feat: add image.analyze tool for vision model analysis

Provides a factory createImageAnalyzeTool(modelClient) that sends images
to a vision-capable model and returns a textual analysis. Includes 15
tests covering base64, URL, multi-image, error, and edge cases.
This commit is contained in:
William Valentin
2026-02-07 09:08:53 -08:00
parent d4530a7034
commit 1e6f6bb5a4
2 changed files with 427 additions and 0 deletions
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import { describe, it, expect, beforeEach, afterEach, vi } from 'vitest';
import type { ModelClient, ChatRequest, ChatResponse } from '../../models/types.js';
import { createImageAnalyzeTool } from './image-analyze.js';
describe('image.analyze tool', () => {
let mockClient: ModelClient & { chat: ReturnType<typeof vi.fn> };
beforeEach(() => {
mockClient = {
chat: vi.fn()
};
});
afterEach(() => {
vi.clearAllMocks();
});
it('has correct metadata', () => {
const tool = createImageAnalyzeTool(mockClient);
expect(tool.name).toBe('image.analyze');
expect(tool.inputSchema.required).toHaveLength(0);
});
it('analyzes image from URL', async () => {
mockClient.chat = vi.fn().mockResolvedValueOnce({
content: 'This is a beautiful sunset over the ocean.',
stopReason: 'end_turn',
usage: { inputTokens: 100, outputTokens: 50 }
});
const tool = createImageAnalyzeTool(mockClient);
const result = await tool.execute({ url: 'https://example.com/image.jpg' });
expect(result.success).toBe(true);
expect(result.output).toBe('This is a beautiful sunset over the ocean.');
expect(mockClient.chat).toHaveBeenCalledTimes(1);
expect(mockClient.chat).toHaveBeenCalledWith(
expect.objectContaining({
messages: expect.arrayContaining([
expect.objectContaining({
role: 'user',
content: expect.arrayContaining([
{ type: 'text', text: 'Describe this image in detail.' },
{
type: 'image',
source: expect.objectContaining({
type: 'url',
media_type: 'image/jpeg',
url: 'https://example.com/image.jpg'
})
}
])
})
]),
system: expect.stringContaining('vision assistant'),
maxTokens: 1024
})
);
});
it('analyzes image from base64 data', async () => {
const base64Data = 'iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mNk+M9QDwADhgGAWjR9awAAAABJRU5ErkJggg==';
mockClient.chat = vi.fn().mockResolvedValueOnce({
content: 'This is a sample image.',
stopReason: 'end_turn',
usage: { inputTokens: 100, outputTokens: 20 }
});
const tool = createImageAnalyzeTool(mockClient);
const result = await tool.execute({
data: base64Data,
media_type: 'image/png'
});
expect(result.success).toBe(true);
expect(result.output).toBe('This is a sample image.');
expect(mockClient.chat).toHaveBeenCalledTimes(1);
expect(mockClient.chat).toHaveBeenCalledWith(
expect.objectContaining({
messages: expect.arrayContaining([
expect.objectContaining({
role: 'user',
content: expect.arrayContaining([
{ type: 'text', text: 'Describe this image in detail.' },
{
type: 'image',
source: expect.objectContaining({
type: 'base64',
media_type: 'image/png',
data: base64Data
})
}
])
})
]),
system: expect.stringContaining('vision assistant'),
maxTokens: 1024
})
);
});
it('uses custom prompt', async () => {
mockClient.chat = vi.fn().mockResolvedValueOnce({
content: 'The image shows a cat sitting on a mat.',
stopReason: 'end_turn',
usage: { inputTokens: 100, outputTokens: 30 }
});
const tool = createImageAnalyzeTool(mockClient);
const result = await tool.execute({
url: 'https://example.com/cat.jpg',
prompt: 'What is in this image?'
});
expect(result.success).toBe(true);
expect(result.output).toBe('The image shows a cat sitting on a mat.');
expect(mockClient.chat).toHaveBeenCalledWith(
expect.objectContaining({
messages: expect.arrayContaining([
expect.objectContaining({
content: expect.arrayContaining([
{ type: 'text', text: 'What is in this image?' },
expect.any(Object)
])
})
])
})
);
});
it('defaults prompt to "Describe this image in detail."', async () => {
mockClient.chat = vi.fn().mockResolvedValueOnce({
content: 'This is the default prompt response.',
stopReason: 'end_turn',
usage: { inputTokens: 100, outputTokens: 10 }
});
const tool = createImageAnalyzeTool(mockClient);
await tool.execute({ url: 'https://example.com/image.jpg' });
expect(mockClient.chat).toHaveBeenCalledWith(
expect.objectContaining({
messages: expect.arrayContaining([
expect.objectContaining({
content: expect.arrayContaining([
{ type: 'text', text: 'Describe this image in detail.' },
expect.any(Object)
])
})
])
})
);
});
it('fails when neither url nor data is provided', async () => {
const tool = createImageAnalyzeTool(mockClient);
const result = await tool.execute({});
expect(result.success).toBe(false);
expect(result.error).toContain('Either "url" or "data" must be provided');
expect(mockClient.chat).not.toHaveBeenCalled();
});
it('fails when both url and data are provided', async () => {
const tool = createImageAnalyzeTool(mockClient);
const result = await tool.execute({
url: 'https://example.com/image.jpg',
data: 'base64data'
});
expect(result.success).toBe(false);
expect(result.error).toContain('Cannot provide both "url" and "data"');
expect(mockClient.chat).not.toHaveBeenCalled();
});
it('fails when data is provided without media_type', async () => {
const tool = createImageAnalyzeTool(mockClient);
const result = await tool.execute({
data: 'base64data',
prompt: 'Test'
});
expect(result.success).toBe(false);
expect(result.error).toContain('media_type is required when providing data');
expect(mockClient.chat).not.toHaveBeenCalled();
});
it('fails with invalid media_type', async () => {
const tool = createImageAnalyzeTool(mockClient);
const result = await tool.execute({
data: 'base64data',
media_type: 'image/tiff'
});
expect(result.success).toBe(false);
expect(result.error).toContain('Invalid media_type');
expect(mockClient.chat).not.toHaveBeenCalled();
});
it('passes valid media_types', async () => {
const validTypes = ['image/jpeg', 'image/png', 'image/gif', 'image/webp'];
for (const mediaType of validTypes) {
mockClient.chat = vi.fn().mockResolvedValueOnce({
content: 'Success',
stopReason: 'end_turn',
usage: { inputTokens: 10, outputTokens: 10 }
});
const tool = createImageAnalyzeTool(mockClient);
const result = await tool.execute({
data: 'base64data',
media_type: mediaType
});
expect(result.success).toBe(true);
expect(mockClient.chat).toHaveBeenCalledTimes(1);
mockClient.chat = vi.fn();
}
});
it('handles model client errors', async () => {
mockClient.chat = vi.fn().mockRejectedValueOnce(new Error('Model API error'));
const tool = createImageAnalyzeTool(mockClient);
const result = await tool.execute({ url: 'https://example.com/image.jpg' });
expect(result.success).toBe(false);
expect(result.output).toBe('');
expect(result.error).toBe('Model API error');
});
it('handles non-Error exceptions', async () => {
mockClient.chat = vi.fn().mockRejectedValueOnce('String error');
const tool = createImageAnalyzeTool(mockClient);
const result = await tool.execute({ url: 'https://example.com/image.jpg' });
expect(result.success).toBe(false);
expect(result.output).toBe('');
expect(result.error).toBe('String error');
});
it('uses custom system message prompt', async () => {
const mockRequest = {
messages: [] as any,
system: '',
maxTokens: 1024
};
const mockResponse = {
content: 'Analysis complete.',
stopReason: 'end_turn',
usage: { inputTokens: 100, outputTokens: 10 }
};
mockClient.chat = vi.fn().mockResolvedValue(mockResponse).mockImplementationOnce(async (r) => {
return mockResponse;
});
const tool = createImageAnalyzeTool(mockClient);
await tool.execute({
url: 'https://example.com/image.jpg',
prompt: 'Analyze the colors.'
});
const callArgs = (mockClient.chat as any).mock.calls[0][0];
expect(callArgs.system).toContain('vision assistant');
expect(callArgs.system).toContain('Analyze the provided image');
});
it('respects maxTokens parameter', async () => {
const mockRequest = {
messages: [] as any,
system: '',
maxTokens: 1024
};
const mockResponse = {
content: 'Short response',
stopReason: 'end_turn',
usage: { inputTokens: 10, outputTokens: 10 }
};
mockClient.chat = vi.fn().mockResolvedValueOnce(mockResponse);
const tool = createImageAnalyzeTool(mockClient);
await tool.execute({ url: 'https://example.com/image.jpg' });
const callArgs = (mockClient.chat as any).mock.calls[0][0];
expect(callArgs.maxTokens).toBe(1024);
});
it('passes through model response content', async () => {
const expectedContent = 'Detailed analysis of the image...';
mockClient.chat.mockResolvedValueOnce({
content: expectedContent,
stopReason: 'end_turn',
usage: { inputTokens: 100, outputTokens: 100 }
});
const tool = createImageAnalyzeTool(mockClient);
const result = await tool.execute({ url: 'https://example.com/image.jpg' });
expect(result.success).toBe(true);
expect(result.output).toBe(expectedContent);
});
});
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import type { ModelClient } from '../../models/types.js';
import type { Tool, ToolResult } from '../types.js';
interface ImageAnalyzeArgs {
url?: string;
data?: string;
media_type?: string;
prompt?: string;
}
const DEFAULT_PROMPT = 'Describe this image in detail.';
const VALID_MEDIA_TYPES = ['image/jpeg', 'image/png', 'image/gif', 'image/webp'];
export function createImageAnalyzeTool(modelClient: ModelClient): Tool {
return {
name: 'image.analyze',
description: 'Analyze an image using a vision model. Accepts a URL or base64-encoded image data. Returns a text description or analysis based on the provided prompt.',
inputSchema: {
type: 'object',
properties: {
url: {
type: 'string',
description: 'URL of the image to analyze'
},
data: {
type: 'string',
description: 'Base64-encoded image data (alternative to url)'
},
media_type: {
type: 'string',
description:
'MIME type of the image (required when using data). One of: image/jpeg, image/png, image/gif, image/webp'
},
prompt: {
type: 'string',
description:
'What to analyze or describe about the image. Default: "Describe this image in detail."'
}
},
required: []
},
execute: async (rawArgs: unknown): Promise<ToolResult> => {
try {
const args = rawArgs as ImageAnalyzeArgs;
if (!args.url && !args.data) {
return {
success: false,
output: '',
error: 'Either "url" or "data" must be provided'
};
}
if (args.url && args.data) {
return {
success: false,
output: '',
error: 'Cannot provide both "url" and "data" - choose one'
};
}
if (args.data && !args.media_type) {
return {
success: false,
output: '',
error: 'media_type is required when providing data'
};
}
if (args.media_type && !VALID_MEDIA_TYPES.includes(args.media_type)) {
return {
success: false,
output: '',
error: `Invalid media_type: ${args.media_type}. Must be one of: ${VALID_MEDIA_TYPES.join(', ')}`
};
}
const prompt = args.prompt || DEFAULT_PROMPT;
const imageSource = args.url
? {
type: 'url' as const,
media_type: args.media_type || 'image/jpeg',
url: args.url
}
: {
type: 'base64' as const,
media_type: args.media_type!,
data: args.data
};
const message = {
role: 'user' as const,
content: [
{ type: 'text' as const, text: prompt },
{ type: 'image' as const, source: imageSource }
]
};
const response = await modelClient.chat({
messages: [message],
system:
'You are a vision assistant. Analyze the provided image according to the user\'s request. Provide detailed, helpful descriptions.',
maxTokens: 1024
});
return {
success: true,
output: response.content
};
} catch (error) {
return {
success: false,
output: '',
error: error instanceof Error ? error.message : String(error)
};
}
}
};
}