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Add examples for structured outputs and tool use (#172)
--------- Co-authored-by: Bruce MacDonald <[email protected]>
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import ollama from 'ollama'; | ||
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import { z } from 'zod'; | ||
import { zodToJsonSchema } from 'zod-to-json-schema'; | ||
import { readFileSync } from 'fs'; | ||
import { resolve } from 'path'; | ||
import { createInterface } from 'readline'; | ||
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/* | ||
Ollama vision capabilities with structured outputs | ||
It takes an image file as input and returns a structured JSON description of the image contents | ||
including detected objects, scene analysis, colors, and any text found in the image | ||
*/ | ||
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// Schema for individual objects detected in the image | ||
const ObjectSchema = z.object({ | ||
name: z.string().describe('The name of the object'), | ||
confidence: z.number().min(0).max(1).describe('The confidence score of the object detection'), | ||
attributes: z.record(z.any()).optional().describe('Additional attributes of the object') | ||
}); | ||
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// Schema for individual objects detected in the image | ||
const ImageDescriptionSchema = z.object({ | ||
summary: z.string().describe('A concise summary of the image'), | ||
objects: z.array(ObjectSchema).describe('An array of objects detected in the image'), | ||
scene: z.string().describe('The scene of the image'), | ||
colors: z.array(z.string()).describe('An array of colors detected in the image'), | ||
time_of_day: z.enum(['Morning', 'Afternoon', 'Evening', 'Night']).describe('The time of day the image was taken'), | ||
setting: z.enum(['Indoor', 'Outdoor', 'Unknown']).describe('The setting of the image'), | ||
text_content: z.string().describe('Any text detected in the image') | ||
}); | ||
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async function run(model: string) { | ||
// Create readline interface for user input | ||
const rl = createInterface({ | ||
input: process.stdin, | ||
output: process.stdout | ||
}); | ||
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// Get path from user input | ||
const path = await new Promise<string>(resolve => { | ||
rl.question('Enter the path to your image: ', resolve); | ||
}); | ||
rl.close(); | ||
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// Verify the file exists and read it | ||
try { | ||
const imagePath = resolve(path); | ||
const imageBuffer = readFileSync(imagePath); | ||
const base64Image = imageBuffer.toString('base64'); | ||
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// Convert the Zod schema to JSON Schema format | ||
const jsonSchema = zodToJsonSchema(ImageDescriptionSchema); | ||
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const messages = [{ | ||
role: 'user', | ||
content: 'Analyze this image and return a detailed JSON description including objects, scene, colors and any text detected. If you cannot determine certain details, leave those fields empty.', | ||
images: [base64Image] | ||
}]; | ||
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const response = await ollama.chat({ | ||
model: model, | ||
messages: messages, | ||
format: jsonSchema, | ||
options: { | ||
temperature: 0 // Make responses more deterministic | ||
} | ||
}); | ||
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// Parse and validate the response | ||
try { | ||
const imageAnalysis = ImageDescriptionSchema.parse(JSON.parse(response.message.content)); | ||
console.log('Image Analysis:', imageAnalysis); | ||
} catch (error) { | ||
console.error("Generated invalid response:", error); | ||
} | ||
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} catch (error) { | ||
console.error("Error reading image file:", error); | ||
} | ||
} | ||
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run('llama3.2-vision').catch(console.error); |
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import ollama from 'ollama'; | ||
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import { z } from 'zod'; | ||
import { zodToJsonSchema } from 'zod-to-json-schema'; | ||
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/* | ||
Ollama structured outputs capabilities | ||
It parses the response from the model into a structured JSON object using Zod | ||
*/ | ||
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// Define the schema for friend info | ||
const FriendInfoSchema = z.object({ | ||
name: z.string().describe('The name of the friend'), | ||
age: z.number().int().describe('The age of the friend'), | ||
is_available: z.boolean().describe('Whether the friend is available') | ||
}); | ||
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// Define the schema for friend list | ||
const FriendListSchema = z.object({ | ||
friends: z.array(FriendInfoSchema).describe('An array of friends') | ||
}); | ||
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async function run(model: string) { | ||
// Convert the Zod schema to JSON Schema format | ||
const jsonSchema = zodToJsonSchema(FriendListSchema); | ||
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/* Can use manually defined schema directly | ||
const schema = { | ||
'type': 'object', | ||
'properties': { | ||
'friends': { | ||
'type': 'array', | ||
'items': { | ||
'type': 'object', | ||
'properties': { | ||
'name': { 'type': 'string' }, | ||
'age': { 'type': 'integer' }, | ||
'is_available': { 'type': 'boolean' } | ||
}, | ||
'required': ['name', 'age', 'is_available'] | ||
} | ||
} | ||
}, | ||
'required': ['friends'] | ||
} | ||
*/ | ||
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const messages = [{ | ||
role: 'user', | ||
content: 'I have two friends. The first is Ollama 22 years old busy saving the world, and the second is Alonso 23 years old and wants to hang out. Return a list of friends in JSON format' | ||
}]; | ||
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const response = await ollama.chat({ | ||
model: model, | ||
messages: messages, | ||
format: jsonSchema, // or format: schema | ||
options: { | ||
temperature: 0 // Make responses more deterministic | ||
} | ||
}); | ||
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// Parse and validate the response | ||
try { | ||
const friendsResponse = FriendListSchema.parse(JSON.parse(response.message.content)); | ||
console.log(friendsResponse); | ||
} catch (error) { | ||
console.error("Generated invalid response:", error); | ||
} | ||
} | ||
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run('llama3.1:8b').catch(console.error); |
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import ollama from 'ollama'; | ||
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// Add two numbers function | ||
function addTwoNumbers(args: { a: number, b: number }): number { | ||
return args.a + args.b; | ||
} | ||
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// Subtract two numbers function | ||
function subtractTwoNumbers(args: { a: number, b: number }): number { | ||
return args.a - args.b; | ||
} | ||
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// Tool definition for add function | ||
const addTwoNumbersTool = { | ||
type: 'function', | ||
function: { | ||
name: 'addTwoNumbers', | ||
description: 'Add two numbers together', | ||
parameters: { | ||
type: 'object', | ||
required: ['a', 'b'], | ||
properties: { | ||
a: { type: 'number', description: 'The first number' }, | ||
b: { type: 'number', description: 'The second number' } | ||
} | ||
} | ||
} | ||
}; | ||
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// Tool definition for subtract function | ||
const subtractTwoNumbersTool = { | ||
type: 'function', | ||
function: { | ||
name: 'subtractTwoNumbers', | ||
description: 'Subtract two numbers', | ||
parameters: { | ||
type: 'object', | ||
required: ['a', 'b'], | ||
properties: { | ||
a: { type: 'number', description: 'The first number' }, | ||
b: { type: 'number', description: 'The second number' } | ||
} | ||
} | ||
} | ||
}; | ||
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async function run(model: string) { | ||
const messages = [{ role: 'user', content: 'What is three minus one?' }]; | ||
console.log('Prompt:', messages[0].content); | ||
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const availableFunctions = { | ||
addTwoNumbers: addTwoNumbers, | ||
subtractTwoNumbers: subtractTwoNumbers | ||
}; | ||
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const response = await ollama.chat({ | ||
model: model, | ||
messages: messages, | ||
tools: [addTwoNumbersTool, subtractTwoNumbersTool] | ||
}); | ||
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let output: number; | ||
if (response.message.tool_calls) { | ||
// Process tool calls from the response | ||
for (const tool of response.message.tool_calls) { | ||
const functionToCall = availableFunctions[tool.function.name]; | ||
if (functionToCall) { | ||
console.log('Calling function:', tool.function.name); | ||
console.log('Arguments:', tool.function.arguments); | ||
output = functionToCall(tool.function.arguments); | ||
console.log('Function output:', output); | ||
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// Add the function response to messages for the model to use | ||
messages.push(response.message); | ||
messages.push({ | ||
role: 'tool', | ||
content: output.toString(), | ||
}); | ||
} else { | ||
console.log('Function', tool.function.name, 'not found'); | ||
} | ||
} | ||
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// Get final response from model with function outputs | ||
const finalResponse = await ollama.chat({ | ||
model: model, | ||
messages: messages | ||
}); | ||
console.log('Final response:', finalResponse.message.content); | ||
} else { | ||
console.log('No tool calls returned from model'); | ||
} | ||
} | ||
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run('llama3.1:8b').catch(error => console.error("An error occurred:", error)); |
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