async () => {
+            const stream = handler.createMessage(systemPrompt, [
+                {
+                    role: 'user',
+                    content: [{ type: 'text' as const, text: 'First message' }]
+                },
+                {
+                    role: 'assistant',
+                    content: [{ type: 'text' as const, text: 'Response' }]
+                },
+                {
+                    role: 'user',
+                    content: [{ type: 'text' as const, text: 'Second message' }]
+                }
+            ]);
+
+            const chunks: any[] = [];
+            for await (const chunk of stream) {
+                chunks.push(chunk);
+            }
+
+            // Verify usage information
+            const usageChunk = chunks.find(chunk => chunk.type === 'usage');
+            expect(usageChunk).toBeDefined();
+            expect(usageChunk?.inputTokens).toBe(100);
+            expect(usageChunk?.outputTokens).toBe(50);
+            expect(usageChunk?.cacheWriteTokens).toBe(20);
+            expect(usageChunk?.cacheReadTokens).toBe(10);
+
+            // Verify text content
+            const textChunks = chunks.filter(chunk => chunk.type === 'text');
+            expect(textChunks).toHaveLength(2);
+            expect(textChunks[0].text).toBe('Hello');
+            expect(textChunks[1].text).toBe(' world');
+
+            // Verify beta API was used
+            expect(mockBetaCreate).toHaveBeenCalled();
+            expect(mockCreate).not.toHaveBeenCalled();
+        });
+    });
+
+    describe('completePrompt', () => {
+        it('should complete prompt successfully', async () => {
+            const result = await handler.completePrompt('Test prompt');
+            expect(result).toBe('Test response');
+            expect(mockCreate).toHaveBeenCalledWith({
+                model: mockOptions.apiModelId,
+                messages: [{ role: 'user', content: 'Test prompt' }],
+                max_tokens: 8192,
+                temperature: 0,
+                stream: false
+            });
+        });
+
+        it('should handle API errors', async () => {
+            mockCreate.mockRejectedValueOnce(new Error('API Error'));
+            await expect(handler.completePrompt('Test prompt'))
+                .rejects.toThrow('Anthropic completion error: API Error');
+        });
+
+        it('should handle non-text content', async () => {
+            mockCreate.mockImplementationOnce(async () => ({
+                content: [{ type: 'image' }]
+            }));
+            const result = await handler.completePrompt('Test prompt');
+            expect(result).toBe('');
+        });
+
+        it('should handle empty response', async () => {
+            mockCreate.mockImplementationOnce(async () => ({
+                content: [{ type: 'text', text: '' }]
+            }));
+            const result = await handler.completePrompt('Test prompt');
+            expect(result).toBe('');
+        });
+    });
+
+    describe('getModel', () => {
+        it('should return default model if no model ID is provided', () => {
+            const handlerWithoutModel = new AnthropicHandler({
+                ...mockOptions,
+                apiModelId: undefined
+            });
+            const model = handlerWithoutModel.getModel();
+            expect(model.id).toBeDefined();
+            expect(model.info).toBeDefined();
+        });
+
+        it('should return specified model if valid model ID is provided', () => {
+            const model = handler.getModel();
+            expect(model.id).toBe(mockOptions.apiModelId);
+            expect(model.info).toBeDefined();
+            expect(model.info.maxTokens).toBe(8192);
+            expect(model.info.contextWindow).toBe(200_000);
+            expect(model.info.supportsImages).toBe(true);
+            expect(model.info.supportsPromptCache).toBe(true);
+        });
+    });
+});

src/api/providers/__tests__/bedrock.test.ts

@@ -1,191 +1,246 @@
-import { AwsBedrockHandler } from '../bedrock'
-import { ApiHandlerOptions, ModelInfo } from '../../../shared/api'
-import { Anthropic } from '@anthropic-ai/sdk'
-import { StreamEvent } from '../bedrock'
-
-// Simplified mock for BedrockRuntimeClient
-class MockBedrockRuntimeClient {
-    private _region: string
-    private mockStream: StreamEvent[] = []
-
-    constructor(config: { region: string }) {
-        this._region = config.region
-    }
-
-    async send(command: any): Promise<{ stream: AsyncIterableIterator<StreamEvent> }> {
-        return {
-            stream: this.createMockStream()
-        }
-    }
-
-    private createMockStream(): AsyncIterableIterator<StreamEvent> {
-        const self = this;
-        return {
-            async *[Symbol.asyncIterator]() {
-                for (const event of self.mockStream) {
-                    yield event;
-                }
-            },
-            next: async () => {
-                const value = this.mockStream.shift();
-                return value ? { value, done: false } : { value: undefined, done: true };
-            },
-            return: async () => ({ value: undefined, done: true }),
-            throw: async (e) => { throw e; }
-        };
-    }
-
-    setMockStream(stream: StreamEvent[]) {
-        this.mockStream = stream;
-    }
-
-    get config() {
-        return { region: this._region };
-    }
-}
+import { AwsBedrockHandler } from '../bedrock';
+import { MessageContent } from '../../../shared/api';
+import { BedrockRuntimeClient } from '@aws-sdk/client-bedrock-runtime';
+import { Anthropic } from '@anthropic-ai/sdk';
 
 describe('AwsBedrockHandler', () => {
-    const mockOptions: ApiHandlerOptions = {
-        awsRegion: 'us-east-1',
-        awsAccessKey: 'mock-access-key',
-        awsSecretKey: 'mock-secret-key',
-        apiModelId: 'anthropic.claude-v2',
-    }
+    let handler: AwsBedrockHandler;
 
-    // Override the BedrockRuntimeClient creation in the constructor
-    class TestAwsBedrockHandler extends AwsBedrockHandler {
-        constructor(options: ApiHandlerOptions, mockClient?: MockBedrockRuntimeClient) {
-            super(options)
-            if (mockClient) {
-                // Force type casting to bypass strict type checking
-                (this as any)['client'] = mockClient
-            }
-        }
-    }
+    beforeEach(() => {
+        handler = new AwsBedrockHandler({
+            apiModelId: 'anthropic.claude-3-5-sonnet-20241022-v2:0',
+            awsAccessKey: 'test-access-key',
+            awsSecretKey: 'test-secret-key',
+            awsRegion: 'us-east-1'
+        });
+    });
 
-    test('constructor initializes with correct AWS credentials', () => {
-        const mockClient = new MockBedrockRuntimeClient({
-            region: 'us-east-1'
-        })
+    describe('constructor', () => {
+        it('should initialize with provided config', () => {
+            expect(handler['options'].awsAccessKey).toBe('test-access-key');
+            expect(handler['options'].awsSecretKey).toBe('test-secret-key');
+            expect(handler['options'].awsRegion).toBe('us-east-1');
+            expect(handler['options'].apiModelId).toBe('anthropic.claude-3-5-sonnet-20241022-v2:0');
+        });
 
-        const handler = new TestAwsBedrockHandler(mockOptions, mockClient)
-        
-        // Verify that the client is created with the correct configuration
-        expect(handler['client']).toBeDefined()
-        expect(handler['client'].config.region).toBe('us-east-1')
-    })
+        it('should initialize with missing AWS credentials', () => {
+            const handlerWithoutCreds = new AwsBedrockHandler({
+                apiModelId: 'anthropic.claude-3-5-sonnet-20241022-v2:0',
+                awsRegion: 'us-east-1'
+            });
+            expect(handlerWithoutCreds).toBeInstanceOf(AwsBedrockHandler);
+        });
+    });
 
-    test('getModel returns correct model info', () => {
-        const mockClient = new MockBedrockRuntimeClient({
-            region: 'us-east-1'
-        })
-
-        const handler = new TestAwsBedrockHandler(mockOptions, mockClient)
-        const result = handler.getModel()
-        
-        expect(result).toEqual({
-            id: 'anthropic.claude-v2',
-            info: {
-                maxTokens: 5000,
-                contextWindow: 128_000,
-                supportsPromptCache: false
-            }
-        })
-    })
-
-    test('createMessage handles successful stream events', async () => {
-        const mockClient = new MockBedrockRuntimeClient({
-            region: 'us-east-1'
-        })
-        
-        // Mock stream events
-        const mockStreamEvents: StreamEvent[] = [
+    describe('createMessage', () => {
+        const mockMessages: Anthropic.Messages.MessageParam[] = [
             {
-                metadata: {
-                    usage: {
-                        inputTokens: 50,
-                        outputTokens: 100
-                    }
-                }
+                role: 'user',
+                content: 'Hello'
             },
             {
-                contentBlockStart: {
-                    start: {
-                        text: 'Hello'
-                    }
-                }
-            },
-            {
-                contentBlockDelta: {
-                    delta: {
-                        text: ' world'
-                    }
-                }
-            },
-            {
-                messageStop: {
-                    stopReason: 'end_turn'
-                }
+                role: 'assistant',
+                content: 'Hi there!'
             }
-        ]
+        ];
 
-        mockClient.setMockStream(mockStreamEvents)
+        const systemPrompt = 'You are a helpful assistant';
 
-        const handler = new TestAwsBedrockHandler(mockOptions, mockClient)
+        it('should handle text messages correctly', async () => {
+            const mockResponse = {
+                messages: [{
+                    role: 'assistant',
+                    content: [{ type: 'text', text: 'Hello! How can I help you?' }]
+                }],
+                usage: {
+                    input_tokens: 10,
+                    output_tokens: 5
+                }
+            };
 
-        const systemPrompt = 'You are a helpful assistant'
-        const messages: Anthropic.Messages.MessageParam[] = [
-            { role: 'user', content: 'Say hello' }
-        ]
+            // Mock AWS SDK invoke
+            const mockStream = {
+                [Symbol.asyncIterator]: async function* () {
+                    yield {
+                        metadata: {
+                            usage: {
+                                inputTokens: 10,
+                                outputTokens: 5
+                            }
+                        }
+                    };
+                }
+            };
 
-        const generator = handler.createMessage(systemPrompt, messages)
-        const chunks = []
+            const mockInvoke = jest.fn().mockResolvedValue({
+                stream: mockStream
+            });
 
-        for await (const chunk of generator) {
-            chunks.push(chunk)
-        }
+            handler['client'] = {
+                send: mockInvoke
+            } as unknown as BedrockRuntimeClient;
 
-        // Verify the chunks match expected stream events
-        expect(chunks).toHaveLength(3)
-        expect(chunks[0]).toEqual({
-            type: 'usage',
-            inputTokens: 50,
-            outputTokens: 100
-        })
-        expect(chunks[1]).toEqual({
-            type: 'text',
-            text: 'Hello'
-        })
-        expect(chunks[2]).toEqual({
-            type: 'text',
-            text: ' world'
-        })
-    })
-
-    test('createMessage handles error scenarios', async () => {
-        const mockClient = new MockBedrockRuntimeClient({
-            region: 'us-east-1'
-        })
-
-        // Simulate an error by overriding the send method
-        mockClient.send = () => {
-            throw new Error('API request failed')
-        }
-
-        const handler = new TestAwsBedrockHandler(mockOptions, mockClient)
-
-        const systemPrompt = 'You are a helpful assistant'
-        const messages: Anthropic.Messages.MessageParam[] = [
-            { role: 'user', content: 'Cause an error' }
-        ]
-
-        await expect(async () => {
-            const generator = handler.createMessage(systemPrompt, messages)
-            const chunks = []
+            const stream = handler.createMessage(systemPrompt, mockMessages);
+            const chunks = [];
             
-            for await (const chunk of generator) {
-                chunks.push(chunk)
+            for await (const chunk of stream) {
+                chunks.push(chunk);
             }
-        }).rejects.toThrow('API request failed')
-    })
-})
+
+            expect(chunks.length).toBeGreaterThan(0);
+            expect(chunks[0]).toEqual({
+                type: 'usage',
+                inputTokens: 10,
+                outputTokens: 5
+            });
+
+            expect(mockInvoke).toHaveBeenCalledWith(expect.objectContaining({
+                input: expect.objectContaining({
+                    modelId: 'anthropic.claude-3-5-sonnet-20241022-v2:0'
+                })
+            }));
+        });
+
+        it('should handle API errors', async () => {
+            // Mock AWS SDK invoke with error
+            const mockInvoke = jest.fn().mockRejectedValue(new Error('AWS Bedrock error'));
+
+            handler['client'] = {
+                send: mockInvoke
+            } as unknown as BedrockRuntimeClient;
+
+            const stream = handler.createMessage(systemPrompt, mockMessages);
+
+            await expect(async () => {
+                for await (const chunk of stream) {
+                    // Should throw before yielding any chunks
+                }
+            }).rejects.toThrow('AWS Bedrock error');
+        });
+    });
+
+    describe('completePrompt', () => {
+        it('should complete prompt successfully', async () => {
+            const mockResponse = {
+                output: new TextEncoder().encode(JSON.stringify({
+                    content: 'Test response'
+                }))
+            };
+
+            const mockSend = jest.fn().mockResolvedValue(mockResponse);
+            handler['client'] = {
+                send: mockSend
+            } as unknown as BedrockRuntimeClient;
+
+            const result = await handler.completePrompt('Test prompt');
+            expect(result).toBe('Test response');
+            expect(mockSend).toHaveBeenCalledWith(expect.objectContaining({
+                input: expect.objectContaining({
+                    modelId: 'anthropic.claude-3-5-sonnet-20241022-v2:0',
+                    messages: expect.arrayContaining([
+                        expect.objectContaining({
+                            role: 'user',
+                            content: [{ text: 'Test prompt' }]
+                        })
+                    ]),
+                    inferenceConfig: expect.objectContaining({
+                        maxTokens: 5000,
+                        temperature: 0.3,
+                        topP: 0.1
+                    })
+                })
+            }));
+        });
+
+        it('should handle API errors', async () => {
+            const mockError = new Error('AWS Bedrock error');
+            const mockSend = jest.fn().mockRejectedValue(mockError);
+            handler['client'] = {
+                send: mockSend
+            } as unknown as BedrockRuntimeClient;
+
+            await expect(handler.completePrompt('Test prompt'))
+                .rejects.toThrow('Bedrock completion error: AWS Bedrock error');
+        });
+
+        it('should handle invalid response format', async () => {
+            const mockResponse = {
+                output: new TextEncoder().encode('invalid json')
+            };
+
+            const mockSend = jest.fn().mockResolvedValue(mockResponse);
+            handler['client'] = {
+                send: mockSend
+            } as unknown as BedrockRuntimeClient;
+
+            const result = await handler.completePrompt('Test prompt');
+            expect(result).toBe('');
+        });
+
+        it('should handle empty response', async () => {
+            const mockResponse = {
+                output: new TextEncoder().encode(JSON.stringify({}))
+            };
+
+            const mockSend = jest.fn().mockResolvedValue(mockResponse);
+            handler['client'] = {
+                send: mockSend
+            } as unknown as BedrockRuntimeClient;
+
+            const result = await handler.completePrompt('Test prompt');
+            expect(result).toBe('');
+        });
+
+        it('should handle cross-region inference', async () => {
+            handler = new AwsBedrockHandler({
+                apiModelId: 'anthropic.claude-3-5-sonnet-20241022-v2:0',
+                awsAccessKey: 'test-access-key',
+                awsSecretKey: 'test-secret-key',
+                awsRegion: 'us-east-1',
+                awsUseCrossRegionInference: true
+            });
+
+            const mockResponse = {
+                output: new TextEncoder().encode(JSON.stringify({
+                    content: 'Test response'
+                }))
+            };
+
+            const mockSend = jest.fn().mockResolvedValue(mockResponse);
+            handler['client'] = {
+                send: mockSend
+            } as unknown as BedrockRuntimeClient;
+
+            const result = await handler.completePrompt('Test prompt');
+            expect(result).toBe('Test response');
+            expect(mockSend).toHaveBeenCalledWith(expect.objectContaining({
+                input: expect.objectContaining({
+                    modelId: 'us.anthropic.claude-3-5-sonnet-20241022-v2:0'
+                })
+            }));
+        });
+    });
+
+    describe('getModel', () => {
+        it('should return correct model info in test environment', () => {
+            const modelInfo = handler.getModel();
+            expect(modelInfo.id).toBe('anthropic.claude-3-5-sonnet-20241022-v2:0');
+            expect(modelInfo.info).toBeDefined();
+            expect(modelInfo.info.maxTokens).toBe(5000); // Test environment value
+            expect(modelInfo.info.contextWindow).toBe(128_000); // Test environment value
+        });
+
+        it('should return test model info for invalid model in test environment', () => {
+            const invalidHandler = new AwsBedrockHandler({
+                apiModelId: 'invalid-model',
+                awsAccessKey: 'test-access-key',
+                awsSecretKey: 'test-secret-key',
+                awsRegion: 'us-east-1'
+            });
+            const modelInfo = invalidHandler.getModel();
+            expect(modelInfo.id).toBe('invalid-model'); // In test env, returns whatever is passed
+            expect(modelInfo.info.maxTokens).toBe(5000);
+            expect(modelInfo.info.contextWindow).toBe(128_000);
+        });
+    });
+});

src/api/providers/__tests__/deepseek.test.ts

@@ -1,167 +1,203 @@
-import { DeepSeekHandler } from '../deepseek'
-import { ApiHandlerOptions } from '../../../shared/api'
-import OpenAI from 'openai'
-import { Anthropic } from '@anthropic-ai/sdk'
+import { DeepSeekHandler } from '../deepseek';
+import { ApiHandlerOptions, deepSeekDefaultModelId } from '../../../shared/api';
+import OpenAI from 'openai';
+import { Anthropic } from '@anthropic-ai/sdk';
 
-// Mock dependencies
-jest.mock('openai')
+// Mock OpenAI client
+const mockCreate = jest.fn();
+jest.mock('openai', () => {
+    return {
+        __esModule: true,
+        default: jest.fn().mockImplementation(() => ({
+            chat: {
+                completions: {
+                    create: mockCreate.mockImplementation(async (options) => {
+                        if (!options.stream) {
+                            return {
+                                id: 'test-completion',
+                                choices: [{
+                                    message: { role: 'assistant', content: 'Test response', refusal: null },
+                                    finish_reason: 'stop',
+                                    index: 0
+                                }],
+                                usage: {
+                                    prompt_tokens: 10,
+                                    completion_tokens: 5,
+                                    total_tokens: 15
+                                }
+                            };
+                        }
+                        
+                        // Return async iterator for streaming
+                        return {
+                            [Symbol.asyncIterator]: async function* () {
+                                yield {
+                                    choices: [{
+                                        delta: { content: 'Test response' },
+                                        index: 0
+                                    }],
+                                    usage: null
+                                };
+                                yield {
+                                    choices: [{
+                                        delta: {},
+                                        index: 0
+                                    }],
+                                    usage: {
+                                        prompt_tokens: 10,
+                                        completion_tokens: 5,
+                                        total_tokens: 15
+                                    }
+                                };
+                            }
+                        };
+                    })
+                }
+            }
+        }))
+    };
+});
 
 describe('DeepSeekHandler', () => {
-
-    const mockOptions: ApiHandlerOptions = {
-        deepSeekApiKey: 'test-key',
-        deepSeekModelId: 'deepseek-chat',
-    }
+    let handler: DeepSeekHandler;
+    let mockOptions: ApiHandlerOptions;
 
     beforeEach(() => {
-        jest.clearAllMocks()
-    })
+        mockOptions = {
+            deepSeekApiKey: 'test-api-key',
+            deepSeekModelId: 'deepseek-chat',
+            deepSeekBaseUrl: 'https://api.deepseek.com/v1'
+        };
+        handler = new DeepSeekHandler(mockOptions);
+        mockCreate.mockClear();
+    });
 
-    test('constructor initializes with correct options', () => {
-        const handler = new DeepSeekHandler(mockOptions)
-        expect(handler).toBeInstanceOf(DeepSeekHandler)
-        expect(OpenAI).toHaveBeenCalledWith({
-            baseURL: 'https://api.deepseek.com/v1',
-            apiKey: mockOptions.deepSeekApiKey,
-        })
-    })
+    describe('constructor', () => {
+        it('should initialize with provided options', () => {
+            expect(handler).toBeInstanceOf(DeepSeekHandler);
+            expect(handler.getModel().id).toBe(mockOptions.deepSeekModelId);
+        });
 
-    test('getModel returns correct model info', () => {
-        const handler = new DeepSeekHandler(mockOptions)
-        const result = handler.getModel()
-        
-        expect(result).toEqual({
-            id: mockOptions.deepSeekModelId,
-            info: expect.objectContaining({
-                maxTokens: 8192,
-                contextWindow: 64000,
-                supportsPromptCache: false,
-                supportsImages: false,
-                inputPrice: 0.014,
-                outputPrice: 0.28,
-            })
-        })
-    })
+        it('should throw error if API key is missing', () => {
+            expect(() => {
+                new DeepSeekHandler({
+                    ...mockOptions,
+                    deepSeekApiKey: undefined
+                });
+            }).toThrow('DeepSeek API key is required');
+        });
 
-    test('getModel returns default model info when no model specified', () => {
-        const handler = new DeepSeekHandler({ deepSeekApiKey: 'test-key' })
-        const result = handler.getModel()
-        
-        expect(result.id).toBe('deepseek-chat')
-        expect(result.info.maxTokens).toBe(8192)
-    })
+        it('should use default model ID if not provided', () => {
+            const handlerWithoutModel = new DeepSeekHandler({
+                ...mockOptions,
+                deepSeekModelId: undefined
+            });
+            expect(handlerWithoutModel.getModel().id).toBe(deepSeekDefaultModelId);
+        });
 
-    test('createMessage handles string content correctly', async () => {
-        const handler = new DeepSeekHandler(mockOptions)
-        const mockStream = {
-            async *[Symbol.asyncIterator]() {
-                yield {
-                    choices: [{
-                        delta: {
-                            content: 'test response'
-                        }
-                    }]
-                }
-            }
-        }
+        it('should use default base URL if not provided', () => {
+            const handlerWithoutBaseUrl = new DeepSeekHandler({
+                ...mockOptions,
+                deepSeekBaseUrl: undefined
+            });
+            expect(handlerWithoutBaseUrl).toBeInstanceOf(DeepSeekHandler);
+            // The base URL is passed to OpenAI client internally
+            expect(OpenAI).toHaveBeenCalledWith(expect.objectContaining({
+                baseURL: 'https://api.deepseek.com/v1'
+            }));
+        });
 
-        const mockCreate = jest.fn().mockResolvedValue(mockStream)
-        ;(OpenAI as jest.MockedClass<typeof OpenAI>).prototype.chat = {
-            completions: { create: mockCreate }
-        } as any
+        it('should use custom base URL if provided', () => {
+            const customBaseUrl = 'https://custom.deepseek.com/v1';
+            const handlerWithCustomUrl = new DeepSeekHandler({
+                ...mockOptions,
+                deepSeekBaseUrl: customBaseUrl
+            });
+            expect(handlerWithCustomUrl).toBeInstanceOf(DeepSeekHandler);
+            // The custom base URL is passed to OpenAI client
+            expect(OpenAI).toHaveBeenCalledWith(expect.objectContaining({
+                baseURL: customBaseUrl
+            }));
+        });
 
-        const systemPrompt = 'test system prompt'
-        const messages: Anthropic.Messages.MessageParam[] = [
-            { role: 'user', content: 'test message' }
-        ]
+        it('should set includeMaxTokens to true', () => {
+            // Create a new handler and verify OpenAI client was called with includeMaxTokens
+            new DeepSeekHandler(mockOptions);
+            expect(OpenAI).toHaveBeenCalledWith(expect.objectContaining({
+                apiKey: mockOptions.deepSeekApiKey
+            }));
+        });
+    });
 
-        const generator = handler.createMessage(systemPrompt, messages)
-        const chunks = []
-        
-        for await (const chunk of generator) {
-            chunks.push(chunk)
-        }
+    describe('getModel', () => {
+        it('should return model info for valid model ID', () => {
+            const model = handler.getModel();
+            expect(model.id).toBe(mockOptions.deepSeekModelId);
+            expect(model.info).toBeDefined();
+            expect(model.info.maxTokens).toBe(8192);
+            expect(model.info.contextWindow).toBe(64_000);
+            expect(model.info.supportsImages).toBe(false);
+            expect(model.info.supportsPromptCache).toBe(false);
+        });
 
-        expect(chunks).toHaveLength(1)
-        expect(chunks[0]).toEqual({
-            type: 'text',
-            text: 'test response'
-        })
+        it('should return provided model ID with default model info if model does not exist', () => {
+            const handlerWithInvalidModel = new DeepSeekHandler({
+                ...mockOptions,
+                deepSeekModelId: 'invalid-model'
+            });
+            const model = handlerWithInvalidModel.getModel();
+            expect(model.id).toBe('invalid-model'); // Returns provided ID
+            expect(model.info).toBeDefined();
+            expect(model.info).toBe(handler.getModel().info); // But uses default model info
+        });
 
-        expect(mockCreate).toHaveBeenCalledWith(expect.objectContaining({
-            model: mockOptions.deepSeekModelId,
-            messages: [
-                { role: 'system', content: systemPrompt },
-                { role: 'user', content: 'test message' }
-            ],
-            temperature: 0,
-            stream: true,
-            max_tokens: 8192,
-            stream_options: { include_usage: true }
-        }))
-    })
+        it('should return default model if no model ID is provided', () => {
+            const handlerWithoutModel = new DeepSeekHandler({
+                ...mockOptions,
+                deepSeekModelId: undefined
+            });
+            const model = handlerWithoutModel.getModel();
+            expect(model.id).toBe(deepSeekDefaultModelId);
+            expect(model.info).toBeDefined();
+        });
+    });
 
-    test('createMessage handles complex content correctly', async () => {
-        const handler = new DeepSeekHandler(mockOptions)
-        const mockStream = {
-            async *[Symbol.asyncIterator]() {
-                yield {
-                    choices: [{
-                        delta: {
-                            content: 'test response'
-                        }
-                    }]
-                }
-            }
-        }
-
-        const mockCreate = jest.fn().mockResolvedValue(mockStream)
-        ;(OpenAI as jest.MockedClass<typeof OpenAI>).prototype.chat = {
-            completions: { create: mockCreate }
-        } as any
-
-        const systemPrompt = 'test system prompt'
+    describe('createMessage', () => {
+        const systemPrompt = 'You are a helpful assistant.';
         const messages: Anthropic.Messages.MessageParam[] = [
             {
                 role: 'user',
-                content: [
-                    { type: 'text', text: 'part 1' },
-                    { type: 'text', text: 'part 2' }
-                ]
+                content: [{ 
+                    type: 'text' as const,
+                    text: 'Hello!'
+                }]
             }
-        ]
+        ];
 
-        const generator = handler.createMessage(systemPrompt, messages)
-        await generator.next()
-
-        expect(mockCreate).toHaveBeenCalledWith(expect.objectContaining({
-            messages: [
-                { role: 'system', content: systemPrompt },
-                {
-                    role: 'user',
-                    content: [
-                        { type: 'text', text: 'part 1' },
-                        { type: 'text', text: 'part 2' }
-                    ]
-                }
-            ]
-        }))
-    })
-
-    test('createMessage handles API errors', async () => {
-        const handler = new DeepSeekHandler(mockOptions)
-        const mockStream = {
-            async *[Symbol.asyncIterator]() {
-                throw new Error('API Error')
+        it('should handle streaming responses', async () => {
+            const stream = handler.createMessage(systemPrompt, messages);
+            const chunks: any[] = [];
+            for await (const chunk of stream) {
+                chunks.push(chunk);
             }
-        }
 
-        const mockCreate = jest.fn().mockResolvedValue(mockStream)
-        ;(OpenAI as jest.MockedClass<typeof OpenAI>).prototype.chat = {
-            completions: { create: mockCreate }
-        } as any
+            expect(chunks.length).toBeGreaterThan(0);
+            const textChunks = chunks.filter(chunk => chunk.type === 'text');
+            expect(textChunks).toHaveLength(1);
+            expect(textChunks[0].text).toBe('Test response');
+        });
 
-        const generator = handler.createMessage('test', [])
-        await expect(generator.next()).rejects.toThrow('API Error')
-    })
-})
+        it('should include usage information', async () => {
+            const stream = handler.createMessage(systemPrompt, messages);
+            const chunks: any[] = [];
+            for await (const chunk of stream) {
+                chunks.push(chunk);
+            }
+
+            const usageChunks = chunks.filter(chunk => chunk.type === 'usage');
+            expect(usageChunks.length).toBeGreaterThan(0);
+            expect(usageChunks[0].inputTokens).toBe(10);
+            expect(usageChunks[0].outputTokens).toBe(5);
+        });
+    });
+});

src/api/providers/__tests__/gemini.test.ts

@@ -0,0 +1,212 @@
+import { GeminiHandler } from '../gemini';
+import { Anthropic } from '@anthropic-ai/sdk';
+import { GoogleGenerativeAI } from '@google/generative-ai';
+
+// Mock the Google Generative AI SDK
+jest.mock('@google/generative-ai', () => ({
+    GoogleGenerativeAI: jest.fn().mockImplementation(() => ({
+        getGenerativeModel: jest.fn().mockReturnValue({
+            generateContentStream: jest.fn(),
+            generateContent: jest.fn().mockResolvedValue({
+                response: {
+                    text: () => 'Test response'
+                }
+            })
+        })
+    }))
+}));
+
+describe('GeminiHandler', () => {
+    let handler: GeminiHandler;
+
+    beforeEach(() => {
+        handler = new GeminiHandler({
+            apiKey: 'test-key',
+            apiModelId: 'gemini-2.0-flash-thinking-exp-1219',
+            geminiApiKey: 'test-key'
+        });
+    });
+
+    describe('constructor', () => {
+        it('should initialize with provided config', () => {
+            expect(handler['options'].geminiApiKey).toBe('test-key');
+            expect(handler['options'].apiModelId).toBe('gemini-2.0-flash-thinking-exp-1219');
+        });
+
+        it('should throw if API key is missing', () => {
+            expect(() => {
+                new GeminiHandler({
+                    apiModelId: 'gemini-2.0-flash-thinking-exp-1219',
+                    geminiApiKey: ''
+                });
+            }).toThrow('API key is required for Google Gemini');
+        });
+    });
+
+    describe('createMessage', () => {
+        const mockMessages: Anthropic.Messages.MessageParam[] = [
+            {
+                role: 'user',
+                content: 'Hello'
+            },
+            {
+                role: 'assistant',
+                content: 'Hi there!'
+            }
+        ];
+
+        const systemPrompt = 'You are a helpful assistant';
+
+        it('should handle text messages correctly', async () => {
+            // Mock the stream response
+            const mockStream = {
+                stream: [
+                    { text: () => 'Hello' },
+                    { text: () => ' world!' }
+                ],
+                response: {
+                    usageMetadata: {
+                        promptTokenCount: 10,
+                        candidatesTokenCount: 5
+                    }
+                }
+            };
+
+            // Setup the mock implementation
+            const mockGenerateContentStream = jest.fn().mockResolvedValue(mockStream);
+            const mockGetGenerativeModel = jest.fn().mockReturnValue({
+                generateContentStream: mockGenerateContentStream
+            });
+
+            (handler['client'] as any).getGenerativeModel = mockGetGenerativeModel;
+
+            const stream = handler.createMessage(systemPrompt, mockMessages);
+            const chunks = [];
+            
+            for await (const chunk of stream) {
+                chunks.push(chunk);
+            }
+
+            // Should have 3 chunks: 'Hello', ' world!', and usage info
+            expect(chunks.length).toBe(3);
+            expect(chunks[0]).toEqual({
+                type: 'text',
+                text: 'Hello'
+            });
+            expect(chunks[1]).toEqual({
+                type: 'text',
+                text: ' world!'
+            });
+            expect(chunks[2]).toEqual({
+                type: 'usage',
+                inputTokens: 10,
+                outputTokens: 5
+            });
+
+            // Verify the model configuration
+            expect(mockGetGenerativeModel).toHaveBeenCalledWith({
+                model: 'gemini-2.0-flash-thinking-exp-1219',
+                systemInstruction: systemPrompt
+            });
+
+            // Verify generation config
+            expect(mockGenerateContentStream).toHaveBeenCalledWith(
+                expect.objectContaining({
+                    generationConfig: {
+                        temperature: 0
+                    }
+                })
+            );
+        });
+
+        it('should handle API errors', async () => {
+            const mockError = new Error('Gemini API error');
+            const mockGenerateContentStream = jest.fn().mockRejectedValue(mockError);
+            const mockGetGenerativeModel = jest.fn().mockReturnValue({
+                generateContentStream: mockGenerateContentStream
+            });
+
+            (handler['client'] as any).getGenerativeModel = mockGetGenerativeModel;
+
+            const stream = handler.createMessage(systemPrompt, mockMessages);
+
+            await expect(async () => {
+                for await (const chunk of stream) {
+                    // Should throw before yielding any chunks
+                }
+            }).rejects.toThrow('Gemini API error');
+        });
+    });
+
+    describe('completePrompt', () => {
+        it('should complete prompt successfully', async () => {
+            const mockGenerateContent = jest.fn().mockResolvedValue({
+                response: {
+                    text: () => 'Test response'
+                }
+            });
+            const mockGetGenerativeModel = jest.fn().mockReturnValue({
+                generateContent: mockGenerateContent
+            });
+            (handler['client'] as any).getGenerativeModel = mockGetGenerativeModel;
+
+            const result = await handler.completePrompt('Test prompt');
+            expect(result).toBe('Test response');
+            expect(mockGetGenerativeModel).toHaveBeenCalledWith({
+                model: 'gemini-2.0-flash-thinking-exp-1219'
+            });
+            expect(mockGenerateContent).toHaveBeenCalledWith({
+                contents: [{ role: 'user', parts: [{ text: 'Test prompt' }] }],
+                generationConfig: {
+                    temperature: 0
+                }
+            });
+        });
+
+        it('should handle API errors', async () => {
+            const mockError = new Error('Gemini API error');
+            const mockGenerateContent = jest.fn().mockRejectedValue(mockError);
+            const mockGetGenerativeModel = jest.fn().mockReturnValue({
+                generateContent: mockGenerateContent
+            });
+            (handler['client'] as any).getGenerativeModel = mockGetGenerativeModel;
+
+            await expect(handler.completePrompt('Test prompt'))
+                .rejects.toThrow('Gemini completion error: Gemini API error');
+        });
+
+        it('should handle empty response', async () => {
+            const mockGenerateContent = jest.fn().mockResolvedValue({
+                response: {
+                    text: () => ''
+                }
+            });
+            const mockGetGenerativeModel = jest.fn().mockReturnValue({
+                generateContent: mockGenerateContent
+            });
+            (handler['client'] as any).getGenerativeModel = mockGetGenerativeModel;
+
+            const result = await handler.completePrompt('Test prompt');
+            expect(result).toBe('');
+        });
+    });
+
+    describe('getModel', () => {
+        it('should return correct model info', () => {
+            const modelInfo = handler.getModel();
+            expect(modelInfo.id).toBe('gemini-2.0-flash-thinking-exp-1219');
+            expect(modelInfo.info).toBeDefined();
+            expect(modelInfo.info.maxTokens).toBe(8192);
+            expect(modelInfo.info.contextWindow).toBe(32_767);
+        });
+
+        it('should return default model if invalid model specified', () => {
+            const invalidHandler = new GeminiHandler({
+                apiModelId: 'invalid-model',
+                geminiApiKey: 'test-key'
+            });
+            const modelInfo = invalidHandler.getModel();
+            expect(modelInfo.id).toBe('gemini-2.0-flash-thinking-exp-1219'); // Default model
+        });
+    });
+});

src/api/providers/__tests__/glama.test.ts

@@ -0,0 +1,226 @@
+import { GlamaHandler } from '../glama';
+import { ApiHandlerOptions } from '../../../shared/api';
+import OpenAI from 'openai';
+import { Anthropic } from '@anthropic-ai/sdk';
+import axios from 'axios';
+
+// Mock OpenAI client
+const mockCreate = jest.fn();
+const mockWithResponse = jest.fn();
+
+jest.mock('openai', () => {
+    return {
+        __esModule: true,
+        default: jest.fn().mockImplementation(() => ({
+            chat: {
+                completions: {
+                    create: (...args: any[]) => {
+                        const stream = {
+                            [Symbol.asyncIterator]: async function* () {
+                                yield {
+                                    choices: [{
+                                        delta: { content: 'Test response' },
+                                        index: 0
+                                    }],
+                                    usage: null
+                                };
+                                yield {
+                                    choices: [{
+                                        delta: {},
+                                        index: 0
+                                    }],
+                                    usage: {
+                                        prompt_tokens: 10,
+                                        completion_tokens: 5,
+                                        total_tokens: 15
+                                    }
+                                };
+                            }
+                        };
+
+                        const result = mockCreate(...args);
+                        if (args[0].stream) {
+                            mockWithResponse.mockReturnValue(Promise.resolve({
+                                data: stream,
+                                response: {
+                                    headers: {
+                                        get: (name: string) => name === 'x-completion-request-id' ? 'test-request-id' : null
+                                    }
+                                }
+                            }));
+                            result.withResponse = mockWithResponse;
+                        }
+                        return result;
+                    }
+                }
+            }
+        }))
+    };
+});
+
+describe('GlamaHandler', () => {
+    let handler: GlamaHandler;
+    let mockOptions: ApiHandlerOptions;
+
+    beforeEach(() => {
+        mockOptions = {
+            apiModelId: 'anthropic/claude-3-5-sonnet',
+            glamaModelId: 'anthropic/claude-3-5-sonnet',
+            glamaApiKey: 'test-api-key'
+        };
+        handler = new GlamaHandler(mockOptions);
+        mockCreate.mockClear();
+        mockWithResponse.mockClear();
+
+        // Default mock implementation for non-streaming responses
+        mockCreate.mockResolvedValue({
+            id: 'test-completion',
+            choices: [{
+                message: { role: 'assistant', content: 'Test response' },
+                finish_reason: 'stop',
+                index: 0
+            }],
+            usage: {
+                prompt_tokens: 10,
+                completion_tokens: 5,
+                total_tokens: 15
+            }
+        });
+    });
+
+    describe('constructor', () => {
+        it('should initialize with provided options', () => {
+            expect(handler).toBeInstanceOf(GlamaHandler);
+            expect(handler.getModel().id).toBe(mockOptions.apiModelId);
+        });
+    });
+
+    describe('createMessage', () => {
+        const systemPrompt = 'You are a helpful assistant.';
+        const messages: Anthropic.Messages.MessageParam[] = [
+            {
+                role: 'user',
+                content: 'Hello!'
+            }
+        ];
+
+        it('should handle streaming responses', async () => {
+            // Mock axios for token usage request
+            const mockAxios = jest.spyOn(axios, 'get').mockResolvedValueOnce({
+                data: {
+                    tokenUsage: {
+                        promptTokens: 10,
+                        completionTokens: 5,
+                        cacheCreationInputTokens: 0,
+                        cacheReadInputTokens: 0
+                    },
+                    totalCostUsd: "0.00"
+                }
+            });
+
+            const stream = handler.createMessage(systemPrompt, messages);
+            const chunks: any[] = [];
+            for await (const chunk of stream) {
+                chunks.push(chunk);
+            }
+
+            expect(chunks.length).toBe(2); // Text chunk and usage chunk
+            expect(chunks[0]).toEqual({
+                type: 'text',
+                text: 'Test response'
+            });
+            expect(chunks[1]).toEqual({
+                type: 'usage',
+                inputTokens: 10,
+                outputTokens: 5,
+                cacheWriteTokens: 0,
+                cacheReadTokens: 0,
+                totalCost: 0
+            });
+
+            mockAxios.mockRestore();
+        });
+
+        it('should handle API errors', async () => {
+            mockCreate.mockImplementationOnce(() => {
+                throw new Error('API Error');
+            });
+
+            const stream = handler.createMessage(systemPrompt, messages);
+            const chunks = [];
+
+            try {
+                for await (const chunk of stream) {
+                    chunks.push(chunk);
+                }
+                fail('Expected error to be thrown');
+            } catch (error) {
+                expect(error).toBeInstanceOf(Error);
+                expect(error.message).toBe('API Error');
+            }
+        });
+    });
+
+    describe('completePrompt', () => {
+        it('should complete prompt successfully', async () => {
+            const result = await handler.completePrompt('Test prompt');
+            expect(result).toBe('Test response');
+            expect(mockCreate).toHaveBeenCalledWith(expect.objectContaining({
+                model: mockOptions.apiModelId,
+                messages: [{ role: 'user', content: 'Test prompt' }],
+                temperature: 0,
+                max_tokens: 8192
+            }));
+        });
+
+        it('should handle API errors', async () => {
+            mockCreate.mockRejectedValueOnce(new Error('API Error'));
+            await expect(handler.completePrompt('Test prompt'))
+                .rejects.toThrow('Glama completion error: API Error');
+        });
+
+        it('should handle empty response', async () => {
+            mockCreate.mockResolvedValueOnce({
+                choices: [{ message: { content: '' } }]
+            });
+            const result = await handler.completePrompt('Test prompt');
+            expect(result).toBe('');
+        });
+
+        it('should not set max_tokens for non-Anthropic models', async () => {
+            // Reset mock to clear any previous calls
+            mockCreate.mockClear();
+            
+            const nonAnthropicOptions = {
+                apiModelId: 'openai/gpt-4',
+                glamaModelId: 'openai/gpt-4',
+                glamaApiKey: 'test-key',
+                glamaModelInfo: {
+                    maxTokens: 4096,
+                    contextWindow: 8192,
+                    supportsImages: true,
+                    supportsPromptCache: false
+                }
+            };
+            const nonAnthropicHandler = new GlamaHandler(nonAnthropicOptions);
+
+            await nonAnthropicHandler.completePrompt('Test prompt');
+            expect(mockCreate).toHaveBeenCalledWith(expect.objectContaining({
+                model: 'openai/gpt-4',
+                messages: [{ role: 'user', content: 'Test prompt' }],
+                temperature: 0
+            }));
+            expect(mockCreate.mock.calls[0][0]).not.toHaveProperty('max_tokens');
+        });
+    });
+
+    describe('getModel', () => {
+        it('should return model info', () => {
+            const modelInfo = handler.getModel();
+            expect(modelInfo.id).toBe(mockOptions.apiModelId);
+            expect(modelInfo.info).toBeDefined();
+            expect(modelInfo.info.maxTokens).toBe(8192);
+            expect(modelInfo.info.contextWindow).toBe(200_000);
+        });
+    });
+});

src/api/providers/__tests__/lmstudio.test.ts

@@ -0,0 +1,160 @@
+import { LmStudioHandler } from '../lmstudio';
+import { ApiHandlerOptions } from '../../../shared/api';
+import OpenAI from 'openai';
+import { Anthropic } from '@anthropic-ai/sdk';
+
+// Mock OpenAI client
+const mockCreate = jest.fn();
+jest.mock('openai', () => {
+    return {
+        __esModule: true,
+        default: jest.fn().mockImplementation(() => ({
+            chat: {
+                completions: {
+                    create: mockCreate.mockImplementation(async (options) => {
+                        if (!options.stream) {
+                            return {
+                                id: 'test-completion',
+                                choices: [{
+                                    message: { role: 'assistant', content: 'Test response' },
+                                    finish_reason: 'stop',
+                                    index: 0
+                                }],
+                                usage: {
+                                    prompt_tokens: 10,
+                                    completion_tokens: 5,
+                                    total_tokens: 15
+                                }
+                            };
+                        }
+                        
+                        return {
+                            [Symbol.asyncIterator]: async function* () {
+                                yield {
+                                    choices: [{
+                                        delta: { content: 'Test response' },
+                                        index: 0
+                                    }],
+                                    usage: null
+                                };
+                                yield {
+                                    choices: [{
+                                        delta: {},
+                                        index: 0
+                                    }],
+                                    usage: {
+                                        prompt_tokens: 10,
+                                        completion_tokens: 5,
+                                        total_tokens: 15
+                                    }
+                                };
+                            }
+                        };
+                    })
+                }
+            }
+        }))
+    };
+});
+
+describe('LmStudioHandler', () => {
+    let handler: LmStudioHandler;
+    let mockOptions: ApiHandlerOptions;
+
+    beforeEach(() => {
+        mockOptions = {
+            apiModelId: 'local-model',
+            lmStudioModelId: 'local-model',
+            lmStudioBaseUrl: 'http://localhost:1234/v1'
+        };
+        handler = new LmStudioHandler(mockOptions);
+        mockCreate.mockClear();
+    });
+
+    describe('constructor', () => {
+        it('should initialize with provided options', () => {
+            expect(handler).toBeInstanceOf(LmStudioHandler);
+            expect(handler.getModel().id).toBe(mockOptions.lmStudioModelId);
+        });
+
+        it('should use default base URL if not provided', () => {
+            const handlerWithoutUrl = new LmStudioHandler({
+                apiModelId: 'local-model',
+                lmStudioModelId: 'local-model'
+            });
+            expect(handlerWithoutUrl).toBeInstanceOf(LmStudioHandler);
+        });
+    });
+
+    describe('createMessage', () => {
+        const systemPrompt = 'You are a helpful assistant.';
+        const messages: Anthropic.Messages.MessageParam[] = [
+            {
+                role: 'user',
+                content: 'Hello!'
+            }
+        ];
+
+        it('should handle streaming responses', async () => {
+            const stream = handler.createMessage(systemPrompt, messages);
+            const chunks: any[] = [];
+            for await (const chunk of stream) {
+                chunks.push(chunk);
+            }
+
+            expect(chunks.length).toBeGreaterThan(0);
+            const textChunks = chunks.filter(chunk => chunk.type === 'text');
+            expect(textChunks).toHaveLength(1);
+            expect(textChunks[0].text).toBe('Test response');
+        });
+
+        it('should handle API errors', async () => {
+            mockCreate.mockRejectedValueOnce(new Error('API Error'));
+
+            const stream = handler.createMessage(systemPrompt, messages);
+
+            await expect(async () => {
+                for await (const chunk of stream) {
+                    // Should not reach here
+                }
+            }).rejects.toThrow('Please check the LM Studio developer logs to debug what went wrong');
+        });
+    });
+
+    describe('completePrompt', () => {
+        it('should complete prompt successfully', async () => {
+            const result = await handler.completePrompt('Test prompt');
+            expect(result).toBe('Test response');
+            expect(mockCreate).toHaveBeenCalledWith({
+                model: mockOptions.lmStudioModelId,
+                messages: [{ role: 'user', content: 'Test prompt' }],
+                temperature: 0,
+                stream: false
+            });
+        });
+
+        it('should handle API errors', async () => {
+            mockCreate.mockRejectedValueOnce(new Error('API Error'));
+            await expect(handler.completePrompt('Test prompt'))
+                .rejects.toThrow('Please check the LM Studio developer logs to debug what went wrong');
+        });
+
+        it('should handle empty response', async () => {
+            mockCreate.mockResolvedValueOnce({
+                choices: [{ message: { content: '' } }]
+            });
+            const result = await handler.completePrompt('Test prompt');
+            expect(result).toBe('');
+        });
+    });
+
+    describe('getModel', () => {
+        it('should return model info', () => {
+            const modelInfo = handler.getModel();
+            expect(modelInfo.id).toBe(mockOptions.lmStudioModelId);
+            expect(modelInfo.info).toBeDefined();
+            expect(modelInfo.info.maxTokens).toBe(-1);
+            expect(modelInfo.info.contextWindow).toBe(128_000);
+        });
+    });
+});

src/api/providers/__tests__/ollama.test.ts

@@ -0,0 +1,160 @@
+import { OllamaHandler } from '../ollama';
+import { ApiHandlerOptions } from '../../../shared/api';
+import OpenAI from 'openai';
+import { Anthropic } from '@anthropic-ai/sdk';
+
+// Mock OpenAI client
+const mockCreate = jest.fn();
+jest.mock('openai', () => {
+    return {
+        __esModule: true,
+        default: jest.fn().mockImplementation(() => ({
+            chat: {
+                completions: {
+                    create: mockCreate.mockImplementation(async (options) => {
+                        if (!options.stream) {
+                            return {
+                                id: 'test-completion',
+                                choices: [{
+                                    message: { role: 'assistant', content: 'Test response' },
+                                    finish_reason: 'stop',
+                                    index: 0
+                                }],
+                                usage: {
+                                    prompt_tokens: 10,
+                                    completion_tokens: 5,
+                                    total_tokens: 15
+                                }
+                            };
+                        }
+                        
+                        return {
+                            [Symbol.asyncIterator]: async function* () {
+                                yield {
+                                    choices: [{
+                                        delta: { content: 'Test response' },
+                                        index: 0
+                                    }],
+                                    usage: null
+                                };
+                                yield {
+                                    choices: [{
+                                        delta: {},
+                                        index: 0
+                                    }],
+                                    usage: {
+                                        prompt_tokens: 10,
+                                        completion_tokens: 5,
+                                        total_tokens: 15
+                                    }
+                                };
+                            }
+                        };
+                    })
+                }
+            }
+        }))
+    };
+});
+
+describe('OllamaHandler', () => {
+    let handler: OllamaHandler;
+    let mockOptions: ApiHandlerOptions;
+
+    beforeEach(() => {
+        mockOptions = {
+            apiModelId: 'llama2',
+            ollamaModelId: 'llama2',
+            ollamaBaseUrl: 'http://localhost:11434/v1'
+        };
+        handler = new OllamaHandler(mockOptions);
+        mockCreate.mockClear();
+    });
+
+    describe('constructor', () => {
+        it('should initialize with provided options', () => {
+            expect(handler).toBeInstanceOf(OllamaHandler);
+            expect(handler.getModel().id).toBe(mockOptions.ollamaModelId);
+        });
+
+        it('should use default base URL if not provided', () => {
+            const handlerWithoutUrl = new OllamaHandler({
+                apiModelId: 'llama2',
+                ollamaModelId: 'llama2'
+            });
+            expect(handlerWithoutUrl).toBeInstanceOf(OllamaHandler);
+        });
+    });
+
+    describe('createMessage', () => {
+        const systemPrompt = 'You are a helpful assistant.';
+        const messages: Anthropic.Messages.MessageParam[] = [
+            {
+                role: 'user',
+                content: 'Hello!'
+            }
+        ];
+
+        it('should handle streaming responses', async () => {
+            const stream = handler.createMessage(systemPrompt, messages);
+            const chunks: any[] = [];
+            for await (const chunk of stream) {
+                chunks.push(chunk);
+            }
+
+            expect(chunks.length).toBeGreaterThan(0);
+            const textChunks = chunks.filter(chunk => chunk.type === 'text');
+            expect(textChunks).toHaveLength(1);
+            expect(textChunks[0].text).toBe('Test response');
+        });
+
+        it('should handle API errors', async () => {
+            mockCreate.mockRejectedValueOnce(new Error('API Error'));
+
+            const stream = handler.createMessage(systemPrompt, messages);
+
+            await expect(async () => {
+                for await (const chunk of stream) {
+                    // Should not reach here
+                }
+            }).rejects.toThrow('API Error');
+        });
+    });
+
+    describe('completePrompt', () => {
+        it('should complete prompt successfully', async () => {
+            const result = await handler.completePrompt('Test prompt');
+            expect(result).toBe('Test response');
+            expect(mockCreate).toHaveBeenCalledWith({
+                model: mockOptions.ollamaModelId,
+                messages: [{ role: 'user', content: 'Test prompt' }],
+                temperature: 0,
+                stream: false
+            });
+        });
+
+        it('should handle API errors', async () => {
+            mockCreate.mockRejectedValueOnce(new Error('API Error'));
+            await expect(handler.completePrompt('Test prompt'))
+                .rejects.toThrow('Ollama completion error: API Error');
+        });
+
+        it('should handle empty response', async () => {
+            mockCreate.mockResolvedValueOnce({
+                choices: [{ message: { content: '' } }]
+            });
+            const result = await handler.completePrompt('Test prompt');
+            expect(result).toBe('');
+        });
+    });
+
+    describe('getModel', () => {
+        it('should return model info', () => {
+            const modelInfo = handler.getModel();
+            expect(modelInfo.id).toBe(mockOptions.ollamaModelId);
+            expect(modelInfo.info).toBeDefined();
+            expect(modelInfo.info.maxTokens).toBe(-1);
+            expect(modelInfo.info.contextWindow).toBe(128_000);
+        });
+    });
+});

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

@@ -0,0 +1,209 @@
+import { OpenAiNativeHandler } from '../openai-native';
+import { ApiHandlerOptions } from '../../../shared/api';
+import OpenAI from 'openai';
+import { Anthropic } from '@anthropic-ai/sdk';
+
+// Mock OpenAI client
+const mockCreate = jest.fn();
+jest.mock('openai', () => {
+    return {
+        __esModule: true,
+        default: jest.fn().mockImplementation(() => ({
+            chat: {
+                completions: {
+                    create: mockCreate.mockImplementation(async (options) => {
+                        if (!options.stream) {
+                            return {
+                                id: 'test-completion',
+                                choices: [{
+                                    message: { role: 'assistant', content: 'Test response' },
+                                    finish_reason: 'stop',
+                                    index: 0
+                                }],
+                                usage: {
+                                    prompt_tokens: 10,
+                                    completion_tokens: 5,
+                                    total_tokens: 15
+                                }
+                            };
+                        }
+                        
+                        return {
+                            [Symbol.asyncIterator]: async function* () {
+                                yield {
+                                    choices: [{
+                                        delta: { content: 'Test response' },
+                                        index: 0
+                                    }],
+                                    usage: null
+                                };
+                                yield {
+                                    choices: [{
+                                        delta: {},
+                                        index: 0
+                                    }],
+                                    usage: {
+                                        prompt_tokens: 10,
+                                        completion_tokens: 5,
+                                        total_tokens: 15
+                                    }
+                                };
+                            }
+                        };
+                    })
+                }
+            }
+        }))
+    };
+});
+
+describe('OpenAiNativeHandler', () => {
+    let handler: OpenAiNativeHandler;
+    let mockOptions: ApiHandlerOptions;
+
+    beforeEach(() => {
+        mockOptions = {
+            apiModelId: 'gpt-4o',
+            openAiNativeApiKey: 'test-api-key'
+        };
+        handler = new OpenAiNativeHandler(mockOptions);
+        mockCreate.mockClear();
+    });
+
+    describe('constructor', () => {
+        it('should initialize with provided options', () => {
+            expect(handler).toBeInstanceOf(OpenAiNativeHandler);
+            expect(handler.getModel().id).toBe(mockOptions.apiModelId);
+        });
+
+        it('should initialize with empty API key', () => {
+            const handlerWithoutKey = new OpenAiNativeHandler({
+                apiModelId: 'gpt-4o',
+                openAiNativeApiKey: ''
+            });
+            expect(handlerWithoutKey).toBeInstanceOf(OpenAiNativeHandler);
+        });
+    });
+
+    describe('createMessage', () => {
+        const systemPrompt = 'You are a helpful assistant.';
+        const messages: Anthropic.Messages.MessageParam[] = [
+            {
+                role: 'user',
+                content: 'Hello!'
+            }
+        ];
+
+        it('should handle streaming responses', async () => {
+            const stream = handler.createMessage(systemPrompt, messages);
+            const chunks: any[] = [];
+            for await (const chunk of stream) {
+                chunks.push(chunk);
+            }
+
+            expect(chunks.length).toBeGreaterThan(0);
+            const textChunks = chunks.filter(chunk => chunk.type === 'text');
+            expect(textChunks).toHaveLength(1);
+            expect(textChunks[0].text).toBe('Test response');
+        });
+
+        it('should handle API errors', async () => {
+            mockCreate.mockRejectedValueOnce(new Error('API Error'));
+
+            const stream = handler.createMessage(systemPrompt, messages);
+
+            await expect(async () => {
+                for await (const chunk of stream) {
+                    // Should not reach here
+                }
+            }).rejects.toThrow('API Error');
+        });
+    });
+
+    describe('completePrompt', () => {
+        it('should complete prompt successfully with gpt-4o model', async () => {
+            const result = await handler.completePrompt('Test prompt');
+            expect(result).toBe('Test response');
+            expect(mockCreate).toHaveBeenCalledWith({
+                model: 'gpt-4o',
+                messages: [{ role: 'user', content: 'Test prompt' }],
+                temperature: 0
+            });
+        });
+
+        it('should complete prompt successfully with o1 model', async () => {
+            handler = new OpenAiNativeHandler({
+                apiModelId: 'o1',
+                openAiNativeApiKey: 'test-api-key'
+            });
+
+            const result = await handler.completePrompt('Test prompt');
+            expect(result).toBe('Test response');
+            expect(mockCreate).toHaveBeenCalledWith({
+                model: 'o1',
+                messages: [{ role: 'user', content: 'Test prompt' }]
+            });
+        });
+
+        it('should complete prompt successfully with o1-preview model', async () => {
+            handler = new OpenAiNativeHandler({
+                apiModelId: 'o1-preview',
+                openAiNativeApiKey: 'test-api-key'
+            });
+
+            const result = await handler.completePrompt('Test prompt');
+            expect(result).toBe('Test response');
+            expect(mockCreate).toHaveBeenCalledWith({
+                model: 'o1-preview',
+                messages: [{ role: 'user', content: 'Test prompt' }]
+            });
+        });
+
+        it('should complete prompt successfully with o1-mini model', async () => {
+            handler = new OpenAiNativeHandler({
+                apiModelId: 'o1-mini',
+                openAiNativeApiKey: 'test-api-key'
+            });
+
+            const result = await handler.completePrompt('Test prompt');
+            expect(result).toBe('Test response');
+            expect(mockCreate).toHaveBeenCalledWith({
+                model: 'o1-mini',
+                messages: [{ role: 'user', content: 'Test prompt' }]
+            });
+        });
+
+        it('should handle API errors', async () => {
+            mockCreate.mockRejectedValueOnce(new Error('API Error'));
+            await expect(handler.completePrompt('Test prompt'))
+                .rejects.toThrow('OpenAI Native completion error: API Error');
+        });
+
+        it('should handle empty response', async () => {
+            mockCreate.mockResolvedValueOnce({
+                choices: [{ message: { content: '' } }]
+            });
+            const result = await handler.completePrompt('Test prompt');
+            expect(result).toBe('');
+        });
+    });
+
+    describe('getModel', () => {
+        it('should return model info', () => {
+            const modelInfo = handler.getModel();
+            expect(modelInfo.id).toBe(mockOptions.apiModelId);
+            expect(modelInfo.info).toBeDefined();
+            expect(modelInfo.info.maxTokens).toBe(4096);
+            expect(modelInfo.info.contextWindow).toBe(128_000);
+        });
+
+        it('should handle undefined model ID', () => {
+            const handlerWithoutModel = new OpenAiNativeHandler({
+                openAiNativeApiKey: 'test-api-key'
+            });
+            const modelInfo = handlerWithoutModel.getModel();
+            expect(modelInfo.id).toBe('gpt-4o'); // Default model
+            expect(modelInfo.info).toBeDefined();
+        });
+    });
+});

src/api/providers/__tests__/openai.test.ts

@@ -1,192 +1,224 @@
-import { OpenAiHandler } from '../openai'
-import { ApiHandlerOptions, openAiModelInfoSaneDefaults } from '../../../shared/api'
-import OpenAI, { AzureOpenAI } from 'openai'
-import { Anthropic } from '@anthropic-ai/sdk'
+import { OpenAiHandler } from '../openai';
+import { ApiHandlerOptions } from '../../../shared/api';
+import { ApiStream } from '../../transform/stream';
+import OpenAI from 'openai';
+import { Anthropic } from '@anthropic-ai/sdk';
 
-// Mock dependencies
-jest.mock('openai')
+// Mock OpenAI client
+const mockCreate = jest.fn();
+jest.mock('openai', () => {
+    return {
+        __esModule: true,
+        default: jest.fn().mockImplementation(() => ({
+            chat: {
+                completions: {
+                    create: mockCreate.mockImplementation(async (options) => {
+                        if (!options.stream) {
+                            return {
+                                id: 'test-completion',
+                                choices: [{
+                                    message: { role: 'assistant', content: 'Test response', refusal: null },
+                                    finish_reason: 'stop',
+                                    index: 0
+                                }],
+                                usage: {
+                                    prompt_tokens: 10,
+                                    completion_tokens: 5,
+                                    total_tokens: 15
+                                }
+                            };
+                        }
+                        
+                        return {
+                            [Symbol.asyncIterator]: async function* () {
+                                yield {
+                                    choices: [{
+                                        delta: { content: 'Test response' },
+                                        index: 0
+                                    }],
+                                    usage: null
+                                };
+                                yield {
+                                    choices: [{
+                                        delta: {},
+                                        index: 0
+                                    }],
+                                    usage: {
+                                        prompt_tokens: 10,
+                                        completion_tokens: 5,
+                                        total_tokens: 15
+                                    }
+                                };
+                            }
+                        };
+                    })
+                }
+            }
+        }))
+    };
+});
 
 describe('OpenAiHandler', () => {
-    const mockOptions: ApiHandlerOptions = {
-        openAiApiKey: 'test-key',
-        openAiModelId: 'gpt-4',
-        openAiStreamingEnabled: true,
-        openAiBaseUrl: 'https://api.openai.com/v1'
-    }
+    let handler: OpenAiHandler;
+    let mockOptions: ApiHandlerOptions;
 
     beforeEach(() => {
-        jest.clearAllMocks()
-    })
+        mockOptions = {
+            openAiApiKey: 'test-api-key',
+            openAiModelId: 'gpt-4',
+            openAiBaseUrl: 'https://api.openai.com/v1'
+        };
+        handler = new OpenAiHandler(mockOptions);
+        mockCreate.mockClear();
+    });
 
-    test('constructor initializes with correct options', () => {
-        const handler = new OpenAiHandler(mockOptions)
-        expect(handler).toBeInstanceOf(OpenAiHandler)
-        expect(OpenAI).toHaveBeenCalledWith({
-            apiKey: mockOptions.openAiApiKey,
-            baseURL: mockOptions.openAiBaseUrl
-        })
-    })
+    describe('constructor', () => {
+        it('should initialize with provided options', () => {
+            expect(handler).toBeInstanceOf(OpenAiHandler);
+            expect(handler.getModel().id).toBe(mockOptions.openAiModelId);
+        });
 
-    test('constructor initializes Azure client when Azure URL is provided', () => {
-        const azureOptions: ApiHandlerOptions = {
-            ...mockOptions,
-            openAiBaseUrl: 'https://example.azure.com',
-            azureApiVersion: '2023-05-15'
-        }
-        const handler = new OpenAiHandler(azureOptions)
-        expect(handler).toBeInstanceOf(OpenAiHandler)
-        expect(AzureOpenAI).toHaveBeenCalledWith({
-            baseURL: azureOptions.openAiBaseUrl,
-            apiKey: azureOptions.openAiApiKey,
-            apiVersion: azureOptions.azureApiVersion
-        })
-    })
+        it('should use custom base URL if provided', () => {
+            const customBaseUrl = 'https://custom.openai.com/v1';
+            const handlerWithCustomUrl = new OpenAiHandler({
+                ...mockOptions,
+                openAiBaseUrl: customBaseUrl
+            });
+            expect(handlerWithCustomUrl).toBeInstanceOf(OpenAiHandler);
+        });
+    });
 
-    test('getModel returns correct model info', () => {
-        const handler = new OpenAiHandler(mockOptions)
-        const result = handler.getModel()
-        
-        expect(result).toEqual({
-            id: mockOptions.openAiModelId,
-            info: openAiModelInfoSaneDefaults
-        })
-    })
-
-    test('createMessage handles streaming correctly when enabled', async () => {
-        const handler = new OpenAiHandler({
-            ...mockOptions,
-            openAiStreamingEnabled: true,
-            includeMaxTokens: true
-        })
-        
-        const mockStream = {
-            async *[Symbol.asyncIterator]() {
-                yield {
-                    choices: [{
-                        delta: {
-                            content: 'test response'
-                        }
-                    }],
-                    usage: {
-                        prompt_tokens: 10,
-                        completion_tokens: 5
-                    }
-                }
-            }
-        }
-
-        const mockCreate = jest.fn().mockResolvedValue(mockStream)
-        ;(OpenAI as jest.MockedClass<typeof OpenAI>).prototype.chat = {
-            completions: { create: mockCreate }
-        } as any
-
-        const systemPrompt = 'test system prompt'
+    describe('createMessage', () => {
+        const systemPrompt = 'You are a helpful assistant.';
         const messages: Anthropic.Messages.MessageParam[] = [
-            { role: 'user', content: 'test message' }
-        ]
-
-        const generator = handler.createMessage(systemPrompt, messages)
-        const chunks = []
-        
-        for await (const chunk of generator) {
-            chunks.push(chunk)
-        }
-
-        expect(chunks).toEqual([
             {
-                type: 'text',
-                text: 'test response'
-            },
-            {
-                type: 'usage',
-                inputTokens: 10,
-                outputTokens: 5
+                role: 'user',
+                content: [{ 
+                    type: 'text' as const,
+                    text: 'Hello!'
+                }]
             }
-        ])
+        ];
 
-        expect(mockCreate).toHaveBeenCalledWith({
-            model: mockOptions.openAiModelId,
-            messages: [
-                { role: 'system', content: systemPrompt },
-                { role: 'user', content: 'test message' }
-            ],
-            temperature: 0,
-            stream: true,
-            stream_options: { include_usage: true },
-            max_tokens: openAiModelInfoSaneDefaults.maxTokens
-        })
-    })
+        it('should handle non-streaming mode', async () => {
+            const handler = new OpenAiHandler({
+                ...mockOptions,
+                openAiStreamingEnabled: false
+            });
 
-    test('createMessage handles non-streaming correctly when disabled', async () => {
-        const handler = new OpenAiHandler({
-            ...mockOptions,
-            openAiStreamingEnabled: false
-        })
-        
-        const mockResponse = {
-            choices: [{
-                message: {
-                    content: 'test response'
+            const stream = handler.createMessage(systemPrompt, messages);
+            const chunks: any[] = [];
+            for await (const chunk of stream) {
+                chunks.push(chunk);
+            }
+
+            expect(chunks.length).toBeGreaterThan(0);
+            const textChunk = chunks.find(chunk => chunk.type === 'text');
+            const usageChunk = chunks.find(chunk => chunk.type === 'usage');
+            
+            expect(textChunk).toBeDefined();
+            expect(textChunk?.text).toBe('Test response');
+            expect(usageChunk).toBeDefined();
+            expect(usageChunk?.inputTokens).toBe(10);
+            expect(usageChunk?.outputTokens).toBe(5);
+        });
+
+        it('should handle streaming responses', async () => {
+            const stream = handler.createMessage(systemPrompt, messages);
+            const chunks: any[] = [];
+            for await (const chunk of stream) {
+                chunks.push(chunk);
+            }
+
+            expect(chunks.length).toBeGreaterThan(0);
+            const textChunks = chunks.filter(chunk => chunk.type === 'text');
+            expect(textChunks).toHaveLength(1);
+            expect(textChunks[0].text).toBe('Test response');
+        });
+    });
+
+    describe('error handling', () => {
+        const testMessages: Anthropic.Messages.MessageParam[] = [
+            {
+                role: 'user',
+                content: [{ 
+                    type: 'text' as const,
+                    text: 'Hello'
+                }]
+            }
+        ];
+
+        it('should handle API errors', async () => {
+            mockCreate.mockRejectedValueOnce(new Error('API Error'));
+
+            const stream = handler.createMessage('system prompt', testMessages);
+
+            await expect(async () => {
+                for await (const chunk of stream) {
+                    // Should not reach here
                 }
-            }],
-            usage: {
-                prompt_tokens: 10,
-                completion_tokens: 5
-            }
-        }
+            }).rejects.toThrow('API Error');
+        });
 
-        const mockCreate = jest.fn().mockResolvedValue(mockResponse)
-        ;(OpenAI as jest.MockedClass<typeof OpenAI>).prototype.chat = {
-            completions: { create: mockCreate }
-        } as any
+        it('should handle rate limiting', async () => {
+            const rateLimitError = new Error('Rate limit exceeded');
+            rateLimitError.name = 'Error';
+            (rateLimitError as any).status = 429;
+            mockCreate.mockRejectedValueOnce(rateLimitError);
 
-        const systemPrompt = 'test system prompt'
-        const messages: Anthropic.Messages.MessageParam[] = [
-            { role: 'user', content: 'test message' }
-        ]
+            const stream = handler.createMessage('system prompt', testMessages);
 
-        const generator = handler.createMessage(systemPrompt, messages)
-        const chunks = []
-        
-        for await (const chunk of generator) {
-            chunks.push(chunk)
-        }
+            await expect(async () => {
+                for await (const chunk of stream) {
+                    // Should not reach here
+                }
+            }).rejects.toThrow('Rate limit exceeded');
+        });
+    });
 
-        expect(chunks).toEqual([
-            {
-                type: 'text',
-                text: 'test response'
-            },
-            {
-                type: 'usage',
-                inputTokens: 10,
-                outputTokens: 5
-            }
-        ])
+    describe('completePrompt', () => {
+        it('should complete prompt successfully', async () => {
+            const result = await handler.completePrompt('Test prompt');
+            expect(result).toBe('Test response');
+            expect(mockCreate).toHaveBeenCalledWith({
+                model: mockOptions.openAiModelId,
+                messages: [{ role: 'user', content: 'Test prompt' }],
+                temperature: 0
+            });
+        });
 
-        expect(mockCreate).toHaveBeenCalledWith({
-            model: mockOptions.openAiModelId,
-            messages: [
-                { role: 'user', content: systemPrompt },
-                { role: 'user', content: 'test message' }
-            ]
-        })
-    })
+        it('should handle API errors', async () => {
+            mockCreate.mockRejectedValueOnce(new Error('API Error'));
+            await expect(handler.completePrompt('Test prompt'))
+                .rejects.toThrow('OpenAI completion error: API Error');
+        });
 
-    test('createMessage handles API errors', async () => {
-        const handler = new OpenAiHandler(mockOptions)
-        const mockStream = {
-            async *[Symbol.asyncIterator]() {
-                throw new Error('API Error')
-            }
-        }
+        it('should handle empty response', async () => {
+            mockCreate.mockImplementationOnce(() => ({
+                choices: [{ message: { content: '' } }]
+            }));
+            const result = await handler.completePrompt('Test prompt');
+            expect(result).toBe('');
+        });
+    });
 
-        const mockCreate = jest.fn().mockResolvedValue(mockStream)
-        ;(OpenAI as jest.MockedClass<typeof OpenAI>).prototype.chat = {
-            completions: { create: mockCreate }
-        } as any
+    describe('getModel', () => {
+        it('should return model info with sane defaults', () => {
+            const model = handler.getModel();
+            expect(model.id).toBe(mockOptions.openAiModelId);
+            expect(model.info).toBeDefined();
+            expect(model.info.contextWindow).toBe(128_000);
+            expect(model.info.supportsImages).toBe(true);
+        });
 
-        const generator = handler.createMessage('test', [])
-        await expect(generator.next()).rejects.toThrow('API Error')
-    })
-})
+        it('should handle undefined model ID', () => {
+            const handlerWithoutModel = new OpenAiHandler({
+                ...mockOptions,
+                openAiModelId: undefined
+            });
+            const model = handlerWithoutModel.getModel();
+            expect(model.id).toBe('');
+            expect(model.info).toBeDefined();
+        });
+    });
+});

src/api/providers/__tests__/vertex.test.ts

@@ -0,0 +1,296 @@
+import { VertexHandler } from '../vertex';
+import { Anthropic } from '@anthropic-ai/sdk';
+import { AnthropicVertex } from '@anthropic-ai/vertex-sdk';
+
+// Mock Vertex SDK
+jest.mock('@anthropic-ai/vertex-sdk', () => ({
+    AnthropicVertex: jest.fn().mockImplementation(() => ({
+        messages: {
+            create: jest.fn().mockImplementation(async (options) => {
+                if (!options.stream) {
+                    return {
+                        id: 'test-completion',
+                        content: [
+                            { type: 'text', text: 'Test response' }
+                        ],
+                        role: 'assistant',
+                        model: options.model,
+                        usage: {
+                            input_tokens: 10,
+                            output_tokens: 5
+                        }
+                    }
+                }
+                return {
+                    async *[Symbol.asyncIterator]() {
+                        yield {
+                            type: 'message_start',
+                            message: {
+                                usage: {
+                                    input_tokens: 10,
+                                    output_tokens: 5
+                                }
+                            }
+                        }
+                        yield {
+                            type: 'content_block_start',
+                            content_block: {
+                                type: 'text',
+                                text: 'Test response'
+                            }
+                        }
+                    }
+                }
+            })
+        }
+    }))
+}));
+
+describe('VertexHandler', () => {
+    let handler: VertexHandler;
+
+    beforeEach(() => {
+        handler = new VertexHandler({
+            apiModelId: 'claude-3-5-sonnet-v2@20241022',
+            vertexProjectId: 'test-project',
+            vertexRegion: 'us-central1'
+        });
+    });
+
+    describe('constructor', () => {
+        it('should initialize with provided config', () => {
+            expect(AnthropicVertex).toHaveBeenCalledWith({
+                projectId: 'test-project',
+                region: 'us-central1'
+            });
+        });
+    });
+
+    describe('createMessage', () => {
+        const mockMessages: Anthropic.Messages.MessageParam[] = [
+            {
+                role: 'user',
+                content: 'Hello'
+            },
+            {
+                role: 'assistant',
+                content: 'Hi there!'
+            }
+        ];
+
+        const systemPrompt = 'You are a helpful assistant';
+
+        it('should handle streaming responses correctly', async () => {
+            const mockStream = [
+                {
+                    type: 'message_start',
+                    message: {
+                        usage: {
+                            input_tokens: 10,
+                            output_tokens: 0
+                        }
+                    }
+                },
+                {
+                    type: 'content_block_start',
+                    index: 0,
+                    content_block: {
+                        type: 'text',
+                        text: 'Hello'
+                    }
+                },
+                {
+                    type: 'content_block_delta',
+                    delta: {
+                        type: 'text_delta',
+                        text: ' world!'
+                    }
+                },
+                {
+                    type: 'message_delta',
+                    usage: {
+                        output_tokens: 5
+                    }
+                }
+            ];
+
+            // Setup async iterator for mock stream
+            const asyncIterator = {
+                async *[Symbol.asyncIterator]() {
+                    for (const chunk of mockStream) {
+                        yield chunk;
+                    }
+                }
+            };
+
+            const mockCreate = jest.fn().mockResolvedValue(asyncIterator);
+            (handler['client'].messages as any).create = mockCreate;
+
+            const stream = handler.createMessage(systemPrompt, mockMessages);
+            const chunks = [];
+            
+            for await (const chunk of stream) {
+                chunks.push(chunk);
+            }
+
+            expect(chunks.length).toBe(4);
+            expect(chunks[0]).toEqual({
+                type: 'usage',
+                inputTokens: 10,
+                outputTokens: 0
+            });
+            expect(chunks[1]).toEqual({
+                type: 'text',
+                text: 'Hello'
+            });
+            expect(chunks[2]).toEqual({
+                type: 'text',
+                text: ' world!'
+            });
+            expect(chunks[3]).toEqual({
+                type: 'usage',
+                inputTokens: 0,
+                outputTokens: 5
+            });
+
+            expect(mockCreate).toHaveBeenCalledWith({
+                model: 'claude-3-5-sonnet-v2@20241022',
+                max_tokens: 8192,
+                temperature: 0,
+                system: systemPrompt,
+                messages: mockMessages,
+                stream: true
+            });
+        });
+
+        it('should handle multiple content blocks with line breaks', async () => {
+            const mockStream = [
+                {
+                    type: 'content_block_start',
+                    index: 0,
+                    content_block: {
+                        type: 'text',
+                        text: 'First line'
+                    }
+                },
+                {
+                    type: 'content_block_start',
+                    index: 1,
+                    content_block: {
+                        type: 'text',
+                        text: 'Second line'
+                    }
+                }
+            ];
+
+            const asyncIterator = {
+                async *[Symbol.asyncIterator]() {
+                    for (const chunk of mockStream) {
+                        yield chunk;
+                    }
+                }
+            };
+
+            const mockCreate = jest.fn().mockResolvedValue(asyncIterator);
+            (handler['client'].messages as any).create = mockCreate;
+
+            const stream = handler.createMessage(systemPrompt, mockMessages);
+            const chunks = [];
+            
+            for await (const chunk of stream) {
+                chunks.push(chunk);
+            }
+
+            expect(chunks.length).toBe(3);
+            expect(chunks[0]).toEqual({
+                type: 'text',
+                text: 'First line'
+            });
+            expect(chunks[1]).toEqual({
+                type: 'text',
+                text: '\n'
+            });
+            expect(chunks[2]).toEqual({
+                type: 'text',
+                text: 'Second line'
+            });
+        });
+
+        it('should handle API errors', async () => {
+            const mockError = new Error('Vertex API error');
+            const mockCreate = jest.fn().mockRejectedValue(mockError);
+            (handler['client'].messages as any).create = mockCreate;
+
+            const stream = handler.createMessage(systemPrompt, mockMessages);
+
+            await expect(async () => {
+                for await (const chunk of stream) {
+                    // Should throw before yielding any chunks
+                }
+            }).rejects.toThrow('Vertex API error');
+        });
+    });
+
+    describe('completePrompt', () => {
+        it('should complete prompt successfully', async () => {
+            const result = await handler.completePrompt('Test prompt');
+            expect(result).toBe('Test response');
+            expect(handler['client'].messages.create).toHaveBeenCalledWith({
+                model: 'claude-3-5-sonnet-v2@20241022',
+                max_tokens: 8192,
+                temperature: 0,
+                messages: [{ role: 'user', content: 'Test prompt' }],
+                stream: false
+            });
+        });
+
+        it('should handle API errors', async () => {
+            const mockError = new Error('Vertex API error');
+            const mockCreate = jest.fn().mockRejectedValue(mockError);
+            (handler['client'].messages as any).create = mockCreate;
+
+            await expect(handler.completePrompt('Test prompt'))
+                .rejects.toThrow('Vertex completion error: Vertex API error');
+        });
+
+        it('should handle non-text content', async () => {
+            const mockCreate = jest.fn().mockResolvedValue({
+                content: [{ type: 'image' }]
+            });
+            (handler['client'].messages as any).create = mockCreate;
+
+            const result = await handler.completePrompt('Test prompt');
+            expect(result).toBe('');
+        });
+
+        it('should handle empty response', async () => {
+            const mockCreate = jest.fn().mockResolvedValue({
+                content: [{ type: 'text', text: '' }]
+            });
+            (handler['client'].messages as any).create = mockCreate;
+
+            const result = await handler.completePrompt('Test prompt');
+            expect(result).toBe('');
+        });
+    });
+
+    describe('getModel', () => {
+        it('should return correct model info', () => {
+            const modelInfo = handler.getModel();
+            expect(modelInfo.id).toBe('claude-3-5-sonnet-v2@20241022');
+            expect(modelInfo.info).toBeDefined();
+            expect(modelInfo.info.maxTokens).toBe(8192);
+            expect(modelInfo.info.contextWindow).toBe(200_000);
+        });
+
+        it('should return default model if invalid model specified', () => {
+            const invalidHandler = new VertexHandler({
+                apiModelId: 'invalid-model',
+                vertexProjectId: 'test-project',
+                vertexRegion: 'us-central1'
+            });
+            const modelInfo = invalidHandler.getModel();
+            expect(modelInfo.id).toBe('claude-3-5-sonnet-v2@20241022'); // Default model
+        });
+    });
+});

src/api/providers/anthropic.ts

@@ -7,10 +7,10 @@ import {
 	ApiHandlerOptions,
 	ModelInfo,
 } from "../../shared/api"
-import { ApiHandler } from "../index"
+import { ApiHandler, SingleCompletionHandler } from "../index"
 import { ApiStream } from "../transform/stream"
 
-export class AnthropicHandler implements ApiHandler {
+export class AnthropicHandler implements ApiHandler, SingleCompletionHandler {
 	private options: ApiHandlerOptions
 	private client: Anthropic
 
@@ -173,4 +173,27 @@ export class AnthropicHandler implements ApiHandler {
 		}
 		return { id: anthropicDefaultModelId, info: anthropicModels[anthropicDefaultModelId] }
 	}
+
+	async completePrompt(prompt: string): Promise<string> {
+		try {
+			const response = await this.client.messages.create({
+				model: this.getModel().id,
+				max_tokens: this.getModel().info.maxTokens || 8192,
+				temperature: 0,
+				messages: [{ role: "user", content: prompt }],
+				stream: false
+			})
+
+			const content = response.content[0]
+			if (content.type === 'text') {
+				return content.text
+			}
+			return ''
+		} catch (error) {
+			if (error instanceof Error) {
+				throw new Error(`Anthropic completion error: ${error.message}`)
+			}
+			throw error
+		}
+	}
 }

src/api/providers/bedrock.ts

@@ -1,6 +1,6 @@
-import { BedrockRuntimeClient, ConverseStreamCommand, BedrockRuntimeClientConfig } from "@aws-sdk/client-bedrock-runtime"
+import { BedrockRuntimeClient, ConverseStreamCommand, ConverseCommand, BedrockRuntimeClientConfig } from "@aws-sdk/client-bedrock-runtime"
 import { Anthropic } from "@anthropic-ai/sdk"
-import { ApiHandler } from "../"
+import { ApiHandler, SingleCompletionHandler } from "../"
 import { ApiHandlerOptions, BedrockModelId, ModelInfo, bedrockDefaultModelId, bedrockModels } from "../../shared/api"
 import { ApiStream } from "../transform/stream"
 import { convertToBedrockConverseMessages, convertToAnthropicMessage } from "../transform/bedrock-converse-format"
@@ -38,7 +38,7 @@ export interface StreamEvent {
     };
 }
 
-export class AwsBedrockHandler implements ApiHandler {
+export class AwsBedrockHandler implements ApiHandler, SingleCompletionHandler {
     private options: ApiHandlerOptions
     private client: BedrockRuntimeClient
 
@@ -199,7 +199,7 @@ export class AwsBedrockHandler implements ApiHandler {
         if (modelId) {
             // For tests, allow any model ID
             if (process.env.NODE_ENV === 'test') {
-                return { 
+                return {
                     id: modelId,
                     info: {
                         maxTokens: 5000,
@@ -214,9 +214,68 @@ export class AwsBedrockHandler implements ApiHandler {
                 return { id, info: bedrockModels[id] }
             }
         }
-        return { 
-            id: bedrockDefaultModelId, 
-            info: bedrockModels[bedrockDefaultModelId] 
+        return {
+            id: bedrockDefaultModelId,
+            info: bedrockModels[bedrockDefaultModelId]
+        }
+    }
+
+    async completePrompt(prompt: string): Promise<string> {
+        try {
+            const modelConfig = this.getModel()
+            
+            // Handle cross-region inference
+            let modelId: string
+            if (this.options.awsUseCrossRegionInference) {
+                let regionPrefix = (this.options.awsRegion || "").slice(0, 3)
+                switch (regionPrefix) {
+                    case "us-":
+                        modelId = `us.${modelConfig.id}`
+                        break
+                    case "eu-":
+                        modelId = `eu.${modelConfig.id}`
+                        break
+                    default:
+                        modelId = modelConfig.id
+                        break
+                }
+            } else {
+                modelId = modelConfig.id
+            }
+
+            const payload = {
+                modelId,
+                messages: convertToBedrockConverseMessages([{
+                    role: "user",
+                    content: prompt
+                }]),
+                inferenceConfig: {
+                    maxTokens: modelConfig.info.maxTokens || 5000,
+                    temperature: 0.3,
+                    topP: 0.1
+                }
+            }
+
+            const command = new ConverseCommand(payload)
+            const response = await this.client.send(command)
+
+            if (response.output && response.output instanceof Uint8Array) {
+                try {
+                    const outputStr = new TextDecoder().decode(response.output)
+                    const output = JSON.parse(outputStr)
+                    if (output.content) {
+                        return output.content
+                    }
+                } catch (parseError) {
+                    console.error('Failed to parse Bedrock response:', parseError)
+                }
+            }
+            return ''
+        } catch (error) {
+            if (error instanceof Error) {
+                throw new Error(`Bedrock completion error: ${error.message}`)
+            }
+            throw error
         }
     }
 }

src/api/providers/gemini.ts

@@ -1,11 +1,11 @@
 import { Anthropic } from "@anthropic-ai/sdk"
 import { GoogleGenerativeAI } from "@google/generative-ai"
-import { ApiHandler } from "../"
+import { ApiHandler, SingleCompletionHandler } from "../"
 import { ApiHandlerOptions, geminiDefaultModelId, GeminiModelId, geminiModels, ModelInfo } from "../../shared/api"
 import { convertAnthropicMessageToGemini } from "../transform/gemini-format"
 import { ApiStream } from "../transform/stream"
 
-export class GeminiHandler implements ApiHandler {
+export class GeminiHandler implements ApiHandler, SingleCompletionHandler {
 	private options: ApiHandlerOptions
 	private client: GoogleGenerativeAI
 
@@ -53,4 +53,26 @@ export class GeminiHandler implements ApiHandler {
 		}
 		return { id: geminiDefaultModelId, info: geminiModels[geminiDefaultModelId] }
 	}
+
+	async completePrompt(prompt: string): Promise<string> {
+		try {
+			const model = this.client.getGenerativeModel({
+				model: this.getModel().id,
+			})
+
+			const result = await model.generateContent({
+				contents: [{ role: "user", parts: [{ text: prompt }] }],
+				generationConfig: {
+					temperature: 0,
+				},
+			})
+
+			return result.response.text()
+		} catch (error) {
+			if (error instanceof Error) {
+				throw new Error(`Gemini completion error: ${error.message}`)
+			}
+			throw error
+		}
+	}
 }

src/api/providers/glama.ts

@@ -1,13 +1,13 @@
 import { Anthropic } from "@anthropic-ai/sdk"
 import axios from "axios"
 import OpenAI from "openai"
-import { ApiHandler } from "../"
+import { ApiHandler, SingleCompletionHandler } from "../"
 import { ApiHandlerOptions, ModelInfo, glamaDefaultModelId, glamaDefaultModelInfo } from "../../shared/api"
 import { convertToOpenAiMessages } from "../transform/openai-format"
 import { ApiStream } from "../transform/stream"
 import delay from "delay"
 
-export class GlamaHandler implements ApiHandler {
+export class GlamaHandler implements ApiHandler, SingleCompletionHandler {
 	private options: ApiHandlerOptions
 	private client: OpenAI
 
@@ -129,4 +129,26 @@ export class GlamaHandler implements ApiHandler {
 		
 		return { id: glamaDefaultModelId, info: glamaDefaultModelInfo }
 	}
+
+	async completePrompt(prompt: string): Promise<string> {
+		try {
+			const requestOptions: OpenAI.Chat.Completions.ChatCompletionCreateParamsNonStreaming = {
+				model: this.getModel().id,
+				messages: [{ role: "user", content: prompt }],
+				temperature: 0,
+			}
+
+			if (this.getModel().id.startsWith("anthropic/")) {
+				requestOptions.max_tokens = 8192
+			}
+			
+			const response = await this.client.chat.completions.create(requestOptions)
+			return response.choices[0]?.message.content || ""
+		} catch (error) {
+			if (error instanceof Error) {
+				throw new Error(`Glama completion error: ${error.message}`)
+			}
+			throw error
+		}
+	}
 }

src/api/providers/lmstudio.ts

@@ -1,11 +1,11 @@
 import { Anthropic } from "@anthropic-ai/sdk"
 import OpenAI from "openai"
-import { ApiHandler } from "../"
+import { ApiHandler, SingleCompletionHandler } from "../"
 import { ApiHandlerOptions, ModelInfo, openAiModelInfoSaneDefaults } from "../../shared/api"
 import { convertToOpenAiMessages } from "../transform/openai-format"
 import { ApiStream } from "../transform/stream"
 
-export class LmStudioHandler implements ApiHandler {
+export class LmStudioHandler implements ApiHandler, SingleCompletionHandler {
 	private options: ApiHandlerOptions
 	private client: OpenAI
 
@@ -53,4 +53,20 @@ export class LmStudioHandler implements ApiHandler {
 			info: openAiModelInfoSaneDefaults,
 		}
 	}
+
+	async completePrompt(prompt: string): Promise<string> {
+		try {
+			const response = await this.client.chat.completions.create({
+				model: this.getModel().id,
+				messages: [{ role: "user", content: prompt }],
+				temperature: 0,
+				stream: false
+			})
+			return response.choices[0]?.message.content || ""
+		} catch (error) {
+			throw new Error(
+				"Please check the LM Studio developer logs to debug what went wrong. You may need to load the model with a larger context length to work with Cline's prompts.",
+			)
+		}
+	}
 }

src/api/providers/ollama.ts

@@ -1,11 +1,11 @@
 import { Anthropic } from "@anthropic-ai/sdk"
 import OpenAI from "openai"
-import { ApiHandler } from "../"
+import { ApiHandler, SingleCompletionHandler } from "../"
 import { ApiHandlerOptions, ModelInfo, openAiModelInfoSaneDefaults } from "../../shared/api"
 import { convertToOpenAiMessages } from "../transform/openai-format"
 import { ApiStream } from "../transform/stream"
 
-export class OllamaHandler implements ApiHandler {
+export class OllamaHandler implements ApiHandler, SingleCompletionHandler {
 	private options: ApiHandlerOptions
 	private client: OpenAI
 
@@ -46,4 +46,21 @@ export class OllamaHandler implements ApiHandler {
 			info: openAiModelInfoSaneDefaults,
 		}
 	}
+
+	async completePrompt(prompt: string): Promise<string> {
+		try {
+			const response = await this.client.chat.completions.create({
+				model: this.getModel().id,
+				messages: [{ role: "user", content: prompt }],
+				temperature: 0,
+				stream: false
+			})
+			return response.choices[0]?.message.content || ""
+		} catch (error) {
+			if (error instanceof Error) {
+				throw new Error(`Ollama completion error: ${error.message}`)
+			}
+			throw error
+		}
+	}
 }

src/api/providers/openai-native.ts

@@ -1,6 +1,6 @@
 import { Anthropic } from "@anthropic-ai/sdk"
 import OpenAI from "openai"
-import { ApiHandler } from "../"
+import { ApiHandler, SingleCompletionHandler } from "../"
 import {
 	ApiHandlerOptions,
 	ModelInfo,
@@ -11,7 +11,7 @@ import {
 import { convertToOpenAiMessages } from "../transform/openai-format"
 import { ApiStream } from "../transform/stream"
 
-export class OpenAiNativeHandler implements ApiHandler {
+export class OpenAiNativeHandler implements ApiHandler, SingleCompletionHandler {
 	private options: ApiHandlerOptions
 	private client: OpenAI
 
@@ -83,4 +83,37 @@ export class OpenAiNativeHandler implements ApiHandler {
 		}
 		return { id: openAiNativeDefaultModelId, info: openAiNativeModels[openAiNativeDefaultModelId] }
 	}
+
+	async completePrompt(prompt: string): Promise<string> {
+		try {
+			const modelId = this.getModel().id
+			let requestOptions: OpenAI.Chat.Completions.ChatCompletionCreateParamsNonStreaming
+
+			switch (modelId) {
+				case "o1":
+				case "o1-preview":
+				case "o1-mini":
+					// o1 doesn't support non-1 temp or system prompt
+					requestOptions = {
+						model: modelId,
+						messages: [{ role: "user", content: prompt }]
+					}
+					break
+				default:
+					requestOptions = {
+						model: modelId,
+						messages: [{ role: "user", content: prompt }],
+						temperature: 0
+					}
+			}
+
+			const response = await this.client.chat.completions.create(requestOptions)
+			return response.choices[0]?.message.content || ""
+		} catch (error) {
+			if (error instanceof Error) {
+				throw new Error(`OpenAI Native completion error: ${error.message}`)
+			}
+			throw error
+		}
+	}
 }

src/api/providers/openai.ts

@@ -6,11 +6,11 @@ import {
 	ModelInfo,
 	openAiModelInfoSaneDefaults,
 } from "../../shared/api"
-import { ApiHandler } from "../index"
+import { ApiHandler, SingleCompletionHandler } from "../index"
 import { convertToOpenAiMessages } from "../transform/openai-format"
 import { ApiStream } from "../transform/stream"
 
-export class OpenAiHandler implements ApiHandler {
+export class OpenAiHandler implements ApiHandler, SingleCompletionHandler {
 	protected options: ApiHandlerOptions
 	private client: OpenAI
 
@@ -100,4 +100,22 @@ export class OpenAiHandler implements ApiHandler {
 			info: openAiModelInfoSaneDefaults,
 		}
 	}
+
+	async completePrompt(prompt: string): Promise<string> {
+		try {
+			const requestOptions: OpenAI.Chat.Completions.ChatCompletionCreateParamsNonStreaming = {
+				model: this.getModel().id,
+				messages: [{ role: "user", content: prompt }],
+				temperature: 0,
+			}
+			
+			const response = await this.client.chat.completions.create(requestOptions)
+			return response.choices[0]?.message.content || ""
+		} catch (error) {
+			if (error instanceof Error) {
+				throw new Error(`OpenAI completion error: ${error.message}`)
+			}
+			throw error
+		}
+	}
 }

src/api/providers/vertex.ts

@@ -1,11 +1,11 @@
 import { Anthropic } from "@anthropic-ai/sdk"
 import { AnthropicVertex } from "@anthropic-ai/vertex-sdk"
-import { ApiHandler } from "../"
+import { ApiHandler, SingleCompletionHandler } from "../"
 import { ApiHandlerOptions, ModelInfo, vertexDefaultModelId, VertexModelId, vertexModels } from "../../shared/api"
 import { ApiStream } from "../transform/stream"
 
 // https://docs.anthropic.com/en/api/claude-on-vertex-ai
-export class VertexHandler implements ApiHandler {
+export class VertexHandler implements ApiHandler, SingleCompletionHandler {
 	private options: ApiHandlerOptions
 	private client: AnthropicVertex
 
@@ -83,4 +83,27 @@ export class VertexHandler implements ApiHandler {
 		}
 		return { id: vertexDefaultModelId, info: vertexModels[vertexDefaultModelId] }
 	}
+
+	async completePrompt(prompt: string): Promise<string> {
+		try {
+			const response = await this.client.messages.create({
+				model: this.getModel().id,
+				max_tokens: this.getModel().info.maxTokens || 8192,
+				temperature: 0,
+				messages: [{ role: "user", content: prompt }],
+				stream: false
+			})
+
+			const content = response.content[0]
+			if (content.type === 'text') {
+				return content.text
+			}
+			return ''
+		} catch (error) {
+			if (error instanceof Error) {
+				throw new Error(`Vertex completion error: ${error.message}`)
+			}
+			throw error
+		}
+	}
 }

src/api/transform/__tests__/openai-format.test.ts

@@ -0,0 +1,257 @@
+import { convertToOpenAiMessages, convertToAnthropicMessage } from '../openai-format';
+import { Anthropic } from '@anthropic-ai/sdk';
+import OpenAI from 'openai';
+
+type PartialChatCompletion = Omit<OpenAI.Chat.Completions.ChatCompletion, 'choices'> & {
+    choices: Array<Partial<OpenAI.Chat.Completions.ChatCompletion.Choice> & {
+        message: OpenAI.Chat.Completions.ChatCompletion.Choice['message'];
+        finish_reason: string;
+        index: number;
+    }>;
+};
+
+describe('OpenAI Format Transformations', () => {
+    describe('convertToOpenAiMessages', () => {
+        it('should convert simple text messages', () => {
+            const anthropicMessages: Anthropic.Messages.MessageParam[] = [
+                {
+                    role: 'user',
+                    content: 'Hello'
+                },
+                {
+                    role: 'assistant',
+                    content: 'Hi there!'
+                }
+            ];
+
+            const openAiMessages = convertToOpenAiMessages(anthropicMessages);
+            expect(openAiMessages).toHaveLength(2);
+            expect(openAiMessages[0]).toEqual({
+                role: 'user',
+                content: 'Hello'
+            });
+            expect(openAiMessages[1]).toEqual({
+                role: 'assistant',
+                content: 'Hi there!'
+            });
+        });
+
+        it('should handle messages with image content', () => {
+            const anthropicMessages: Anthropic.Messages.MessageParam[] = [
+                {
+                    role: 'user',
+                    content: [
+                        {
+                            type: 'text',
+                            text: 'What is in this image?'
+                        },
+                        {
+                            type: 'image',
+                            source: {
+                                type: 'base64',
+                                media_type: 'image/jpeg',
+                                data: 'base64data'
+                            }
+                        }
+                    ]
+                }
+            ];
+
+            const openAiMessages = convertToOpenAiMessages(anthropicMessages);
+            expect(openAiMessages).toHaveLength(1);
+            expect(openAiMessages[0].role).toBe('user');
+            
+            const content = openAiMessages[0].content as Array<{
+                type: string;
+                text?: string;
+                image_url?: { url: string };
+            }>;
+            
+            expect(Array.isArray(content)).toBe(true);
+            expect(content).toHaveLength(2);
+            expect(content[0]).toEqual({ type: 'text', text: 'What is in this image?' });
+            expect(content[1]).toEqual({
+                type: 'image_url',
+                image_url: { url: 'data:image/jpeg;base64,base64data' }
+            });
+        });
+
+        it('should handle assistant messages with tool use', () => {
+            const anthropicMessages: Anthropic.Messages.MessageParam[] = [
+                {
+                    role: 'assistant',
+                    content: [
+                        {
+                            type: 'text',
+                            text: 'Let me check the weather.'
+                        },
+                        {
+                            type: 'tool_use',
+                            id: 'weather-123',
+                            name: 'get_weather',
+                            input: { city: 'London' }
+                        }
+                    ]
+                }
+            ];
+
+            const openAiMessages = convertToOpenAiMessages(anthropicMessages);
+            expect(openAiMessages).toHaveLength(1);
+            
+            const assistantMessage = openAiMessages[0] as OpenAI.Chat.ChatCompletionAssistantMessageParam;
+            expect(assistantMessage.role).toBe('assistant');
+            expect(assistantMessage.content).toBe('Let me check the weather.');
+            expect(assistantMessage.tool_calls).toHaveLength(1);
+            expect(assistantMessage.tool_calls![0]).toEqual({
+                id: 'weather-123',
+                type: 'function',
+                function: {
+                    name: 'get_weather',
+                    arguments: JSON.stringify({ city: 'London' })
+                }
+            });
+        });
+
+        it('should handle user messages with tool results', () => {
+            const anthropicMessages: Anthropic.Messages.MessageParam[] = [
+                {
+                    role: 'user',
+                    content: [
+                        {
+                            type: 'tool_result',
+                            tool_use_id: 'weather-123',
+                            content: 'Current temperature in London: 20°C'
+                        }
+                    ]
+                }
+            ];
+
+            const openAiMessages = convertToOpenAiMessages(anthropicMessages);
+            expect(openAiMessages).toHaveLength(1);
+            
+            const toolMessage = openAiMessages[0] as OpenAI.Chat.ChatCompletionToolMessageParam;
+            expect(toolMessage.role).toBe('tool');
+            expect(toolMessage.tool_call_id).toBe('weather-123');
+            expect(toolMessage.content).toBe('Current temperature in London: 20°C');
+        });
+    });
+
+    describe('convertToAnthropicMessage', () => {
+        it('should convert simple completion', () => {
+            const openAiCompletion: PartialChatCompletion = {
+                id: 'completion-123',
+                model: 'gpt-4',
+                choices: [{
+                    message: {
+                        role: 'assistant',
+                        content: 'Hello there!',
+                        refusal: null
+                    },
+                    finish_reason: 'stop',
+                    index: 0
+                }],
+                usage: {
+                    prompt_tokens: 10,
+                    completion_tokens: 5,
+                    total_tokens: 15
+                },
+                created: 123456789,
+                object: 'chat.completion'
+            };
+
+            const anthropicMessage = convertToAnthropicMessage(openAiCompletion as OpenAI.Chat.Completions.ChatCompletion);
+            expect(anthropicMessage.id).toBe('completion-123');
+            expect(anthropicMessage.role).toBe('assistant');
+            expect(anthropicMessage.content).toHaveLength(1);
+            expect(anthropicMessage.content[0]).toEqual({
+                type: 'text',
+                text: 'Hello there!'
+            });
+            expect(anthropicMessage.stop_reason).toBe('end_turn');
+            expect(anthropicMessage.usage).toEqual({
+                input_tokens: 10,
+                output_tokens: 5
+            });
+        });
+
+        it('should handle tool calls in completion', () => {
+            const openAiCompletion: PartialChatCompletion = {
+                id: 'completion-123',
+                model: 'gpt-4',
+                choices: [{
+                    message: {
+                        role: 'assistant',
+                        content: 'Let me check the weather.',
+                        tool_calls: [{
+                            id: 'weather-123',
+                            type: 'function',
+                            function: {
+                                name: 'get_weather',
+                                arguments: '{"city":"London"}'
+                            }
+                        }],
+                        refusal: null
+                    },
+                    finish_reason: 'tool_calls',
+                    index: 0
+                }],
+                usage: {
+                    prompt_tokens: 15,
+                    completion_tokens: 8,
+                    total_tokens: 23
+                },
+                created: 123456789,
+                object: 'chat.completion'
+            };
+
+            const anthropicMessage = convertToAnthropicMessage(openAiCompletion as OpenAI.Chat.Completions.ChatCompletion);
+            expect(anthropicMessage.content).toHaveLength(2);
+            expect(anthropicMessage.content[0]).toEqual({
+                type: 'text',
+                text: 'Let me check the weather.'
+            });
+            expect(anthropicMessage.content[1]).toEqual({
+                type: 'tool_use',
+                id: 'weather-123',
+                name: 'get_weather',
+                input: { city: 'London' }
+            });
+            expect(anthropicMessage.stop_reason).toBe('tool_use');
+        });
+
+        it('should handle invalid tool call arguments', () => {
+            const openAiCompletion: PartialChatCompletion = {
+                id: 'completion-123',
+                model: 'gpt-4',
+                choices: [{
+                    message: {
+                        role: 'assistant',
+                        content: 'Testing invalid arguments',
+                        tool_calls: [{
+                            id: 'test-123',
+                            type: 'function',
+                            function: {
+                                name: 'test_function',
+                                arguments: 'invalid json'
+                            }
+                        }],
+                        refusal: null
+                    },
+                    finish_reason: 'tool_calls',
+                    index: 0
+                }],
+                created: 123456789,
+                object: 'chat.completion'
+            };
+
+            const anthropicMessage = convertToAnthropicMessage(openAiCompletion as OpenAI.Chat.Completions.ChatCompletion);
+            expect(anthropicMessage.content).toHaveLength(2);
+            expect(anthropicMessage.content[1]).toEqual({
+                type: 'tool_use',
+                id: 'test-123',
+                name: 'test_function',
+                input: {}  // Should default to empty object for invalid JSON
+            });
+        });
+    });
+});

src/api/transform/__tests__/stream.test.ts

@@ -0,0 +1,114 @@
+import { ApiStreamChunk } from '../stream';
+
+describe('API Stream Types', () => {
+    describe('ApiStreamChunk', () => {
+        it('should correctly handle text chunks', () => {
+            const textChunk: ApiStreamChunk = {
+                type: 'text',
+                text: 'Hello world'
+            };
+
+            expect(textChunk.type).toBe('text');
+            expect(textChunk.text).toBe('Hello world');
+        });
+
+        it('should correctly handle usage chunks with cache information', () => {
+            const usageChunk: ApiStreamChunk = {
+                type: 'usage',
+                inputTokens: 100,
+                outputTokens: 50,
+                cacheWriteTokens: 20,
+                cacheReadTokens: 10
+            };
+
+            expect(usageChunk.type).toBe('usage');
+            expect(usageChunk.inputTokens).toBe(100);
+            expect(usageChunk.outputTokens).toBe(50);
+            expect(usageChunk.cacheWriteTokens).toBe(20);
+            expect(usageChunk.cacheReadTokens).toBe(10);
+        });
+
+        it('should handle usage chunks without cache tokens', () => {
+            const usageChunk: ApiStreamChunk = {
+                type: 'usage',
+                inputTokens: 100,
+                outputTokens: 50
+            };
+
+            expect(usageChunk.type).toBe('usage');
+            expect(usageChunk.inputTokens).toBe(100);
+            expect(usageChunk.outputTokens).toBe(50);
+            expect(usageChunk.cacheWriteTokens).toBeUndefined();
+            expect(usageChunk.cacheReadTokens).toBeUndefined();
+        });
+
+        it('should handle text chunks with empty strings', () => {
+            const emptyTextChunk: ApiStreamChunk = {
+                type: 'text',
+                text: ''
+            };
+
+            expect(emptyTextChunk.type).toBe('text');
+            expect(emptyTextChunk.text).toBe('');
+        });
+
+        it('should handle usage chunks with zero tokens', () => {
+            const zeroUsageChunk: ApiStreamChunk = {
+                type: 'usage',
+                inputTokens: 0,
+                outputTokens: 0
+            };
+
+            expect(zeroUsageChunk.type).toBe('usage');
+            expect(zeroUsageChunk.inputTokens).toBe(0);
+            expect(zeroUsageChunk.outputTokens).toBe(0);
+        });
+
+        it('should handle usage chunks with large token counts', () => {
+            const largeUsageChunk: ApiStreamChunk = {
+                type: 'usage',
+                inputTokens: 1000000,
+                outputTokens: 500000,
+                cacheWriteTokens: 200000,
+                cacheReadTokens: 100000
+            };
+
+            expect(largeUsageChunk.type).toBe('usage');
+            expect(largeUsageChunk.inputTokens).toBe(1000000);
+            expect(largeUsageChunk.outputTokens).toBe(500000);
+            expect(largeUsageChunk.cacheWriteTokens).toBe(200000);
+            expect(largeUsageChunk.cacheReadTokens).toBe(100000);
+        });
+
+        it('should handle text chunks with special characters', () => {
+            const specialCharsChunk: ApiStreamChunk = {
+                type: 'text',
+                text: '!@#$%^&*()_+-=[]{}|;:,.<>?`~'
+            };
+
+            expect(specialCharsChunk.type).toBe('text');
+            expect(specialCharsChunk.text).toBe('!@#$%^&*()_+-=[]{}|;:,.<>?`~');
+        });
+
+        it('should handle text chunks with unicode characters', () => {
+            const unicodeChunk: ApiStreamChunk = {
+                type: 'text',
+                text: '你好世界👋🌍'
+            };
+
+            expect(unicodeChunk.type).toBe('text');
+            expect(unicodeChunk.text).toBe('你好世界👋🌍');
+        });
+
+        it('should handle text chunks with multiline content', () => {
+            const multilineChunk: ApiStreamChunk = {
+                type: 'text',
+                text: 'Line 1\nLine 2\nLine 3'
+            };
+
+            expect(multilineChunk.type).toBe('text');
+            expect(multilineChunk.text).toBe('Line 1\nLine 2\nLine 3');
+            expect(multilineChunk.text.split('\n')).toHaveLength(3);
+        });
+    });
+});